The forecast said you should order 10,000 units, so you did it. And why wouldn’t you? The numbers make sense. Then, 6 weeks go by, and you have 7,000 units collecting dust in the warehouse. It turns out that your forecast was nothing more than a guess, and it also turned out to be very expensive.
Forecasting isn’t perfect, and it never will be because there’s no way to accurately predict what will happen in the future.Still, it exists for a reason, so why does it seem not to work for you?
Where Things Usually Go Wrong
Before you can fix what doesn’t work, you first need to know which mistakes you’re making, so let’s take a look.
Relying Too Much on Past Data
It makes perfect sense to look at historical data. After all, where else will you look? You need real numbers to plug into the spreadsheet, and this is where you get them. The problem with past patterns is that you can’t know if they’ll repeat or not.
Products that may have sold out every single February for the past 5 years could end up sitting on the shelf until September because the demand has changed. That doesn’t mean you shouldn’t look at past data, but you have to combine it with what’s currently happening, like web traffic and early orders.
Ignoring What’s Happening Outside Your Business
You need internal data, but you can’t count on that alone. Weather and local events have a huge impact on the market, not to mention how much economic shifts can impact demand. But these factors are not as easy to track, so people decide they won’t bother with them. And they’re left with guessing.
Outside data has to be a part of your forecasts, which is why you should look for the easiest weather API. It will help your team make tweaks to the forecasts and make them more accurate.
Treating Forecasting Like Something You Do Once
You’ll see teams build a forecast once a month, and that’s it. Done. But forecasting is never actually DONE because the market doesn’t stay the same. Things change around you all day, every day; your competitor runs a sale, suppliers raise their prices, TikTok makes a product viral, and so on. If forecasting is a one-and-done thing in your company, you’ll react too slowly to take advantage of what’s happening.
Luckily, the fix is really simple. All you have to do is regularly use rolling forecasts. Check the most important numbers every week, and adjust them as you get new information.
Teams Don’t Share the Same Data
You have the sales team working off one set of numbers, the marketing team has something else, and the numbers the operations team hasn’t even close to what either of the previous teams has. That’s no way to work.
None of these numbers is necessarily wrong, but nobody has the full picture, and the only result you can expect is a mess. Demand jumps, but operations had no idea the promotion was coming, so there’s no extra stock to ship out. Now your customers are angry, and you’re losing business, when all you had to do was give everyone shared access to the same live data.
Making the Model Too Complicated
If your forecasting system has dozens of variables and custom formulas, who can even understand any of it? Even if this were easy to maintain (and it isn’t), it’s just too complicated. And complicated systems spit out strange numbers, so you have no idea if you can trust what it says or not.
The simpler models are usually the most useful tool. What you want – as a business owner – is a clear and fully transparent forecast that pretty much anyone can read. To get there, you can use last year’s sales and add in a couple of current signals (eg, website traffic trends, conversion rates, search demand, card additions/wishlists, ad performance, social media, competitor data, weather changes, logistics, etc.).
Then, if you want (or have) to add more, that’s fine because you’ve got a foundation. Just make sure that, regardless of how complex you make it, it is kept useful (user-friendly, combined with data that matters).
Not Planning for Unexpected Spikes
Demand is unpredictable. A celebrity wears a new jacket, and suddenly everyone wants it. You’re used to selling 50 units a day, but now your customers are asking for 500. If your forecasting model is rigid, it can’t handle spikes like these. As a result, you react too late, and by the time your stock is in, the spike is over.
Build flexible plans. You should keep small buffers on the products in your inventory that could go viral. And the way to see what could go viral is to watch for signs like who’s mentioning what on social media, or what people are searching for the most.
Conclusion
If you try to make your forecasting perfect, you’ll drive yourself insane because that can’t be done. Nobody’s after perfection here; what you want is flexibility in the sense that one wrong number doesn’t result in a catastrophe.
When you look at all these mistakes, you can see that they all come down to 2 things: missing information or using information that’s too old to be useful.
