Data Transparency is Key to Ensuring Improved Demand Forecasting Models
CI&T, a leader in driving digital transformation for global brands, today published Solving CPG & Retailer Demand Forecasting Dilemmas, which examines the demand forecasting relationship between retailers and suppliers. The report highlights pain points and opportunities for both parties, revealing a misalignment of data strategies causing ineffective forecasting.
Demand forecasting, using data and insights to predict how much of a specific product consumers will want to purchase during a defined time period, is often a unique process to the retailer-supplier relationship and historically limited in its data sharing capabilities. The purchase pattern unpredictability accelerated by the pandemic, combined with the rise in suppliers heading towards DTC make the case to reexamine this outdated relationship.
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2020 saw major shortages in toilet paper, bottled water and other necessities that could have been prevented had retailers and suppliers established more collaborative and aligned partnerships by co-owning sales data and objectives. In this report, CI&T asserts that the best way to ensure improved demand forecasting is for retailers and suppliers to share consumer, sales and basket data with each other, and for both parties to push for upgrading their processes.
Key findings from the report include:
- Suppliers’ highest ranking challenge related to forecasting demand was visibility and access to data. Retailers’ highest ranking challenge related to demand forecasting was scaling the data platform
- Suppliers reported they were most likely to break demand forecasting down by geography, while retailers were most likely to report breaking down demand forecasting by channel
- The majority of suppliers reported looking at sales data from the same month over years prior as their predictive approach, while the majority of retailers reported referencing the previous month’s sales to predict the following month
- Both suppliers and retailers overwhelmingly reported that consumer-level data (gender, age, household size) is the most likely type of data leveraged for demand forecasting
“Demand forecasting is the foundation of the retail industry. Recalibrating the retailer-supplier relationship to ensure more accurate forecasting will lead to a wide range of benefits for all parties involved in the supply chain,” added Melissa Minkow, Retail Industry Lead at CI&T.
“If demand forecasting models improve through shared data, stockouts are reduced, waste generation is decreased, and less items go to markdown.”
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CI&T’s research centered around interviews and a survey of 115 executives at various big box retailers and CPG suppliers to determine where the demand forecasting disparities, pain points and opportunities exist for each party.