THE CALL PLAN IS DEAD!
By Rich Sokolosky and Chael Christopher
The Pharma engagement model is undergoing a significant transformation. Analysts will have to adapt to support the change.
The traditional, once-a-quarter call plan dictating pharma sales force activity is rapidly fading into history. Sales representatives are being reimagined as components of a symbiotic omnichannel strategy where customer preferences, interests, and responses determine engagement. The future of customer engagement will include new channels, and it will be based on dynamic data and AI-driven assessments of the customer’s history, most recent interactions, and “like” peers.
The disruption in the engagement model is forcing a similar disruption to analyst activities with the new paradigm looking very different from the old. How are business requests changing as a result of the new engagement model and what are the implications for analysts?
New Asks
The business is moving from activity specific, periodic requests to requiring comprehensive dynamic analytic inputs. The highlights of this shift are:
Single-Activity Focused to All-Inclusive - Requests have been primarily single activity focused. This entails a call plan for the sales force, a target list for the email campaigns, and various other lists provided on demand for one-off initiatives. Now the need is to consider all activities and how they relate to each other when making recommendations.
Once-a-Year or Once-a-Quarter to Real-Time - The new paradigm requires that analytic inputs are available as frequently as needed. This might be daily in the case of sales reps logging into their CRM platform and seeing who they need to send follow up emails to that day.
Static to Dynamic - In conjunction with the shift to frequency (noted above), analytic inputs need to be generated at the time of the request based on the most recent interactions. An example of this would be a policy for an individual HCP that, when bumped up against the latest interactions, recommends a text on safety as the next best action.
Lists to System-Connected - In order for real-time, dynamic analytic inputs to be effective, they must be available to other systems. The omnichannel hub is a prime example.
Implications for Analysts
Traditionally, analysts answer questions through highly intensive one-off efforts. The approach, data, technology, and delivery mechanisms have all been left to the analytic team to engineer. Given the nature of previous business requests, even a cumbersome process could be delivered 1 to 4 times a year. However, as discussed above, the nature of business requests are changing dramatically. In order to support the new order, analyst functions will have to upend the decades-old approaches and change in the following ways:
Rely on AI and Machine Learning Algorithms - Individual analysts cannot hand crank the next best action recommendation for every channel team member for every HCP based on the most recent activity. AI provides the means to accurately, computationally, and frequently update recommendations on the latest data available.
Establish an Analytic Focused Data Hub - In order for AI to be effective, it has to be fed data with the right dimensions in the right format. There are repositories for transactional data, there are data lakes for availability, and there are data warehouses for reporting but very few organizations have stood up the analytic focused repositories necessary to support AI.
Manage and Support Operations - In many cases AI models will be updated daily requiring daily updates to the analytic data all of which will require some form of repeatable operations. DataOps and MLOps will have to become processes that analysts are tied into for monitoring and adjustment.
Think about Interconnectivity - Omni Channel platforms will require APIs (application programming interfaces) to ingest inputs delivered via AI. Analysts will now have to understand that there is an application layer between the results and the execution platforms.
Work Closely with Channel Owners - AI is not magical. Commercial organizations cannot set up intelligent marketing platforms in a vacuum. There are many inputs to AI that are best provided by the business owners of the channels. For example, how are channels intended to work together in a coordinated, efficient manner? Analysts will need to do more with channel owners as AI is set up, adjusted, and monitored.
Work Closely with IT - IT will undergo a renaissance because of the need for AI. AI will require technologies, technical processes, and the systematic management of both. But IT left solely to technologists will never meet the business need. Analysts will have to work closely with IT to ensure the environment is delivering on the analytic requirements.
There is a lot of risk, work, and opportunity associated with the changing engagement model for Pharma. One prediction we can put forth with a minimal error band is that the analyst function will play a key role in making it all happen. But to play that role analysts will have to upend the nature of their analytics and activities. This will not happen overnight but there is solace in the fact that other industries have done it. With the right analytic leadership, planning, and cross functional collaboration, it will happen in Pharma as well.
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