iStock 000044728926Small resized 600(This blog series introduces emerging trends in sales planning that every commercial operations department must prepare to face in the future.)

Embracing Big Data and unlocking its power with analytics will only take you so far. What happens when months are required to use those insights or react productively? The true endgame involves both systems and internal processes evolving into real-time resource and activity reallocation.

How can we change our processes and systems to make this happen? Building capabilities to eliminate the cycle may be hardest of all because it requires going from today’s analog state—the equivalent of printing maps and directions before traveling — to automated, real-time systems and processes to advise the field — like GPS with road and traffic information constantly recalculating directions. It takes both the systems that can do it, and the field processes that expect it.

Some companies are on their way: for example, a company promoting an allergy brand, with most of its annual sales captured the few months of pollen season. Efficiency of the sales effort during those months is paramount to brand performance, yet the peak of pollen season varies annually and by region and can be unpredictable. To support its highest prescribers before and during the outbreak, the company uses CDC outbreak data and forecasts by zip codes to develop weekly targeting guidance for reps. Targeted support by telesales and other channels were implemented to help the overwhelmed field. The company is also exploring monitoring social chatter to spot allergy complaints in various areas.

Obviously, building these insights into next quarter would be too late. An allergy outbreak needs attention the week it happens.

To make this happen, organizations face three challenges:

  1. Design a repeatable data and analytics process. Data acquisition and integration and the execution of analytical models must be reliable and repeatable if sales planning and other operational processes are to depend on them. In addition to traditional data-warehousing systems and processes, data stewards and scientists need to be part of the operational process when dealing with Big Data, especially when data consistency is a challenge and business rules need to be reviewed and adjusted, and models retested regularly.
  2. Enhance your planning systems. Configure planning systems to rely on additional modeling inputs, such as changing physician scores, promotional responses or customer channel preferences. Planning systems also should not stop at effort allocation, but go further to suggest messages and coordinate non-sales channels, because some of the changing preferences and situations will require different response than just increasing number of details.
  3. Redesign processes for greater flexibility. For example, today many sales compensation plans rely on a frozen customer and target universe. We will need to design goals and metrics that allow targets to change within the quarter, without reps feeling unrewarded for different effort. Representatives will also need to learn how to incorporate new information into call plans in real time, based on alerts or weekly newsletters. Without such redesign, even the best analytics will not be acted on.

Only by rewiring our systems and processes to respond as changes happen will we be able to harness the power of the data and analytics and ultimately eliminate the cycle.

Topics: big data, sales, call planning, territory management, commercial operations, Maria Kliatchko, Sales Planning, Life Sciences, Analytics