Using Artificial Intelligence (AI) in Pharma Commercial Excellence to increase field teams performance.
Working with raw data is cumbersome, visualizations paint the picture that helps to understand what is going on.
But, with so many data sources such as IMS, Hospital sales, pharmacy sales, CRM, marketing investment... the number of KPIs is soaring, making difficult to understand the correlations between them, especially for people without an analytic background, or enough time to spend on converting data into valuable decision-making information.
Correlation links people and processes to profit, so connecting the dots between plain old KPIs is the cornerstone to increasing efficiency.
AI algorithms allow combining disparate metrics from different data sources to uncover hidden patterns and tell the story in plain language.
Of course, it is not about magic, the system must be trained and has to know the product life cycle, therapeutic area, business rules and the scoring thresholds to apply.
But, once this step is reached the benefits for field teams are:
- Delivering complex business analysis in plain but clear and concise language.
- Risk warnings & scoring.
- Focus FLMs time on coaching effort with team members that need it.
- Discover which high-potential territories or hospitals have mid-term risks and why.
- Suggest action plans and goals to address identified opportunities & risks.
Although AI algorithms have been around for many years, it is with the data explosion we are living, that they are becoming a must for decision-making in any business.
Only with a focused interpretation of the key relevant information among the huge amount of available data, decisions on strategies and tactics will have an impact.
Much remains to be done, we all have access to quantitative data, but qualitative data sets are not included in most information processes.
This is the area that promised to cover the CRM systems, but to date, the information is buried in them.
We are working on it, in order to have a combined quantitative and qualitative vision to refine the diagnosis and the possibility of suggesting action plans.