Case Study: Metabical

Problem Statement

It is important to underline that the product had a tangible market. Metabical, a prescription obesity drug to be launched by CSP was quite different from other products in the market including those from CSP. First, it was set to be the first prescription drug for overweight people (BMI between 25-30) and had less side effects compared to substitutes. In addition, most overweight people relied on Over the Counter (OTC) drugs that had serious health implications that left them with a preference for diet and exercise alternatives. Therefore, there was a tangible opportunity in the overweight segment that was to be exploited. The product had a ready market to enter and presented a healthier option to most of the available alternatives for overweight people.

Despite the lucrative nature of the market, there were issues with pricing and packaging. First, most healthcare insurers did not cover anti-obesity drugs and only a few drug plans would cover metabical costs despite it being a prescription drug. This meant that a new pricing model was required. In addition, there was the packaging conundrum whereas it was necessary to decide how many tablets would be included in a single package (Luna-Reyes et al., 2014). The pill needed to be taken daily to maintain its presence in the bloodstream and hence packaging needed to consider the routine. Another option was to package the entire 12-week dosage to avoid individuals defaulting on the dose after failing to refill. This was to be done in consideration of the regulations for packaging which range between a week to a 3- month supply (Stake, 2013). Therefore, there was need to determine how the drugs were to be packaged and the pricing to be attached to every package.

Forecasting demand was another issue that needed to be problematized. There were several ways in which this could be done beginning with analyzing the population of overweight people in the United States, narrowing down to the percentage of those attempting to lose weight and those that were looking at prescription drugs for solutions. Elsewhere, a survey could also suffice where information would be collected with respect to consumer interest on weight loss prescription drugs (Rahman & Sarker, 2015). Alternatively, segmentation would be used, with the ideal customer being an educated female, middle aged and with a BMI between 25-31. There was thus need to identify the best approach to demand forecasting.


            There are a number of variables that need to be explored in the study. First were the regulatory forces. The FDA had several conditions that needed to be met prior to Metabical being approved for distribution. These included directions on packaging and pricing, influencing how the launch strategy would be shaped in the end. Another variable was the market. There was need to understand who the customers were, where they were located and their purchasing power. Still with respect to the market was factors like demand and return on investment (ROI). Other variables include the price of the product and its packaging.


            Stakeholders are people who make decisions or are affected by the decisions made by an entity (Davenport & Kim, 2013). In this case, Barbara Printup and Bernard Long were among the main stakeholders responsible for the overall marketing responsibility. The FDA was equally a major stakeholder given that they were the ones to offer approval for the drug as it entered the market. They were capable of inhibiting the drugs rollout and needed to be fully satisfied. The consumers of Metabical (overweight persons) were yet another group of essential stakeholders as they were the ones to purchase the product. Other stakeholders include the staff at CSP involved in production and the board of directors at the company who offered financial and technical support. Barbara Printup shall be responsible for devising the launch strategy once the analysis results were out.


            There were a number of alternatives that could be explored in solving the problem raised. These were specific to pricing, packaging and demand forecasting. Alternatives included:

  1. Adopting more than one pricing and packaging model; for instance a week package for low income consumers and a month package for higher income users.
  2. Exploiting the few available drug plans that would consider covering Metabical.
  3. Use of a survey approach to forecast demand. Surveys offer detailed, primary data that creates a more credible basis of forecasting demand.
  4. Combining surveys and segmentation in forecasting demand.

Analytical Story

            Analytical stories are used to convey the information from quantitative analysis to both data savvy and layman audiences (Davenport & Kim, 2013). In this case, the best analytical story to adopt was predictive. This would examine what would most likely fit for a price, packing and demand forecasting model for the organization. In this respect, the consequences of each action/ choice would be closely evaluated and projected (Davenport & Kim, 2013). A communication of the same would justify the decisions of the marketing team with respect to the stated problem.

Past Experiences

            Within the organization, Barbara Printup had the experience of launching new products. She had successfully launched Zimistat, which holds the record as the most successful launch by CSP. There were several lessons she could draw from that experience including pricing and packaging as well as forecasting demand. Elsewhere, there are numerous examples of successful and failed product launches in the market today that they could draw on.


Davenport, T. H., & Kim, J. (2013). Keeping up with the quants: Your guide to understanding and using analytics. Harvard Business Review Press.

Luna-Reyes, L. F., Zhang, J., Whitmore, A., Jarman, H., Picazo-Vela, S., Andersen, D. L., … & Andersen, D. F. (2014). Full Information Product Pricing: An Information Strategy for Harnessing Consumer Choice to Create a More Sustainable World. CAIS34, 32.

Rahman, M. M., & Sarker, S. (2015). Demand Forecasting for Seasonal Demand Patterns: Case Study of a Pharmaceutical Company. Journal of Production Research & Management4(3), 1-7.

Stake, R. E. (2013). Multiple case study analysis. Guilford Press.

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