The basics of MRP planning

2. How the FG (finish goods) forecast become RM (Raw material) forecast?

What is the purpose of MRP?

MRP planning takes your sales forecast of FG (finished goods) and translates it into RM consumptions.

The sales forecast is given as quantity needed for every period and the output is the quantity needed for each raw material in every period.

The MRP takes into account the inventory of RM, WIP (work in progress), and FG, but in this article we will focus purely on the consumption of raw materials not taking into consideration the inventory.

How does the FG forecast become RM forecast?

Each sales forecast creates a demand that has quantity and time period. You can enter many forecasts (such as from each salesperson/region/country) to many finished goods on many time periods.

The basic record of the sales forecast will look like this:

FG ID number | Time period | Quantity — Finished goods forecast record

The MRP will take this record and translate it into raw materials using BOM (Bill of materials). The BOM tells the MRP what is the ratio between the finished product and the raw material (for example: 1 car has 4 wheels).

The MRP output for every FG input record will look like this:

Here is an example of translating flying cars into raw materials:

Combine the data:

Every FG forecast record becomes one or more RM forecast records. Now the MRP combines all records to get the sum quantity for every RM ID number per period.

Let’s add another flying car with different wings and the same wheels:

The MRP will combine the wheels demand for the same period of time if the RM ID number is the same.

Now let’s put the data into a column graph and the wheel demand will look like this:

Reminder: This is only the forecast demand for wheels. The MRP will give its recommendation base on the current inventory and the purchase order to come. BUT we want to analyze the demand and see if it makes sense. So we ignore the inventory and purchase orders to see if the demand is real or why it changes.

Past base forecast

Another way to predict the future demand is to look at the past demand. NOT the PAST CONSUMPTION.

I will explain the difference in tier2.

Lets look at the past demand in a time frame.

For this example we will use 4 months as a time frame. The actual demand might look like this:

If we want to predict the future consumptions (assuming no seasonal factors), we will predict that on average the future consumption will be 8 per month.

Next month we will do the average with Jan 18 and without Sep 17. This is called moving average and helps us keep the average changing according to the real demand.

Moving average example — The average follows the actual demand reducing the statistical noise

The advantage of using an average is that it is not affected by every time peak. In fact, the average will follow the actual demand, but at a slower pace. Let’s look at the example above. If we change the Dec 17 demand to be 16 (twice the previous month), the average will become 9. So although we doubled the demand from the previous month, the average only changed from 8 to 9.

This property of the average is also the disadvantage of this method. If there is a major change in the market, we will have a slow reaction to it.