The following post is published by the Partner and Global Head for Digital Transformation of Zinnov, a leading Globalization and Market Expansion Advisory firm.
The consumer packaged goods (CPG) industry is undergoing rapid changes due to digital transformation, evolving retail formats and a new breed of competitors. While this increases complexities for CPG manufacturers and retailers alike, it also presents new opportunities for proactive enterprises.
One such opportunity lies within trade promotions, where the spending today forms 15–25% of the total revenue and represents one of the biggest line items in the profit and loss statement (second only to the cost of goods sold). Therefore, it is imperative for a CPG enterprise to analyze and optimize trade promotions to derive bottom-line efficiencies and enhance profitability.
The four phases of trade promotions
The first two phases involve the planning and execution of incentive programs that occur between CPG manufacturers and retailers. This is known as the trade promotion management (TPM) process. The next phase is evaluation of the promotion results post execution. Evaluation requires a trade promotions intelligence (TPI) infrastructure, which leverages an enterprise demand signal repository (DSR) that stores and integrates all the syndicated and point of sale (POS) data with the internal master data. The TPI infrastructure allows the TPM solution to become another data source where plan data can also be fed in to the enterprise infrastructure along with forecasts and shipment information. The final phase, trade promotions optimization (TPO), leverages predictive analytics on top of the TPI infrastructure to recalibrate and reallocate trade spend to high-growth opportunities.
To achieve trade promotion effectiveness, a CPG enterprise must transition through each phase. TPO requires a TPI infrastructure, however, most CPG enterprises try to jump directly from TPM to TPO. This leaves the majority of CPG enterprises today stuck in the early stages of trade promotions maturity.
Top roadblocks in achieving trade promotions optimization
What are the top challenges that enterprises face in moving from TPM to TPO maturity?
In terms of execution, too many CPG enterprises still use manual processes, such as Excel spreadsheets. This failure to leverage technology leaves them unable to analyze real-time data and apply course corrections dynamically.
CPG enterprises also struggle with implementing trade programs across multiple regions and countries, since each market presents its own variances and complexities. This hampers the uniformity in the trade promotion planning and evaluation process and the visibility of the entire value chain from creation to evaluation.
Finally, enterprises rarely have access to high-quality data. This primarily results from a lack of uniformity among retail partners and distributors. For example, retailers may use different product taxonomies, supply inaccurate or missing data, or provide incompatible formats (Oracle, SAP, Excel) that require conversion to a common data type. A confluence of these scenarios makes it very difficult for CPG enterprises to maintain data uniformity and quality, integrate data effectively, and reach the next level of insights and action.
Road map for effective trade promotion strategy
A successful trade promotions strategy begins with addressing the right questions. An enterprise should ask itself:
- How much should we spend on promotions?
- Who are my top-performing retail partners?
- Which products deliver the best ROI on promotions?
- How frequently should I manage and optimize my trade promotion strategy?
- Do we measure the correct KPIs to gauge success?
- Are all senior stakeholders in agreement on the trade promotion strategy?
To answer these questions accurately, the CPG enterprise needs access to high-quality data and the ability to make sense of it. Otherwise, it cannot reach optimization.
The first and most important step toward TPO is data integration. Enterprises must invest in a capable data signal repository solution that can harmonize data across disparate sources. Key outcomes include automated integration of critical data sources (POS, syndicated, plan, COGS, forecasts), enforced consistency in reporting and applied business rules, and enhanced data quality.
The next step is data intelligence. The TPI infrastructure stores and analyzes the integrated data, which provides enhanced visibility of ROI, lift and cannibalization scenarios, and more.
Finally, data analytics offers CPG enterprises predictive insights for course correction and strategy modification. Top outcomes include what-if and causal analysis of pre- and post-event trade scenarios, and a science-led approach to directing funds from low profitability promotions to high-impact profitability areas.
This three-step phased approach would ultimately help the CPG enterprise achieve the maturity to reach trade promotions optimization.
Learn how Unilever is developing and managing winning promotions in the modern, volatile world.