Pilar Gamboa


Donia Rachdi





General Description

The KPI Forecast Accuracy (FA) evaluates the ability to get a visibility on customers' demand.
As an input of S&OP process, reliable forecasts constitute the major way to improve the customer satisfaction via an optimized planning of operations. The Forecast Accuracy in this dashboard is calculated based on the Final Forecast and the Actual Sales (Gross History).
For a particular month, the Forecast Accuracy is calculated over the last 5 months forecast (M-1 ... M-5); allowing the possibility to evaluate the accuracy of the forecast at several periods ahead. 
It is available for all GBUs currently using Dynasys or APO as Demand Planning systems: Aroma Performance, Novecare, Peroxides Silica, Soda Ash&Derivatives, Special Chem and Technology Solutions.


Key figures

Standard Forecast Accuracy : This measure is related to the gap between the Actual Sales and the forecasted quantities. To have a better representation of the true forecast error, the calculation, we take the absolute value, also called the Mean Absolute Percentage Error (MAPE). This allows us to summarize multiple values as the negative and positive values cancel each other out when averaged.


Forecast Accuracy = Max(0; 1- Abs((Final Forecast - Actual Sales)/ Actual Sales) x 100)


Weighted Forecast Accuracy : This measure takes into account the volumes delivered at the lowest level of granularity (Material x Ship-to x Distribution Channel (if any) ), then aggregates them according to the selected level.
We currently have 12 levels of aggregation:
1.Material / Ship Destination / Distribution Channel
2.Product
3.Product / Ship Destination Zone / Group of Activity
4.Product Hierarchy
5.Product / Plant
6.Ship Destination Country
7.Ship Destination Zone / Sales Rep
8.Sales Rep / Product / Ship-to-KA
9.GBU Product Family
10.GBU Zone / Ship Destination Country / Ship Destination (Plant)
11.GBU Zone / Ship Destination Country / Tactical Material
12.GBU Zone / Ship Destination Country / Product Hierarchy




 


Weighted: Forecast Accuracy taking into account the at the level Ship-to x DC (if any) x Material level =
Bias ratio (%): Average deviation of forecast from actuals.
= Sum(FF)-Sum(GH)/Sum(GH)
In many cases it is useful to know if demand is systematically over- or under-estimated. For example, even if a slight forecast bias would not have notable effect on store replenishment, it can lead to over- or under-supply at the central warehouse or distribution centers if this kind of systematic error concerns many stores.



  • Global Supply Chain Managers
  • Regional Supply Chain
  • Local Supply Chain
  • Supply Chain Analyst
  • S&OP Manager
  • Purchasing Manager / Buyers
  • Supply Chain Excellence
  • Account Managers


All the accesses must be validated by:
Supply Chain Excellence
Click here for the Access form to get access to the Global Supply Chain Dashboard.


Glossary

Actual Sales = Gross History = Last Requested Goods Issue






How does it work?

The Forecast Accuracy is calculated at 2 levels, based on Gross History (GH) from last month :
The forecast Accuracy is calculated at 2 levels, based on Gross History (GH) from last month :
  • at detailed level : material, Distribution Channel, Ship-to and weighted
  • at aggregated level : at the level required by the user (dynamic calculation at displayed level)
  • Snapshots : every 6th of each month, a snapshot is taken for each month in the future up to 5 months. This will allow to calculate FA for periods M-1, M-2, M-3, M-4, and M-5.








Exemple :  For June, the FA M is the picture taken the 6th of July for the month of June (to capture the changes made on June).   M-1 will the the picture taken the 6th of June for June (to capture the changes made on May).  M-2 the picture taken the 6th of May for June (to capture the changes made on April).
Technical Documentation
Source: DYNASYS / APO (WP1) / APO (PF1) - QV_BW_QRY_MVDYN11_0005
Update: Daily
Technical BW Documentation: BW - DP - Forecast Accuracy (Core Query)
Naming convention by Source System (Dynasys vs APO)
Global SC Dashboard
Dynasys
APO (WP1)
APO (PF1)
Actual Sales
GH / Gross History
Demand History
History
Final Forecast
FF / Final Forecast
PreSOIP Plan
Consensus Forecast
Dimensions: Global Overview of Dimensions



Forecast Accuracy
Global Filters
Period
Month Year
Calendar Year/Month [0CALMONTH]
Organization
GBU
BFC GBU [CPFCTR1_2]
Group of Activity
BFC Group of activ [C_DYN_010__CPFCTR2_2]
Sub-Activity
BFC Activity 1 [0G_CWWE01_C_MAGNITU]
Company
[C_DYN_018__C_COMPCDE] Company code
Plant
Zone
Geographie/Zone [C_DYN_018__C_MPPLANT__C_GZONE]
Country
Country [C_DYN_018__C_MPPLANT__C_0COUNTRY]
Plant
Main Shipping Plant [C_DYN_018__C_MPPLANT]
Ship Destination
Zone
BFC Geographie/Zone [C_SHIPTID__C_ZONE]
Country
Country [C_SHIPTID__C_0COUNTRY]
Corporate Group
Corporate group [C_SHIPTID__C_CORPGR]
Ship Destination
Ship-to [C_SHIPTID]
Product
Product Hierarchy
Prod.hierarchy [C_MATNR2__0PROD_HIER]
Product
Com Prod / Mat Grp [C_MATNR2__C_PROD]
Bulk/Packed
N/A
Transport Mode
N/A
Specific Filters

Material Group
Material Group [C_MATNR2__C_MAT_GRP]
Material
Material [C_MATNR2]
Distribution Channel
Distribution Channel [0DISTR_CHAN]
Product Family
[C_MATNR2] Material\Attributes\[C_FMPRD] Product Family Code
Product Group (PGMI)
Product Group (PGMI) [C_DYN_005__C_GRPPGMI]
Product Line 00
[C_MATNR2] Material\Attributes\[C_LPROD] Product line 00