Data And A Dose Of Experience Create Best Path To Decision-Making
By Jim Prevor, Editor-in-Chief, Produce Business
There is no question that the explosion in data available about fresh produce sales at retail creates an enormous opportunity for both retailers and vendors to use this data to find more effective ways to boost produce sales. Data, however, is not insight. Recognizing and appreciating the valuable contribution that United Fresh, the Perishables Group, and Del Monte Fresh made in supporting such research, it still is easy to struggle to understand the meaning and significance of the reams of data now available.
Take a look at generational data; it is interesting to pinpoint behavioral differences between Baby Boomers, Millennials, Gen X, Generation Z, and other generational cohorts. But do the differences signify divergent attitudes of distinct generational cohorts, or do the differences represent the transition of attitudes as people age? What one would really like are studies of Baby Boomers when they were 14 years old so we can compare with Generation Z — but we don’t have such long-term data.
Increases and decreases in sales of individual items change dramatically based on crop quality, quantity and timing. Even the location of production can have a dramatic impact on sales channels and price. Let Washington have a bumper crop of apples, and the large grower/shipper/packers in that state will carefully manage sales using substantial cold storage facilities and other resources. The exact same volume in states with smaller shippers is likely to find apples being dumped in terminal markets all over the country with prices collapsing.
Sometimes getting a deeper understanding of the data requires bringing in outside data. For example, if produce is picking up market share against meat, we want to know how prices of meat and poultry in that period stack up against price levels on produce.
Data also can’t be viewed in isolation. Did spinach sales plummet? One can’t just read the POS data; one needs to know that the FDA declared nobody should eat it that week.
And knowing the current news is not enough either. Food safety events, as an example, could have sales implications for years to come. And winnowing out the actual cause of data shifts is an exercise worthy of Sherlock Holmes.
Take the Alar crisis of 1988 — 60 Minutes ran a story that scared people away from apples, and apple sales declined. It seemed simple, and many surmised that consumers alone reacted to the 60 Minutes exposé and shied away from apples. But later, more in-depth studies said the situation was more complicated than that. Because of the news report, retailers shied away from promoting apples so they were removed from best food day ads and other promotions. A big chunk of the decline in apple sales seemed to have been due to retailers and their decisions to react to the Alar report as they did.
There are some things data can’t tell. We can’t sell more of a product than is produced. So if sales hold steady, that may be a sign of steady demand, or it may mean there is great untapped demand because production is not rising.
The produce department also evolves, and only careful attention to the data can winnow out the details. Winter produce sales exploded as production centers in Latin America became prominent during the past 30 years. So evaluating one year’s data against a different year requires assessment of product availability in each year.
Merchandising can also distort the numbers. If retailers decide to carry only one organic SKU on low volume items, organic sales may rise — but that might not signal any particular increase in consumer demand for organic produce.
The weak-willed may desire to run away from this data, yet that path guarantees the industry will not advance. The goal, instead, is to deeply engage with data and then interpret the data shrewdly. The subtext of the word shrewdly is utilizing the experience of multiple analysts, gathered through working in produce and with consumers over the course of a lifetime.
In other words, the popular perception that data is best used as a replacement for decisions previously made based on gut instinct, or mentoring delivered by old-timers, is not quite right. Yes, of course, decisions made based on good data are likely to be closer to optimal than decisions blindly followed because one’s first boss said it was so. But data, in and of itself, never tells us what to do.
There is no decision that automatically flows from streams of sales statistics. So those who will use data best are those who leverage the experience of people long active in the trade, with new insights from collected data, to identify paths to optimal decision-making. Data doesn’t eliminate the need for experience. Data provides a new forum for experience to add value.
So get this most interesting report, and make it useful by adding a good dose of produce expertise.