5 Tips to Incorporate Illness Data into your Demand Planning

August 12, 2021

At the height of the COVID-19 pandemic, it was a safe bet that almost everyone almost everywhere needed products like hand sanitizer and disinfectants. But now, as we move into what looks like a more regular illness season, how will brands decide where products with illness-based demand, like decongestants and tissues, will be needed and when? With illness data, that’s how!

1. Map Demand by Location

One of the most potent tools illness data can unlock is forecasting where exactly people will become sick. If you’re stuck using historical information, you’ll miss out on the changing and dynamic landscape of illness. But with illness data, you can understand where customers will need your products up to 20 weeks before their illness episode.

2. Reduce Forecasting Error

Forecasting anything, let alone illness, is both a science and an art. No matter how complex the modeling or data is, there is always a chance of something unpredictable. But using illness data, you can reduce forecasting errors by up to 50%. That gives you extra time to adapt your strategies and make sure your product is in front of the people who need it most.

3. Account for Pantry Loading  

An essential aspect of demand planning is understanding what customers already have. You won’t sell much toilet paper if everyone has enough stock for a small army in their closet. Prior to the pandemic, illness products were generally purchased close to when a consumer needed them - but since then, purchase patterns have changed. Consumers are now more likely to “pantry load” and keep multiple products in their homes in advance of when they actually want to consume them, creating inventory in consumer homes. Kinsa Insight’s Illness Forecast can help assess how much product is actually used based on underlying illness levels. 

4. Avoid Out-Of-Stocks:

Illness seasons are volatile. Unexpected surges in demand can outstrip inventory in stores and distribution centers. Out-of-stocks quickly translate into “lost sales” for retailers and impact shopper loyalty. For example, stopping by your go-to store for cold and flu remedies, only to find they’re out, will cause loyal shoppers to shop elsewhere, potentially losing them as a customer altogether. 

5. Plan Ahead

With high accuracy and long lead time, illness data can help your business get and stay ahead of your competitors. You can make sure your products are on the shelf long after other brands have sold out. 


Kinsa Insights is a leading provider of illness data, allowing your company to be the first mover in the illness market. Our illness forecast is the earliest and most accurate, giving you up to 20 weeks lead time. With Kinsa Insights as part of your demand planning strategy, you can stay a step ahead of the competition and keep your products in stock.

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