Case Study #2: AmerisourceBergen Challenge

Pharmacies typically engage with a single pharmaceutical distributor to purchase all the drugs they need. This type of arrangement is governed by a contract called a Prime Vendor Agreement (PVA), which the pharmacy enters into with the distributor for a specific number of years defined in the agreement itself. The PVA also stipulates what percentage of its drugs a pharmacy must buy from the distributor in order to be compliant with the agreement. A pharmacy may choose to purchase drugs from a distributor other than the one it has a PVA with; this is referred to as “leakage,” and it can sometimes be significant.

Your challenge is to determine which drugs are being bought outside the PVA from other distributors, hypothesize why this is happening, and recommend where AmerisourceBergen should concentrate efforts to reduce this leakage and regain lost revenue and profit.

Your analysis needs to answer question #1 as well as address one or more of questions #2 through #4.

  1. Which drug families appear to be purchased outside the PVA most often?
  2. Is leakage based on quantity? Based on $? Based on Therapeutic Class or disease state?
  3. Is price always the cause of leakage? Or are there other reasons for it?
  4. Where should AmerisourceBergen focus its efforts to reduce leakage to regain revenue and profit?


Click here for AmerisourceBergen Data

  • Be certain to view the PDF file named AmerisourceBergen 2018_analytics_challenge for detailed information about the datasets and other reference materials.

Other Rules

  • The project submissions must entirely be the work of the project team. While faculty and other individuals can help review the submission, they should not contribute to the content of the report or the solution.
  • Incomplete submissions will not be considered, so make sure you have all of your submission deliverables are in the submission package.
  • The contest materials must be submitted by the due dates. Late submissions will not be accepted and no extensions will be given.
  • Submission Instructions

    What you should submit

    • A case study file will be submitted as a Word document: The case study is expected to have various figures and graphics (See the resources for creating infographics and case study). Refer to the Resources section for access to resources for creating info graphics and case studies.
    • Participants are encouraged to use data to present tables, to present their arguments. (See the resources for data and visualization).Refer to the Resources section for access to resources for data and visualization.
    • The Word file should be between 5-15 pages long (not including references or appendix).
    • The file should specify the names of the participants as well as the topic chosen. See the details of the topics and more resources about the topic at computational society resource pages
    • A cover letter in the format found at

    How you should submit

    • Inform about the intent to participate in the competition as soon as possible by writing to
    • Register after you are provided access to the website (you will receive this as a reply to your intent to participate request) at The membership will be upgraded to a premium membership after registration for no additional fee.
    • Email your entry to by 11:59 p.m. U.S. Eastern Time, March 1, 2019.

    What happens after you submit

    • You will receive a confirmation email acknowledging your entry.
    • Finalists will be notified by email after March 1, 2019.
    • Finalists will present their work in front of the judging panel at the AIS SCLC April 11-13, 2019. See the page on The Computational Society website for details of prizes and awards. Visit or contact for details.
  • Timeline

    All preliminary submissions must be recieved no later than March 1, 2020
    Finalists will be announced after March 1, 2020
    The winner will be revealed at the Student Chapters Leadership Conference between April 11 – 13, 2020

  • Prizes

    Entrants to the 2019 Computational Society Case Challenge will be competing with AIS and non-AIS student chapter teams and individuals across the globe, in Stage 1. Non-AIS members will be awarded based on their Stage 1 performance. The top AIS-affiliated teams and individuals from Stage 1 of the competition will move forward to compete at the 2019 AIS Student Chapter Leadership Conference in Philadelphia April 11-13. Stage 2 is exclusively for AIS student chapter teams and individuals* selected as finalist in Stage 1. AIS Stage 1 finalist will then compete for top prizes in Philadelphia. Submissions to all case studies are judged collectively and prizes are awarded to the top 3 cases regardless of the selected case scenario: (1) Retail Analytics and Automation of Choice, or (2) AI and Analytics to Unravel Individual Choice, or (3) Artificial Intelligence (AI), Computational technologies, and well-being!

    Monetary Prizes, based on Stage 1 performance

    First place – $250
    Second place – $150
    Third place – $100

    Monetary Prizes, based on Stage 2 performance

    First place – $2,000
    Second place – $1,000
    Third place – $500

    Other Prizes

    Certificates: All finalists are given certificates indicating their rank.

    *To compete as an AIS team or individual, you must be an officially recognized chapter or a member of an officially recognized chapter. Forming an AIS Student Chapter at your institution is easy, but can take as much 6-8 weeks to complete the process depending on your university policy and procedures so get started today. For more information on how you can start a chapter, contact Dr. Rhonda Syler, AIS Vice President for Student Chapters, at

  • Questions


How entries will be evaluated

All entries will be evaluated by the judges in two categories: visualization and analysis. The finals will also be judged by industry professionals.

The specific criteria for each category are:


  • Clarity (how well the graphic stands on its own without additional explanation)
  • Novelty/creativity (originality of thought; surprising way of approaching the data)
  • Insight (graphic aids understanding of the data)
  • Utility (ability of the graphic to aid decision making)


  • Relevance (analysis relates to the problem statement)
  • Completeness (degree to which the analysis answers the stated question)
  • Depth (sophistication of the analysis)
  • Consistency (conclusions consistent with the analysis)

Your entry will be disqualified if…

  • It is submitted after the deadline.
  • The attachments won’t open or are in the wrong file format.
  • Your interactive graphic won’t run.
  • You don’t specify the challenge you are addressing.
  • Team member names and college name are not on both the graphic and the description.