The Role of Data Analytics in Demand Planning
Data analytics, when pulled off right, can transform your demand planning apps into your most valuable assets. The dream is to have a data analytics machine that accounts for every variable, allowing you to move them around to see how the picture changes when you increase supply here instead of there. Of course, not every prediction can be totally accurate, but a choice that improves sales by 20% is well worth looking into.
Managing Customer Unpredictability
The biggest factor, of course, is a customer or region and their unpredictability. They may suddenly decide they're cutting down on your product or service next quarter. What are you supposed to do then?
If you start data analytics today, that shift in demand can be recorded in a history of customer behavior. Over time, you build a collection of profiles that help you make better decisions going forward. You might even have an automated app that accounts for and anticipates those changes in demand – and offers solutions that mitigate any associated risk.
And because the data is entered and analyzed automatically, nothing gets missed. Ever.
Some Processes are Better Automated
If you go with automated data analytics, you save a ton on money and resources as you'd no longer need a team for analyzing and forecasting. The AI in the app considers every data point and makes a suggestion – while the human element can forget key statistics in favor of an imperfect intuition.
One additional difference between these two is that you don't have to do what the AI says, while your relationship with a team member or partner may be affected by your response to their input.
Humans are creatures of habit, relying on old ways of thinking even when industry standards change or abnormal situations arise. An AI-powered forecaster can serve as the voice of reason when you or your coworkers have severe tunnel vision. The software might not be right 100% of the time, but it will always remind you of things you may have forgotten or neglected.
Every Variable Accounted For
Wouldn't it be great if you could account for things like the weather and increasing gas prices when forecasting? Is it even possible to do that without devoting hundreds of employee hours unnecessarily?
The truth is that, for many industries, data analytics solutions are woefully incomplete if they don't take weather and gas into account. Replace weather and gas with any number of other things, depending on your sector. These are the kinds of factors that can help make your decisions more informed.
You can never have too many eyes watching for important trends in your supply chain operations. Data analytics make you privy to things you never would've noticed otherwise – giving you the opportunity to transform your business like never before.
When to Go With an Automated Data Analytics Solution
John Galt Solutions has an array of demand planning apps that read what's happening on your supply chain and make changes to your schedule based on customer demand and other variables. That's exactly how Reddy Ice uses Atlas, which automates the company's forecasting and allows them to reassess needs on a daily basis. The result is hundreds of working hours saved and an increase in profits. We think those results speak for themselves.