The demand history can’t tell us everything about the future, but it can tell us some things. This article and video outlines exactly what and shows an example of automated forecasting in an Excel tool.
Here is a story about an attempt to size inventory buffers, by measuring demand variability. It is based on a true story and there are lessons learned from real experience.
I’ll tell you the story in both words and data. I have compiled a dataset and will share it here.
Demand-Driven MRP in an Excel Planning System. See a demo system and get a free, fully-functional copy of the DDMRP planning system in Excel.
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Setting service levels usually starts with inventory.
Here’s a way to improve supply for important customers, that doesn’t involve inventory sizing.
And it doesn’t involve production either…
In times of shortage, how do you allocate inventory to customer orders?
It is tempting to fall back on hard allocation. This could be a mistake.
Here’s why. With a download simulation to prove it.
Here are five things you need to know about forecasting.
This is a statistics-free zone. Five forecasting principles for demand planning.
This is a core method to apply the Fast Excel Development Method in building a planning and scheduling system in Excel.
Convert forecasts, explode demand and generate work orders — this method is something that every planner should know.
Is the purpose of production scheduling to feed MRP and execution?
If you’re satisfied with this answer, then you’re missing something. A small, two-letter word will change the way you look at scheduling.
The biggest headache in material planning is long lead-time materials.
Here is a simple tool that gives visibility between a buyer and a factory separated by a lot of water.
Also see an easy trick to connect multiple Excel users on different continents with free data integration over the cloud.
Predictive planning provides a way to manage uncertainty. Planning can resolve the dilemma between schedule-push and demand-pull.
How an Excel-based predictive planning tool can work alongside the business transaction system.
Analytics for demand planning in Excel usually involves big tables of data.
To understand the demand for a product, you need to look into its history. An order history can easily have 100K+ records.
Here is a technique to perform fast analytical formulas on many thousand rows.
The dilemma of demand planning: to use a forecast or history.
We cannot expect history to repeat itself, yet every day we are reminded of inaccuracy and bias in the forecast.
How to combine the forecast and history to get a true measure of demand.
