03 May IBP Demand Sensing: How Can I Make My Forecast Team Less Wrong?
(By Libby Evans)
So you get a forecast that turns out to be decent, at a high level. However, they’ve really missed the boat when it came to downstream proportions for a particular week and the consumption at different locations varies greatly throughout the week. IBP to the rescue. IBP offers a super powerful tool to help you more accurately execute the demand plan and pick up on those weekly or daily fluctuations in order to service the correct customers at the correct locations. And in order for this to happen, you don’t have to hope that your forecasting team is super accurate at the customer level on a daily basis.
Here’s how it works. Let’s say I have a forecast of 100 banjos for the week. I ship out banjos daily from my manufacturing facility to two warehouses that service my customers. Over the course of the past year, each warehouse has had equal demand. Based on that historical data, my execution plan would tell me to ship 10 units to each warehouse each day. But what if demand at each warehouse was not that simple? What if weather patterns had an effect on banjo demand? What if my sales team put pressure on customers at the end of the week when final banjo sales numbers were due?
Now what if you could somehow “see” those banjo patterns, whatever the cause, and react? Or, here’s the big one – what if history wasn’t a good indicator of future banjo sales?! That’s where IBP comes in. A better delivery pattern for banjos this week might actually look like the image on below, and now I actually have inventory where and when I’ve got real demand!
Dollars & Sense
IBP Demand Sensing allows near-term tweaking of the execution plan (production sequencing, packaging material procurement, and logistics) to adjust to short-term patterns and changes. IBP also allows integration of Point of Sale data from your retailers, which gets you that much closer to the root of your demand, and closer to understanding the true patterns. The result of all of this? I’ve minimized non-value add movement of goods by reducing the need to expedite transfers from Warehouse B to cover Warehouse A. This also reduces the strain on customer service and logistics to coordinate the movements. I’ve maximized customer service by having products where they are needed when the customer asks for them. Again, this reduces strain on customer service. And I’ve minimized my inventory cost by improving forecast accuracy which in turn reduces safety stock at all nodes. And I come out looking like a hero. Well done, IBP.
Ready to see how this plays out? Get in touch with us. We’d love to chat. Or check out the other blogs in this series.