Proportional Factors and Life Cycle

[Former Member]

We are just beginning to look at utilizing Life Cycle as part of our Demand planning process.

I have used the Like modelling and Phase In/Out profiles successfully when creating a statistical forecast.

I do not see where the "Like and Phase" has any affect on my proportional factors when I generate them from my shipping history key figure.

Could someone explain how the "Like and Phase" affect the proportional factors and potentially how to configure it so that they do. We do alot of forecast manupulation so if the proportional factors are not adapted by life cycle I am assuming all the benefits of life cycle will become nullified when we do an update at an aggrigated level and let it propigate down.

Thanks for any information on this!

[former_member503200 · Accepted solution]

Tim,

When u use Like model, it will create only Stat Fcst, it wont generate any prop factors to disaggregate. What we did is. We created a dummy stat fcst KF and used fcst Method 60 (historical data adopted), Modeled product history get copied into this dummy KF. Then generate the Prop Factors using this data. Run a fcst job using, what ever fcst method u want to use for this new product.

thx

Jeff

[former_member309586]

Hi Tim,

For Life cycle you need to maintain Manual proportional factor for the particular characteristic combination till the product gets maturity statues (100%).

Running proportional factor using shipment history takes to old products /Location. What i can suggest you is

.1.Run proportional factor using shipment history to APODPDANT and copy proportional factor to another key figure where you can call adjustment proportional factor key figure, maintain proportional percentage to life cycle products / location to the new key figure and assign to forecast key figure to generate forecast .