Latest Precima News
Jan 7, 2021
Press enter to search By Thad Rueter - 01/07/2021 Brian Ross, President of Precima, a Nielsen company. Retailers of food and consumables begin 2021 with an operational challenge unlike any they have faced previously. Accurately forecasting shopper demand by category, brand and channel has been disrupted due to challenging comparisons with prior year results when the onset of the COVID-19 pandemic led to erratic and irrational spending behaviors. To better understand how retailers can address these unusual circumstances to make optimal assortment decisions, Progressive Grocer spoke with Brian Ross, the president of Precima, a global retail strategy and analytics company that was acquired by Nielsen in 2020. Progressive Grocer: Given the disruption in demand we saw throughout 2020, what do you think are the main challenges and opportunities when it comes to assortment planning in 2021? Brian Ross: Assortment management is a challenge in the best of times and requires the constant deployment of best practices. The COVID-19 pandemic has elevated assortment management to a new level as demand signals have been shattered by unpredictable shopper behavior across categories. Massive disruptions mean supply chains struggle to catch up with shortages caused by both consumer stockpiling and production challenges, impacting the entire industry in profound ways. Retailers and their suppliers responded heroically, but out-of-stocks and supply-chain complications have persisted in many categories. I fully expect this situation to dominate the thinking of merchandisers for most if not all of this year. Beyond 2021, there will be a significant SKU rationalization as retailers do a postmortem review of assortment planning during the pandemic, which will likely result in a cutting of many existing SKUs and the addition of many new ones. PG: How can artificial intelligence help with assortment planning? BR: The disruptions at the shelf in 2020 are not evidence the existing merchandising and assortment planning technology has failed — it does exactly what it was designed to do. But measuring actual demand at the shelf during the crisis relied on data that wasn’t a true reflection of long term shopper preference or consumption behavior. This is where AI comes in. AI can analyze all of the transaction log data from before and during the crisis, combine it with other variables that accurately imitate the changes in consumer behavior due to the pandemic and create models for future demand that marketers and merchandisers can base their plans on. AI also helps address a wide range of marketing, merchandising and demand fulfillment issues in the as-yet-to-be-undetermined post-quarantine world, and build out scenarios to understand how customer behavior is changing in each category, for each demographic segment and for each geographic region. PG: Have any best practices emerged for AI food retail product assortment planning? BR: A few things. Food retailers need to start by understanding the true consumer behavior change over the past year. This will reveal implications and opportunities for assortment. Given the “black-swan” nature of COVID-19, it is critical not to solely rely on traditional assortment modeling and algorithms. An adjusted approach will help understand item preferences and substitution and demand-transfer. Retailers need to assess assortments more frequently. In periods of instability they should review and adjust their plans as behaviors and circumstances change, not according to a fixed schedule. This also requires closer collaboration with vendors, especially on the demand and supply forecasts. PG: What are the main things food retailers need to know about AI assortment planning going into 2021? BR: Assortments will certainly look different in many categories. There will likely be fewer varieties, package sizes and brands. It is also probable that a few new brands that gained a toehold during the crisis will remain in the mix. This presents an opportunity for retailers that have struggled with SKU proliferation to smartly rationalize the assortment to key items in key categories that appeal to key customers. This rationalization can only be optimized with the help of AI-based solutions that automate many of the easy decisions, leaving the most critical ones to the merchandisers. AI helps retailers truly understand the impacts of everything from how delisting a product that could result in profitable customers shopping elsewhere to what synergies there are between products that result in bigger market baskets. And it does it in near real time so there is little latency in perusing the opportunities identified.