Flatworld Helped a US-based Healthcare Client Develop a Forecasting Model
The client is a U.S.-based health care company that is well-known for its medical devices and diagnostic equipment, as well as its diagnostic tests, branded generic medications, and nutritional supplements.
They wanted to better predict the success of candidates they were considering in-licensing and the products that they would license those product candidates.
The client was facing a few challenges before they approached us for the project. Some of the key challenges they faced were -
- Considering a new model to keep tabs on potential market shares and stats from potential customers, the company could use its internal resources to ensure to be providing up-to-date information to use in making future decisions.
- The current order of entry models was developed using small molecule historical sales and do not accurately reflect the changing market dynamics in the key global markets that are of high interest to the client.
Considering the customer's business challenges and requirements, our team at FWS devised a streamlined plan for the client -
- The objective, output, and effectiveness-based forecasting approaches were used to conduct a detailed analysis of the number of products released in multiple therapeutic areas during the past given time.
- We created a forecasting tool for Order of Entry (based on historic IMS patient data) to help project the share of each therapeutic area for new products and in-licensing candidates.
- A forecast model that enables Clients to refine their forecasting based on specific product attributes of pipeline products.
- An automated, Excel-based quick dashboard for keeping track of "New Order Of Entry" and "Launched Products Attribute" based forecast models.
The client was highly impressed by the results delivered by our team. This project demonstrated a combination of client requirements - (1) accuracy and (2) fast delivery. Both qualities were delivered by an experienced research team. The project was completed within 6 weeks.
We were proud to work with top-tier research analysts. We monitored and cross-checked the work of these researchers to produce precise data.
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