How to overcome the top five challenges demand planners face

Demand planning can be hard—really hard. Here are the top 5 challenges that demand planners face. In the end, we’ll explain how you can overcome these in your organization.

1. Collecting information from various siloed teams

Creating a demand plan means consolidating information from multiple teams to get critical information like sales activity or promotion information. The problem? Most of them have no vested interest in getting you accurate information on time. Collecting key information is a weekly ‘cat-herding’ exercise.

2. Making sense of differently formatted information

Collecting information from various cross-functional silos in your organization means collecting spreadsheets. Lots of spreadsheets, all formatted differently. How can anyone tell what’s changed from last month with all this differently-formatted, inconsistent information?

3. Creating the demand plan

Once you’ve painstakingly collected as much information as possible, you upload it into your demand planning system and create your plan. But once again—something doesn’t feel quite right. You worked your usual magic (which you don’t get enough credit for), but it’s like a piece of the puzzle is missing. Historical sales and demand data are helpful, but it’s only creating a two-dimensional forecast. If only your well-honed planning skills could be enabled by real-time, leading indicators of demand to make a genuinely comprehensive forecast.

4. Getting teams to use it

Your plan was approved. Great! Once you’ve created your forecast, it will be implemented and generate impressive results. We wish. It turns out the supply chain team didn’t even implement your plan because they couldn’t see or understand any of the assumptions you baked into it. Ultimately, they implemented their plan because they didn’t want to get stuck with excess inventory and be blamed for it.

5. Getting blamed for poor forecast accuracy

After all your work, management isn’t happy with the forecast you created—again. The worst part is that they’re blaming you as if you were solely responsible for excess inventory and poor on-shelf availability. When you raise issues to management about poor planning processes, all you hear back is some version of ‘Don’t Bring Me Problems, Bring Me Solutions’.

As you’ve undoubtedly realized, overcoming these challenges that you face on a day-to-day basis is going to take more than an ‘agile’ methodology and a whiteboard covered in post-it notes (not that we have anything against agile.)

Luckily, there is good news.

The good news is that technology is quickly evolving how companies forecast demand. Artificial intelligence techniques and machine-learning algorithms enable platforms to take leading indicators of demand (e.g., weather, future sales activity, promotions) into account and make forecasts much more accurate.

That’s precisely what we’ve been working on at o9—a platform enabled with AI-based techniques such as ML forecasting that will move the needle for you and your organization. It was designed to overcome the Top 5 challenges a Demand Planner faces by enabling truly streamlined demand planning processes, ML-powered forecasting that processes massive amounts of internal and external data (not just historical data), to deliver dramatically more accurate results.

This isn’t a ‘pie-in-the-sky’ idea. We’ve built it, and businesses are already reaping the rewards. It’s not just transforming how companies forecast demand; it’s converting companies’ DNA from traditional to digital. Soon, planning the conventional way will be like printing directions on MapQuest before your road trip.

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