Sales force effectiveness: An approach to innovate and win using data science

January 19, 2023

Sales force effectiveness (SFE) has been an area of interest in pharma for many years, but rather because of its administrative aspects than its capability to accelerate business results through a proper use of data and technology.

Now that investment in digital and data analytics is a priority in pharma, it’s time to look at how SFE can join this trend and play a transformative and protagonist role. SFE could impact the effectiveness of sales roles and every field role (sales reps, MSLs, KAMs, etc.), with the ultimate goal being to improve customer satisfaction, demand generation, fulfillment, and the company margin.

Where this could be most impactful is with the optimal allocation of resources: what are the novel methods out there to perform segmentation and targeting proficiently?

Propelling your data-driven strategy 

“If you torture the data long enough, it will confess to anything.” (Ronald Coase, Economics, Nobel prize Laureate)

Technology can now gather relevant data from HCPs and get to know each of them, enhancing the segmentation and targeting practices to make the impact model more efficient to boost demand generation. Not only can we score HCPs by the number of PXs, but we can also now understand the customer from the attitudinal, behavioral, and demographic perspective and their preferences when relating to the pharma industry

On the other hand, marketing/medical activities have become more customer-centered, so the role of the sales representatives is still a fundamental piece to building that relationship, and that interaction needs to be as efficient and personalized as possible, orchestrating along the omnichannel journey. 

How can we leverage the amount of data available in the cloud to personalize the experience for each HCP and understand their needs to increase engagement and long-term relationships? 

Every modern data strategy needs to consider 3 layers:

  1. Data architecture: Customer 360° platforms
  2. Business insights with dashboards powered by advanced analytics
  3. AI models (predictive and prescriptive analytics)

We will now focus on how prescriptive analytics, such as math optimization, gives organizations the power to use their ever-growing amounts of data to make millions of automated decisions. As a result, organizations can maximize return on investments, while both expanding and improving customer relationships, thus allowing organizations to translate customer data into actionable strategies. 

Enter the realm of mathematical optimization

The use of mathematical modeling and optimization techniques to solve complex problems consists of maximizing or minimizing one or more objectives, considering the problem’s constraints and limitations. Mathematical approximations to solving these issues have existed for a long time, but now computing power and data availability make it possible to implement in business case settings.

With mathematical optimization we can solve classic pharma problems to make business decisions like:

  • How to allocate the most efficient amount of HCPs to a given REP? 
  • How to create optimal sales or medical territories?
  • How to choose the best route to visit every customer in the minimum possible time?
  • How to do the best mix between channels of contact, considering the whole omnichannel strategy?

Whatever the situation, we can understand the impact of different decisions so that the results of each decision gets quantified, and we can select those that better meet the objectives.

Sales team territory planning for field force effectiveness

A sales territory is a geographic region composed of customers assigned to a specific salesperson or sales team. The goal of a sales territory is to target a specific market using a streamlined sales strategy that efficiently delivers resources to sales teams so they can close deals in that market. 

The target of sales territory planning is to find the optimal division of the market areas among the sales team to better exploit the market’s potential and thereby maximize profit. With the aid of territory planning, realistic and fair sales areas can be specified based on the distribution of market potentials. 

There are many reasons why companies would decide to undertake a territory optimization exercise. Examples include a change in the go-to-market strategy, the addition of new products to the portfolio, insufficient customer coverage, high costs due to inefficient travel routing, poor use of the effort amongst the salesforce, etc.

Companies can optimize sales territory size and composition by combining the data from the CRM, ERP, CMS, other internal databases, and external signals.  Some common data points needed for setting sales territories include workload, sales potential, geographic constraints, and travel time. With a previous implementation of a customer segmentation algorithm, it is also possible to use that output and consider contact and schedule results for each kind of customer. 

A highly efficient approach for sales territory planning is combinatorial optimization algorithms. Combinatorial optimization is a mathematical technique to solve problems where we must find an optimal solution amongst many possible combinations of features. For example, in the traveling salesman problem, the objective is to find the shortest route between a set of points and locations a salesperson must visit, keeping the travel costs and the distance traveled as low as possible. 

We can leverage the heuristics used to solve this problem to find the optimal route for a sales representative. Like this example, many other combinatorial optimization problems already solved can be translated to the healthcare and pharmaceutical industries to improve and scale operations.

Ready to transform your sales/field force operations and maximize effectiveness?

At Globant, we seek digital transformation, believing that technology can revolutionize the healthcare and life sciences industry. Through our vast experience with Data & Artificial Intelligence and Healthcare & Life Sciences, we combine technical and domain-specific experts to bring innovation to the pharmaceutical industry. 

Learn more about the Healthcare & Life Sciences Studio at Globant here.

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The Healthcare & Life Sciences Studio aims to reinvent the life sciences industry ecosystem through tangible technology-driven solutions. Globant aims to bridge the gap to help life sciences and healthcare organizations to achieve their mission of delivering innovation and services faster and more efficiently to enhance patient value and improve outcomes.