Written by: Paulina Krzyszczyk
Edited by: Huri Mücahit and Tomas Kasza
On February 1st, I attended the iJOBS-sponsored consulting workshop led by Sidnee Pinho, the U.S. Chief Operating Officer of Prescient Healthcare Group. The workshop opened up my eyes to a field that I had previously poorly understood, and therefore not seriously considered as a potential career path. I am very glad that I attended, as I learned a lot about this exciting field. It also may be of particular interest to our readers that the consulting world is generally open to hiring fresh PhDs!
Sidnee Pinho began the workshop by defining what a consultant does, and all the hats that they must wear. A consultant is, “a person who facilitates change and provides subject matter expertise; someone who provides advice”. In this workshop, the scope of consulting was limited to agencies that work with pharmaceutical and biotechnology companies, their clients, to help them make key business decisions. This simple definition was then expanded to include the many different hats that a consultant must wear. They must act as a:
1) Problem Definer – Define the scope of the project. What is the specific question that the client is expecting the consultant to answer?
2) Project Manager – Develop a work plan for the project. How long will the project take? What tasks will be completed, and when?
3) Data Searcher/Creator – Obtain primary and secondary research from key opinion leaders and published sources. Schedule interviews and check the credibility of any data that is acquired from other sources.
4) Thought Process Organizer – Develop a framework or methodology for using the data to lead the team to an answer. Define key criteria that the client is looking for, turn those into questions that can be answered by key personnel, and quantify all data obtained using a scoring system that assigns weights to the client’s priorities.
5) Quality Controller – Identify accurate data to maintain credibility of the consultant agency’s work. Is the data current and relevant to the demographic at hand? Are the statistics specific and do they come from a reputable source?
6) Storyteller – Present ideas in a way that suits your audience (top-down vs bottom-up approaches). Is your audience interested in all of the details that led to your answer, or do they prefer to hear the main conclusions with key reasoning and supporting evidence?
7) Relationship Manager – Clearly and efficiently communicate with the client to update them on the project. At meetings, remind them of previous work, the purpose of the current meeting, and key project goals. Tie this into the next steps of the project moving forward.
Once we understood the broad set of responsibilities that a consultant must fulfill, we were given the task of taking on a consultant’s role in the following simulation:
Company X is considering releasing Product X, a long-acting steroid, for rheumatoid arthritis (RA), however they only want to proceed if the revenue can reach at least $200 million.
We were given a packet of information with data and statistics, such as RA prevalence, the difference between acute and chronic RA, treatment options and regimens, etc.
As I began sifting through the slides, one of the first things that came to my mind was, “Too much data!” This proved to be a major challenge – determining which data was important, extraneous, or reliable, especially as we were trying to simultaneously learn the background information about the disease. For example, we had to determine if we should focus on statistics regarding chronic or acute cases of RA, or both, and also read over physician opinions on their likelihood to adopt Product X over other treatment options. To complicate things even further, many of the statistics were given as ranges (e.g. 30-40% of RA patients are on steroids at a given time). As we began discussing the data within my group, I also realized that each person had slightly different interpretations about the exact meaning of each statistic, as well as its credibility or relative importance. This led to some interesting discussions at our table, as we wanted to determine the best data to use for our final revenue calculation.
At the end of the day, our task was seemingly simple: “Is the product a “go” or a “no go”, based on whether or not it is likely to yield a revenue of over $200 million”. With this seemingly simple question, we got opposing answers. Some groups said “Go”; however others said “No Go”, and the range of revenue estimates that we came up with was vast, from approximately $100 to 400 million. This was due to the fact that each group had a different interpretation of the data and the consequence was a more or less conservative final revenue estimate.
After debriefing the exercise with Sidnee Pinho, we realized our experiences reflected the common obstacles that consultants must tackle, such as which data to use and why. Furthermore, the final answer is rarely a, “YES – go for it!” or a, “Definitely No!”, but more so falls within a spectrum based on a, “Yes, if…” or a, “No, unless…”, phrasing.
Overall, I would highly recommend this workshop to anyone who is even slightly curious about consulting. The dynamic hands-on activity gave participants a taste of the challenging tasks that consultants must perform daily. I most enjoyed the complex thought processes required to complete these tasks. I also recognized that the PhD degree provides graduates with the invaluable skill of breaking down a large question into smaller parts. Throughout the workshop, we were able to use this skill in a completely different scenario outside of the lab.
Who would have known that a single iJOBS workshop could open my eyes and allow me to consider an entirely new career path? Only time will tell whether or not it is in my future, but it is definitely one that I will further consider.