part 3 case study example

Part 3 Exam Question Guide 

Scroll to the end to download this guide as a handy PDF

Introduction

This Part 3 Exam Question Guide is for the RIBA Part 3 course, which is an Advanced Diploma in Professional Practice in Architecture. Once completed, you can register as a fully qualified architect and use the title architect. The final assessment is made up of a case study and exams which are designed to test architectural assistants in a wide variety of positions.

People being examined can be in any size practice, from a large commercial practice, a small one-man band to anything in between. Sometimes people sitting the exam have been architectural assistants for tens of years, other times, people have been working as a part II architectural assistant for the minimum of a year.

The written case study can be a strong suit for people working in small residential based practices, who have had a lot of on-site and project management experience. However, the exam questions can be tricky if you have not been exposed to complicated projects; non-residential, multiple stakeholders with complicated planning and legislative issues.

The Part 3 Handbook by Stephen Brookhouse  can be a good starting point for guidance on these questions. as a feasibility style / site analysis scenario can help structure the questions in a more practical way, rather than feeling that you need to list as many different reference points, which may not be relevant to the question.

Below is an expanded reference list taken from the book to help in answering Problem / Scenario Based Question 1.

Problem/Scenario Based Question 1

The below information is in relation to a time limited exam condition questions paper and not the office-based exam questions. Within this paper, a scenario will be detailed along with a series of questions. The objective of the question and answer is to show both the understanding of relevant legislation and its practical effects.

This is similar to a feasibility although there is more emphasis on Legislation and Programme within the exam questions. For help writing a feasibility for a residential client or developer, check out this article on the Detail Library [ https://detail-library.co.uk/architecture-feasibility-study/ ]

The below outline has been taken from the book and expanded upon to give further details of different key terms.

Looking at the example question in the book:

• a) refer to the legislation, appropriate available relevant information and various organisations that you would consult with (12 marks); and
• b) evaluate the likely effect that relevant statutory procedures will have on the early stages of the development programme (8 marks).

Part A – Legislation

The key to answering the question is using the guide below to reference any possible legislation that may be relevant to the site described and who would need to be consulted.

Part B of the question may require a refocus of the below relevant points of the site, and how anything relevant may affect the early stages of the programme. This part is further detailed in the following section, Part B – Programme.

Possible relevant legislation

TOWN AND COUNTRY PLANNING

Reference points:

Local Plan – What possible things within the Local Plan are relevant to the site? Possible regeneration area, any article 4 directions, other specific land designations.

National Planning Policy Framework (NPPF) – This informs the local plan but elements of the NPPF that are relevant to the site and the project will need to be referenced in preparing planning application.

Planning History – Is there any relevant planning history of the site? Possible planning objections, neighbourhood associations to consult, relevant objections or other possible relevant information.

• Desktop research looking at the local planning authority website
• Local authority development control
• Planning consultant
• Access consultant
• PR consultant

Section 106 Agreement(s) and Community Infrastructure Levy (CIL) – Most large planning applications will have to deal with levies or development mitigation. It is worth getting familiar with these two. A section 106 agreement [ https://www.designingbuildings.co.uk/wiki/Section_106_consultation ] is closely linked to negotiations with the council and is highly related to the site, use, size and needs of the neighbouring area. Sometimes this agreement can be in the form of a payment although it may be beneficial for the site to offer something back to the local community, if possible, like providing affordable housing, station entrance, primary school, health centre, communal park, etc.

The Community Infrastructure Levy (CIL) – [ https://www.designingbuildings.co.uk/wiki/Community_infrastructure_levy_CIL ] is closely linked to the Section 106 Agreements which is why discussing these as early as possible with the Local Authority can help to shape a project and design. Cities such as London also have a Mayoral CIL on top of the Local Authority’s to possibly bear in mind.

• Local authority – This may be via a traditional pre-application process [ https://www.planningportal.co.uk/planning/planning-applications/how-to-apply/pre-application-advice ] or even a Planning Performance Agreement (PPA) [ https://www.designingbuildings.co.uk/wiki/Planning_performance_agreement#:~:text=Planning%20performance%20agreements%20are%20voluntary,to%20process%20a%20planning%20application. ], this is where the applicant enters into an agreement with the Local Authority on a timeline of consultation with the Council and its officers. This can be a more expensive process but can shorten the length of time of a decision. It also encourages conversations with the council from the beginning with a shared vision for the site and iron out any costs such as CIL payments and relevant consultants needed.
• Specialist and legal advisors

CONSERVATION AREA AND LISTED BUILDING CONSENT

• Desktop research looking at the local planning authority website – This is used to see if the site is within a conservation area and listed building. Some buildings can also be locally listed. Whilst this means the building is not covered by the Listed Building and Conservation Areas Act 1990, it can mean that the Local Authority with require extra input from a specialist heritage consultant.
• Local authority conservation officer
• English Heritage
• Specialist heritage architect

SUSTAINABILITY

Land contamination – Could there be possible risk of contaminated land? If the site has historically been used for industrial purposes, even light industrial purposes, there can be a risk of land contamination and need for a further assessment.

Flood risk data – Is the site in a flood risk zone? This can include both surface water flooding as well as risk of flooding from rivers, sea or reservoirs.  

Transport studies – How will this development affect the existing transport network? For possible parking provision, refuse collection, deliveries and if there is any increase visit to site: also if many people are to visit the site in the proposal; how will people get there, are there sufficient public transport means, etc.

Ecology – Is there any potential for bats or other protected species to be on the site? If a site has been abandoned for a long time or in a rural area there may be possibility of protected species within the site. This will require further consultation and possible surveys at specific times of the year. It can be useful to do this as and when, rather than having to wait a further 9 months to get the right time of year.

• Desktop research – Some local authorities will have specific information detailing if a site has contamination, or if it is a flood zone.
• Local Authority – The local authority will be able to give further information on what studies will need to be conducted by any specialist consultants to mitigate any risks to future users.
• Environment Agency – They will be able to give you further information as to the level of contamination, historic contamination to a site as well as the flood risk level to an area.
• Specialist consultant hydrologist
• Transport consultant

HEALTH AND SAFETY

CDM Regulations – This is relevant from the beginning of a project and the client should be advised of their duties as soon as possible.

Asbestos Regulations, etc.   – An asbestos survey and remediation many be required before any other surveys are conducted.

Local authority Environmental Health Department

• CDM co-ordinator

Central government guidelines

• Local authority Highways Department
• Consultant civil engineer

ADJOINING OWNER’S RIGHTS, AND RIGHTS OF OTHERS OVER SITE

Land Registry data – Where title deeds for a site can be obtained.

Deeds to site – The title deeds of the site should give information to confirm boundaries and any possible covenants, easements, cautions, notices and therefore restrictions on the site.

Utility companies and other stakeholders – This may be relevant if there are any public sewers, overhead cables or substations on or crossing the site. They may require extra exploration and agreements such as build-over applications.

Client solicitor

• Utility companies
• Specialist surveyor: rights to light – Are there many neighbouring properties that could be affected by reduction in light to existing windows by the development? Further studies and modelling may be required.

Part B – Programme

Example part b as detailed in the book:

This part of the question is asking for the likely effect of the procedures on the early stages of the development programme. Your task is to explain the activities and possible timescales to your client. This point will be related to the ones in part a, but refer to the programme, possible delays and how identifying issues from the outset can shorten the programme.

• Title deeds
• Pre-application advice
• Planning Performance Agreement (PPA) to ascertain a more certain time frame
• Public Consultation
• Putting together a design team base on part a of the question or pre-application advice, if this has not been done prior to pre-application advice
• Preparation of specialist reports and surveys
• Application (including type of application and why): registration, public consultation, time for decision (varies)
• Section 106 Agreement / Community Infrastructure Levy – time to negotiate and agree this as well as integrate any possible design changes could lengthen planning any application.
• Planning permission: ‘reserved matters’ to be addressed or ‘conditions’ to be met
• Refusal: appeal (but note the question does not expect you to give full details of
• appeal procedures)

LISTED BUILDING / CONSERVATION AREA CONSENT

This will run in parallel to the above planning programme.

• More time possibly required if the Conservation Officer or English Heritage and comments, changes, further requests for information.
• More time possibly required for consultants to comment, make changes, provide further information and further studies to the Planning Officers in relations to, Land contamination, Flood risk, Transport, or Ecology.
• Time will be required for surveys and incorporating any findings into the design.
• Possible unforeseen risks – such as extra a survey discovering extreme contamination that will need longer to remediate.
• Whilst this does not affect the early stages of the planning process, it can affect the design and timeline of a project.
• Separate consultation and negotiation with each adjoining owner affected by the works will take.

Answering the Part 3 exam questions can be difficult if your experience in practice is not reflected directly in the questions. However, the questions are there to test background knowledge and understanding what issues may arise and who may need to be consulted.

Using the Part 3 Handbook by Stephen Brookhouse can help in understanding some of the key points which will need to be covered. Looking at the scenario like a feasibility can also help in framing what issues there could be with the site.

Download the PDF Guide:

Download this handy pdf guide for quick reference when working on your Part 3.

Written by Aida Rodriguez-Vega, architect and researcher. Aida keeps busy by carrying out technical research and drawing new details for the ever-growing library and construction detailing books.

Part 3 Exam Question Guide Resources

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Final Examination in Professional Practice (Part 3) Architecture

Study Exemption Final Examination in Professional Practice (Part 3) Architecture at the University of Portsmouth. Further your studies at a postgraduate level and achieve your goals.

Key information

Accreditation:.

This course is Accredited

• 1 year part-time
• September 2024

Course information

Please select the page of your interest

Showing content for section Overview

If you've studied architecture, surveying or civil engineering, and have completed RIBA parts 1 and 2, this Final Examination in Professional Practice (part 3) Architecture course is your final step to become a professional architect. When you graduate, you'll be able to apply for the Final Certificate in Architecture (Part 3) ARB/RIBA and practise as a qualified architect.

On this course you'll learn about current practice issues, legal and building legislation, and contractual issues in the industry, as well as improving your knowledge of the environment and sustainability, and the social and economic side of the construction industry. 

You'll join a smaller cohort of students than many postgraduate degrees and have plenty of opportunities to get to know your peers and lectures. You’ll learn in a friendly and relaxed atmosphere, and enhance your teamwork, communication and project management skills throughout the course. 

You’ll apply your learning in workshops including our Contract Workshop, where you'll practise your contract administration skills by following a series of scenarios and role play with a JCT Standard Building Contract. 

To apply for this course you need to hold RIBA Part 1 and Part 2, and have at least two years' experience in architectural practice. 12 months of this experience should be in a UK/EU practice. 

Eligibility

This course accepts only UK students.

If you’re an EU or international student interested in this course, consider our International Professional Practice (Part 3) Architecture instead.

Course highlights

• Study Practice Management, Law and Contract, as set out in the ARB/RIBA syllabus
• Complete a case study of a live project, relevant to your current professional role
• Use our design studios, featuring advanced architectural computer facilities, CNC milling machine, laser cutting machines, the virtual reality suite and professional printers Benefit from our nurturing teaching environment and a mix of lectures and workshops
• Be supported by staff with extensive academic and architectural practice experience, and construction industry experts. 
• Hear from industry experts working in UK construction, including barristers (Crown Office Chambers) , lawyers (Fenwick Elliott), solicitors, architects (National practices such as AHMM and local practices), and planning consultants (Savills)
• Be eligible to apply for the Final Certificate in Architecture (Part 3) ARB/RIBA and practise as a qualified architect when you graduate

Accreditation

Once you’ve completed this course, you can apply for the Final Certificate in Architecture (Part 3), which is recognised by the ARB and RIBA.

You must already have RIBA Parts 1 and 2, as well as the minimum required practical training, documented in your Professional Experience and Development Record.

With your Final Certificate in Architecture, you'll be eligible to join the register of architects held by the ARB.

Contact information

+44 (0) 23 9284 5566

What you’ll study

Core modules.

All modules in the year are core.

Practice Management, Law and Contract - 30 credits Accelerate your career in architecture with key business knowledge in this professional practice module.

You’ll learn both the theory and how to apply it, getting to grips with laws, managing projects, handling risks, and understanding finances. We’ll help you see how social responsibility and ethics fit into architecture. You’ll become skilled at inspecting how you work with clients and how to manage projects from start to finish. You’ll also get coaching on how to communicate like a pro, so you can competently present your ideas.

When you finish, you’ll be prepared to take on the real-world problems you’ll face as a smart architectural manager and leader. Broaden your abilities beyond just design, which is crucial for successful practice.

Professional Experience and Practice - 60 credits In this module, you’ll inspect your professional experience and gain vital practical insights.

You’ll show how your skills align with architect roles and ethical conduct standards by analysing your work placement. We’ll guide you to thoughtfully assess how projects are carried out, teams work together, and companies operate. Reflecting on your own growth, you’ll pinpoint ways to keep improving through professional development opportunities. Learn how to showcase your unique skills and understanding in a CV, a case study, and self-evaluation, proving you’re ready for a professional role.

By the end, you’ll have the tools to adeptly handle the challenges of the architectural field. Make a smooth move from your studies to a meaningful career.

Topical Research Project - 30 credits In this module, you’ll grow your research skills by studying a topic that’s relevant to real-world professional standards.

You’ll gain a deep understanding of your subject with help from tutors. We’ll teach you how to carefully choose and analyse sources, and how to make convincing arguments backed up by solid proof. You’ll also work with others, learning to share tasks and work as a team while also improving your public speaking skills. This module will help you ask the right questions, write well-organised papers, and present your ideas persuasively.

By the end, you’ll be equipped with the important research abilities that are key in the fields of architecture and scholarly study.

Become a proactive and adaptable researcher who can contribute significantly to your field.

Changes to course content

We use the best and most current research and professional practice alongside feedback from our students to make sure course content is relevant to your future career or further studies.

Therefore, some course content may change over time to reflect changes in the discipline or industry. If a module doesn't run, we'll let you know as soon as possible and help you choose an alternative module.

Careers and opportunities

Careers this master’s prepares you for.

To practice as an architect or use the title of Architect in the UK you must hold RIBA 1, 2 and 3. 

You'll graduate from this course with the skills and knowledge you need to work as an architect in the UK or abroad and have opportunities in both the public and private sectors. You may choose to start your own architectural practice.

When you apply for this course you'll already be working in an architectural practice. In addition to support from your employer you'll be supported by your supervisor, lecturers and fellow students. These networking opportunities mean you'll build your professional network during the course, which will benefit you whether you stay with your current employer or seek alternative employment once you graduate. 

Qualifying as an architect

When you graduate you'll be eligible to apply for the Final Certificate in Architecture (Part 3), recognised by ARB and RIBA, and practise as a qualified architect. Once you have your Final Certificate you'll be able to join the register of architects held by the ARB.

To apply for your Final Certificate you need to hold RIBA Parts 1 and 2 (or equivalent), and have the minimum amount of required practical training documented in your Professional Experience and Development Record.

9 reasons to do a Master's  

Career planning

During your course you'll have expert careers advice from our Careers and Employability Centre, your tutors and our Student Placements and Employability Centre. You can access support from our Careers and Employability Centre for up to 5 years after you graduate.

You'll benefit from:

• Networking events
• 1-to-1 appointments
• CV and cover letter advice
• Interview preparation and practice
• Workshops to enhance your employability skills
• Recruitment events including the Student and Graduate Opportunities Fair
• Support starting your own business

How you'll spend your time

We recognise that you'll probably be juggling more demands when you do your Master's degree, as you may be working or you may have family responsibilities.

We'll give you as much indication here as we can of how much time you'll need to be on campus and how many hours you can expect to spend in self-directed study, but please note that these indications are always subject to change. You should receive your full timetable several weeks before you start with us.

Course structure

This course takes: 

• 1 year (part-time) 

You can expect: 

• to attend campus throughout the academic year 
• to attend 10 days of taught lectures or workshops, including 1 induction day, three 3-day seminars and 2 assessment days
• to complete study roughly 20 hours of independent study per week
• to access learning materials online in your own time

Master's study is deeper and more specialised than an undergraduate degree. This means you'll focus on something that really matters to you and your career as you work closely with academics committed to the subject.

You'll spend more time in independent study and research than you did for your undergraduate degree, but the majority of your teaching time will be in-person and face-to-face.

You'll be assessed through:

• essays and written assignments (25%)
• written case study and career evaluation (50%)
• written examinations (25%)
• oral examination (Pass/Fail)
• Professional Experience and Development Records (24 months worth - Pass/Fail)

Teaching staff

These are some of the expert staff who'll teach you on this course:

Mrs Emma Dalton

Senior Lecturer

[email protected]

School of Architecture

Faculty of Creative and Cultural Industries

Miss Clare Ridout

[email protected]

Mrs Vanessa Orekan

[email protected]

September start

The Master's academic year runs from September to the following September. There are breaks at Christmas and Easter. Over the summer you'll be writing your project/dissertation.

See key dates

Joining us as an international student

You'll feel at home in our international community and our diverse city. You'll be joining over 5,000 international students from more than 150 countries who are studying with us.

Learn more about international student life and how we can help you with visas, applications, arrival and settling in. 

Information for international students

Architecture Studios

Our open-plan learning spaces encourage a studio culture of collaboration, creativity and dialogue – preparing you for the ways of working you'll experience in your career.

Explore the Studios

Architecture Project Office

Get practical architecture experience and enhance your CV with real clients on intensive, fast-paced design workshops or consultancy projects.

Find out more about the Project Office

Supporting you

Master's study is more focused on independent learning than undergraduate study, but you'll get lots of  support via video, phone and face-to-face  from teaching and support staff to enhance your learning experience and help you succeed. You can build your personalised network of support from the following people and services:

Types of support

Personal tutor.

Your personal tutor helps you make the transition to independent study and gives you academic and personal support throughout your time at university.

You'll have regular contact with your personal tutor in learning activities or scheduled meetings. You can also make an appointment with them if you need extra support.

Student support advisor

Academic skills tutors.

You'll have help from a team of faculty academic skills tutors. They can help you improve and develop your academic skills and support you in any area of your study.

They can help with:

• improving your academic writing (for example, essays, reports, dissertations)
• delivering presentations (including observing and filming presentations)
• understanding and using assignment feedback
• managing your time and workload
• revision and exam techniques

Creative skills tutors

It and computing support, academic skills support (ask).

As well as support from faculty staff and your personal tutor, you can use the University’s Academic Skills Unit (ASK).

ASK provides one-to-one support in areas such as:

• academic writing
• note taking
• time management
• critical thinking
• presentation skills
• referencing
• working in groups
• revision, memory and exam techniques

If you have a disability or need extra support, the Additional Support and Disability Centre (ASDAC) will give you help, support and advice.

Wellbeing and mental health support

Our online  Learning Well mini-course will help you plan for managing the challenges of learning and student life, so you can fulfil your potential and have a great student experience.

You can get personal, emotional and mental health support from our Student Wellbeing Service , in person and online. This includes 1–2–1 support as well as courses and workshops that help you better manage stress, anxiety or depression.

Disability advice and additional support

If you require extra support because of a disability or additional learning need our  specialist team  can help you.

They'll help you to

• discuss and agree on reasonable adjustments
• liaise with other University services and facilities, such as the library
• access specialist study skills and strategies tutors, and assistive technology tutors, on a 1-to-1 basis or in groups
• liaise with external services

Library support

Library staff are available in person or by email, phone, or online chat to help you make the most of the University’s library resources. You can also request one-to-one appointments and get support from a librarian who specialises in your subject area.

The library is open 24 hours a day, every day, in term time.

Support with English

If English isn't your first language, you can do one of our English language courses  to improve your written and spoken English language skills before starting your degree. Once you're here, you can take part in our free In-Sessional English (ISE) programme  to improve your English further.

​Course costs and funding

Tuition fees.

This course is for UK applicants only. Fees below apply to UK, Channel Islands, and Isle of Man.

September 2024 start

• Part-time: £2,875

Fees are subject to annual increase.  Read our tuition fees terms and conditions .

You'll be able to pay your fees in instalments. Find out  how to pay your tuition fees .

Tuition fees terms and conditions

Funding your studies

Find out more how to fund your studies , including the scholarships and bursaries you could get. You can also find more about tuition fees and living costs , including what your tuition fees cover. 

If you're a UK student, you may be eligible for a Government postgraduate loan, which you can use to help with course fees and living costs.

Applying from outside the UK? Find out about funding options for international students  and our  international student scholarships .

Loans, scholarships and bursaries

Browse funding such as the Government Postgraduate Loan, our scholarships for new and returning students, and subject specific loans.

Fees and funding for Master's courses

Explore Master's funding options, including loans, scholarships, bursaries and more.

Additional costs

These course-related costs aren't included in the tuition fees, so you'll need to budget for them when you plan your spending. Additional costs could include:

• Accommodation:  Accommodation options and costs can be found on our  accommodation pages .
• Recommended reading:  You can borrow key texts from the library and if you choose to purchase these texts they may cost up to £60 each.
• General costs: Such as photocopying, memory sticks, printing charges, binding and specialist printing. We suggest budgeting £75 per year.
• Final project transport or accommodation:  where necessary, which related to your research activities. The amount will depend on the project you choose.

Read more about tuition fees and living costs , including what your tuition fees cover.

Entry requirements

Uk qualifications.

• Professional status in Surveying, Architecture or Civil Engineering from a UK institution.
• RIBA part 1 and 2 are essential for entry.

Please get in touch if you're not sure if your undergraduate subject is relevant to this degree.

Equivalent professional experience and/or qualifications will also be considered, such as previous study, employment, voluntary work and training courses, including courses and qualifications you didn't complete. Learn more about our Recognition of Prior Learning (RPL) .

English language requirements

• English language proficiency at a minimum of IELTS band 6.5 (or equivalent) with no component score below 6.0.

You do not need an IELTS or equivalent certification if:

• you have a UK degree
• you have a degree from a majority English speaking country (not taught by Distance Learning)
• you are a national of a majority English speaking country

Degrees taught solely in English from non-majority English speaking countries will be considered on a case by case basis. Find out more about our  English language requirements .

If you do not meet the English language requirements yet, you can achieve the level you need by successfully completing a  pre-sessional English programme  before you start your course.

Selection process

• All applicants will be invited to attend an interview.
• Full time employment in a UK/EU architectural practice is essential for entry, along with a case study project, assessed by course leader for suitability.
• Minimum 15 months of recorded experience (PEDRs) is required prior to starting the course. Refer to ARB for practical training requirements.

How to apply

Unlike undergraduate applications, which go through UCAS, applications for this Master's course are made directly to us.

There's no deadline for applications to this course. We accept applications right up until the start date in September, as long as there are places available. If you wait until September to apply, you may find that the course is full.

If you're applying as an international student, remember that you'll need to leave plenty of time to get your visa organised.

You can find more advice about applying in our  Master's application checklist . International students and current students and recent graduates of the University of Portsmouth also have some different application options, which are detailed below.

Extra information for international students

I'm an international student.

If you're an international student, you can apply directly to us using the same application form as UK students.

You could also get an agent to help with your application. Check  your country  page for details of agents in your region. To find out what to include in your application, head to the  how to apply page of our international students section .

If you don’t meet the  English language requirements  for this course yet, you can achieve the level you need by successfully completing a  pre-sessional English programme  before you start your course.

Ready to apply?

Start this course in september 2024.

Apply now (Part-time)

I'm a current Portsmouth student, or a recent Portsmouth graduate

If you're currently in your final year of study at Portsmouth, or you graduated since July 2023, you're eligible to make a fast track application. You'll have:

• a shorter application form to complete
• access to the 20% Alumni fee discount
• a guaranteed conditional offer, for most Master's courses 

Learn more about fast track

After you apply

Once we receive your application, we may ask you for further information. We will then either make you an offer or suggest alternatives if your application is unsuccessful.

You'll usually get a decision within 10 working days, so you shouldn't have to wait too long. Some courses have an interview stage – we'll let you know if you need to prepare for one.

Learn more about how we assess your application .

Admissions terms and conditions

When you accept an offer to study at the University of Portsmouth, you also agree to abide by our  Student Contract  (which includes the University's relevant policies, rules and regulations). You should read and consider these before you apply.

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• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

What Is a Case Study?

Weighing the pros and cons of this method of research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Cara Lustik is a fact-checker and copywriter.

Verywell / Colleen Tighe

• Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.  

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

• Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
• Gives researchers the chance to collect information on why one strategy might be chosen over another
• Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

• It cannot necessarily be generalized to the larger population
• Cannot demonstrate cause and effect
• It may not be scientifically rigorous
• It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of  Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

• Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
• Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
• Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

• Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
• Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
• Explanatory case studies : These   are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
• Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
• Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
• Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

• Archival records : Census records, survey records, and name lists are examples of archival records.
• Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
• Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
• Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
• Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
• Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

• Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
• Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
• Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
• Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research. 

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

• Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
• Read examples of case studies to gain an idea about the style and format.
• Remember to use APA format when citing references .

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach .  BMC Med Res Methodol . 2011;11:100.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal.  The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

How to write a case study — examples, templates, and tools

It’s a marketer’s job to communicate the effectiveness of a product or service to potential and current customers to convince them to buy and keep business moving. One of the best methods for doing this is to share success stories that are relatable to prospects and customers based on their pain points, experiences, and overall needs.

That’s where case studies come in. Case studies are an essential part of a content marketing plan. These in-depth stories of customer experiences are some of the most effective at demonstrating the value of a product or service. Yet many marketers don’t use them, whether because of their regimented formats or the process of customer involvement and approval.

A case study is a powerful tool for showcasing your hard work and the success your customer achieved. But writing a great case study can be difficult if you’ve never done it before or if it’s been a while. This guide will show you how to write an effective case study and provide real-world examples and templates that will keep readers engaged and support your business.

In this article, you’ll learn:

What is a case study?

How to write a case study, case study templates, case study examples, case study tools.

A case study is the detailed story of a customer’s experience with a product or service that demonstrates their success and often includes measurable outcomes. Case studies are used in a range of fields and for various reasons, from business to academic research. They’re especially impactful in marketing as brands work to convince and convert consumers with relatable, real-world stories of actual customer experiences.

The best case studies tell the story of a customer’s success, including the steps they took, the results they achieved, and the support they received from a brand along the way. To write a great case study, you need to:

• Celebrate the customer and make them — not a product or service — the star of the story.
• Craft the story with specific audiences or target segments in mind so that the story of one customer will be viewed as relatable and actionable for another customer.
• Write copy that is easy to read and engaging so that readers will gain the insights and messages intended.
• Follow a standardized format that includes all of the essentials a potential customer would find interesting and useful.
• Support all of the claims for success made in the story with data in the forms of hard numbers and customer statements.

Case studies are a type of review but more in depth, aiming to show — rather than just tell — the positive experiences that customers have with a brand. Notably, 89% of consumers read reviews before deciding to buy, and 79% view case study content as part of their purchasing process. When it comes to B2B sales, 52% of buyers rank case studies as an important part of their evaluation process.

Telling a brand story through the experience of a tried-and-true customer matters. The story is relatable to potential new customers as they imagine themselves in the shoes of the company or individual featured in the case study. Showcasing previous customers can help new ones see themselves engaging with your brand in the ways that are most meaningful to them.

Besides sharing the perspective of another customer, case studies stand out from other content marketing forms because they are based on evidence. Whether pulling from client testimonials or data-driven results, case studies tend to have more impact on new business because the story contains information that is both objective (data) and subjective (customer experience) — and the brand doesn’t sound too self-promotional.

Case studies are unique in that there’s a fairly standardized format for telling a customer’s story. But that doesn’t mean there isn’t room for creativity. It’s all about making sure that teams are clear on the goals for the case study — along with strategies for supporting content and channels — and understanding how the story fits within the framework of the company’s overall marketing goals.

Here are the basic steps to writing a good case study.

1. Identify your goal

Start by defining exactly who your case study will be designed to help. Case studies are about specific instances where a company works with a customer to achieve a goal. Identify which customers are likely to have these goals, as well as other needs the story should cover to appeal to them.

The answer is often found in one of the buyer personas that have been constructed as part of your larger marketing strategy. This can include anything from new leads generated by the marketing team to long-term customers that are being pressed for cross-sell opportunities. In all of these cases, demonstrating value through a relatable customer success story can be part of the solution to conversion.

2. Choose your client or subject

Who you highlight matters. Case studies tie brands together that might otherwise not cross paths. A writer will want to ensure that the highlighted customer aligns with their own company’s brand identity and offerings. Look for a customer with positive name recognition who has had great success with a product or service and is willing to be an advocate.

The client should also match up with the identified target audience. Whichever company or individual is selected should be a reflection of other potential customers who can see themselves in similar circumstances, having the same problems and possible solutions.

Some of the most compelling case studies feature customers who:

• Switch from one product or service to another while naming competitors that missed the mark.
• Experience measurable results that are relatable to others in a specific industry.
• Represent well-known brands and recognizable names that are likely to compel action.
• Advocate for a product or service as a champion and are well-versed in its advantages.

Whoever or whatever customer is selected, marketers must ensure they have the permission of the company involved before getting started. Some brands have strict review and approval procedures for any official marketing or promotional materials that include their name. Acquiring those approvals in advance will prevent any miscommunication or wasted effort if there is an issue with their legal or compliance teams.

3. Conduct research and compile data

Substantiating the claims made in a case study — either by the marketing team or customers themselves — adds validity to the story. To do this, include data and feedback from the client that defines what success looks like. This can be anything from demonstrating return on investment (ROI) to a specific metric the customer was striving to improve. Case studies should prove how an outcome was achieved and show tangible results that indicate to the customer that your solution is the right one.

This step could also include customer interviews. Make sure that the people being interviewed are key stakeholders in the purchase decision or deployment and use of the product or service that is being highlighted. Content writers should work off a set list of questions prepared in advance. It can be helpful to share these with the interviewees beforehand so they have time to consider and craft their responses. One of the best interview tactics to keep in mind is to ask questions where yes and no are not natural answers. This way, your subject will provide more open-ended responses that produce more meaningful content.

4. Choose the right format

There are a number of different ways to format a case study. Depending on what you hope to achieve, one style will be better than another. However, there are some common elements to include, such as:

• An engaging headline
• A subject and customer introduction
• The unique challenge or challenges the customer faced
• The solution the customer used to solve the problem
• The results achieved
• Data and statistics to back up claims of success
• A strong call to action (CTA) to engage with the vendor

It’s also important to note that while case studies are traditionally written as stories, they don’t have to be in a written format. Some companies choose to get more creative with their case studies and produce multimedia content, depending on their audience and objectives. Case study formats can include traditional print stories, interactive web or social content, data-heavy infographics, professionally shot videos, podcasts, and more.

5. Write your case study

We’ll go into more detail later about how exactly to write a case study, including templates and examples. Generally speaking, though, there are a few things to keep in mind when writing your case study.

• Be clear and concise. Readers want to get to the point of the story quickly and easily, and they’ll be looking to see themselves reflected in the story right from the start.
• Provide a big picture. Always make sure to explain who the client is, their goals, and how they achieved success in a short introduction to engage the reader.
• Construct a clear narrative. Stick to the story from the perspective of the customer and what they needed to solve instead of just listing product features or benefits.
• Leverage graphics. Incorporating infographics, charts, and sidebars can be a more engaging and eye-catching way to share key statistics and data in readable ways.
• Offer the right amount of detail. Most case studies are one or two pages with clear sections that a reader can skim to find the information most important to them.
• Include data to support claims. Show real results — both facts and figures and customer quotes — to demonstrate credibility and prove the solution works.

6. Promote your story

Marketers have a number of options for distribution of a freshly minted case study. Many brands choose to publish case studies on their website and post them on social media. This can help support SEO and organic content strategies while also boosting company credibility and trust as visitors see that other businesses have used the product or service.

Marketers are always looking for quality content they can use for lead generation. Consider offering a case study as gated content behind a form on a landing page or as an offer in an email message. One great way to do this is to summarize the content and tease the full story available for download after the user takes an action.

Sales teams can also leverage case studies, so be sure they are aware that the assets exist once they’re published. Especially when it comes to larger B2B sales, companies often ask for examples of similar customer challenges that have been solved.

Now that you’ve learned a bit about case studies and what they should include, you may be wondering how to start creating great customer story content. Here are a couple of templates you can use to structure your case study.

Template 1 — Challenge-solution-result format

• Start with an engaging title. This should be fewer than 70 characters long for SEO best practices. One of the best ways to approach the title is to include the customer’s name and a hint at the challenge they overcame in the end.
• Create an introduction. Lead with an explanation as to who the customer is, the need they had, and the opportunity they found with a specific product or solution. Writers can also suggest the success the customer experienced with the solution they chose.
• Present the challenge. This should be several paragraphs long and explain the problem the customer faced and the issues they were trying to solve. Details should tie into the company’s products and services naturally. This section needs to be the most relatable to the reader so they can picture themselves in a similar situation.
• Share the solution. Explain which product or service offered was the ideal fit for the customer and why. Feel free to delve into their experience setting up, purchasing, and onboarding the solution.
• Explain the results. Demonstrate the impact of the solution they chose by backing up their positive experience with data. Fill in with customer quotes and tangible, measurable results that show the effect of their choice.
• Ask for action. Include a CTA at the end of the case study that invites readers to reach out for more information, try a demo, or learn more — to nurture them further in the marketing pipeline. What you ask of the reader should tie directly into the goals that were established for the case study in the first place.

Template 2 — Data-driven format

• Start with an engaging title. Be sure to include a statistic or data point in the first 70 characters. Again, it’s best to include the customer’s name as part of the title.
• Create an overview. Share the customer’s background and a short version of the challenge they faced. Present the reason a particular product or service was chosen, and feel free to include quotes from the customer about their selection process.
• Present data point 1. Isolate the first metric that the customer used to define success and explain how the product or solution helped to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
• Present data point 2. Isolate the second metric that the customer used to define success and explain what the product or solution did to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
• Present data point 3. Isolate the final metric that the customer used to define success and explain what the product or solution did to achieve this goal. Provide data points and quotes to substantiate the claim that success was achieved.
• Summarize the results. Reiterate the fact that the customer was able to achieve success thanks to a specific product or service. Include quotes and statements that reflect customer satisfaction and suggest they plan to continue using the solution.
• Ask for action. Include a CTA at the end of the case study that asks readers to reach out for more information, try a demo, or learn more — to further nurture them in the marketing pipeline. Again, remember that this is where marketers can look to convert their content into action with the customer.

While templates are helpful, seeing a case study in action can also be a great way to learn. Here are some examples of how Adobe customers have experienced success.

Juniper Networks

One example is the Adobe and Juniper Networks case study , which puts the reader in the customer’s shoes. The beginning of the story quickly orients the reader so that they know exactly who the article is about and what they were trying to achieve. Solutions are outlined in a way that shows Adobe Experience Manager is the best choice and a natural fit for the customer. Along the way, quotes from the client are incorporated to help add validity to the statements. The results in the case study are conveyed with clear evidence of scale and volume using tangible data.

The story of Lenovo’s journey with Adobe is one that spans years of planning, implementation, and rollout. The Lenovo case study does a great job of consolidating all of this into a relatable journey that other enterprise organizations can see themselves taking, despite the project size. This case study also features descriptive headers and compelling visual elements that engage the reader and strengthen the content.

Tata Consulting

When it comes to using data to show customer results, this case study does an excellent job of conveying details and numbers in an easy-to-digest manner. Bullet points at the start break up the content while also helping the reader understand exactly what the case study will be about. Tata Consulting used Adobe to deliver elevated, engaging content experiences for a large telecommunications client of its own — an objective that’s relatable for a lot of companies.

Case studies are a vital tool for any marketing team as they enable you to demonstrate the value of your company’s products and services to others. They help marketers do their job and add credibility to a brand trying to promote its solutions by using the experiences and stories of real customers.

When you’re ready to get started with a case study:

• Think about a few goals you’d like to accomplish with your content.
• Make a list of successful clients that would be strong candidates for a case study.
• Reach out to the client to get their approval and conduct an interview.
• Gather the data to present an engaging and effective customer story.

Adobe can help

There are several Adobe products that can help you craft compelling case studies. Adobe Experience Platform helps you collect data and deliver great customer experiences across every channel. Once you’ve created your case studies, Experience Platform will help you deliver the right information to the right customer at the right time for maximum impact.

To learn more, watch the Adobe Experience Platform story .

Keep in mind that the best case studies are backed by data. That’s where Adobe Real-Time Customer Data Platform and Adobe Analytics come into play. With Real-Time CDP, you can gather the data you need to build a great case study and target specific customers to deliver the content to the right audience at the perfect moment.

Watch the Real-Time CDP overview video to learn more.

Finally, Adobe Analytics turns real-time data into real-time insights. It helps your business collect and synthesize data from multiple platforms to make more informed decisions and create the best case study possible.

Request a demo to learn more about Adobe Analytics.

https://business.adobe.com/blog/perspectives/b2b-ecommerce-10-case-studies-inspire-you

https://business.adobe.com/blog/basics/business-case

https://business.adobe.com/blog/basics/what-is-real-time-analytics

Business growth

Marketing tips

16 case study examples (+ 3 templates to make your own)

I like to think of case studies as a business's version of a resume. It highlights what the business can do, lends credibility to its offer, and contains only the positive bullet points that paint it in the best light possible.

Imagine if the guy running your favorite taco truck followed you home so that he could "really dig into how that burrito changed your life." I see the value in the practice. People naturally prefer a tried-and-true burrito just as they prefer tried-and-true products or services.

To help you showcase your success and flesh out your burrito questionnaire, I've put together some case study examples and key takeaways.

What is a case study?

A case study is an in-depth analysis of how your business, product, or service has helped past clients. It can be a document, a webpage, or a slide deck that showcases measurable, real-life results.

For example, if you're a SaaS company, you can analyze your customers' results after a few months of using your product to measure its effectiveness. You can then turn this analysis into a case study that further proves to potential customers what your product can do and how it can help them overcome their challenges.

It changes the narrative from "I promise that we can do X and Y for you" to "Here's what we've done for businesses like yours, and we can do it for you, too."

16 case study examples 

While most case studies follow the same structure, quite a few try to break the mold and create something unique. Some businesses lean heavily on design and presentation, while others pursue a detailed, stat-oriented approach. Some businesses try to mix both.

There's no set formula to follow, but I've found that the best case studies utilize impactful design to engage readers and leverage statistics and case details to drive the point home. A case study typically highlights the companies, the challenges, the solution, and the results. The examples below will help inspire you to do it, too.

1. .css-1l9i3yq-Link[class][class][class][class][class]{all:unset;box-sizing:border-box;-webkit-text-fill-color:currentColor;cursor:pointer;}.css-1l9i3yq-Link[class][class][class][class][class]{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='ocean']{color:#3d4592;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='ocean']:hover{color:#2b2358;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='ocean']:focus{color:#3d4592;outline-color:#3d4592;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='white']{color:#fffdf9;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='white']:hover{color:#a8a5a0;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='white']:focus{color:#fffdf9;outline-color:#fffdf9;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='primary']{color:#3d4592;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='primary']:hover{color:#2b2358;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='primary']:focus{color:#3d4592;outline-color:#3d4592;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='secondary']{color:#fffdf9;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='secondary']:hover{color:#a8a5a0;}.css-1l9i3yq-Link[class][class][class][class][class][data-color='secondary']:focus{color:#fffdf9;outline-color:#fffdf9;}.css-1l9i3yq-Link[class][class][class][class][class][data-weight='inherit']{font-weight:inherit;}.css-1l9i3yq-Link[class][class][class][class][class][data-weight='normal']{font-weight:400;}.css-1l9i3yq-Link[class][class][class][class][class][data-weight='bold']{font-weight:700;} Volcanica Coffee and AdRoll

People love a good farm-to-table coffee story, and boy am I one of them. But I've shared this case study with you for more reasons than my love of coffee. I enjoyed this study because it was written as though it was a letter.

In this case study, the founder of Volcanica Coffee talks about the journey from founding the company to personally struggling with learning and applying digital marketing to finding and enlisting AdRoll's services.

It felt more authentic, less about AdRoll showcasing their worth and more like a testimonial from a grateful and appreciative client. After the story, the case study wraps up with successes, milestones, and achievements. Note that quite a few percentages are prominently displayed at the top, providing supporting evidence that backs up an inspiring story.

Takeaway: Highlight your goals and measurable results to draw the reader in and provide concise, easily digestible information.

2. Taylor Guitars and Airtable

This Airtable case study on Taylor Guitars comes as close as one can to an optimal structure. It features a video that represents the artistic nature of the client, highlighting key achievements and dissecting each element of Airtable's influence.

It also supplements each section with a testimonial or quote from the client, using their insights as a catalyst for the case study's narrative. For example, the case study quotes the social media manager and project manager's insights regarding team-wide communication and access before explaining in greater detail.

Takeaway: Highlight pain points your business solves for its client, and explore that influence in greater detail.

3. EndeavourX and Figma

My favorite part of Figma's case study is highlighting why EndeavourX chose its solution. You'll notice an entire section on what Figma does for teams and then specifically for EndeavourX.

It also places a heavy emphasis on numbers and stats. The study, as brief as it is, still manages to pack in a lot of compelling statistics about what's possible with Figma.

Takeaway: Showcase the "how" and "why" of your product's differentiators and how they benefit your customers.

4. ActiveCampaign and Zapier

Zapier's case study leans heavily on design, using graphics to present statistics and goals in a manner that not only remains consistent with the branding but also actively pushes it forward, drawing users' eyes to the information most important to them. 

The graphics, emphasis on branding elements, and cause/effect style tell the story without requiring long, drawn-out copy that risks boring readers. Instead, the cause and effect are concisely portrayed alongside the client company's information for a brief and easily scannable case study.

Takeaway: Lean on design to call attention to the most important elements of your case study, and make sure it stays consistent with your branding.

5. Ironclad and OpenAI

In true OpenAI fashion, this case study is a block of text. There's a distinct lack of imagery, but the study features a narrated video walking readers through the product.

The lack of imagery and color may not be the most inviting, but utilizing video format is commendable. It helps thoroughly communicate how OpenAI supported Ironclad in a way that allows the user to sit back, relax, listen, and be impressed. 

Takeaway: Get creative with the media you implement in your case study. Videos can be a very powerful addition when a case study requires more detailed storytelling.

6. Shopify and GitHub

GitHub's case study on Shopify is a light read. It addresses client pain points and discusses the different aspects its product considers and improves for clients. It touches on workflow issues, internal systems, automation, and security. It does a great job of representing what one company can do with GitHub.

To drive the point home, the case study features colorful quote callouts from the Shopify team, sharing their insights and perspectives on the partnership, the key issues, and how they were addressed.

Takeaway: Leverage quotes to boost the authoritativeness and trustworthiness of your case study. 

7 . Audible and Contentful

Contentful's case study on Audible features almost every element a case study should. It includes not one but two videos and clearly outlines the challenge, solution, and outcome before diving deeper into what Contentful did for Audible. The language is simple, and the writing is heavy with quotes and personal insights.

This case study is a uniquely original experience. The fact that the companies in question are perhaps two of the most creative brands out there may be the reason. I expected nothing short of a detailed analysis, a compelling story, and video content. 

Takeaway: Inject some brand voice into the case study, and create assets that tell the story for you.

8 . Zoom and Asana

Asana's case study on Zoom is longer than the average piece and features detailed data on Zoom's growth since 2020. Instead of relying on imagery and graphics, it features several quotes and testimonials. 

It's designed to be direct, informative, and promotional. At some point, the case study reads more like a feature list. There were a few sections that felt a tad too promotional for my liking, but to each their own burrito.

Takeaway: Maintain a balance between promotional and informative. You want to showcase the high-level goals your product helped achieve without losing the reader.

9 . Hickies and Mailchimp

I've always been a fan of Mailchimp's comic-like branding, and this case study does an excellent job of sticking to their tradition of making information easy to understand, casual, and inviting.

It features a short video that briefly covers Hickies as a company and Mailchimp's efforts to serve its needs for customer relationships and education processes. Overall, this case study is a concise overview of the partnership that manages to convey success data and tell a story at the same time. What sets it apart is that it does so in a uniquely colorful and brand-consistent manner.

Takeaway: Be concise to provide as much value in as little text as possible.

10. NVIDIA and Workday

The gaming industry is notoriously difficult to recruit for, as it requires a very specific set of skills and experience. This case study focuses on how Workday was able to help fill that recruitment gap for NVIDIA, one of the biggest names in the gaming world.

Though it doesn't feature videos or graphics, this case study stood out to me in how it structures information like "key products used" to give readers insight into which tools helped achieve these results.

Takeaway: If your company offers multiple products or services, outline exactly which ones were involved in your case study, so readers can assess each tool.

11. KFC and Contentful

I'm personally not a big KFC fan, but that's only because I refuse to eat out of a bucket. My aversion to the bucket format aside, Contentful follows its consistent case study format in this one, outlining challenges, solutions, and outcomes before diving into the nitty-gritty details of the project.

Say what you will about KFC, but their primary product (chicken) does present a unique opportunity for wordplay like "Continuing to march to the beat of a digital-first drum(stick)" or "Delivering deep-fried goodness to every channel."

Takeaway: Inject humor into your case study if there's room for it and if it fits your brand. 

12. Intuit and Twilio

Twilio does an excellent job of delivering achievements at the very beginning of the case study and going into detail in this two-minute read. While there aren't many graphics, the way quotes from the Intuit team are implemented adds a certain flair to the study and breaks up the sections nicely.

It's simple, concise, and manages to fit a lot of information in easily digestible sections.

Takeaway: Make sure each section is long enough to inform but brief enough to avoid boring readers. Break down information for each section, and don't go into so much detail that you lose the reader halfway through.

13. Spotify and Salesforce

Salesforce created a video that accurately summarizes the key points of the case study. Beyond that, the page itself is very light on content, and sections are as short as one paragraph.

I especially like how information is broken down into "What you need to know," "Why it matters," and "What the difference looks like." I'm not ashamed of being spoon-fed information. When it's structured so well and so simply, it makes for an entertaining read.

Takeaway: Invest in videos that capture and promote your partnership with your case study subject. Video content plays a promotional role that extends beyond the case study in social media and marketing initiatives .

14. Benchling and Airtable

Benchling is an impressive entity in its own right. Biotech R&D and health care nuances go right over my head. But the research and digging I've been doing in the name of these burritos (case studies) revealed that these products are immensely complex. 

And that's precisely why this case study deserves a read—it succeeds at explaining a complex project that readers outside the industry wouldn't know much about.

Takeaway: Simplify complex information, and walk readers through the company's operations and how your business helped streamline them.

15. Chipotle and Hubble

The concision of this case study is refreshing. It features two sections—the challenge and the solution—all in 316 words. This goes to show that your case study doesn't necessarily need to be a four-figure investment with video shoots and studio time. 

Sometimes, the message is simple and short enough to convey in a handful of paragraphs.

Takeaway: Consider what you should include instead of what you can include. Assess the time, resources, and effort you're able and willing to invest in a case study, and choose which elements you want to include from there.

16. Hudl and Zapier

I may be biased, but I'm a big fan of seeing metrics and achievements represented in branded graphics. It can be a jarring experience to navigate a website, then visit a case study page and feel as though you've gone to a completely different website.

The Zapier format provides nuggets of high-level insights, milestones, and achievements, as well as the challenge, solution, and results. My favorite part of this case study is how it's supplemented with a blog post detailing how Hudl uses Zapier automation to build a seamless user experience.

The case study is essentially the summary, and the blog article is the detailed analysis that provides context beyond X achievement or Y goal.

Takeaway: Keep your case study concise and informative. Create other resources to provide context under your blog, media or press, and product pages.

3 case study templates

Now that you've had your fill of case studies (if that's possible), I've got just what you need: an infinite number of case studies, which you can create yourself with these case study templates.

Case study template 1

If you've got a quick hit of stats you want to show off, try this template. The opening section gives space for a short summary and three visually appealing stats you can highlight, followed by a headline and body where you can break the case study down more thoroughly. This one's pretty simple, with only sections for solutions and results, but you can easily continue the formatting to add more sections as needed.

Case study template 2

For a case study template with a little more detail, use this one. Opening with a striking cover page for a quick overview, this one goes on to include context, stakeholders, challenges, multiple quote callouts, and quick-hit stats. 

Case study template 3

Whether you want a little structural variation or just like a nice dark green, this template has similar components to the last template but is designed to help tell a story. Move from the client overview through a description of your company before getting to the details of how you fixed said company's problems.

Tips for writing a case study

Examples are all well and good, but you don't learn how to make a burrito just by watching tutorials on YouTube without knowing what any of the ingredients are. You could , but it probably wouldn't be all that good.

Writing a good case study comes down to a mix of creativity, branding, and the capacity to invest in the project. With those details in mind, here are some case study tips to follow:

Have an objective: Define your objective by identifying the challenge, solution, and results. Assess your work with the client and focus on the most prominent wins. You're speaking to multiple businesses and industries through the case study, so make sure you know what you want to say to them.

Focus on persuasive data: Growth percentages and measurable results are your best friends. Extract your most compelling data and highlight it in your case study.

Use eye-grabbing graphics: Branded design goes a long way in accurately representing your brand and retaining readers as they review the study. Leverage unique and eye-catching graphics to keep readers engaged. 

Simplify data presentation: Some industries are more complex than others, and sometimes, data can be difficult to understand at a glance. Make sure you present your data in the simplest way possible. Make it concise, informative, and easy to understand.

Use automation to drive results for your case study

A case study example is a source of inspiration you can leverage to determine how to best position your brand's work. Find your unique angle, and refine it over time to help your business stand out. Ask anyone: the best burrito in town doesn't just appear at the number one spot. They find their angle (usually the house sauce) and leverage it to stand out.

In fact, with the right technology, it can be refined to work better . Explore how Zapier's automation features can help drive results for your case study by making your case study a part of a developed workflow that creates a user journey through your website, your case studies, and into the pipeline.

Case study FAQ

Got your case study template? Great—it's time to gather the team for an awkward semi-vague data collection task. While you do that, here are some case study quick answers for you to skim through while you contemplate what to call your team meeting.

What is an example of a case study?

An example of a case study is when a software company analyzes its results from a client project and creates a webpage, presentation, or document that focuses on high-level results, challenges, and solutions in an attempt to showcase effectiveness and promote the software.

How do you write a case study?

To write a good case study, you should have an objective, identify persuasive and compelling data, leverage graphics, and simplify data. Case studies typically include an analysis of the challenge, solution, and results of the partnership.

What is the format of a case study?

While case studies don't have a set format, they're often portrayed as reports or essays that inform readers about the partnership and its results. 

Related reading:

How Hudl uses automation to create a seamless user experience

How to make your case studies high-stakes—and why it matters

How experts write case studies that convert, not bore

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Hachem Ramki

Hachem is a writer and digital marketer from Montreal. After graduating with a degree in English, Hachem spent seven years traveling around the world before moving to Canada. When he's not writing, he enjoys Basketball, Dungeons and Dragons, and playing music for friends and family.

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Exploratory Data Analysis (EDA) – Retail Case Study Example (Part 3)

Exploratory data analysis for Soccer – by Roopam

For the last couple of weeks we have been working on a marketing analytics case study example (read Part 1 and Part 2 ). In the last part ( Part 2 ) we defined a couple of advanced analytics objectives based on the business problem at an online retail company called DresSmart Inc. In this part, we will perform some exploratory data analysis as a part of the same case study example. But before that let’s explore the power of exploratory data analysis (EDA) to reveal hidden facts about the greatest game on the planet – soccer or football.

Soccer – Exploratory Data Analysis

Soccer is undoubtedly the most popular game on the planet with over 200 nations having their official soccer teams. No other game has such a universal appeal with millions of hardcore followers.  Every detail of soccer is analyzed by the players, the coaches and the support staff. Despite this, a careful exploratory data analysis of the game could unravel match-winning secrets about the greatest game, as you will see in the next two example case studies.

Penalty Kicks

Let’s relive the first knockout (pre-quarterfinal) match of the Soccer World Cup 2014 between Brazil and Chile. The scores were level at 1-1 at the end of allotted 90 minutes. Even the extra half an hour could not conclude the match with the scoreboard still reading 1-1. This led the match towards penalty shoot-outs to break the tie. After the Brazilian player, Neymar, scored the goal in the penultimate penalty kick, Brazil  were 3-2 ahead in the penalty shootouts. Chile still has a penalty kick left from Gonzalo Jara and the opportunity to extend the tie further – but if he misses Chile’s campaign will be over in the competition. What should Gonzalo Jara do to extend the tie?

Gonzalo Jara’s Kick – Source: irishtimes.com

On average, at this level around 75% penalty kicks convert to goals. The odds, by this definition, are highly in favor of Gonzalo Jara. Where should he kick the ball to improve his odds further? All the fans, coaches, and players will say kick the ball in either corner, away from the goalkeeper who is standing in the center of the goal. They will also advise never to shoot the ball at the dead center towards the goalkeeper. A group of researchers asked the same question and did the exploratory data analysis of penalty kicks at the elite level of soccer. Goalkeepers usually go by their instincts when the ball is kicked at them with undecipherable pace. They either jump towards their left (57% of times) or right (41% of times). This leaves them at the center just 2% of times to stop the ball hit right towards them. Hence, a kick hit dead towards the center of the goal has significantly higher chances of conversion to goal then kicks on either corner at the same height.

Back to Gonzalo Jara, he hits the ball towards his right, in the direction of the diving goalkeeper as shown in the picture above. He misses the shot, the ball hits the goal post and ricochets away from the goal. As a result, Chile got knocked out of the world cup and Brazil advanced to the next stage. In Gonzalo Jara’s defense, the conversion rate for crucial penalty kicks like this one (to avoid elimination) drops to 44%. Yes, pressure is another beast to which even the best succumb.

Corner Kicks

In another case, a few years ago Manchester City’s soccer team was struggling with corner kicks and hence decided to do some exploratory data analysis to differentiate effective corner kicks from ineffective. The team of analysts analyzed hundreds of videos of corner kicks from the premier league. After their analysis, they found that in-swinging kicks towards the goal were far more effective and dangerous than the out-swinging kicks. They took their findings to Roberto Mancini, the coach of  Manchester City team at that time. Mancini, who has played and followed the game since his childhood, rejected the findings outrightly. He recalled all those memorable and picture perfects goals by great headers of out-swingers. On the other hand, clumsy goals of in-swingers hardly created a lasting impression on the spectators’ mind. Mancini, it turned out, was wrong. All that looks great and memorable is not always optimal. This is a great case for how simple but sincere exploratory data analysis can challenge the deeply ingrained beliefs developed over centuries (yes, soccer is a really old game).

Exploratory Data Analysis – Retail Case Study Example

Back to our case study example (read  Part 1  and  Part 2 ), in which you are  the chief analytics officer & business strategy head at an online shopping store called DresSMart Inc. You are helping out the CMO of the company to enhance the company’s campaigns’ results. For the last few days, you are playing around with data as a part of exploratory data analysis. The following is one of the several interesting results and patterns you have noticed in the data. When you analyzed the distribution of customers across a number of product categories (men’s shirt, casual trousers, formal skirts etc.) purchased by each customer you found the following pattern.

Exploratory data analysis – marketing analytics case study (retail)

The above distribution looks more or less as expected. However, there is an interesting peak for customers purchasing more than 50 product-categories. Who are these customers? Why are they buying so many product categories for their usage? You further analyzed this small set of customers and found that they are growing at a faster rate than the other set of customers. Since the inception of the company 7 years ago, the percentage of customers purchasing 50+ product categories in a year has exponentially gone up (currently at 2.1%). This set of customers also contributes to about 23% of all the sales for DresSMart Inc. The following graphs are part of your above analysis.

Exploratory data analysis

So, what is going on here? You further analyzed the patterns and size(s) of clothes these customers are buying and noticed they are buying the same style in different sizes. Aha! Now you know them, these are small neighborhood retailers using DresSMart Inc as a wholesaler. The following is what you concluded from the above analysis

• There is no point sending these retailers the same retail product catalog and campaign as to retail customers
• There is an opportunity to strengthen business ties with these mom-&-pop retailers and in turn, improve profitability of your company through a separate business program

Additionally, your further analysis revealed that order fulfillment or delivery patterns (delivery quantity / chargers etc.)  for these retailers are similar to other customers. Your company is incurring additional cost for these customers in delivery. You could plan the overall supply chain much better keeping these small retailers in the equation. This exploratory data analysis has given you ideas for more low hanging fruits to improve company’s profitability.

Sign-off Note

Exploratory data analysis is a powerful tool. A diligent EDA is an absolute must to put your advanced business analytics in the right direction. EDA provides a great opportunity to test your simple business hypotheses and hunches before jumping into a rigorous model building. Coming back to soccer, we are approaching the final stages of the World Cup. Enjoy the last few games and may the best team lift the prized trophy.

8 thoughts on “ Exploratory Data Analysis (EDA) – Retail Case Study Example (Part 3) ”

Roopam, Excellent way to kick-start the core of the case study. Having spent a fair bit of time in Marketing Analytics (not core modeling, but a lot of EDA and A/B scenarios), I kind of have a hunch where this is going to go – excellent work. But, just out of curiosity, where do you pick up these case studies from? The reason I ask is because, the data though very interesting, is very case specific and may not apply to situations most of us may encounter in real life. As you said, EDA is the key to analysis before jumping right in, and sometimes it’s very painful and tedious – because there are no obvious trends or insights. I have sometimes spent hours slicing and dicing data before I could really form a hypothesis and test it (which by the way was less painful). Any tips / tricks to your readers like me, who could really save some time on EDA ?

P.S. I have to admit, all of your case studies do seem real and may well be so, but I would be wary to admit if any of us could directly find same or similar trends in our data (that would seem too good to be true ;-))

Thanks Kisalay for your kind words! All these cases in some form or other come from the work I have done at various stages of my career. Of course, I take a lot of creative liberty to completely modify information, trends, storylines, scenarios, and conclusions to protect confidentiality. Additionally, I also try to make the cases easy to understand for the readers. However, for most of these cases the general principles of analysis and logical flow is preserved to a greater extent.

I agree EDA is a tedious exercise but it also makes one feel like a detective 🙂 . Let me share my strategy for EDA, I never touch data before having a plan of action. Like a detective investigation you might destroy evidence if you go in without a plan. I usually prefer to have a mental map of my analysis and logical flow before I start slicing and dicing data. It makes me feel much more in control. I also prefer to have a reasonably defined hypothesis based on a business hunch before analysis. Also when you get completely stuck, take a long break away from your computer – fresh air usually helps.

In case, you have to mine a completely unknown data use machine learning algorithms like decision trees, apriori etc. to slice and dice your data. At times you may have to create your own modified algorithms specific to your requirements. Machines, I am completely sure, are any day better than us humans at this task.

I gone through your blogs with a keen intrest to develop Data Analytics skill from scratch.

As you said in one of your article is ” The best way to develop analytics skill is to have a project in your existing job itself “.

I want to have project in my existing job, i am working for a Furniture Manufacturing company in Sales department . This company manufacture house hold furniture and office furniture at massive scale in central India.

I am an Industrial Engineering graduate passout 2015, my 10th score in maths 147/150 .

I want to have career in data science, please guide me the learning path.

Kapil, to create an analytics opportunity in your company I suggest you answer these questions:

– Is there an analytics team in your company? If yes, what kind of business questions this team usually work on?

– If the answer to the above question is no, are there IT systems (ERP, MIS etc.) available in your company? What kind of data fields could be retrieved from these systems? Talk to your IT team to learn more about it.

– What are some of the quick business questions you could answer using the above data? Focus on important questions but simple analysis to begin with.

Since you are in sales with experience in industrial engineering, I suggest you build your analytical skills on top of your core skills. Supply chain analytics is a major area of growth with lots of opportunities. If you could deliver a few simple yet successful projects in your company it will make your CV really powerful. All the best.

Till now there is no analytics team in company, but needs one who can do analytics, i want to fill this gap.

According to your guidance, i discussed with my IT team about the systems available and the kind of data field can get retrieve so that we can answer some basic questions, but to think strategically we are not trained enough. Here i want do a simple analysis project.

To have more clarity, I also prepared three columns in excel with title IT Systems, Data fields and Quick business questions .

I will be very fortunate if you can guide me in the direction to improve my analytical skill and have a simple data analysis project at the same time .

HI, can you share data for this case study, So I will get practical exposure to this problem. Your blogs are very intuitive and easy to understand.

I got some rough data with 20 columns & 5000 No. row data. There is no exact details of data for what this data is & no nomenclature for the data.

with this open ended problem wherein no problem has been defined.

So, can we do data paralytics for such data….?

Nice post regarding Data Analysis.

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Tareq Miah | Architect & Designer

Writing A Case Study

Case Study Examples

Brilliant Case Study Examples and Templates For Your Help

15 min read

People also read

A Complete Case Study Writing Guide With Examples

Simple Case Study Format for Students to Follow

Understand the Types of Case Study Here

It’s no surprise that writing a case study is one of the most challenging academic tasks for students. You’re definitely not alone here!

Most people don't realize that there are specific guidelines to follow when writing a case study. If you don't know where to start, it's easy to get overwhelmed and give up before you even begin.

Don't worry! Let us help you out!

We've collected over 25 free case study examples with solutions just for you. These samples with solutions will help you win over your panel and score high marks on your case studies.

So, what are you waiting for? Let's dive in and learn the secrets to writing a successful case study.

• 1. An Overview of Case Studies
• 2. Case Study Examples for Students
• 3. Business Case Study Examples
• 4. Medical Case Study Examples
• 5. Psychology Case Study Examples 
• 6. Sales Case Study Examples
• 7. Interview Case Study Examples
• 8. Marketing Case Study Examples
• 9. Tips to Write a Good Case Study

An Overview of Case Studies

A case study is a research method used to study a particular individual, group, or situation in depth. It involves analyzing and interpreting data from a variety of sources to gain insight into the subject being studied. 

Case studies are often used in psychology, business, and education to explore complicated problems and find solutions. They usually have detailed descriptions of the subject, background info, and an analysis of the main issues.

The goal of a case study is to provide a comprehensive understanding of the subject. Typically, case studies can be divided into three parts, challenges, solutions, and results. 

Here is a case study sample PDF so you can have a clearer understanding of what a case study actually is:

Case Study Sample PDF

How to Write a Case Study Examples

Learn how to write a case study with the help of our comprehensive case study guide.

Case Study Examples for Students

Quite often, students are asked to present case studies in their academic journeys. The reason instructors assign case studies is for students to sharpen their critical analysis skills, understand how companies make profits, etc.

Below are some case study examples in research, suitable for students:

Case Study Example in Software Engineering

Qualitative Research Case Study Sample

Software Quality Assurance Case Study

Social Work Case Study Example

Ethical Case Study

Case Study Example PDF

These examples can guide you on how to structure and format your own case studies.

Struggling with formatting your case study? Check this case study format guide and perfect your document’s structure today.

Business Case Study Examples

A business case study examines a business’s specific challenge or goal and how it should be solved. Business case studies usually focus on several details related to the initial challenge and proposed solution. 

To help you out, here are some samples so you can create case studies that are related to businesses: 

Here are some more business case study examples:

Business Case Studies PDF

Business Case Studies Example

Typically, a business case study discovers one of your customer's stories and how you solved a problem for them. It allows your prospects to see how your solutions address their needs. 

Medical Case Study Examples

Medical case studies are an essential part of medical education. They help students to understand how to diagnose and treat patients. 

Here are some medical case study examples to help you.

Medical Case Study Example

Nursing Case Study Example

Want to understand the various types of case studies? Check out our types of case study blog to select the perfect type.

Psychology Case Study Examples 

Case studies are a great way of investigating individuals with psychological abnormalities. This is why it is a very common assignment in psychology courses. 

By examining all the aspects of your subject’s life, you discover the possible causes of exhibiting such behavior. 

For your help, here are some interesting psychology case study examples:

Psychology Case Study Example

Mental Health Case Study Example

Sales Case Study Examples

Case studies are important tools for sales teams’ performance improvement. By examining sales successes, teams can gain insights into effective strategies and create action plans to employ similar tactics.

By researching case studies of successful sales campaigns, sales teams can more accurately identify challenges and develop solutions.

Sales Case Study Example

Interview Case Study Examples

Interview case studies provide businesses with invaluable information. This data allows them to make informed decisions related to certain markets or subjects.

Interview Case Study Example

Marketing Case Study Examples

Marketing case studies are real-life stories that showcase how a business solves a problem. They typically discuss how a business achieves a goal using a specific marketing strategy or tactic.

They typically describe a challenge faced by a business, the solution implemented, and the results achieved.

This is a short sample marketing case study for you to get an idea of what an actual marketing case study looks like.

 Here are some more popular marketing studies that show how companies use case studies as a means of marketing and promotion:

“Chevrolet Discover the Unexpected” by Carol H. Williams

This case study explores Chevrolet's “ DTU Journalism Fellows ” program. The case study uses the initials “DTU” to generate interest and encourage readers to learn more. 

Multiple types of media, such as images and videos, are used to explain the challenges faced. The case study concludes with an overview of the achievements that were met.

Key points from the case study include:

• Using a well-known brand name in the title can create interest.
• Combining different media types, such as headings, images, and videos, can help engage readers and make the content more memorable.
• Providing a summary of the key achievements at the end of the case study can help readers better understand the project's impact.

“The Met” by Fantasy

“ The Met ” by Fantasy is a fictional redesign of the Metropolitan Museum of Art in New York City, created by the design studio Fantasy. The case study clearly and simply showcases the museum's website redesign.

The Met emphasizes the website’s features and interface by showcasing each section of the interface individually, allowing the readers to concentrate on the significant elements.

For those who prefer text, each feature includes an objective description. The case study also includes a “Contact Us” call-to-action at the bottom of the page, inviting visitors to contact the company.

Key points from this “The Met” include:

• Keeping the case study simple and clean can help readers focus on the most important aspects.
• Presenting the features and solutions with a visual showcase can be more effective than writing a lot of text.
• Including a clear call-to-action at the end of the case study can encourage visitors to contact the company for more information.

“Better Experiences for All” by Herman Miller

Herman Miller's minimalist approach to furniture design translates to their case study, “ Better Experiences for All ”, for a Dubai hospital. The page features a captivating video with closed-captioning and expandable text for accessibility.

The case study presents a wealth of information in a concise format, enabling users to grasp the complexities of the strategy with ease. It concludes with a client testimonial and a list of furniture items purchased from the brand.

Key points from the “Better Experiences” include:

• Make sure your case study is user-friendly by including accessibility features like closed captioning and expandable text.
• Include a list of products that were used in the project to guide potential customers.

“NetApp” by Evisort 

Evisort's case study on “ NetApp ” stands out for its informative and compelling approach. The study begins with a client-centric overview of NetApp, strategically directing attention to the client rather than the company or team involved.

The case study incorporates client quotes and explores NetApp’s challenges during COVID-19. Evisort showcases its value as a client partner by showing how its services supported NetApp through difficult times. 

• Provide an overview of the company in the client’s words, and put focus on the customer. 
• Highlight how your services can help clients during challenging times.
• Make your case study accessible by providing it in various formats.

“Red Sox Season Campaign,” by CTP Boston

The “ Red Sox Season Campaign ” showcases a perfect blend of different media, such as video, text, and images. Upon visiting the page, the video plays automatically, there are videos of Red Sox players, their images, and print ads that can be enlarged with a click.

The page features an intuitive design and invites viewers to appreciate CTP's well-rounded campaign for Boston's beloved baseball team. There’s also a CTA that prompts viewers to learn how CTP can create a similar campaign for their brand.

Some key points to take away from the “Red Sox Season Campaign”: 

• Including a variety of media such as video, images, and text can make your case study more engaging and compelling.
• Include a call-to-action at the end of your study that encourages viewers to take the next step towards becoming a customer or prospect.

“Airbnb + Zendesk” by Zendesk

The case study by Zendesk, titled “ Airbnb + Zendesk : Building a powerful solution together,” showcases a true partnership between Airbnb and Zendesk. 

The article begins with an intriguing opening statement, “Halfway around the globe is a place to stay with your name on it. At least for a weekend,” and uses stunning images of beautiful Airbnb locations to captivate readers.

Instead of solely highlighting Zendesk's product, the case study is crafted to tell a good story and highlight Airbnb's service in detail. This strategy makes the case study more authentic and relatable.

Some key points to take away from this case study are:

• Use client's offerings' images rather than just screenshots of your own product or service.
• To begin the case study, it is recommended to include a distinct CTA. For instance, Zendesk presents two alternatives, namely to initiate a trial or seek a solution.

“Influencer Marketing” by Trend and WarbyParker

The case study "Influencer Marketing" by Trend and Warby Parker highlights the potential of influencer content marketing, even when working with a limited budget. 

The “Wearing Warby” campaign involved influencers wearing Warby Parker glasses during their daily activities, providing a glimpse of the brand's products in use. 

This strategy enhanced the brand's relatability with influencers' followers. While not detailing specific tactics, the case study effectively illustrates the impact of third-person case studies in showcasing campaign results.

Key points to take away from this case study are:

• Influencer marketing can be effective even with a limited budget.
• Showcasing products being used in everyday life can make a brand more approachable and relatable.
• Third-person case studies can be useful in highlighting the success of a campaign.

Marketing Case Study Example

Marketing Case Study Template

Now that you have read multiple case study examples, hop on to our tips.

Tips to Write a Good Case Study

Here are some note-worthy tips to craft a winning case study 

• Define the purpose of the case study This will help you to focus on the most important aspects of the case. The case study objective helps to ensure that your finished product is concise and to the point.
• Choose a real-life example. One of the best ways to write a successful case study is to choose a real-life example. This will give your readers a chance to see how the concepts apply in a real-world setting.
• Keep it brief. This means that you should only include information that is directly relevant to your topic and avoid adding unnecessary details.
• Use strong evidence. To make your case study convincing, you will need to use strong evidence. This can include statistics, data from research studies, or quotes from experts in the field.
• Edit and proofread your work. Before you submit your case study, be sure to edit and proofread your work carefully. This will help to ensure that there are no errors and that your paper is clear and concise.

There you go!

We’re sure that now you have secrets to writing a great case study at your fingertips! This blog teaches the key guidelines of various case studies with samples. So grab your pen and start crafting a winning case study right away!

Having said that, we do understand that some of you might be having a hard time writing compelling case studies.

But worry not! Our expert case study writing service is here to take all your case-writing blues away! 

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All You Wanted to Know About How to Write a Case Study

What do you study in your college? If you are a psychology, sociology, or anthropology student, we bet you might be familiar with what a case study is. This research method is used to study a certain person, group, or situation. In this guide from our dissertation writing service , you will learn how to write a case study professionally, from researching to citing sources properly. Also, we will explore different types of case studies and show you examples — so that you won’t have any other questions left.

What Is a Case Study?

A case study is a subcategory of research design which investigates problems and offers solutions. Case studies can range from academic research studies to corporate promotional tools trying to sell an idea—their scope is quite vast.

What Is the Difference Between a Research Paper and a Case Study?

While research papers turn the reader’s attention to a certain problem, case studies go even further. Case study guidelines require students to pay attention to details, examining issues closely and in-depth using different research methods. For example, case studies may be used to examine court cases if you study Law, or a patient's health history if you study Medicine. Case studies are also used in Marketing, which are thorough, empirically supported analysis of a good or service's performance. Well-designed case studies can be valuable for prospective customers as they can identify and solve the potential customers pain point.

Case studies involve a lot of storytelling – they usually examine particular cases for a person or a group of people. This method of research is very helpful, as it is very practical and can give a lot of hands-on information. Most commonly, the length of the case study is about 500-900 words, which is much less than the length of an average research paper.

The structure of a case study is very similar to storytelling. It has a protagonist or main character, which in your case is actually a problem you are trying to solve. You can use the system of 3 Acts to make it a compelling story. It should have an introduction, rising action, a climax where transformation occurs, falling action, and a solution.

Here is a rough formula for you to use in your case study:

Problem (Act I): > Solution (Act II) > Result (Act III) > Conclusion.

Types of Case Studies

The purpose of a case study is to provide detailed reports on an event, an institution, a place, future customers, or pretty much anything. There are a few common types of case study, but the type depends on the topic. The following are the most common domains where case studies are needed:

• Historical case studies are great to learn from. Historical events have a multitude of source info offering different perspectives. There are always modern parallels where these perspectives can be applied, compared, and thoroughly analyzed.
• Problem-oriented case studies are usually used for solving problems. These are often assigned as theoretical situations where you need to immerse yourself in the situation to examine it. Imagine you’re working for a startup and you’ve just noticed a significant flaw in your product’s design. Before taking it to the senior manager, you want to do a comprehensive study on the issue and provide solutions. On a greater scale, problem-oriented case studies are a vital part of relevant socio-economic discussions.
• Cumulative case studies collect information and offer comparisons. In business, case studies are often used to tell people about the value of a product.
• Critical case studies explore the causes and effects of a certain case.
• Illustrative case studies describe certain events, investigating outcomes and lessons learned.

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Case Study Format

The case study format is typically made up of eight parts:

• Executive Summary. Explain what you will examine in the case study. Write an overview of the field you’re researching. Make a thesis statement and sum up the results of your observation in a maximum of 2 sentences.
• Background. Provide background information and the most relevant facts. Isolate the issues.
• Case Evaluation. Isolate the sections of the study you want to focus on. In it, explain why something is working or is not working.
• Proposed Solutions. Offer realistic ways to solve what isn’t working or how to improve its current condition. Explain why these solutions work by offering testable evidence.
• Conclusion. Summarize the main points from the case evaluations and proposed solutions. 6. Recommendations. Talk about the strategy that you should choose. Explain why this choice is the most appropriate.
• Implementation. Explain how to put the specific strategies into action.
• References. Provide all the citations.

How to Write a Case Study

Let's discover how to write a case study.

Setting Up the Research

When writing a case study, remember that research should always come first. Reading many different sources and analyzing other points of view will help you come up with more creative solutions. You can also conduct an actual interview to thoroughly investigate the customer story that you'll need for your case study. Including all of the necessary research, writing a case study may take some time. The research process involves doing the following:

• Define your objective. Explain the reason why you’re presenting your subject. Figure out where you will feature your case study; whether it is written, on video, shown as an infographic, streamed as a podcast, etc.
• Determine who will be the right candidate for your case study. Get permission, quotes, and other features that will make your case study effective. Get in touch with your candidate to see if they approve of being part of your work. Study that candidate’s situation and note down what caused it.
• Identify which various consequences could result from the situation. Follow these guidelines on how to start a case study: surf the net to find some general information you might find useful.
• Make a list of credible sources and examine them. Seek out important facts and highlight problems. Always write down your ideas and make sure to brainstorm.
• Focus on several key issues – why they exist, and how they impact your research subject. Think of several unique solutions. Draw from class discussions, readings, and personal experience. When writing a case study, focus on the best solution and explore it in depth. After having all your research in place, writing a case study will be easy. You may first want to check the rubric and criteria of your assignment for the correct case study structure.

Read Also: ' WHAT IS A CREDIBLE SOURCES ?'

Although your instructor might be looking at slightly different criteria, every case study rubric essentially has the same standards. Your professor will want you to exhibit 8 different outcomes:

• Correctly identify the concepts, theories, and practices in the discipline.
• Identify the relevant theories and principles associated with the particular study.
• Evaluate legal and ethical principles and apply them to your decision-making.
• Recognize the global importance and contribution of your case.
• Construct a coherent summary and explanation of the study.
• Demonstrate analytical and critical-thinking skills.
• Explain the interrelationships between the environment and nature.
• Integrate theory and practice of the discipline within the analysis.

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Case Study Outline

Let's look at the structure of an outline based on the issue of the alcoholic addiction of 30 people.

Introduction

• Statement of the issue: Alcoholism is a disease rather than a weakness of character.
• Presentation of the problem: Alcoholism is affecting more than 14 million people in the USA, which makes it the third most common mental illness there.
• Explanation of the terms: In the past, alcoholism was commonly referred to as alcohol dependence or alcohol addiction. Alcoholism is now the more severe stage of this addiction in the disorder spectrum.
• Hypotheses: Drinking in excess can lead to the use of other drugs.
• Importance of your story: How the information you present can help people with their addictions.
• Background of the story: Include an explanation of why you chose this topic.
• Presentation of analysis and data: Describe the criteria for choosing 30 candidates, the structure of the interview, and the outcomes.
• Strong argument 1: ex. X% of candidates dealing with anxiety and depression...
• Strong argument 2: ex. X amount of people started drinking by their mid-teens.
• Strong argument 3: ex. X% of respondents’ parents had issues with alcohol.
• Concluding statement: I have researched if alcoholism is a disease and found out that…
• Recommendations: Ways and actions for preventing alcohol use.

Writing a Case Study Draft

After you’ve done your case study research and written the outline, it’s time to focus on the draft. In a draft, you have to develop and write your case study by using: the data which you collected throughout the research, interviews, and the analysis processes that were undertaken. Follow these rules for the draft:

• Your draft should contain at least 4 sections: an introduction; a body where you should include background information, an explanation of why you decided to do this case study, and a presentation of your main findings; a conclusion where you present data; and references.
• In the introduction, you should set the pace very clearly. You can even raise a question or quote someone you interviewed in the research phase. It must provide adequate background information on the topic. The background may include analyses of previous studies on your topic. Include the aim of your case here as well. Think of it as a thesis statement. The aim must describe the purpose of your work—presenting the issues that you want to tackle. Include background information, such as photos or videos you used when doing the research.
• Describe your unique research process, whether it was through interviews, observations, academic journals, etc. The next point includes providing the results of your research. Tell the audience what you found out. Why is this important, and what could be learned from it? Discuss the real implications of the problem and its significance in the world.
• Include quotes and data (such as findings, percentages, and awards). This will add a personal touch and better credibility to the case you present. Explain what results you find during your interviews in regards to the problem and how it developed. Also, write about solutions which have already been proposed by other people who have already written about this case.
• At the end of your case study, you should offer possible solutions, but don’t worry about solving them yourself.

Use Data to Illustrate Key Points in Your Case Study

Even though your case study is a story, it should be based on evidence. Use as much data as possible to illustrate your point. Without the right data, your case study may appear weak and the readers may not be able to relate to your issue as much as they should. Let's see the examples from essay writing service :

‍ With data: Alcoholism is affecting more than 14 million people in the USA, which makes it the third most common mental illness there. Without data: A lot of people suffer from alcoholism in the United States.

Try to include as many credible sources as possible. You may have terms or sources that could be hard for other cultures to understand. If this is the case, you should include them in the appendix or Notes for the Instructor or Professor.

Finalizing the Draft: Checklist

After you finish drafting your case study, polish it up by answering these ‘ask yourself’ questions and think about how to end your case study:

• Check that you follow the correct case study format, also in regards to text formatting.
• Check that your work is consistent with its referencing and citation style.
• Micro-editing — check for grammar and spelling issues.
• Macro-editing — does ‘the big picture’ come across to the reader? Is there enough raw data, such as real-life examples or personal experiences? Have you made your data collection process completely transparent? Does your analysis provide a clear conclusion, allowing for further research and practice?

Problems to avoid:

• Overgeneralization – Do not go into further research that deviates from the main problem.
• Failure to Document Limitations – Just as you have to clearly state the limitations of a general research study, you must describe the specific limitations inherent in the subject of analysis.
• Failure to Extrapolate All Possible Implications – Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings.

How to Create a Title Page and Cite a Case Study

Let's see how to create an awesome title page.

Your title page depends on the prescribed citation format. The title page should include:

• A title that attracts some attention and describes your study
• The title should have the words “case study” in it
• The title should range between 5-9 words in length
• Your name and contact information
• Your finished paper should be only 500 to 1,500 words in length.With this type of assignment, write effectively and avoid fluff

Here is a template for the APA and MLA format title page:

There are some cases when you need to cite someone else's study in your own one – therefore, you need to master how to cite a case study. A case study is like a research paper when it comes to citations. You can cite it like you cite a book, depending on what style you need.

Citation Example in MLA ‍ Hill, Linda, Tarun Khanna, and Emily A. Stecker. HCL Technologies. Boston: Harvard Business Publishing, 2008. Print.

Citation Example in APA ‍ Hill, L., Khanna, T., & Stecker, E. A. (2008). HCL Technologies. Boston: Harvard Business Publishing.

Citation Example in Chicago Hill, Linda, Tarun Khanna, and Emily A. Stecker. HCL Technologies.

Case Study Examples

To give you an idea of a professional case study example, we gathered and linked some below.

Eastman Kodak Case Study

Case Study Example: Audi Trains Mexican Autoworkers in Germany

To conclude, a case study is one of the best methods of getting an overview of what happened to a person, a group, or a situation in practice. It allows you to have an in-depth glance at the real-life problems that businesses, healthcare industry, criminal justice, etc. may face. This insight helps us look at such situations in a different light. This is because we see scenarios that we otherwise would not, without necessarily being there. If you need custom essays , try our research paper writing services .

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Crafting a case study is not easy. You might want to write one of high quality, but you don’t have the time or expertise. If you’re having trouble with your case study, help with essay request - we'll help. EssayPro writers have read and written countless case studies and are experts in endless disciplines. Request essay writing, editing, or proofreading assistance from our custom case study writing service , and all of your worries will be gone.

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What Is A Case Study?

How to cite a case study in apa, how to write a case study, related articles.

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Study designs: Part 3 - Analytical observational studies

Priya ranganathan.

Department of Anaesthesiology, Tata Memorial Centre, Mumbai, Maharashtra, India

Rakesh Aggarwal

1 Director, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India

In analytical observational studies, researchers try to establish an association between exposure(s) and outcome(s). Depending on the direction of enquiry, these studies can be directed forwards (cohort studies) or backwards (case–control studies). In this article, we examine the key features of these two types of studies.

INTRODUCTION

In a previous article[ 1 ] in this series, we looked at descriptive observational studies, namely case reports, case series, cross-sectional studies, and ecological studies. As compared to descriptive studies which merely describe one or more variables in a sample (or occasionally population), analytical studies attempt to quantify a relationship or association between two variables – an exposure and an outcome. As discussed previously, in observational analytical studies, the exposure is naturally determined as opposed to experimental studies where an investigator assigns each subject to receive or not receive a particular exposure.

COHORT STUDIES

A cohort is defined as a “group of people with a shared characteristic.” In cohort studies, different groups of people with varying levels of exposure are followed over time to evaluate the occurrence of an outcome. These participants have to be free of the outcome at baseline. The presence or absence of the risk factor (exposure) in each subject is recorded. The subjects are then followed up over time (longitudinally) to determine the occurrence of the outcome. Thus, cohort studies are forward-direction studies (moving from exposure to outcome) and are typically prospective studies (the outcome has not occurred at the start of the study).

An example of cohort study design is a study by Viljakainen et al ., which investigated the relation between maternal vitamin D levels during pregnancy and the bone health in their newborns.[ 2 ] Maternal blood vitamin D levels were estimated during pregnancy. Children born to these mothers were then followed up until 14 months of age, and bone parameters were evaluated. Based on the maternal serum 25-hydroxy vitamin D levels during pregnancy, children were divided into two groups – those born to mothers with normal blood vitamin D and those born to mothers with low blood vitamin D. The authors found that children born to mothers with low vitamin D levels had persistent bone abnormalities.

Advantages of cohort studies

• For an exposure to be causative, it must precede the outcome. In a cohort study, one starts with subjects who are known to have or not have the exposure and are free of the outcome at the start of the study, and the outcome develops later. Hence, one is certain that the exposure preceded the outcome, and temporality (and therefore probable causality) can be established. In the above example, one can be certain that the maternal vitamin D deficiency preceded the bone abnormalities.
• For a given exposure, more than one outcome can be studied. In the above example, the authors compared not only bone growth but also the age at which the babies born to low and high vitamin D mothers started walking independently.
• In cohort studies, often several exposures can be studied simultaneously. For this, the investigators begin by assessing several 'exposures', for example, age, sex, smoking status, diabetes, and obesity/overweight status in every member of a population. The entire population is then followed for the outcome of interest, for example, coronary artery disease. At the end of the follow-up, the data can then be analyzed for several contrasting cohorts defined by levels of each “exposure” – old/young, male/female, smoker/nonsmoker, diabetic/nondiabetic, and underweight/ideal body weight/overweight/obese, etc.

Limitations of cohort studies

• Cohort studies often require a long duration of follow-up to determine whether outcome will occur or not. This duration depends on the exposure-outcome pair. In the above example, a follow-up of at least 14 months was used. An even longer follow-up over several years or decades may be necessary – for instance, in the above example, if the investigators wanted to study whether maternal vitamin D levels influence the final height of a person, they would have needed to follow the babies till adolescence. During such follow-up, losses to follow-up, and logistic and cost issues pose major challenges.
• It is not uncommon for one or more unknown confounding factors to affect the occurrence of outcome. For example, in a cohort study looking at coffee drinking as a risk factor for pancreatic cancer, people who drink a large amount of coffee may also be consuming alcohol. In such cases, the finding that coffee drinkers have an increased occurrence of pancreatic cancer may lead the investigator to incorrectly conclude that drinking coffee increases the risk of pancreatic cancer, whereas it is the consumption of alcohol which is the true risk factor. Similarly, in the above study, the mothers with low and high vitamin D levels could have been different in another factor, e.g. overall nutrition or socioeconomic status, and that could be the real reason for the differences in the babies' bone health.

Uses of cohort studies

• Since cohort study design closely resembles the experimental design with the only difference being lack of random assignment to exposure, it is considered as having a greater validity compared to the other observational study designs.
• Since one starts with subjects known to have or not have exposure, one can determine the risk of outcome among exposed persons and unexposed persons, as also the relative risk.
• In situations where experimental studies are not feasible (e.g., when it is either unethical to randomize participants to a potentially harmful intervention, such as smoking, or impractical to create an exposure, such as diabetes or hypertension), cohort studies are a reasonable and arguably the best alternative.

Variations of cohort studies

Sometimes, a researcher may look back at data which have already been collected. For example, let us think of a hospital that records every patient's smoking status at the time of the first visit. A researcher may use these records from 10 years ago, and then contact the persons today to check if any of them have already been diagnosed or currently have features of lung cancer. This is still a forward-direction study (exposure traced forward among exposed and unexposed to outcome) but is retrospective (since the outcome may have already occurred). Such studies are known as 'retrospective cohort studies'.

Large cohort studies, such as the Framingham Heart Study or the Nurses' Health Study, have yielded extremely useful information about risk factors for several chronic diseases.

CASE-CONTROL STUDIES

In case-control studies, the researcher first enrolls cases (participants with the outcome) and controls (participants without the outcome) and then tries to elicit a history of exposure in each group. Thus, these are backward-direction studies (looking from outcome to exposure) and are always retrospective (the outcome must have occurred when the study starts). Typically, cases are identified from hospital records, death certificates or disease registries. This is followed by the identification and enrolment of controls.

Identification of appropriate controls is a key element of the case-control study design and can influence the estimate of association between exposure and outcome (selection bias). The controls should resemble cases in all respects, except for the absence of disease. Thus, they should be representative of the population from which the cases were drawn. For instance, if cases are drawn from a community clinic, an outpatient clinic or an inpatient setting, the controls should also ideally be from the same setting.

Sometimes, controls are individually matched with cases for factors (except for the one which is the exposure of interest) which are considered important to the development of the outcome. For example, in a study on relation of smoking with lung cancer, for each case of lung cancer enrolled, one control with similar age and sex is enrolled. This would reduce the risk of confounding by age and sex – the factors used for matching. Sometimes, the number of controls per case may be larger (e.g. two, three, or more).

Furthermore, to minimize assessment bias, it is important that the person assessing the history of exposure (e.g., smoking in this case) is unaware of (blinded to) whether the participant being interviewed is a case or a control.

For example, Anderson et al . conducted a case–control study to look at risk factors for childhood fractures.[ 3 ] They recruited cases from a hospital fracture clinic and individually matched controls (children without fractures) from a primary care research network. The cases and controls were matched on age, sex, height, and season. They found that the history of previous use of vitamin D supplements was significantly higher in the children without fractures, suggesting an inverse association between vitamin D supplementation and incidence of fractures.

Advantages of case–control studies

• Case-control studies are often cheap, and less time-consuming than cohort studies.
• Once cases and controls are identified and enrolled, it is often easy to study the relationship of outcome with not one but several exposures.

Limitations of case–control studies

• In case-control studies, temporality (whether the outcome or exposure occurred first) is often difficult to establish.
• There may be a bias in selecting cases or controls. For instance, if the cases studied differ from the entire pool of cases of a disease in an important characteristic, then the results of the study may apply only to the selected type of cases and not to the entire population of cases. In the above example,[ 3 ] the cases and controls were derived from different sources, and it is possible that the children that attended the hospital fracture clinic had different socioeconomic backgrounds to those attending the primary care facility from where controls were enrolled.
• Confounding factors, as discussed in cohort studies, also apply to case-control studies. For instance, the children with fractures and controls could have had different overall food intake, milk intake, and outdoor play time. These factors could influence both the likelihood of prior use of vitamin D supplements (exposure) and the risk of fracture (outcome), affecting the measurement of their association.
• The determination of exposure relies on existing records or history taking. Either can be problematic. The records may not contain information on exposure or contain erroneous data (e.g., those collected perfunctorily). This is particularly challenging if the missing or unreliable data are more likely to be present in one of the two groups being compared – cases or controls (misinformation bias). During history taking, cases may be more likely to recall exposure than controls (recall bias), for example, the mother of a child with a congenital anomaly is more likely to recall drugs ingested during pregnancy than a mother with a normal child. In the study by Anderson et al,[ 3 ] the mothers of children with fractures could have underestimated the amount of vitamin D their children have received, believing that this was the reason for the occurrence of fracture.
• Finally, since case–control studies are backward-directed, there is no “at risk” group at the start of the study; therefore, the determination of “risk” (and relative risk or risk ratio) is not possible, and one can only estimate “odds” (and odds ratio). For a detailed discussion on this, please refer to a previous article.[ 4 ]

Uses of case–control studies

• Case-control studies are ideal for rare diseases, where identifying cases is easier than following up large numbers of exposed persons to determine outcome.
• Case-control studies, because of their simplicity and need for fewer resources, are often the initial study design used to assess the relationship of a particular exposure and an outcome. If this study is positive, then a study with more complex and robust study design (cohort or interventional) can be undertaken.

A special variation of case–control study design

Nested case-control design is a special type of case-control study design which is built into a cohort study. From the main cohorts, participants who develop the outcome (irrespective of whether exposed or unexposed) are chosen as cases. From among the remaining study participants who have not developed the outcome, a subset of matched controls are selected. The cases and controls are then compared with respect to exposure. This is still a backward-direction (since the enquiry begins with outcome and then proceeds toward exposure) and retrospective study (since outcomes have already occurred when the study starts). The main advantage is that since one knows that the outcome had not occurred when the cohorts were established, temporal relation of exposure and outcome is ensured.

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15 Inspiring LinkedIn Post Ideas (+ Examples) for Your Page

Written by by Mahnoor Sheikh

Published on  April 23, 2024

Reading time  6 minutes

LinkedIn is one of the most effective channels for building brand awareness, connecting with customers and establishing thought leadership.

Moreover, with 4 out of 5 LinkedIn members driving business decisions, the network is rated #1 for B2B lead generation. As a marketer, you cannot afford to overlook LinkedIn.

But what types of content should you be posting on LinkedIn? In this article, we’ll explore various content formats that work well on the platform and provide post ideas and examples you can adapt for your own LinkedIn marketing strategy .

Why should you post on LinkedIn?

Using LinkedIn for business can benefit you in more than one way. Here are three reasons why you should start posting on LinkedIn regularly as a brand or employee:

Increase brand awareness

LinkedIn is a great platform to show off your expertise and values to a professional audience. Consistently posting high-quality content on LinkedIn can increase your brand’s visibility, especially if you’re using both organic and paid strategies.

The platform’s advanced targeting tools also ensure your posts are seen by the most relevant audiences. This translates into more followers, engagement and leads for your brand.

Expand your network

LinkedIn has over 1 billion members worldwide. This massive user base offers brands a huge opportunity to connect with industry peers and thought leaders as well as potential customers, employees and partners.

Join hundreds of conversations happening on LinkedIn by posting about trending topics, engaging with other posts, asking questions and offering unique insights and opinions. You can also join LinkedIn groups and contribute to articles to establish authority and build your network.

Develop trust and relationships

By consistently providing value to your audience through informative, authentic and engaging content, you can establish yourself as a reliable and trustworthy source of information.

This trust can help build stronger relationships with your followers, who may be more likely to do business with you or recommend your brand to others.

15 LinkedIn post ideas and examples

Below, you’ll find creative LinkedIn post ideas to help you establish a strong brand presence on the platform and grow your following. We’ve also included real-life examples from top brands to inspire you.

1. Poll your audience

Polls are an excellent way to encourage interaction, spark conversations and gather opinions and preferences. They’re also great tools for collecting feedback and analyzing customer sentiment around your brand, products or services.

Image source

LinkedIn allows you to customize the visibility and duration of your polls so you can gather timely and relevant insights. You can also view poll results as a percentage or number of votes, and share them with your audience.

2. Ask questions or solve problems

Ask thought-provoking questions or offer actionable insights or solutions to help your followers overcome challenges and achieve their goals.

This does two things:

• It builds your credibility and positions you as an expert
• It boosts engagement (likes, comments and reposts)

3. Share a post with your thoughts

Share ‘hot takes’ and posts with your thoughts, opinions and experiences on LinkedIn, much like status updates. It’s an excellent way to strengthen your personal brand and drive engagement on your posts.

Don’t be afraid to go against the grain and put your unique perspectives out there. Editing coach Erica Schneider does this often.

Encourage your audience to share their insights as well in the comments to spark a healthy debate.

4. Announce product launches

Want to generate buzz around a new product you’re rolling out? Share a LinkedIn post about it. Highlight key features, benefits and use cases relevant to your audience.

Include eye-catching images or videos that show your product in action to boost the impact of your launch post. Here’s HubSpot announcing a new product in partnership with TikTok with a short and captivating promo video.

5. Celebrate company wins and milestones

Sharing your company’s achievements and success stories on LinkedIn can help you improve your brand’s reputation, attracting more leads and talent in the process.

When people see how well your company is doing in terms of growth, innovation and impact, they’ll naturally want to associate with your brand. Recognizing and rewarding your team’s hard work is also a great way to boost morale and can significantly improve employee productivity and retention rates.

6. Share upcoming events

Hosting a webinar or speaking at an event? Share an update about it on LinkedIn to expand your reach and drive more registrations and attendance.

Here’s Sarah Corley from Sprout Social sharing that she’s hosting an upcoming webinar. This is a win-win for Sprout as this extends the post’s reach beyond Sprout’s LinkedIn followers to Sarah’s network on the platform.

7. Post videos

Video is one of the most engaging content types on social media, including on LinkedIn. Leverage the power of video to stand out and show your brand’s personality.

Create short-form or long-form videos , such as product tutorials, testimonials or behind-the-scenes glimpses into your company culture. Here’s Mailchimp sharing its community service activities with a LinkedIn video.

Make sure you optimize your videos for mobile and add subtitles as most people scrolling through their feeds might not have sound on.

8. Share different visual content formats

Don’t just stick to text posts or share video after video. Mix it up by using a variety of different formats, especially visuals. For example, you can share charts, infographics and case study cover images when promoting your content on LinkedIn.

Using different visual formats helps your posts stand out in the feed and makes your brand seem more interesting and less monotonous.

At Sprout, we like to switch things up regularly. Here’s how we picked out a statistic from our industry trends report and shared it as an image on LinkedIn. We also provided context and a link to download the full resource in the caption.

9. Create carousel posts

Carousel posts allow you to share multiple images, videos or slides in a single post, making them ideal for storytelling, step-by-step guides or showcasing different aspects of your brand.

While LinkedIn carousel posts are no longer available as an organic posting option, they can still be used as an ad post type.

You can also create carousel-like posts by uploading PDFs with multiple pages optimized for size. Here’s how Miro does it to visually showcase its product’s newest features.

10. Create newsletters for your audience

LinkedIn allows you to create newsletters where you can regularly content like tips, insights and resources around specific topics.

Subscribers are notified whenever you publish new articles, and anyone on LinkedIn can find, read and share your content. This makes newsletters a great way to establish thought leadership as well as build community and engagement around your brand.

Here’s an example of a LinkedIn newsletter by Gretchen Rubin called ‘Work Happier’, where she regularly publishes articles on workplace productivity and happiness.

11. Write thought-provoking articles

Formerly known as LinkedIn Pulse, the platform’s publishing feature helps brands and professionals share long-form content with their audience directly on LinkedIn.

Share insightful articles on trending topics that matter to your business to spark conversation and engagement, demonstrate your expertise and build authority.

Users can leave comments on your articles, so encourage readers to share their thoughts and respond quickly to any feedback. Finally, incorporate relevant visuals to break up the text and write SEO titles and descriptions to rank your content on search.

12. Repurpose your content for LinkedIn audiences

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• Published: 17 April 2024

A data-driven combined prediction method for the demand for intensive care unit healthcare resources in public health emergencies

• Weiwei Zhang 1 &
• Xinchun Li 1  

BMC Health Services Research volume  24 , Article number:  477 ( 2024 ) Cite this article

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Public health emergencies are characterized by uncertainty, rapid transmission, a large number of cases, a high rate of critical illness, and a high case fatality rate. The intensive care unit (ICU) is the “last line of defense” for saving lives. And ICU resources play a critical role in the treatment of critical illness and combating public health emergencies.

This study estimates the demand for ICU healthcare resources based on an accurate prediction of the surge in the number of critically ill patients in the short term. The aim is to provide hospitals with a basis for scientific decision-making, to improve rescue efficiency, and to avoid excessive costs due to overly large resource reserves.

A demand forecasting method for ICU healthcare resources is proposed based on the number of current confirmed cases. The number of current confirmed cases is estimated using a bilateral long-short-term memory and genetic algorithm support vector regression (BILSTM-GASVR) combined prediction model. Based on this, this paper constructs demand forecasting models for ICU healthcare workers and healthcare material resources to more accurately understand the patterns of changes in the demand for ICU healthcare resources and more precisely meet the treatment needs of critically ill patients.

Data on the number of COVID-19-infected cases in Shanghai between January 20, 2020, and September 24, 2022, is used to perform a numerical example analysis. Compared to individual prediction models (GASVR, LSTM, BILSTM and Informer), the combined prediction model BILSTM-GASVR produced results that are closer to the real values. The demand forecasting results for ICU healthcare resources showed that the first (ICU human resources) and third (medical equipment resources) categories did not require replenishment during the early stages but experienced a lag in replenishment when shortages occurred during the peak period. The second category (drug resources) is consumed rapidly in the early stages and required earlier replenishment, but replenishment is timelier compared to the first and third categories. However, replenishment is needed throughout the course of the epidemic.

The first category of resources (human resources) requires long-term planning and the deployment of emergency expansion measures. The second category of resources (drugs) is suitable for the combination of dynamic physical reserves in healthcare institutions with the production capacity reserves of corporations. The third category of resources (medical equipment) is more dependent on the physical reserves in healthcare institutions, but care must be taken to strike a balance between normalcy and emergencies.

Peer Review reports

Introduction

The outbreak of severe acute respiratory syndrome (SARS) in 2003 was the first global public health emergency of the 21st century. From SARS to the coronavirus disease (COVID-19) pandemic at the end of 2019, followed shortly by the monkeypox epidemic of 2022, the global community has witnessed eight major public health events within the span of only 20 years [ 1 ]. These events are all characterized by high infection and fatality rates. For example, the number of confirmed COVID-19 cases worldwide is over 700 million, and the number of deaths has exceeded 7 million [ 2 ]. Every major public health emergency typically consists of four stages: incubation, outbreak, peak, and decline. During the outbreak and transmission, surges in the number of infected individuals and the number of critically ill patients led to a corresponding increase in the urgent demand for intensive care unit (ICU) medical resources. ICU healthcare resources provide material security for rescue work during major public health events as they allow critically ill patients to be treated, which decreases the case fatality rate and facilitates the prevention and control of epidemics. Nevertheless, in actual cases of prevention and control, the surge in patients has often led to shortages of ICU healthcare resources and a short-term mismatch of supply and demand, which are problems that have occurred several times in different regions. These issues can drastically impact anti-epidemic frontline healthcare workers and the treatment outcomes of infected patients. According to COVID-19 data from recent years, many infected individuals take about two weeks to progress from mild to severe disease. As the peak of severe cases tends to lag behind that of infected cases, predicting the changes in the number of new infections can serve as a valuable reference for healthcare institutions in forecasting the demand for ICU healthcare resources. The accurate forecasting of the demand for ICU healthcare resources can facilitate the rational resource allocation of hospitals under changes in demand patterns, which is crucial for improving the provision of critical care and rescue efficiency. Therefore, in this study, we combined a support vector regression (SVR) prediction model optimized by a genetic algorithm (GA) with bidirectional long-short-term memory (BILSTM), with the aim of enhancing the dynamic and accurate prediction of the number of current confirmed cases. Based on this, we forecasted the demand for ICU healthcare resources, which in turn may enable more efficient resource deployment during severe epidemic outbreaks and improve the precise supply of ICU healthcare resources.

Research on the demand forecasting of emergency materials generally employs quantitative methods, and traditional approaches mainly include linear regression and GM (1,1). Linear regression involves the use of regression equations to make predictions based on data. Sui et al. proposed a method based on multiple regression that aimed to predict the demand for emergency supplies in the power grid system following natural disasters [ 3 ]. Historical data was used to obtain the impact coefficient of each factor on emergency resource forecasting, enabling the quick calculation of the demand for each emergency resource during a given type of disaster. However, to ensure prediction accuracy, regression analysis needs to be supported by data from a large sample size. Other researchers have carried out demand forecasting for emergency supplies from the perspective of grey prediction models. Li et al. calculated the development coefficient and grey action of the grey GM (1,1) model using the particle swarm optimization algorithm to minimize the relative errors between the real and predicted values [ 4 ]. Although these studies have improved the prediction accuracy of grey models, they mainly involve pre-processing the initial data series without considering the issue of the excessively fast increase in predicted values by traditional grey GM (1,1) models. In emergency situations, the excessively fast increase in predicted values compared to real values will result in the consumption of a large number of unnecessary resources, thereby decreasing efficiency and increasing costs. As traditional demand forecasting models for emergency supplies have relatively poor perfect order rates in demand analysis, which result in low prediction accuracy, they are not mainstream.

At present, dynamic models of infectious diseases and demand forecasting models based on machine learning are at the cutting edge of research. With regard to the dynamic models of infectious diseases, susceptible infected recovered model (SIR) is a classic mathematical model employed by researchers [ 5 , 6 , 7 ]. After many years of development, the SIR model has been expanded into various forms within the field of disease transmission, including susceptible exposed infected recovered model (SEIR) and susceptible exposed infected recovered dead model (SEIRD) [ 8 , 9 ]. Nevertheless, with the outbreak of COVID-19, dynamic models of infectious diseases have once again come under the spotlight, with researchers combining individual and group variables and accounting for different factors to improve the initial models and reflect the state of COVID-19 [ 10 , 11 , 12 , 13 ]. Based on the first round of epidemic data from Wuhan, Li et al. predicted the time-delay distributions, epidemic doubling time, and basic reproductive number [ 14 ]. Upon discovering the presence of asymptomatic COVID-19 infections, researchers began constructing different SEIR models that considered the infectivity of various viral incubation periods, yielding their respective predictions of the inflection point. Based on this, Anggriani et al. further considered the impact of the status of infected individuals and established a transmission model with seven compartments [ 15 ]. Efimov et al. set the model parameters for separating the recovered and the dead as uncertain and applied the improved SEIR model to analyze the transmission trend of the pandemic [ 16 ]. In addition to analyzing the transmission characteristics of normal COVID-19 infection to predict the status of the epidemic, many researchers have also used infectious disease models to evaluate the effects of various epidemic preventive measures. Lin et al. applied an SEIR model that considered individual behavioral responses, government restrictions on public gatherings, pet-related transmission, and short-term population movements [ 17 ]. Cao et al. considered the containment effect of isolation measures on the pandemic and solved the model using Euler’s numerical method [ 18 ]. Reiner et al. employed an improved SEIR model to study the impact of non-pharmaceutical interventions implemented by the government (e.g., restricting population movement, enhancing disease testing, and increasing mask use) on disease transmission and evaluated the effectiveness of social distancing and the closure of public spaces [ 19 ]. These studies have mainly focused on modeling the COVID-19 pandemic to perform dynamic forecasting and analyze the effectiveness of control measures during the epidemic. Infectious disease dynamics offer good predictions for the early transmission trends of epidemics. However, this approach is unable to accurately estimate the spread of the virus in open-flow environments. Furthermore, it is also impossible to set hypothetical parameters, such as disease transmissibility and the recovery probability constant, that are consistent with the conditions in reality. Hence, with the increase in COVID-19 data, this approach has become inadequate for the accurate long-term analysis of epidemic trends.

Machine learning has shown significant advantages in this regard [ 20 , 21 ]. Some researchers have adopted the classic case-based reasoning approach in machine learning to make predictions. However, it is not feasible to find historical cases that fully match the current emergency event, so this approach has limited operability. Other researchers have also employed neural network training in machine learning to make predictions. For example, Hamou et al. predicted the number of injuries and deaths, which in turn were used to forecast the demand for emergency supplies [ 22 ]. However, this approach requires a large initial dataset and a high number of training epochs, while uncertainty due to large changes in intelligence information can lead to significant errors in data prediction [ 23 , 24 , 25 ]. To address these problems, researchers have conducted investigations that account (to varying degrees) for data characterized by time-series and non-linearity and have employed time-series models with good non-linear fitting [ 26 , 27 , 28 ]. The use of LSTM to explore relationships within the data can improve the accuracy of predicting COVID-19 to some extent. However, there are two problems with this approach. First, LSTM neural networks require extremely large datasets, and each wave of the epidemic development cycle would be insufficient to support a dataset suitable for LSTM. Second, neural networks involve a large number of parameters and highly complex models and, hence, are susceptible to overfitting, which can prevent them from achieving their true and expected advantages in prediction.

Overall, Our study differs from other papers in the following three ways. First, the research object of this paper focuses on the specific point of ICU healthcare resource demand prediction, aiming to improve the rate of critical care patient treatment. However, past research on public health emergencies has focused more on resource prediction , such as N95 masks, vaccines, and generalized medical supplies during the epidemic , to mitigate the impact of rapid transmission and high morbidity rates. This has led to less attention being paid to the reality of the surge in critically ill patients due to their high rates of severe illness and mortality.

Second, the idea of this paper is to further forecast resource needs based on the projected number of people with confirmed diagnoses, which is more applicable to healthcare organizations than most other papers that only predict the number of people involved. However, in terms of the methodology for projecting the number of people, this paper adopts a combined prediction method that combines regression algorithms and recurrent neural networks to propose a BILSTM-GASVR prediction model for the number of confirmed diagnoses. It capitalizes on both the suitability of SVR for small samples and non-linear prediction as well as the learning and memory abilities of BILSTM in processing time-series data. On the basis of the prediction model for the number of infected cases, by considering the characteristics of ICU healthcare resources, we constructed a demand forecasting model of emergency healthcare supplies. Past public health emergencies are more likely to use infectious disease models or a single prediction model in deep learning. some of the articles, although using a combination of prediction, but also more for the same method domain combination, such as CNN-LSTM, GRU-LSTM, etc., which are all recurrent neural networks.

Third, in terms of specific categorization of resources to be forecasted, considering the specificity of ICU medical resources, we introduce human resource prediction on the basis of previous studies focusing on material security, and classified ICU medical resources into three categories: ICU human resources, drugs and medical equipment. The purpose of this classification is to match the real-life prediction scenarios of public health emergencies and improve the demand forecasting performance for local ICU healthcare resources. Thus, it is easy for healthcare institutions to grasp the overall development of events, optimizing decision-making, and reducing the risk of healthcare systems collapsing during the outbreak stage.

In this section, we accomplish the following two tasks. Firstly, we introduce the idea of predicting the number of infected cases and show the principle of the relevant models. Secondly, based on the number of infected cases, ICU healthcare resources are divided into two categories (healthcare workers and healthcare supplies), and their respective demand forecasting models are constructed.

Prediction model for the number of infected cases

Gasvr model.

Support vector machine (SVM) is a machine-learning language for classification developed by Vapnik [ 29 ]. Suppose there are two categories of samples: H1 and H2. If hyperplane H is able to correctly classify the samples into these two categories and maximize the margin between the two categories, it is known as the optimal separating hyperplane (OSH). The sample vectors closest to the OSH in H1 and H2 are known as the support vectors. To apply SVM to prediction, it is essential to perform regression fitting. By introducing the \(\varepsilon\) -insensitive loss function, SVM can be converted to a support vector regression machine, where the role of the OSH is to minimize the error of all samples from this plane. SVR has a theoretical basis in statistical learning and relatively high learning performance, making it suitable for performing predictions in small-sample, non-linear, and multi-dimensional fields [ 30 , 31 ].

Assume the training sample set containing \(l\) training samples is given by \(\{({x}_{i},{y}_{i}),i=\mathrm{1,2},...,l\}\) , where \({x}_{i}=[{x}_{i}^{1},{x}_{i}^{2},...,{x}_{i}^{d}{]}^{\rm T}\) and \({y}_{i}\in R\) are the corresponding output values.

Let the regression function be \(f(x)=w\Phi (x)+b\) , where \(\phi (x)\) is the non-linear mapping function. The linear \(\varepsilon\) -insensitive loss function is defined as shown in formula ( 1 ).

Among the rest, \(f(x)\) is the predicted value returned by the regression function, and \(y\) is the corresponding real value. If the error between \(f(x)\) and \(y\) is ≤ \(\varepsilon\) , the loss is 0; otherwise, the loss is \(\left|y-f(x)\right|-\varepsilon\) .

The slack variables \({\xi }_{i}\) and \({\xi }_{i}^{*}\) are introduced, and \(w\) , \(b\) are solved using the following equation as shown in formula ( 2 ).

Among the rest, \(C\) is the penalty factor, with larger values indicating a greater penalty for errors > \(\varepsilon\) ; \(\varepsilon\) is defined as the error requirement, with smaller values indicating a smaller error of the regression function.

The Lagrange function is introduced to solve the above function and transformed into the dual form to give the formula ( 3 ).

Among the rest, \(K({x}_{i},{x}_{j})=\Phi ({x}_{i})\Phi ({x}_{j})\) is the kernel function. The kernel function determines the structure of high-dimensional feature space and the complexity of the final solution. The Gaussian kernel is selected for this study with the function \(K({x}_{i},{x}_{j})=\mathit{exp}(-\frac{\Vert {x}_{i}-{x}_{j}\Vert }{2{\sigma }^{2}})\) .

Let the optimal solution be \(a=[{a}_{1},{a}_{2},...,{a}_{l}]\) and \({a}^{*}=[{a}_{1}^{*},{a}_{2}^{*},...,{a}_{l}]\) to give the formula ( 4 ) and formula ( 5 ).

Among the rest, \({N}_{nsv}\) is the number of support vectors.

In sum, the regression function is as shown in formula ( 6 ).

when some of the parameters are not 0, the corresponding samples are the support vectors in the problem. This is the principle of SVR. The values of the three unknown parameters (penalty factor C, ε -insensitive loss function, and kernel function coefficient \(\sigma )\) , can directly impact the model effect. The penalty factor C affects the degree of function fitting through the selection of outliers in the sample by the function. Thus, excessively large values lead to better fit but poorer generalization, and vice versa. The ε value in the ε-insensitive loss function determines the accuracy of the model by affecting the width of support vector selection. Thus, excessively large values lead to lower accuracy that does not meet the requirements and excessively small values are overly complex and increase the difficulty. The kernel function coefficient \(\sigma\) determines the distribution and range of the training sample by controlling the size of inner product scaling in high-dimensional space, which can affect overfitting.

Therefore, we introduce other algorithms for optimization of the three parameters in SVR. Currently the commonly used algorithms are 32and some heuristic algorithms. Although the grid search method is able to find the highest classification accuracy, which is the global optimal solution. However, sometimes it can be time-consuming to find the optimal parameters for larger scales. If a heuristic algorithm is used, we could find the global optimal solution without having to trace over all the parameter points in the grid. And GA is one of the most commonly used heuristic algorithms, compared to other heuristic algorithms, it has the advantages of strong global search, generalizability, and broader blending with other algorithms.

Given these factors, we employ a GA to encode and optimize the relevant parameters of the model. The inputs are the experimental training dataset, the Gaussian kernel function expression, the maximum number of generations taken by the GA, the accuracy range of the optimized parameters, the GA population size, the fitness function, the probability of crossover, and the probability of mutation. The outputs are the optimal penalty factor C, ε-insensitive loss function parameter \(\varepsilon ,\) and optimal Gaussian kernel parameter \(\sigma\) of SVR, thus achieving the optimization of SVR. The basic steps involved in GA optimization are described in detail below, and the model prediction process is shown in Fig. 1 .

Prediction process of the GASVR model

Population initialization

The three parameters are encoded using binary arrays composed of 0–1 bit-strings. Each parameter consisted of six bits, and the initial population is randomly generated. The population size is set at 60, and the number of iterations is 200.

Fitness calculation

In the same dataset, the K-fold cross-validation technique is used to test each individual in the population, with K = 5. K-fold cross validation effectively avoids the occurrence of model over-learning and under-learning. For the judgment of the individual, this paper evaluates it in terms of fitness calculations. Therefore, combining the two enables the effective optimization of the model’s selected parameters and improves the accuracy of regression prediction.

Fitness is calculated using the mean error method, with smaller mean errors indicating better fitness. The fitness function is shown in formula ( 7 ) [ 32 ].

The individual’s genotype is decoded and mapped to the corresponding parameter value, which is substituted into the SVR model for training. The parameter optimization range is 0.01 ≤ C ≤ 100, 0.1 ≤ \(\sigma\) ≤ 20, and 0.001 ≤ ε ≤ 1.

Selection: The selection operator is performed using the roulette wheel method.

Crossover: The multi-point crossover operator, in which two chromosomes are selected and multiple crossover points are randomly chosen for swapping, is employed. The crossover probability is set at 0.9.

Mutation: The inversion mutation operator, in which two points are randomly selected and the gene values between them are reinserted to the original position in reverse order, is employed. The mutation probability is set at 0.09.

Decoding: The bit strings are converted to parameter sets.

The parameter settings of the GASVR model built in this paper are shown in Table 1 .

BILSTM model

The LSTM model is a special recurrent neural network algorithm that can remember the long-term dependencies of data series and has an excellent capacity for self-learning and non-linear fitting. LSTM automatically connects hidden layers across time points, such that the output of one time point can arbitrarily enter the output terminal or the hidden layer of the next time point. Therefore, it is suitable for the sample prediction of time-series data and can predict future data based on stored data. Details of the model are shown in Fig. 2 .

Schematic diagram of the LSTM model

LSTM consists of a forget gate, an input gate, and an output gate.

The forget gate combines the previous and current time steps to give the output of the sigmoid activation function. Its role is to screen the information from the previous state and identify useful information that truly impacts the subsequent time step. The equation for the forget gate is shown in formula ( 8 ).

Among the number, \(W_{f}\) is the weight of the forget gate, \({b}_{f}\) is the bias, \(\sigma\) is the sigmoid activation function, \({f}_{t}\) is the output of the sigmoid activation function, \(t-1\) is the previous time step, \(t\) is the current time step, and \({x}_{t}\) is the input time-series data at time step \(t\) .

The input gate is composed of the output of the sigmoid and tanh activation functions, and its role is to control the ratio of input information entering the information of a given time step. The equation for the input gate is shown in formula ( 9 ).

Among the number, \({W}_{i}\) is the output weight of the input gate, \({i}_{t}\) is the output of the sigmoid activation function, \({b}_{i}\) and \({b}_{C}\) are the biases of the input gate, and \({W}_{C}\) is the output of the tanh activation function.

The role of the output gate is to control the amount of information output at the current state, and its equation is shown in formula ( 10 ).

Among the number, \({W}_{o}\) is the weight of \({o}_{t}\) , and \({b}_{o}\) is the bias of the output gate.

The values of the above activation functions \(\sigma\) and tanh are generally shown in formulas ( 11 ) and ( 12 ).

\({C}_{t}\) is the data state of the current time step, and its value is determined by the input information of the current state and the information of the previous state. It is shown in formula ( 13 ).

Among the number, \(\widetilde{{C}_{t}}=\mathit{tan}h({W}_{c}[{h}_{t-1},{x}_{t}]+{b}_{c})\) .

\({h}_{t}\) is the state information of the hidden layer at the current time step, \({h}_{t}={o}_{t}\times \mathit{tan}h({c}_{t})\) .Each time step \({T}_{n}\) has a corresponding state \({C}_{t}\) . By undergoing the training process, the model can learn how to modify state \({C}_{t}\) through the forget, output, and input gates. Therefore, this state is consistently passed on, implying that important distant information will neither be forgotten nor significantly affected by unimportant information.

The above describes the principle of LSTM, which involves forward processing when applied. BILSTM consists of two LSTM networks, one of which processes the input sequence in the forward direction (i.e., the original order), while the other inputs the time series in the backward direction into the LSTM model. After processing both LSTM networks, the outputs are combined, which eventually gives the output results of the BILSTM model. Details of the model are presented in Fig. 3 .

Schematic diagram of the BILSTM model

Compared to LSTM, BILSTM can achieve bidirectional information extraction of the time-series and connect the two LSTM layers onto the same output layer. Therefore, in theory, its predictive performance should be superior to that of LSTM. In BILSTM, the equations of the forward hidden layer( \(\overrightarrow{{h}_{t}}\) ) , backward hidden layer( \(\overleftarrow{{h}_{t}}\) ) , and output layer( \({o}_{t}\) ) are shown in formulas ( 14 ) , ( 15 ) and ( 16 ).

The parameter settings of the BILSTM model built in this paper are shown in Table 2 .

Informer model

The Informer model follows the compiler-interpreter architecture in the Transformer model, and based on this, structural optimizations have been made to reduce the computational time complexity of the algorithm and to optimize the output form of the interpreter. The two optimization methods are described in detail next.

With large amounts of input data, neural network models can have difficulty capturing long-term interdependencies in sequences, which can produce gradient explosions or gradient vanishing and affect the model's prediction accuracy. Informer model solves the existential gradient problem by using a ProbSparse Self-attention mechanism to make more efficient than conventional self-attention.

The value of Transformer self-attention is shown in formula ( 17 ).

Among them, \(Q\in {R}^{{L}_{Q}\times d}\) is the query matrix, \(K\in {R}^{{L}_{K}\times d}\) is the key matrix, and \(V\in {R}^{{L}_{V}\times d}\) is the value matrix, which are obtained by multiplying the input matrix X with the corresponding weight matrices \({W}^{Q}\) , \({W}^{K}\) , \({W}^{V}\) respectively, and d is the dimensionality of Q, K, and V. Let \({q}_{i}\) , \({k}_{i}\) , \(v_{i}\) represent the ith row in the Q, K, V matrices respectively, then the ith attention coefficient is shown in formula ( 18 ) as follows.

Therein, \(p({k}_{j}|{q}_{i})\) denotes the traditional Transformer's probability distribution formula, and \(k({q}_{i},{K}_{l})\) denotes the asymmetric exponential sum function. Firstly, q=1 is assumed, which implies that the value of each moment is equally important; secondly, the difference between the observed distribution and the assumed one is evaluated by the KL scatter, if the value of KL is bigger, the bigger the difference with the assumed distribution, which represents the more important this moment is. Then through inequality \(ln{L}_{k}\le M({q}_{i},K)\le {\mathit{max}}_{j}\left\{\frac{{q}_{i}{k}_{j}^{\rm T}}{\sqrt{d}}\right\}-\frac{1}{{L}_{k}}{\sum }_{j=1}^{{L}_{k}}\left\{\frac{{q}_{i}{k}_{j}^{\rm T}}{\sqrt{d}}\right\}+ln{L}_{k}\) , \(M({q}_{i},K)\) is transformed into \(\overline{M}({q}_{i},K)\) . According to the above steps, the ith sparsity evaluation formula is obtained as shown in formula ( 19 ) [ 33 ].

One of them, \(M({q}_{i},K)\) denotes the ith sparsity measure; \(\overline{M}({q}_{i},K)\) denotes the ith approximate sparsity measure; \({L}_{k}\) is the length of query vector. \(TOP-u\) quantities of \(\overline{M}\) are selected to form \(\overline{Q}\) , \(\overline{Q}\) is the first u sparse matrices, and the final sparse self-attention is shown in Formula ( 20 ). At this point, the time complexity is still \(O({n}^{2})\) , and to solve this problem, only l moments of M2 are computed to reduce the time complexity to \(O(L\cdot \mathit{ln}(L))\) .

Informer uses a generative decoder to obtain long sequence outputs.Informer uses the standard decoder architecture shown in Fig. 4 , in long time prediction, the input given to the decoder is shown in formula ( 21 ).

Informer uses a generative decoder to obtain long sequence outputs

Therein, \({X}_{de}^{t}\) denotes the input to the decoder; \({X}_{token}^{t}\in {R}^{({L}_{token}+{L}_{y})\times {d}_{\mathit{mod}el}}\) is the dimension of the encoder output, which is the starting token without using all the output dimensions; \({X}_{0}^{t}\in {R}^{({L}_{token}+{L}_{y})\times {d}_{\mathit{mod}el}}\) is the dimension of the target sequence, which is uniformly set to 0; and finally the splicing input is performed to the encoder for prediction.

The parameter settings of Informer model created in this paper are shown in Table 3 .

BILSTM-GASVR combined prediction model

SVR has demonstrated good performance in solving problems like finite samples and non-linearity. Compared to deep learning methods, it offers faster predictions and smaller empirical risks. BILSTM has the capacity for long-term memory, can effectively identify data periodicity and trends, and is suitable for the processing of time-series data. Hence, it can be used to identify the effect of time-series on the number of confirmed cases. Given the advantages of these two methods in different scenarios, we combined them to perform predictions using GASVR, followed by error repair using BILSTM. The basic steps for prediction based on the BILSTM-GASVR model are as follows:

Normalization is performed on the initial data.

The GASVR model is applied to perform training and parameter optimization of the data to obtain the predicted value \(\widehat{{y}_{i}}\) .

After outputting the predicted value of GASVR, the residual sequence between the predicted value and real data is extracted to obtain the error \({\gamma }_{i}\) (i.e., \({\gamma }_{i}={y}_{i}-\widehat{{y}_{i}}\) ).

The BILSTM model is applied to perform training of the error to improve prediction accuracy. The BILSTM model in this paper is a multiple input single output model. Its inputs are the true and predicted error values \({\gamma }_{i}\) and its output is the new error value \(\widehat{{\gamma }_{i}}\) predicted by BILSTM.

The final predicted value is the sum of the GASVR predicted value and the BILSTM residual predicted value (i.e., \({Y}_{i}=\widehat{{y}_{i}}+\widehat{{\gamma }_{i}}\) ).

The parameter settings of the BILSTM-GASVR model built in this paper are shown in Table 4 .

Model testing criteria

To test the effect of the model, the prediction results of the BILSTM-GASVR model are compared to those of GASVR, LSTM, BILSTM and Informer. The prediction error is mainly quantified using three indicators: mean squared error (MSE), root mean squared error (RMSE), and correlation coefficient ( \(R^{2}\) ). Their respective equations are shown in formulas ( 22 ), ( 23 ) and ( 24 ).

Demand forecasting model of ICU healthcare resources

ICU healthcare resources can be divided into human and material resources. Human resources refer specifically to the professional healthcare workers in the ICU. Material resources, which are combined with the actual consumption of medical supplies, can be divided into consumables and non-consumables. Consumables refer to the commonly used drugs in the ICU, which include drugs for treating cardiac insufficiency, vasodilators, anti-shock vasoactive drugs, analgesics, sedatives, muscle relaxants, anti-asthmatic drugs, and anticholinergics. Given that public health emergencies have a relatively high probability of affecting the respiratory system, we compiled a list of commonly used drugs for respiratory diseases in the ICU (Table 5 ).

Non-consumables refer to therapeutic medical equipment, including electrocardiogram machines, blood gas analyzers, electrolyte analyzers, bedside diagnostic ultrasound machines, central infusion workstations, non-invasive ventilators, invasive ventilators, airway clearance devices, defibrillators, monitoring devices, cardiopulmonary resuscitation devices, and bedside hemofiltration devices.

The demand forecasting model of ICU healthcare resources constructed in this study, as well as its relevant parameters and definitions, are described below. \({R}_{ij}^{n}\) is the forecasted demand for the \(i\) th category of resources on the \(n\) th day in region \(j\) . \({Y}_{j}^{n}\) is the predicted number of current confirmed cases on the \(n\) th day in region \(j\) . \({M}_{j}^{n}\) is the number of ICU healthcare workers on the \(n\) th day in region \(j\) , which is given by the following formula: number of healthcare workers the previous day + number of new recruits − reduction in number the previous day, where the reduction in number refers to the number of healthcare workers who are unable to work due to infection or overwork. In general, the number of ICU healthcare workers should not exceed 5% of the number of current confirmed cases (i.e., it takes the value range [0, \(Y_{j}^{n}\) ×5%]). \(U_{i}\) is the maximum working hours or duration of action of the \(i\) th resource category within one day. \({A}_{j}\) is the number of resources in the \(i\) th category allocated to patients (i.e., how many units of resources in the \(i\) th category is needed for a patient who need the \(i\) th unit of the given resource). \({\varphi }_{i}\) is the demand conversion coefficient (i.e., the proportion of the current number of confirmed cases who need to use the \(i\) th resource category). \({C}_{ij}^{n}\) is the available quantity of material resources of the \(i\) th category on the \(n\) th day in region \(j\) . At the start, this quantity is the initial reserve, and once the initial reserve is exhausted, it is the surplus from the previous day. The formula for this parameter is given as follows: available quantity from the previous day + replenishment on the previous day − quantity consumed on the previous day, where if \({C}_{ij}^{n}\) is a negative number, it indicates the amount of shortage for the given category of resources on the previous day.

In summary, the demand forecast for emergency medical supplies constructed in this study is shown in formula ( 25 ).

The number of confirmed cases based on data-driven prediction is introduced into the demand forecasting model for ICU resources to forecast the demand for the various categories of resources. In addition to the number of current confirmed cases, the main variables of the first demand forecasting model for human resources are the available quantity and maximum working hours. The main variable of the second demand forecasting model for consumable resources is the number of units consumed by the available quantity. The main variable of the third model for non-consumable resources is the allocated quantity. These three resource types can be predicted using the demand forecasting model constructed in this study.

Prediction of the number of current infected cases

The COVID-19 situation in Shanghai is selected for our experiment. A total of 978 entries of epidemic-related data in Shanghai between January 20, 2020, and September 24, 2022, are collected from the epidemic reporting platform. This dataset is distributed over a large range and belongs to a right-skewed leptokurtic distribution. The specific statistical description of data is shown in Table 6 . Part of the data is shown in Table 7 .

And we divided the data training set and test set in an approximate 8:2 ratio, namely, 798 days for training (January 20, 2020 to March 27, 2022) and 180 days for prediction (March 28, 2022 to September 24, 2022).

Due to the large difference in order of magnitude between the various input features, directly implementing training and model construction would lead to suboptimal model performance. Such effects are usually eliminated through normalization. In terms of interval selection, [0, 1] reflects the probability distribution of the sample, whereas [-1, 1] mostly reflects the state distribution or coordinate distribution of the sample. Therefore, [-1, 1] is selected for the normalization interval in this study, and the processing method is shown in formula ( 26 ).

Among the rest, \(X\) is the input sample, \({X}_{min}\) and \({X}_{max}\) are the minimum and maximum values of the input sample, and \({X}_{new}\) is the input feature after normalization.

In addition, we divide the data normalization into two parts, considering that the amount of data in the training set is much more than the test set in the real operating environment. In the first step, we normalize the training set data directly according to the above formula; in the second step, we normalize the test data set using the maximum and minimum values of the training data set.

The values of the preprocessed data are inserted into the GASVR, LSTM, Informer, BILSTM models and the BILSTM-GASVR model is constructed. Figures 5 , 6 , 7 , 8 and 9 show the prediction results. From Figs. 5 , 6 , and 7 , it can be seen that in terms of data accuracy, GASVR more closely matches the real number of infected people relative to BILSTM and LSTM. Especially in the most serious period of the epidemic in Shanghai (April 17, 2022 to April 30, 2022), the advantage of the accuracy of the predicted data of GASVR is even more obvious, which is due to the characteristics of GASVR for small samples and nonlinear prediction. However, in the overall trend of the epidemic, BILSTM and LSTM, which have the ability to learn and memorize to process time series data, are superior. It is clearly seen that in April 1, 2022-April 7, 2022 and May 10, 2022-May 15, 2022, there is a sudden and substantial increase in GASVR in these two time phases, and a sudden and substantial decrease in April 10, 2022-April 14, 2022. These errors also emphasize the stability of BILSTM and LSTM, which are more closely matched to the real epidemic development situation in the whole process of prediction, and the difference between BILSTM and LSTM prediction is that the former predicts data more accurately than the latter, which is focused on the early stage of prediction as well as the peak period of the epidemic. Informer is currently an advanced time series forecasting method. From Fig. 8 , it can be seen that the prediction data accuracy and the overall trend of the epidemic are better than the single prediction models of GASVR, LSTM and BILSTM. However, Informer is more suitable for long time series and more complex and large prediction problems, so the total sample size of less than one thousand cases is not in the comfort zone of Informer model. Figure 9 shows that the BILSTM-GASVR model constructed in this paper is more suitable for this smaller scale prediction problem, with the best prediction results, closest to the actual parameter (number of current confirmed cases), demonstrating small sample and time series advantages. In Short, the prediction effect of models is ranked as follows: BILSTM-GASVR> Informer> GASVR> BILSTM> LSTM.

The prediction result of the GASVR model

The prediction result of the LSTM model

The prediction result of the BILSTM model

The prediction result of the Informer model

The prediction result of the BILSTM-GASVR model

The values of the three indicators (MSE, RMSE, and correlation coefficient \({R}^{2}\) ) for the five models are shown in Table 8 . MSE squares the error so that the larger the model error, the larger the value, which help capture the model's prediction error more sensitively. RMSE is MSE with a root sign added to it, which allows for a more intuitive representation of the order of magnitude difference from the true value. \({R}^{2}\) is a statistical indicator used to assess the overall goodness of fit of the model, which reflects the overall consistency of the predicted trend and does not specifically reflect the degree of data. The results in the Table 8 are consistent with the prediction results in the figure above, while the ranking of MSE, RMSE, and \({R}^{2}\) are also the same (i.e., BILSTM-GASVR> Informer> GASVR> BILSTM> LSTM).

In addition, we analyze the five model prediction data using significance tests as a way of demonstrating whether the model used is truly superior to the other baseline models. The test dataset with kurtosis higher than 4 does not belong to the approximate normal distribution, so parametric tests are not used in this paper. Given that the datasets predicted by each of the five models are continuous and independent datasets, this paper uses the Kruskal-Wallis test, which is a nonparametric test. The test steps are as follows.

Determine hypotheses (H0, H1) and significance level ( \(\alpha\) ).

For each data set, all its sample data are combined and ranked from smallest to largest. Then find the number of data items ( \({n}_{i}\) ), rank sum ( \({R}_{i}\) ) and mean rank of each group of data respectively.

Based on the rank sum, the test statistic (H) is calculated for each data set in the Kruskal-Wallis test. The specific calculation is shown in formula ( 27 ).

According to the test statistic and degrees of freedom, find the corresponding p-value in the Kruskal-Wallis distribution table. Based on the P-value, determine whether the original hypothesis is valid.

In the significance test, we set the significance setting original hypothesis (H0) as there is no significant difference between the five data sets obtained from the five predictive models. We set the alternative hypothesis (H1) as there is a significant difference between the five data sets obtained from the five predictive models. At the same time, we choose the most commonly used significance level taken in the significance test, namely 0.05. In this paper, multiple comparisons and two-by-two comparisons of the five data sets obtained from the five predictive models are performed through the SPSS software. The results of the test show that in the multiple comparison session, P=0.001<0.05, so H0 is rejected, which means that the difference between the five groups of data is significant. In the two-by-two comparison session, BILSTM-GASVR is less than 0.05 from the other four prediction models. The specific order of differences is Informer < GASVR < BILSTM < LSTM, which means that the BILSTM-GASVR prediction model does get a statistically significant difference between the dataset and the other models.

In summary, combined prediction using the BILSTM-GASVR model is superior to the other four single models in various aspects in the case study analysis of Shanghai epidemic with a sample size of 978.

Demand forecasting of ICU healthcare resources

Combined with the predicted number of current infected cases, representatives are selected from the three categories of resources for forecasting. The demand for nurses is selected as the representative for the first category of resources.

In view of the fact that there are currently no specific medications that are especially effective for this public health emergency, many ICU treatment measures involved helping patients survive as their own immune systems eliminated the virus. This involved, for example, administering antibiotics when patients developed a secondary bacterial infection. glucocorticoids are used to temporarily suppress the immune system when their immune system attacked and damaged lung tissues causing patients to have difficulty breathing. extracorporeal membrane oxygenation (ECMO) is used for performing cardiopulmonary resuscitation when patients are suffering from cardiac arrest. In this study, we take dexamethasone injection (5 mg), a typical glucocorticoid drug, as the second category of ICU resources (i.e., drugs); and invasive ventilators as the third category of ICU resources (i.e., medical equipment).

During the actual epidemic in Shanghai, the municipal government organized nine critical care teams, which are stationed in eight municipally designated hospitals and are dedicated to the treatment of critically ill patients. In this study, the ICU nurses, dexamethasone injections, and invasive ventilators in Shanghai are selected as the prediction targets and introduced into their respective demand forecasting models. Forecasting of ICU healthcare resources is then performed for the period from March 28, 2022, to April 28, 2022, as an example. Part of the parameter settings for the three types of resources are shown in Tables 9 , 10 , and 11 , respectively.

Table 12 shows the forecasting results of the demand for ICU nurses, dexamethasone injections, and invasive ventilators during the epidemic wave in Shanghai between March 28, 2022, and April 28, 2022.

For the first category (i.e., ICU nurses), human resource support is only needed near the peak period, but the supply could not be replenished immediately. In the early stages, Shanghai could only rely on the nurses’ perseverance, alleviating the shortage of human resources by reducing the number of shifts and increasing working hours. This situation persisted until about April 10 and is only resolved when nurses from other provinces and regions successively arrived in Shanghai.

The second category of ICU resources is drugs, which are rapidly consumed. The pre-event reserve of 30,000 dexamethasone injections could only be maintained for a short period and is fully consumed during the outbreak. Furthermore, daily replenishment is still needed, even when the epidemic has passed its peak and begun its decline.

The third category is invasive ventilators, which are non-consumables. Thus, the reserve lasted for a relatively long period of time in the early stages and did not require replenishment after its maximum usage during the peak period.

Demand forecasting models are constructed based on the classification of healthcare resources according to their respective features. We choose ICU nurses, dexamethasone injections, and invasive ventilators as examples, and then forecast demand for the epidemic wave in Shanghai between March 28, 2022, and April 28, 2022. The main conclusions are as follows:

A long period of time is needed to train ICU healthcare workers who can independently be on duty, taking at least one year from graduation to entering the hospital, in addition to their requiring continuous learning, regular theoretical training, and the accumulation of clinical experience during this process. Therefore, for the first category of ICU healthcare resources, in the long term, healthcare institutions should place a greater emphasis on their talent reserves. Using China as an example, according to the third ICU census, the ratio of the number of ICU physicians to the number of beds is 0.62:1 and the ratio of the number of nurses to the number of beds is 1.96:1, which are far lower than those stipulated by China itself and those of developed countries. Therefore, a fundamental solution is to undertake proactive and systematic planning and construction to ensure the more effective deployment of human resources in the event of a severe outbreak. In the short term, healthcare institutions should focus on the emergency expansion capacity of their human resources. In case there are healthcare worker shortages during emergencies, the situation can be alleviated by summoning retired workers back to work and asking senior medical students from various universities to help in the hospitals to prevent the passive scenario of severely compressing the rest time of existing staff or waiting for external aid. However, it is worth noting that to ensure the effectiveness of such a strategy of using retired healthcare workers or senior students of university medical faculties, it is necessary for healthcare organizations to provide them with regular training in the norm, such as organizing 2-3 drills a year, to ensure the professionalism and proficiency of healthcare workers who are temporarily and suddenly put on the job. At the same time, it is also necessary to fully mobilize the will of individuals. Medical institutions can provide certain subsidies to retired health-care workers and award them with honorable titles. For senior university medical students, volunteer certificates are issued and priority is given to their internships, so that health-care workers can be motivated to self-realization through spiritual and material rewards.

Regarding the second category of ICU resources (i.e., drugs), healthcare institutions perform the subdivision of drug types and carry out dynamic physical preparations based on 15–20% of the service recipient population for clinically essential drugs. This will enable a combination of good preparedness during normal times and emergency situations. In addition, in-depth collaboration with corporations is needed to fully capitalize on their production capacity reserves. This helps medical institutions to be able to scientifically and rationally optimize the structure and quantity of their drug stockpiles to prevent themselves from being over-stressed. Yet the lower demand for medicines at the end of the epidemic led to the problem of excess inventory of enterprises at a certain point in time must be taken into account. So, the medical institutions should sign a strategic agreement on stockpiling with enterprises, take the initiative to bear the guaranteed acquisition measures, and consider the production costs of the cooperative enterprises. These measures are used to truly safeguard the enthusiasm of the cooperative enterprises to invest in the production capacity.

Regarding the third category of ICU resources (i.e., medical equipment), large-scale medical equipment cannot be rapidly mass-produced due to limitations in the capacity for emergency production and conversion of materials. In addition, the bulk procurement of high-end medical equipment is also relatively difficult in the short term. Therefore, it is more feasible for healthcare institutions to have physical reserves of medical equipment, such as invasive ventilators. However, the investment costs of medical equipment are relatively high. Ventilators, for example, cost up to USD $50,000, and subsequent maintenance costs are also relatively high. After all, according to the depreciable life of specialized hospital equipment, the ventilator, as a surgical emergency equipment, is depreciated over five years. And its depreciation rate is calculated at 20% annually for the first five years, which means a monthly depreciation of $835. Thus, the excessively low utilization rate of such equipment will also impact the hospital. Healthcare institutions should, therefore, conduct further investigations on the number of beds and the reserves of ancillary large-scale medical equipment to find a balance between capital investment and patient needs.

The limitations of this paper are reflected in the following three points. Firstly, in the prediction of the number of infections, the specific research object in this paper is COVID-19, and other public health events such as SARS, H1N1, and Ebola are not comparatively analyzed. The main reason for this is the issue of data accessibility, and it is easier for us to analyze events that have occurred in recent years. In addition, using the Shanghai epidemic as a specific case may be more representative of the epidemic situation in an international metropolis with high population density and mobility. Hence, it has certain regional limitations, and subsequent studies should expand the scope of the case study to reflect the characteristics of epidemic transmission in different types of urban areas and enhance the generalizability.

Secondly, the main emphasis of this study is on forecasting the demand for ICU healthcare resources across the entire region of the epidemic, with a greater focus on patient demand during public emergencies. Our aims are to help all local healthcare institutions more accurately identify changes in ICU healthcare resource demand during this local epidemic wave, gain a more accurate understanding of the treatment demands of critically ill patients, and carry out comprehensive, scientifically based decision-making. Therefore, future studies can examine individual healthcare institutions instead and incorporate the actual conditions of individual units to construct multi-objective models. In this way, medical institutions can further grasp the relationship between different resource inputs and the recovery rate of critically ill patients, and achieve the balance between economic and social benefits.

Finally, for the BILSTM-GASVR prediction method, in addition to the number of confirmed diagnoses predicted for an outbreak in a given region, other potential applications beyond this type of medium-sized dataset still require further experimentation. For example, whether the method is suitable for procurement planning of a certain supply in production management, forecasting of goods sales volume in marketing management, and other long-period, large-scale and other situations.

Within the context of major public health events, the fluctuations and uncertainties in the demand for ICU resources can lead to large errors between the healthcare supply and actual demand. Therefore, this study focuses on the question of forecasting the demand for ICU healthcare resources. Based on the number of current confirmed cases, we construct the BILSTM-GASVR model for predicting the number of patients. By comparing the three indicators (MSE, MAPE, and correlation coefficient \(R^{2}\) ) and the results of the BILSTM, LSTM, and GASVR models, we demonstrate that our model have a higher accuracy. Our findings can improve the timeliness and accuracy of predicting ICU healthcare resources and enhance the dynamics of demand forecasting. Hence, this study may serve as a reference for the scientific deployment of ICU resources in healthcare institutions during major public events.

Given the difficulty in data acquisition, only the Shanghai epidemic dataset is selected in this paper, which is one of the limitations mentioned in Part 4. Although the current experimental cases of papers in the same field do not fully conform to this paper, the results of the study cannot be directly compared. However, after studying the relevant reviews and the results of the latest papers, we realize that there is consistency in the prediction ideas and prediction methods [ 34 , 35 ]. Therefore, we summarize the similarities and differences between the results of the study and other research papers in epidemic forecasting as shown below.

Similarities: on the one hand, we all characterize trends in the spread of the epidemic and predict the number of infections over 14 days. On the other hand, we all select the current mainstream predictive models as the basis and combine or improve them. Moreover, we all use the same evaluation method (comparison of metrics such as MSE and realistic values) to evaluate the improvements against other popular predictive models.

Differences: on the one hand, other papers focus more on predictions at the point of the number of patients, such as hospitalization rate, number of infections, etc. This paper extends the prediction from the number of patients to the specific healthcare resources. This paper extends the prediction from the number of patients to specific healthcare resources. We have divided the medical resources and summarized the demand regularities of the three types of information in the epidemic, which provides the basis for decision-making on epidemic prevention to the government or medical institutions. On the other hand, in addition to the two assessment methods mentioned in the same point, this paper assesses the performance of the prediction methods with the help of significance tests, which is a statistical approach to data. This can make the practicality of the forecasting methodology more convincing.

Availability of data and materials

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

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We would like to acknowledge the hard and dedicated work of all the staff that implemented the intervention and evaluation components of the study.

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WWZ and XCL conceived the idea and conceptualised the study. XCL collected the data. WWZ analysed the data. WWZ and XCL drafted the manuscript, then WWZ and XCLreviewed the manuscript. WWZ and XCL read and approved the final draft.

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Zhang, W., Li, X. A data-driven combined prediction method for the demand for intensive care unit healthcare resources in public health emergencies. BMC Health Serv Res 24 , 477 (2024). https://doi.org/10.1186/s12913-024-10955-8

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DOI : https://doi.org/10.1186/s12913-024-10955-8

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