The struggles of analysis and forecasting with incentive programs

 

Many organizations have adopted some form of an incentive program to capture and retain customers. Point systems with associated rewards abound for everything from travel to coffee consumption. While rebate promotions for the general populous are usually straightforward tiered levels, enterprise-focused programs can get immensely complex, with multi-year rollovers and inter-product dependencies. Nowhere is this complexity more prevalent than within the manufacturing segment of the ag realm—specifically, animal health pharmaceuticals and crop production seed/chemicals.

Fundamentally, rebates are designed to give away profits to secure customer loyalty while making up for loss margin by encouraging higher volumes of purchase. This requires that the hundreds of rebate programs that span an organization’s portfolio must be purposefully structured, both individually and holistically, to maximize market share while minimizing margin loss. Unfortunately, most rebate systems are ill-equipped to handle the sophisticated and dynamic forecasting methodologies needed to design, predict, and analyze program performance.

Three primary bottlenecks hamper rebate forecasting and analysis: misappropriated applications, inadequate integration, and lack of analytics and forecasting systems.

Misappropriated Applications

Many rebate solutions attempt to handle processes outside of their intended domain. When rebate applications encroach on roles normally reserved for ERPs or CRMs, their rebate-centric design will lead to functional inadequacies within other parts of the organization. Excellent rebate management requires harnessing data across several systems – ERPs, CRMs, SCMs, etc. – to derive intelligence and execute rebate-specific tasks.

On the contrary, many organizations attempt to force ERPs or CRMs to perform rebate management duties. These systems, along with their rebate add-ons, can typically handle simple rebate logic but prove inadequate with complex rebate programs. This frequently results in data being wrangled from multiple systems, then managed within spreadsheets. Over time, the spreadsheets themselves become the rebate management system, thus creating an insufferable environment for deep analysis and forecasting.

Inadequate Integration

Because enterprise rebate management should deliver synchronous results across a chain of buyers and sellers, the complications extend beyond a manufacturer’s internal systems (CRMs, ERPs, etc.) and entail harmonizing data across a broad, system-of-systems network spanning multiple stakeholders. Such stakeholders include distributors, buying groups, ag retailers, veterinarians, and growers.

Since the level of sophistication for data exchange and communication standards will vary greatly across clients, ranging from robust API integration to submission via fax machine, data cleansing and standardization become new bottlenecks, not only for forecasting and analysis but rebate management in general. This often necessitates additional staff or a managed service to handle the incoming data from disparate systems.

Lack of analytics and forecasting systems

Once the bottlenecks of misappropriated applications and inadequate integration have been resolved, data is now primed and ready for analysis and forecasting. However, just as ERPs and CRMs play a unique role in rebate management, so do enterprise-level analytics and forecasting applications. Since rebate programs have a direct impact on profit margin and customer loyalty, every rebate program is a vital strategy that contributes to an organization’s commercial success.

A good forecasting tool will, at a minimum, allow marketing teams to test select variables against different models, generate tracking signals, and forecast sales estimates. However, those who are serious about using rebate programs to enhance competitive advantage will seek to advance forecasting with new insights from market data, consumer trends, sales rep feedback, and numerous other sources to design more robust rebate programs that capture higher degrees of customer loyalty while optimizing profit margins.

Summary

Proagrica’s suite of technologies delivers the key components for implementing a best-in-class, enterprise-level rebate program that empowers robust analytics and forecasting. Proagrica’s modulated rebate platform provides the foundations for creating and managing rebate programs and the associated workflows while allowing collaboration with other internal and external systems. Interlok handles the necessary transformations between disparate systems while Agility provides customized analytics. At this point, the data is prepped and ready to be seamlessly fed into a forecasting system of choice, ensuring an organization is ready to compete on the future of rebate formulation by harnessing next-gen technologies such as IoT, ML, and AI with dynamic, event-driven forecasting capabilities.

If you’d like to find out more about how Proagrica can help with your rebate management struggles, please contact me on my email below.

brandon.buie@proagrica.com

Brandon Buie, Director of Enterprise Development for Proagrica Animal Health, North America

“Brandon Buie is Director of Enterprise Development for Proagrica’s North America Animal Health initiatives. He was raised in a ranching family and has +20 years’ experience in digital agriculture. Proagrica’s animal health team works globally with the major pharmaceutical manufacturers, distributors, buying groups, and corporate vet practices to deliver more value with digital and analytics. Such applications specifically include integrated connectivity via Proagrica’s B2B network, rebate management, health plans/compliance programs, and custom applications across various species divisions.”

 

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