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Not all demand is true demand
For consumer goods companies with omnichannel sales, downstream demand is a key signal to guide inventory allocation, new product launches, demand planning, and other decisions. However, not all downstream demand is created equal.
To minimize lost sales due to out-of-stocks, companies must measure against true demand. But what is true demand, and why is it so important? We had the opportunity to give a presentation on this topic at the TPA Supply Chain Conference; here are some of the key points we discussed.
First, an example
At a high level, measuring true demand is important because it helps reduce lost sales that stem from out-of-stocks. As an illustration, imagine that a shopper comes to a Safeway in Northern California. She intends to purchase a specific brand of toothpaste, but finds that the store is out-of-stock.
Past studies have estimated that lost sales are generally equivalent to about 4% of revenue.
She may decide to purchase a different brand’s whitening toothpaste instead, which would be revenue lost for the brand she intended to buy. Or, she may decide to make the trip to a neighboring Target, where the preferred brand is in stock. That would be revenue lost for Safeway. In both scenarios, the stock-out has led to a lost sale. Across all shoppers, both consumer goods companies and the retailers they sell through are impacted.
For this reason, both parties are incentivized to work together to use true demand for inventory management. It helps ensure consumers can purchase the products they want, when and where they want them.
Calculating the costs
So, lost sales because of out-of-stocks are clearly a real issue. But just how big of a problem is it for the collective retail ecosystem? As it turns out, it’s a very expensive problem.
It’s estimated that there are 38,571 supermarkets in the United States that exceed $2M in annual sales, and they do about $682.7B in total revenue. Past studies have estimated that lost sales are generally equivalent to about 4% of revenue — in this case, that would be $27.3B. If we can prevent even a fourth of lost sales by decreasing out-of-stocks, that would amount to an extra $6.8B in revenue every year, and that’s just for grocery stores!
The key to recouping this revenue is the difference between generic demand and “true demand.” Tracking for true demand means thinking about demand at the individual consumer level — shifting from “filling orders” to “filling shelves.” This granular approach is different from typical supply chain management that stops tracking at the distribution center or other higher levels. Demand at the DC is just a proxy for true demand.
Why use a proxy when you have the real thing?
In our experience, several obstacles stand in the way of companies hoping to measure true demand.
- Generic business intelligence tools. Many companies are working with generic tools that are not designed for consumer goods manufacturers’ use cases. On top of that, outdated infrastructure and legacy systems often create unstructured or difficult-to-access data. The disconnect makes it difficult to trace up and down the supply chain to find the root cause of issues and take corrective action.
- Data paralysis. Measuring true demand means tracking every purchase of every item by SKU, store, geography, etc. The result is a lot of data! For companies already taxed by current reporting and analysis needs, it can be overwhelming to try to spin this proverbial mountain of straw into gold.
- Culture. The organizational process for consumer goods companies selling to retailers focuses on bulk orders, and incentives and KPIs structured around sell-in rather than the way each product actually moves in each store — in other words, sell-through.
Shifting from proxies to true demand
Companies might also wonder if such granularity really makes enough of a difference to be worth the investment. Based on working with clients across a number of industries, we’ve found the answer to be a resounding “yes!”. Here are three situations where the lack of access to true demand can get you in trouble.
- Using averages instead of granular data obfuscates the important variation that leads to actionable insights. By definition, a portion of your stores, SKUs, or whatever you’re measuring are performing below average, and should be the targets of optimization to avoid lost sales.
- If visibility stops at the distribution center, it can create a false sense of security and increase the time it takes for consumer demand signals to propagate back to the manufacturer, hampering the company’s ability to respond in time to current sales trends and opportunities.
- Efficiently conducting a root cause analysis when problems occur is key to minimizing impact, but without granular sales data, it’s impossible to truly access the “roots” of issues.
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