Tackling demand volatility using data? Here’s what you need to knowCOVID-19 is still causing supply chain challenges two years into the pandemic, keeping everyone from manufacturers to retailers guessing. Those who don’t have a good grasp of their data feel the volatility most keenly.
Recently, Alloy CEO Joel Beal spoke to Tile CEO CJ Prober about how Tile harnessed the power of data to ease their supply chain woes. You can watch the whole conversation here – but if you just have time for the highlights, we’ve outlined the top four tips on how to tackle demand volatility below.
Most people predicted that supply chain disruption, consumer demand, inflation and consumer confidence would normalize at some point, but there’s still no evidence of it. Smart retailers like Tile are planning as if this is the new reality, at least on the supply side.
Demand is starting to go back to its pre-COVID trend as people venture out to brick and mortar stores again. But some shifts are irreversible and a lot depends on future COVID waves. The recovery from COVID has been slower in some countries, and new variants with new mask and distancing requirements can cause brand-new disruptions.
Prober’s advice? Use a supply-constrained planning strategy — meaning it’s better to have less supply on hand than you need than to be stuck with a lot of excess product when demand drops or moves online again.
"You're getting immediate feedback on how consumers are reacting to a new product, immediate feedback on the performance of your marketing, I view Alloy as the foundation of enabling that for a consumer goods business."
Since new challenges are hard to predict, Prober recommended a multi-pronged approach to reducing your risk. “There’s no silver bullet,” he said. “If anybody’s expecting an easy solution, I don’t have it.”
But he does have some suggestions based on Tile’s success. Prober suggested building a longer-term planning process. For example, Tile is now planning roadmaps a year ahead of where they would in a normal supply chain environment to account for much longer lead times for components. They’re also working with two-year supply models that they constantly update to reflect changing variables.
The company has proactively sourced key components from multiple suppliers. That firms up their supply chain, since another supplier may be able to provide components when the first has trouble getting them from their fabricator.
Tile’s acquisition by Life360 highlighted another key strategy, one more brands are focusing on: memberships vs. just hardware sales. Membership models help create a more predictable demand, which reduces the amount of scrambling you have to do in times of upheaval.
Finally, Prober said you should be in a constant state of continuous planning based on the latest supply and demand signals and iterating on a weekly basis. He pointed out that having a platform (rather than a cumbersome Excel spreadsheet) to easily change data points and iterate solutions is crucial.
A big piece of advice Prober shared was to marry demand and supply together, rather than looking at them separately.
Approaching your business in a data-driven manner and connecting these supply and demand signals helps you build a more sustainable planning process.
Many companies still plan based on how much product they’re selling into a specific retailer, rather than how much of that product is actually getting sold through to consumers. This creates a degree of separation between them and their actual demand signals, making it even harder to avoid inventory buildups and drops in order volume.
“I think we’re in a unique time where data’s never been more available than it is today,” Prober said. He stressed the importance of using your data to set yourself up for long-term success and navigate through short-term to years-long challenges. Narrowing the gap between the amount of product you have on hand versus demand helps you to mitigate those challenges. A Connected Planning and Execution platform makes this more achievable.
Most people use Excel to handle their planning – but that comes with a lot of headaches. It can take upwards of two weeks to run demand signals through Excel and interpret the data to figure out what it means and come up with a plan of action. That’s two weeks too long.
Alloy, Prober pointed out, takes this stress out of the process. You can connect demand signals from a retailer’s POS data to your supply side and build a demand planning process you can iterate on the fly.
Another key point: as you scale, people are often looking at different points of data and no one knows what’s happening in the next silo. Having all of your data in one platform that everyone can access keeps all those siloes connected so planning between teams becomes much easier.
Even better, this one-stop-shop for your company’s demand and supply chain data helps you spot and solve problems much more efficiently. If a particular retailer is struggling, you’re better able to figure out whether it’s a store-level, inventory, foot traffic, or placement issue. Being able to identify the most likely problem and proactively make changes can seriously boost your sell-through rate.
Ready to get the most out of your supply chain and demand data? Check out our new Retail Analytics Buyer’s Guide to learn how you can use the POS and inventory data retailers provide to build trust and grow the business.
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