CPG manufacturers need Moneyball for field team orchestration

Guided field execution strategy vs. field rep instinct-driven execution 

Field sales and merchandising reps are overloaded with data and assignments from management. A field sales rep may have eight to twelve things to consider during a visit including paper-based key account plans, plan-o-grams, promotion compliance surveys, category management surveys, point-of-sale and market data, suggested orders, as well as supervisor instructions that could include coaching and training.    

Today, most CPG field reps are receiving all of these materials and instructions without consideration for the requirements of each individual store. At the beginning of each store visit, it’s up to the rep to wade through this mass of information and instructions that comes in multiple media formats, including paper, pdf, email, excel, and text. It can take 15 or 20 minutes to figure out what needs to be done before even getting started.  The rep has a territory to cover and numbers to meet, so the majority don’t take the time to try to make sense of it all.  

CPGs have made great progress on digitizing information, so it is distributed to field reps quickly and more frequently, but it’s still not easily sorted and only increases the workload. We have forgotten the old-school CIO wisdom: If you are going to shoot yourself in the foot, best not use automatic weapons. (1) 

The challenge

For field execution, CPGs are facing two primary challenges: 

  • Prioritizing tasks based on their contribution to your business strategy 
  • Sorting, cleansing and parsing of data so it can be distributed to the right stores at the right time 

How do you make sense of it all? What matters? Do you want prioritization to be driven by gut feel or instinct? Or would you prefer execution priorities be driven by your business strategy which is itself supported by evidence built on hard data analysis using real statistics and advanced machine learning along with rigorous testing of assumptions? 



Moneyball: The Art of Winning an Unfair Game is a book by Michael Lewis, published in 2003.  It describes how the Oakland Athletics baseball team and its general manager Billy Beane used statistics and sabermetrics to assemble a competitive baseball team on a small budget. It led to the 2011 movie Moneyball, starring Brad Pitt and Jonah Hill. (2)

The basic idea of Moneyball and sabermetrics (3) is that you win baseball games by scoring runs. You score runs by getting on base. Therefore, players who get on base and who contribute to scoring the most runs are the most valuable. 

The traditional measures of batting performance such as batting average, runs, and stolen bases did not correlate with success in winning games. Instead, on-base percentage and slugging percentage were more valuable.  

The book also contrasted how traditional player evaluations were largely subjective and based on the collective wisdom rather than hard data. 

Applying Moneyball to retail execution


The first step is to delve deep into your data to understand what drives your business. To do this, you must clarify the definition of success for your business. Do you measure success by sales, volume, or profitability? Are those the right metrics? Should you, for example, first measure execution and skills? The data will tell you this. 

Second, use machine learning to study the data and identify what activities really matter; then validate that with your sales teams. Identify and question things that are driven by opinion or conventional wisdom that are not supported by data. 

 Third, modify your workflows, processes, and incentive plans as necessary to emphasize the critical tasks. For example, help them to “get on base,” and eliminate non-valuable tasks. These “other” tasks may be important and still need to be done somehow, but non-valuable means they do not help the rep or merchandiser to focus only on what contributes to you winning in the market. 


Once you know what really matters, you can start to prioritize tasks and allocate supporting data. This function looks like an orchestra conductor for the last mile or last yard. Their role is to coordinate, moderate, and drive the tempo or speed of the flow. This must be AI-driven and constantly learning. Your orchestration algorithm will:

  • Fetch data from other systems and databases and feed it into the field app. The algorithm knows what data to fetch and where to find it.
  • Clean and normalize the data. Filtering the important from the unimportant.
  • Synthesize data from numerous sources and present to the field app.
  • Allocate tasks in a step-by-step fashion related to a specific store visit.
  • Return the data post-execution to the original database so the upstream systems benefit from the learning.

A new world driven by data


Now imagine your field reps pulling up to each store, opening their mobile app, and seeing a store-specific visit plan driven by what will drive success for that store and ultimately for your overall business. Activities are prioritized and contain clear instructions at the moment of impact at the shelf. No hunting for information. It’s there when and where they need it. 

If your reps have a question, there is a smart query with a Chat GPT-like interface. They can just ask as they would ask another human and the answer will be presented. This includes information on product availability, upcoming deliveries, and more. Now your reps can answer any question within seconds! 

CoachAI can also offer suggestions to the rep for activities and training modules to help improve their performance and allows them to reach out to top performers for advice. 

All of this frees up the rep to focus on what’s important to the business and to be more consultative for each customer, resulting in higher customer satisfaction and reduced churn.  

We have your solutions

Our proposed solution for these problems is Spring Global’s Maestro smart platform and CoachAI solutions. Learn more about them here. 

Author: Conor Keane, Denver, March 26, 2024 

Topics: News