OK, give me an honest answer, what’s your Planner do as soon as they receive the most recent forecast revision?
I mean, after rolling their eyes!
They change it, of course!
And why do they change the carefully-constructed forecast? Because the one thing we all know about a forecast is that it is WRONG.
Typically the Planner has better information. Either something new happened between the time of forecast creation and forecast publication, or new orders came in, or the Planner sees information the Forecaster doesn’t see, or the forecast is in monthly buckets and the planner needs weekly, perhaps the forecast is in weekly buckets and the Planner needs to break this do daily.
Either way, the Planner sees things the Forecaster doesn’t. And time is not a friend of the forecast. The next day the forecast is another day older, and more information comes in. The following day… and so on.
Orders come in, get changed, and ship. Time sensitive information is available about orders, shipments, customer preferences and patterns. As time-specific information comes in, and Planners make more changes. Or, even worse, they don’t make the changes, leading to missed orders, expedites, and over-buffering inventory.
The reality is that Planners can only react to the dozen-or-so products they can manage manually! Other SKU’s are “left to their own devices”, typically on reorder-point planning, possibly over-buffered with inventory, or expedited – or missed.
What is the answer?
In a recent blog titled Know what your consumers are thinking, before they do! Richard Howells talked about the need for getting closer to actual customer demand and improving our traditional forecasting processes. This involves gathering insight from inside and outside of your organization, from all available structured and unstructured sources.
So, what if we could sense all these changes, patterns, and “new” information, and make recommendations FOR the Planner? And let’s do this not on a couple dozen products, but for every last one? And in real-time?
Enterprise Demand Sensing does just that: Manage this “big data”, multiple forecast signals, different forecast and consumption timing, with automatic pattern recognition, automatic weighting of the different demand factors and patterns, and with forecast updates to ASSIST the planners.
All this (big) data is available in a harmonized view of actual demand for your products, helping drive promotional plans, inventory positioning and organizational decisions in real time.
EDS helps you foresee changes in demand sooner and boost sales by predicting and reducing out-of-stocks or slumps in sales. Or make smarter inventory decisions around logistics, safety stocks and transportation plans.
To learn more on how to better sense demand, and get closer to your customer and actual demand SAP and SAP Insider are hosting a webinar on February 27th. Register today to join us online and supercharge your demand management.
Follow us on @scmatsap