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Supply Chain Excellence

Pilar Gamboa


D&PS Expert

Donia Rachdi


Forecast Accuracy Champions

Aroma Performance:
Composite Materials: TBD
Novecare: Azize Aberre
Peroxides: Nicolas Delplanque
Silica: Christine Cipollone
Special Chem: Joerg Braunschweig
Soda Ash & Derivatives: Irina Piticas
Technology Solutions: Adele Fleming

General Description

The KPI Forecast Accuracy (FA) evaluates the ability to get a visibility on customers' demand in terms of quantity.
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 Gross History.
For a particular month, the Forecast Accuracy is calculated for the last 5 months forecast (M-1 ... M-5); allowing the possibility to evaluate the accuracy of the forecast with reference to several different forecast periods.
The refresh of the KPI is made every month on the 7th.
It is available for all GBUs currently using Dynasys or APO as Demand Planning systems: Aroma Performance, Composite Materials, Novecare, Peroxides, Silica, Soda Ash&Derivatives, Special Chem and Technology Solutions.

Key figures

Standard Forecast Accuracy: This figure measures the gap between the Gross History and the forecasted quantities. To have a better representation of the forecast error, an absolute value of the forecast error is calculated at the lowest level of granularity: Material / Ship-to / Distribution Channel.
This is also called the Mean Absolute Percentage Error (MAPE).


Standard Forecast Accuracy = Max(0; 1- Abs((Final Forecast - Gross History)/Gross History)) x 100


Forecast Accuracy = 100%, it means there is no gap between the Forecast and the Gross History
Forecast Accuracy = 0%, it means inaccurate forecasts
Forecast Accuracy Month-2 is the time between produced forecast and the Gross History (FA June M-2: means forecasts done in April)
Weighted Forecast Accuracy: In addition to the Standard Forecast Accuracy, a second method for calculating the Forecast Accuracy is available.
This measure weights the Forecast Error based on the Gross History of the selected month, according to the selected level of aggregation.


Weighted Forecast Accuracy = Sum[Max(0; 1- Abs((Final Forecast - Gross History)/ Gross History))1MonthWeight] / [Sum Gross History 1MonthWeight] x 100


12 levels of aggregation are available, and the calculation is made dynamically depending on the selected level:
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
Forecast Bias ratio (%): It measures the tendency for a forecast to be consistently higher or lower than the actual value.
Forecast Bias is distinct from the forecast error, in that a forecast can have any level of error, but still be completely unbiased. It is calculated as the average deviation (over or below) of forecasts from actuals.

Forecast Bias = Sum(Final Forecast)-Sum(Gross History)/Sum(Gross History) x 100


If the Forecast is greater than the Gross History, then the Forecast Bias is positive (indicates over forecast)
At the opposite, if the Forecast is lower than the Gross History, then the Forecast Bias is negative (indicates under forecast)
A Forecast Bias = 0, indicates a total absence of gap (bias)
Forecast Bias is a “tracking signal” (positive or negative) and percentage can be above 100%
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 a 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.

Target Users

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

Authorization & Rights

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
Gross History = Customer Demand = Last Customer Request
Distribution Channel = Sales Distribution Channel
GBU Prod. Family = by default the Product Family, but also the Product Hierarchy, the GBU Material Group, or the Forecasts Family
GBU Zone = Group of Countries, Specific by GBU
Packaging Type = used on a material
Product Group (PGMI) = Group of products from Dynasys
Product Line 00 = Attribute of a material. There are 6 differents product line levels, corresponding to differents aggregations of products
Sales Rep = Sales Representative from Dynasys Sales Group
Ship-to KA = Ship-to Key Account, final account
Tactical Material = Concatenation of Product Hierarchy and Packaging


How does it work?

1. Select Filters
On top of the dashboard, several different filters allow you to reduce the scope of data for the analysis


as well as Specific Filters to select in the dedicated box


2. Select the Forecast Accuracy calculation method
As explained above, the Forecast Accuracy is calculated according to:
    • the standard calculation at the detailed level Material x Distribution Channel x Ship-to
    • the weighted calculation at selected level within the 12 available ones in the drop-down menu (dynamic calculation at displayed level)
3. Select the reference period
On every 6th of each month, a snapshot of the Forecast is taken, keeping the reference of the forecast provided up to 5 months before. This will allow to calculate the FA for periods M-1, M-2, M-3, M-4, and M-5.


Example: For June, the FA M in the picture is taken on the 6th of July for the month of June (to capture the changes made in June). 
M-1 will be the picture taken on the 6th of June for June (to capture the changes made in May). 
M-2 is the picture taken the 6th of May for June (to capture the changes made in April).








4. Check the Forecast Accuracy table
After applying the filters, selecting an aggregation level and a reference period, there is still a way to customize a detail table with the desired Indicators and Dimensions

Please note that all dimensions don't match with all aggregation levels.
As a consequence, only the dimensions that are available for the selected aggregation level are displayed.
Mismatching dimensions are disabled to avoid calculation errors.

Retrieve below the interlinking of the aggregation levels




Technical Documentation
Source: DYNASYS / APO (WP1) / APO (PF1) - QV_BW_QRY_MVDYN11_0005
Update: Monthly full reload (history included) on the night of the 6th and the 7th (minor corrections in Gross History may still occur from one month to another)
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)
Gross History
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]
Exception: IECRA for Novecare
Sub-Activity
BFC Activity 1 [0G_CWWE01_C_MAGNITU]
Exception: IECRA for Novecare
Company
[C_DYN_018__C_COMPCDE] Company code
Plant
Zone
Main Shipping Plant Geo Zone [C_DYN_018__C_MPPLANT__C_GEOZONE]
Country
Main Shipping Plant Country [C_DYN_018__C_MPPLANT__C_0COUNTRY]
Corporate Group
Ship-to Corporate group [C_SHIPTID__C_CORPGR]
Plant
Main Shipping Plant [C_DYN_018__C_MPPLANT]
Ship Destination
Zone
Ship-to BFC Geo Zone [C_SHIPTID__C_ZONE]
Country
Ship-to Country [C_SHIPTID__C_0COUNTRY]
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

Distribution Channel
Distribution Channel [0DISTR_CHAN]
GBU Product Family
Default: Product Family Code [C_MATNR2] Material\Attributes\[C_FMPRD]
Exceptions:
Soda Ash, Fibras:
WP1: C_MATNR2_C_LIP03
PF1: [C_MATNR2__0PROD_HIER] Prod. Hierarchy
Aroma, Silica = GBU Material Group
Special Chem = GBU Material Group (both WP1 & PF1)
Peroxides:
WP1:LIP2
PF1: Product_Hierarchy_ Cheops PIF (Missing- not possible)
Novecare, Technology Solutions:
WP1: Default
PF1: [C_MATNR2__0PROD_HIER] Prod. Hierarchy
Polytechnyl, Performance Polyamides, Alsachimie:
[C_MATNR2] Material\Attributes\[C_ACRI015] Forecasts Family


GBU Zone
[CGBUZONE__C_ZONEH2] Ship-to GBU zone 2
Exception : [CGBUZONE__C_ZONEH1] GBU zone (hier .1) for TS Mining
Material
Material [C_MATNR2]
Material Group
Material Group [C_MATNR2__C_MAT_GRP]
Packaging Type
Packaging Type [C_MATNR2__C_MAT_GRP]
Product Group (PGMI)
Product Group (PGMI) [C_DYN_005__C_GRPPGMI]
Product Line 00
Product line 00 [C_MATNR2] Material\Attributes\[C_LPROD]
Sales Rep
Sales Group [C_DYN_017__C_SAL_GRP]
Ship-to KA
Ship-to Key Account [C_GBR15_C_SHIPKA]
Tactical Material
Tactical Material [C DYN_005_C_TACTIC2]

Not able to find the solution? Contact SBS Support.

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