Supply Chain Issues Highlight the Need for Predictive Inventory Modeling
If you’ve been in a grocery store with any regularity over the past 12-18 months, there’s likely something on your list you were unable to buy. Chicken breasts. Eggs. Blueberries. Your favorite brand of chips. Supply chain disruptions are causing product shortages of all types, and their not always easy to predict. It’s inconvenient for customers, and it’s created all sorts of headaches for the retailers working to keep stock on their shelves.
Food supply chains will continue to encounter turbulence — at least as long as the pandemic continues. So, retailers must get smarter about they’re response to product shortages. It starts — and ends — with a predictive approach to inventory modeling.
The problem with food supply chains
While every supply chain has experienced some level of disruption in recent years, food and grocery have had it the worst. Food distribution supply chains are some of the broadest and most complex. It’s difficult to get avocados from Mexico with a truck driver shortage. Absenteeism contributes to name-brand snacks disappearing from shelves faster than staff can restock them. Chocolate products take twice as long to get from source to shelf when intermodal transport slows.
Grocery and C-store chains are between a rock and a hard place: rising consumer demand vs. shortages caused by supply chain disruption. As these struggles persist, retailers need to adapt. It starts by looking at data to anticipate future challenges.?
Making the most of empty shelves
For grocers, empty shelves kill profitability. Shelf space is real estate, and the longer it goes unoccupied, the more revenue retailers lose. Keeping products on the shelf is paramount. It’s a mission made even more crucial by the perishability of many food items.
But grocers can now leverage data analytics to finesse inventory inconsistency and move product with regularity. Here’s how it works:
Look at what customers buy and when they’re buying. It’s easy to look at empty spots on the shelf and identify in-demand items, but there are hierarchies. Which is more important, eggs or steak? Bananas or bread? Chart how fast these items fly off the shelves to gauge real demand with quantifiable timeframes. Grocers may find they have mere hours before some items move and inventory for days on other items. A precision look at consumer habits helps stores anticipate inventory turnover.
How much inventory are you receiving based on demand? Retailers should aggregate prior-year data to review figures vs. what they’re receiving today. It’s important to examine both quantity and price. If the weekly average of eggs sold over the five prior years is 1,000 cartons at an aggregate average of $1.29, grocers can do the math to understand what they need today and how to maintain appropriate margins while balancing stock. It’s not enough to say, “We need to order more eggs.” How many more? At what price? To make the most of future predictive modeling, retailers should use real data from prior years.
Now is the time for grocers to diversify supply chains, and forge ahead with new supplier relationships. To do so effectively, they need to compare vendors on an equal playing field. Analytical software can balance costs, terms, volume, delivery times, and more, to provide flat, forward-looking comparisons. As grocers pivot to new relationships with untested suppliers, they can do so with quantifiable KPIs and benchmarks in mind.
All this happens on the back of data. But where does the data come from? For many grocers, it’s currently siloed or segmented. To make use of it, stores need to consolidate data and analyze it with a broader scope.
Create a control tower for monitoring inventory
While many grocers have the tenure and experience to adapt to supply chain disruptions, the current climate demands a more proactive approach. Stores need to anticipate, rather than simply adapt to, problems.
Imagine having the data to know exactly how long the next shipment will last on the shelf. How far in advance does a retailer need to order X, Y, and Z products? How should they price a specific product to maintain margins with a new supplier? Inventory insights make it easier to mitigate friction in the face of a supply and demand tug of war between consumers and producers. A clear look at the right data, with intuitive modeling and data visualization tools, is all it takes to predict trends.
There’s no way to control which products will face shortages or when those shortages will occur. All retailers can do is look ahead. Predictive inventory modeling and new customer fulfillment solutions are key to getting product into the hands of customers quickly and keeping shelves stocked between supplier disruptions.
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To learn more about predictive inventory modeling, explore Nextuple’s Control Tower. It’s a first line of defense for the early identification and mitigation of fulfillment risks.