One of Alloy’s customers, a consumer electronics executive, recently shared with me that he also believes consumer behavior is going to change much faster than anybody thought, and change for good. For example, Best Buy stores are now all closed and shopping has quickly shifted online. Even when stores reopen though, he questions whether consumers will return in the same numbers to experience and purchase products. Touching the same demo product everyone else has and standing in line to check out can suddenly seem unsafe and unnecessary after experiencing an alternative.
The research backs him up too: In February 2014, a three-day strike on the London Tube forced commuters to experiment with new routes. Afterward, around one in 20 stuck with their new commutes—and that’s a very small change compared to what we are experiencing today!
A framework for uncertain times
In the short, medium, and long-term, the size and shape of demand will continue to evolve. To be ready to respond, consumer goods manufacturers need to get closer than ever to the end consumer: identify shifts as soon as they start to happen, and break them down by product, channel, and partner to pinpoint how the business is affected and determine the right course of action.
In this post, we lay out a framework to help you quickly spot when demand for each of your products is rising, falling, or re-distributing. Then by de-averaging the impact, sales and supply chain teams can act swiftly to optimize inventory management and partner effectively with retailers.
The framework doesn’t require waiting for retailers to make the first move—a risky proposition that could mean being too late to respond to demand shifts, mis-allocating inventory, or even moving in the wrong direction as retailers can over- or under- react to fluctuations and anomalies. It takes into account three different definitions of “demand”:
- What retailers expect consumers to buy, which is reflected in orders (commonly referred to as sell-in)
- What consumers actually buy, which is reflected in store point-of-sale and e-commerce sales data (commonly referred to as sell-through or sell-out)
- What consumers would like to buy, whether they are able to do so or not, which must be derived based on sell-through and some measure of lost sales (commonly referred to as true demand or unconstrained demand)
When consumer demand is stable, these three demand metrics are all about the same in an efficiently operating supply chain (seasonality aside). Consumers are able to actually buy just about everything they want (unconstrained demand ≈ sell-through), and retailers are ordering from manufacturers just about enough to meet that demand (sell-through ≈ sell-in). That may still be the case for certain categories that are not really affected by the pandemic, though I struggle to imagine any.