How to Recommend Portfolio Scenarios

Instructor: Scott Tuning

Scott has been a faculty member in higher education for over 10 years. He holds an MBA in Management, an MA in counseling, and an M.Div. in Academic Biblical Studies.

Companies need to be flexible and dynamic in a constantly changing business environment. This lesson illustrates a systematic method that will identify solid portfolio recommendations.

Portfolios and Projects Are Living Things

Portfolios and their components must be dynamic enough to meet the changing needs of an organization. Leadership should be skilled at making recommendations for managing the portfolio while keeping the mission and strategic goals close at hand. When a company's portfolio is in lock step with its mission, the result is strategic alignment.

When the portfolio and mission of an organization are complimentary, there is good strategic alignment.


In this context, a scenario is a forward-looking simulation that is used to make good decisions about their portfolio. It changes parameters and variables and then compares the results. Let's look at an example case in which scenarios would be used to inform an organization's portfolio management practices.

Several years ago, a small pharmaceutical startup had a portfolio of four medications in various stages of development, but no products currently on the market. Ultimately, the company brought only one drug to the market.

When approved by the FDA, the drug was one of only a few pharmaceuticals that could be used for treating alcoholism. Patients taking the drug and consuming alcohol became violently ill with nausea and vomiting. Support for the drug, particularly its mechanism of action, was shaky from the beginning. Most of its opponents argued that it was a penalty rather than a medication. It didn't reduce cravings, change brain biology, or provide patients with tools to overcome their addiction. It simply punished them if they chose to consume alcohol.

As long as this medication was on the market by itself, it didn't face any stiff competition. However, as talk therapy became more common, and better pharmaceuticals were developed, the future of this first-generation drug was clear. This case shows how portfolio recommendations can be made using a scenario-based approach.

An executive in a pharmaceutical company like the one in the case analysis should weigh a variety of options that are tested by scenario.

Breakdown of a Scenario-Based Recommendation

Step 1: Problem Identification

Like many other decision-making processes, a scenario begins by asking the question, ''What is the problem we need to solve?'' This is critical because an incorrect problem definition will render all subsequent testing invalid. In the example of the pharmaceutical company, the problem to be solved was that competition from better pharmaceuticals and strong opposition from many healthcare providers that threatened to make the drug obsolete.

Step 2: Acquiring the Relevant Data

Once the problem has been correctly and succinctly defined, the next step is to collect the correct data. Although there are nuances and subtleties that apply on a case-by-case basis, all data-gathering for scenario analysis should include an analysis of:

  • Industry trends
  • The legislative and regulatory environment (present as well as future)
  • The degree and magnitude of uncertainty
  • Cultural and sociological factors
  • Macro and micro economic data

Collecting accurate data is paramount because bad data will damage the credibility of the results.

Step 3: Determine What is Known and What is Unknown

Greater uncertainty means greater risk. The fewer factors that an organization controls, the more external uncertainty may impact their portfolio. A pharmaceutical firm has a higher than average number of uncontrollable external factors, and their scenario development will reflect this in the number of variables to be considered.

Scenario Development and Testing

When test scenarios are being built, special attention should be paid to the unknown. Although there is no right or wrong number of scenarios, best practice is to build at least one for each major uncertainty. Building too many scenarios isn't good either. The elements of a scenario must be far enough apart that each represents a distinct outcome rather than a slight variation.

Based on the example case, this graphic illustrates the applications of scenario-based testing.

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