SAP Forecasting and Replenishment, add-on for fresh ...

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SAP Forecasting and Replenishment, add-on for fresh products Administrator Guide

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1 About this Guide. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2 Getting Started. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.1 System Requirements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52.2 Required SAP Notes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

First -Time Installation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7Upgrading from SP00 to SP01. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8Upgrading from SP01 to SP02. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.3 Java Binaries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92.4 Hardware Sizing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

3 About SAP Forecasting and Replenishment, add-on for fresh products. . . . . . . . . . . . . . . . . . . 113.1 Transaction Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113.2 Useful Links. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123.3 Glossary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12

4 Configuring SAP Forecasting and Replenishment, add-on for fresh products. . . . . . . . . . . . . . 144.1 Add-On Time Series Settings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Creating Key Figure Parameters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15Defining Time Series. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

4.2 SAP Forecasting and Replenishment Standard Settings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Defining the Internal Qualifier. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18Setting the Goods Processing Time in Hours. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18Assigning the Qualifier to the Time Series Interface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19Maintaining Time Series Settings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20Exceptions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21Maintaining Dispatcher Profiles. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .24Activating Main and Supplementary Scheduling Types. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

4.3 SAP Forecasting and Replenishment, add-on for fresh products Customizing Settings. . . . . . . . . . . 34Master Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35Demand Influencing Factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41Interfaces. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42F&R Processor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45Intraday Functions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .68

4.4 BAdI Implementations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .77BAdI /FRE/IF_CON_BADI_007. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77BAdI /FRE/UI_RWB_BADI_004. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78BAdI /FRE/UI_RWB_BADI_002. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .78

2 P U B L I CSAP Forecasting and Replenishment, add-on for fresh products Administrator Guide

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BAdI /FRE/FU_TS_BADI_007. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79BAdI /FRE/FU_FRP_BADI016. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79BAdI /FRE/FU_FRP_BADI_002. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80BAdI /FRE/FU_CON_BI_BADI2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .80BAdI /FRE/IF_CON_BADI_003. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80BAdI /FRE/IF_CON_BADI_009. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

4.5 BAdI Definitions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81BAdI /FFIS/BD_SELLING_PROF. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

5 Security Information for SAP Forecasting and Replenishment, add-on for fresh products. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83

6 Operating SAP Forecasting and Replenishment, add-on for fresh products. . . . . . . . . . . . . . . 846.1 Monitoring. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

Alert Monitoring. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84Error Logs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .84Background Job Monitoring. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

6.2 Administration and Management. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85Starting and Stopping. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85Daily Consumption Load and Data Initialization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85Load Balancing and Scalability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

SAP Forecasting and Replenishment, add-on for fresh products Administrator GuideContent P U B L I C 3

1 About this Guide

This administrator guide provides a central starting point for the technical implementation and configuration of SAP Forecasting and Replenishment, add-on for fresh products.

In addition to describing everything you have to do to implement and configure SAP Forecasting and Replenishment, add-on for fresh products, this guide also contains the relevant security and operations information.

Target Audience

This document is intended for the following target audiences:

● Consultants● Partners● Customers● System administrators


About this Guide

2 Getting Started

2.1 System Requirements

SAP Forecasting and Replenishment, add-on for fresh products is implemented as an add-on of SAP Forecasting and Replenishment, providing enhanced, Java-based core modules with specific improvements for fresh products. The minimum system component requirements are as follows:

● One of the following EHP for SAP SCM 7.0 versions○ EHP4 for SAP SCM – 7.0 SPS 10○ EHP3 for SAP SCM - 7.0 SPS 16○ EHP2 for SAP SCM – 7.0 SPS 21

● SAP JVM version 7 or 8, or SAPMachine 11● SAP F&R 5.2

NoteThe system can only identify and configure fresh products if it has received product master data from SAP ECC.

RecommendationWe recommend using a minimal system landscape for test and demo purposes only. Do not use a minimal system landscape as your productive landscape, as this could affect performance, scalability, high availability, and security.

2.2 Required SAP Notes

This page constains the information when upgarading SAP Forecasting and Replenishment, add-on for fresh products from the version SP02 to version SP03.

These SAP Notes contain the latest information about the installation process, as well as corrections to the installation information.

It is important to implement all SAP Notes in the correct order. This also applies to the order of the different versions in which SAP Forecasting and Replenishment, add-on for fresh products was released:

● If you install SAP Forecasting and Replenishment, add-on for fresh products for the first time, refer to First -Time Installation [page 7]

SAP Forecasting and Replenishment, add-on for fresh products Administrator GuideGetting Started P U B L I C 5

● If you are upgrading from the initial installation to SP01, refer to Upgrading from SP00 to SP01 [page 8]● If you are upgrading from SP01 to SP02, refer to Upgrading from SP00 to SP01 [page 8]● If you are upgrading from SP02 to SP03, follow the instructions below:

CautionMake sure that you have read all SAP Notes thoroughly before you start implementing the software. To ensure that you are always reading the most up-to-date version, access SAP Notes at https://support.sap.com/en/index.html .

Required SAP Notes

SAP Note Number Title Description

2762723 FFISCM - FFICORE version matrix Release Information - FFICORE

2698575 FFICORE SP09 - Release Notes Release note - FFICORE

2650661 Fresh Product Add-On: Release Information for Support Pack 02

Release note


Release note

2375716 ABAP add-on FFISCM 702: Installation, Upgrade, CSPs

Installation note

2747708 Planning Date of Order Proposals in wrong Timezone

Correction note

Also check SAP Service Marketplace for the latest SAP Notes for support component SCM-FRE-FPA. Some of them might be relevant for FFISCM 702, the installed support pack of SAP Forecasting and Replenishment, add-on for fresh products. In this case, you should implement these SAP Notes as well. Every service pack release of FFISCM requires a specific service pack version of FFICORE. For FFISCM 702 SP03, the required version is FFICORE SP09, as described in SAP Note 2762723 .

The following F&R Standard Notes are relevant for Enhanced Visibility of Intraday features in F&R standard transactions:

CautionRead all F&R Standard Notes thoroughly and implement all manual activities before you start implementing the software.

Required F&R Standard Notes

F&R Standard Note Number Title Description

2729194 F&R Display Location Master Data - Badi to add a customer specific Tab and subscreen

Correction note

2765447 Badi FRE_UI_MD_DISPLAY: Custom Location Tab do not support containers

Correction note

2728286 Additional fields (customer specific) in Calculation Detail view, within ALV Grid 'Demand Periods’

Correction note


Getting Started

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F&R Standard Note Number Title Description

2750815 Correction for note 2728286 (Additional fields for Calculation detail view)

Correction note

2712846 Additional fields (customer specific) in Supplying Location view (/FRE/CADE) or Changed Order proposals (/FRE/CADE or /FRE/RWB)

Correction note

2.2.1 First -Time Installation

This page contains information about installing SAP Forecasting and Replenishment, add-on for fresh products for the first time.

Make sure that you have installed the required software before you start the implementation process. You can find the required installation information in the SAP Notes listed in the table below.

Required SAP Notes


2405382 Release Note. SAP Forecasting and Replenishment for Retail, add-on for fresh products – FRP Enhancement – 1.0.0

Release note


Installation note

2368802 FRP_BAdI_003: Interface-Enhancements

Provides BAdI enhancements

2316913 Change documents are not created for location products

Ensures enhanced functionality

2398914 Delete Sales Items Append Structure Prevents an FRP abort error message being triggered

2401175 Standard FRP run aborts after fresh products add-on installation

Prevents an implementation error being triggered










2.2.2 Upgrading from SP00 to SP01

This page constains the information when upgarading SAP Forecasting and Replenishment, add-on for fresh products from the initial installation to version SP01.

Make sure that you have installed the required software before you start the implementation process. You can find the required installation information in the SAP Notes listed in the table below:

Required SAP Notes


2368802 FRP_BAdI_003: Interface-Enhancements

Provides BAdI enhancements

2405382 Release Note. SAP Forecasting and Replenishment for Retail, add-on for fresh products – FRP Enhancement – 1.0.0

Release note


Installation note

2316913 Change documents are not created for location products

Ensures enhanced functionality

2398914 Delete Sales Items Append Structure Prevents an FRP abort error message being triggered

2401175 Standard FRP run aborts after fresh products add-on installation

Prevents an implementation error being triggered

2.2.3 Upgrading from SP01 to SP02

This page constains the information when upgarading SAP Forecasting and Replenishment, add-on for fresh products from the version SP01 to version SP02.

Make sure that you have installed the required software before you start the implementation process. You can find the required installation information in the SAP Notes listed in the table below

Required SAP Notes



Release note

2649349 Issues after upgrade to SP02 - (SP03) Correction note (high priority)


Installation note

2629197 FBS FFI - Fresh Add-on FFICORE SP07 Info for JAVA Service Pack 07


Getting Started











2.3 Java Binaries

Prerequisites

One of the following must be installed on the host system where Java binaries are executed:

● SAP Java Virtual Machine (JVM) 7 or 8● SAPMachine 11

NotePlease note that SAPMachine is only compatible with Windows, Linux, or OSX operating systems.

Context

If you have already installed SAP JVM for other SAP components, you can use it for SAP Forecasting and Replenishment. Otherwise, you can download the correct version from the software center at:

https://launchpad.support.sap.com/#/softwarecenter/template/products/%20_APP=00200682500000001943&_EVENT=DISPHIER&HEADER=Y&FUNCTIONBAR=N&EVENT=TREE&NE=NAVIGATE&ENR=67837800100200020507&V=MAINT&TA=ACTUAL&PAGE=SEARCH/SAP%20JVM%207.1

NoteDownloading and installing an SAP JVM will not void your support agreement with SAP, even if the host is an ABAP-only system.

SAP JVM is provided as SAR packages. You have to install it using SAP CAR, which you can download from SAP Service Marketplace.

You cannot transport Java binary packages from one system to another. Therefore, you have to manually copy them to every system in your landscape as follows:

NoteAll paths described in the following procedure are case-sensitive. Enter them exactly as shown in the procedure below to avoid errors.


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Procedure

1. Navigate to the folder /sapmnt/<SID>/global/frp/bin/ and check whether a subfolder called FFI exists. If so, rename it to something else, for example, FFI_old_version_xy.

2. In /sapmnt/<SID>/global/frp/bin/, create a new subfolder called FFI.

3. Copy the Java binary content to the folder /sapmnt/<SID>/global/frp/bin/FFI that you just created.

4. (Optional) If you are performing the installation on Unix, for the SAP system, use the following command to grant execution rights for all shell scripts for all files with the suffix .sh in the new FFI folder:

chmod 755 /sapmnt/<SID>/global/frp/bin/FFI/*.sh5. (Optional) If you are performing the installation on Unix, for the SAP system, use the following command to

grant read and write access to the new FFI folder and its content:

chmod -R 775 /sapmnt/<SID>/global/frp/bin/FFI6. Use the following command to assign ownership of all files in the FFI folder to the user <SID>adm and the

group sapsys:

chown -R <SID>adm:sapsys7. Assign the SAP JVM runtime for the user <SID>adm by uncommenting and adjusting the definition of

JAVA_HOME in all batch files (.sh for Unix or .bat for Windows).

8. Verify the content of template folder /sapmnt/<SID>/global/frp/bin/FFI/templates/. To verify the structure of .dsx files, compare the files in /sapmnt/<SID>/global/frp/bin/FFI/templates/ with their .dsx counterpart in an existing standard SAP Forecasting and Replenishment data environment. For example, compare EVENTS_FFI.dsx with EVENTS.dsx and make sure both files have the same structure.

NoteWhen a new site is initialized, these files are copied to the <client>/<site-GUID>/ini folder and referenced by SAP Forecasting and Replenishment, add-on for fresh products during runtime. If there are any changes to the templates, you need to adjust these files accordingly in all existing data environments. To perform these adjustments, copy all template files into each <site GUID>/ini folder manually.

2.4 Hardware Sizing

If you are implementing SAP Forecasting and Replenishment, add-on for fresh products into an existing SAP Forecasting and Replenishment system, SAP recommends updating your hardware sizing. Your system might have to process additional product groups for SAP Forecasting and Replenishment, or one of its add-ons, which could potentially cause performance issues with your current hardware sizing.

Forecast calculation is based on daily consumption history rather than the weekly consumption history used by standard SAP Forecasting and Replenishment. Therefore, it is important to make sure that your consumption data is available with a daily granularity. SAP recommends storing two years' worth of historical data.


Getting Started

3 About SAP Forecasting and Replenishment, add-on for fresh products

Fresh products, such as vegetables, fruits, meat, fish, and convenience foods are essential for grocery retailers because they contribute significantly to margin and revenue. Typically, fresh products are items that are delivered at least four times a week, with delivery times less than or equal to two working days. Fresh products also usually have short replenishment cycles, strong trends, and sell quickly during the week. SAP Forecasting and Replenishment, add-on for fresh products is integrated into SAP Forecasting and Replenishment as an add-on to help customers reduce spoilage and increase the availability of fresh products.

The add-on supports the following processes:

● Identifying fresh products and configuring their profilesTo use the improved forecast calculation for fresh products, this product type must first be identified. This add-on contains rule-based determination functionality to prepare fresh products for subsequent processing during the interface processing of new products.

● Forecasting and automatically replenishing fresh productsAn enhanced forecast calculation for fresh products is part of this add-on. Several features, for example, forecast calculation with a daily granularity or automatic detection of seasonal patterns, are implemented to optimize the forecast and replenishment processes for fresh products.

● Automatically correcting fresh product stock based on the expiration date and calculating projected waste and shrinkageBased on the included projected waste and shrinkage calculation, the shelf-life information of the product is used to calculate potential stock reductions and considers them during demand calculation.

● Using intraday functionsTo increase accuracuy when processing fresh products, you can implement intraday availability calculations, multiple order and delivery times, intraday scheduling, and order split functions. Intraday functions can also be implemented independently of the fresh product forecasting functions. Intraday functions can be used for all types of products.

3.1 Transaction Overview

You can see all the transactions for SAP Forecasting and Replenishment, add-on for fresh products in your system under area menu /FFIS/FRE.

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3.2 Useful Links

The software and additional documentation are available for download on SAP Service Marketplace at https://support.sap.com/swdc Software Downloads Installations and Upgrades By Alphabetical Index (A to Z) F. SAP FRESH PRODUCT ADD-ON .

3.3 Glossary

A list of the terminology used throughout this guide.

Term Abbreviation Definition

demand influencing factor DIF An external factor that describes everything that influences the demand. It can be assigned on a product level or a location level.

ERP Core Component ECC Also known as ERP Central Component. The core of SAP ERP

expiration date Date by which the product has to be sold. The date itself is the last day on which the item can be sold. At the end of this day, any remaining items have to be written off.

first in first out FIFO The principle that the item that was delivered first will be sold first. That means that the consumer always picks the piece that has the shortest remaining time until expiration date.

forecast calculation Also known as forecasting. For fresh products, it consists of the following main process steps:

● OptimizationDetermines optimum model parameters so that the model explaining the historic sales best fits the model.

● EstimationDetermines model coefficients

● PredictionCalculates the forecasts by applying the model coefficients in the future


About SAP Forecasting and Replenishment, add-on for fresh products

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Term Abbreviation Definition

Forecast Replenishment Processor FRP Controls automatic replenishment. Automatic replenishment is made up of forecast calculation and requirements calculation, along with requirement quantity optimization.

fresh product Perishable goods

goods receipt GR List of the quantity of items already delivered to the target location

last in first out LIFO The principle that the item that is delivered last will be sold first. This means that the consumer always picks the piece that has the longest remaining time until expiration date.

outlier A demand quantity for a specific period that deviates sufficiently from the norm for it to be classified as irregular.

planned goods receipt PGR List of open order quantities for the target location on the delivery date. Planned goods receipts in the past (back orders) only are considered if they are still within the past horizon for back orders.

projected waste The predicted reduction in stock. Depending on your configuration this can be calculated as a combination of predicted spoilage and predicted shrinkage or just predicted shrinkage.

scheduling groups A technical key used to store scheduling data at an aggregated data level.

shelf life The maximum number of days a product can be sold starting from the delivery date in the store. As delivery has no time definition, the delivery date itself is counted as the first day.

shrinkage A reduction in stock prior to expiration date due to bad quality, damage, or physical shrinkage.

spoilage (waste) A reduction in stock due to an item reaching its expiration date. In some modules, the term Waste is used instead of Spoilage

Supply Chain Management SCM The planning, fulfillment, regulation, and tracking of supply chain activities in order to add value, build competitiveness, strengthen logistics, match supply with demand, and measure performance.

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4 Configuring SAP Forecasting and Replenishment, add-on for fresh products

This section describes the changes that you need to make to the standard Customizing settings for SAP Forecasting and Replenishment, as well as the entries that you need to make in the system table for time series. These settings are a prerequisite for using the functions provided by SAP Forecasting and Replenishment, add-on for fresh products.

You can make additional changes using the new Customizing for SAP Forecasting and Replenishment, add-on for fresh products, for example, to enable or disable calculations specific to fresh products and to fine-tune individual functions and features.

NoteYou can also make these Customizing settings and system table entries as part of the installation process for the add-on.

RecommendationAfter installing the add-on, SAP recommends that you manually create transport requests with the default settings that you want and then import these settings into each add-on client. Otherwise, you need to make these settings manually on each client.

4.1 Add-On Time Series Settings

SAP Forecasting and Replenishment, add-on for fresh products introduces four new time series. The following key figure parameters are provided for the time series:

Key Figure Parameter Description

/FFIS/CONS_DATA Fresh Product Additional Consumption Data

Contains consumption data saved with a daily granularity for at least two years

/FFIS/FCST Calculated Fresh Product Forecast

Contains the forecast results calculated with the enhanced forecast module

/FFIS/PROJWASTE Calculated Projected Waste

Contains the results of the projected waste calculation

14 P U B L I CSAP Forecasting and Replenishment, add-on for fresh products Administrator GuideConfiguring SAP Forecasting and Replenishment, add-on for fresh products

Key Figure Parameter Description

/FFIS/SHRINKAGE Calculated Shrinkage

Contains the results of the shrinkage calculation

4.1.1 Creating Key Figure Parameters

Context

To create the following key figure parameter for the time series in table /FRE/TSKPRM, proceed as follows:

RecommendationSAP recommends using exactly the same key figure parameter names mentioned in the tables to prevent conflicts while importing support packages and SAP Notes.

Procedure

1. Open transaction SM30.

2. Adjust the relevant settings as follows:

Time Series

CL Key Figure Parameter Parameter Description Short Text

000 /FFIS/CONS_DATA Fresh Product Consumption FPCD

000 /FFIS/FCST Fresh Product Forecast FPFC

000 /FFIS/PROJWASTE Projected Waste FPPW

000 /FFIS/SHRINKAGE Shrinkage FPSH

3. Adjust the relevant settings as follows:

Time Series Definition

Group Description Cell Content Cell Content Cell Content Cell Content

Key Figure Parameter /FFIS/CONS_DATA /FFIS/FCST /FFIS/PROJWASTE /FFIS/SHRINKAGE

SAP Forecasting and Replenishment, add-on for fresh products Administrator GuideConfiguring SAP Forecasting and Replenishment, add-on for fresh products P U B L I C 15

Group Description Cell Content Cell Content Cell Content Cell Content

Key Figure Parameter Data Type

/FRE/QUANTITY /FRE/QUANTITY /FRE/QUANTITY /FRE/QUANTITY

Aggregation Mode SUM SUM SUM SUM

Disaggregation Mode DST DST DST DST

Calendar Identifier SDCAL SDCAL SDCAL SDCAL

Time Series Data Source

5 5 5 5

Time Series Delta Handling Relevancy

2

Relevant for RWB X X X X

Relevant for DIF

Relevant for ANA X X X X

Not Relevant for RWBS

Relevant for CPFR X X X X

UNDEF Values for General TS Types

X X X

UNDEF Values for Reference Module

X X X X

Parameter Description

Fresh Product Consumption

Fresh Product Forecast

Projected Waste Shrinkage

Short Text FPCD FPFC FPPW FPSH

4.1.2 Defining Time Series

Context

After creating the key figure parameters for the time series of SAP Forecasting and Replenishment, add-on for fresh products, you need to assign the time key figure parameters to physical database tables. For each key


figure parameter, you need to assign a database table with both a daily granularity and a weekly granularity. Therefore, you have to make the following entries in system table /FRE/CDM_DEF.

Proceed as follows:

Procedure

1. Open transaction SE16 (Define CDM Time Series Types).

2. Make the following entries in system table /FRE/CDM_DEF:

Time Series Assignment

CLKey Figure Parameter Granularity Type Table CDM Type

000 /FFIS/CONS_DATA D /FFIS/TS_TAB01_D TS

000 /FFIS/CONS_DATA W /FFIS/TS_TAB01_W TS

000 /FFIS/FCST D /FFIS/TS_TAB02_D TS

000 /FFIS/FCST W /FFIS/TS_TAB02_W TS

000 /FFIS/PROJWASTE D /FFIS/TS_TAB03_D TS

000 /FFIS/PROJWASTE W /FFIS/TS_TAB03_W TS

000 /FFIS/SHRINKAGE D /FFIS/TS_TAB04_D TS

000 /FFIS/SHRINKAGE W /FFIS/TS_TAB04_W TS

NoteThe database tables for the time series are part of the add-on installation.

4.2 SAP Forecasting and Replenishment Standard Settings

To use SAP Forecasting and Replenishment, add-on for fresh products, you have to make some additional settings in the standard Customizing for SAP Forecasting and Replenishment. You can also activate standard functions, provided that they are supported by the add-on.

To access the standard Customizing for SAP Forecasting and Replenishment, navigate to Customizing (transaction SPRO) SAP Reference IMG Forecasting and Replenishment .


4.2.1 Defining the Internal Qualifier

Context

Consumption data for fresh products is saved in time series. To ensure that the system updates consumption data in separate time series in parallel, you have to create a new qualifier. This qualifier is only used internally and is not meant to receive data from the external system. To define a new qualifier, proceed as follows:

Procedure

1. Open the SAP Implementation Guide.

2. Navigate to Forecasting and Replenishment Interfaces Define Movement Type Qualifiers and define a qualifier with the following entries:

Qualifier Definition

Qualifier Qualifier Name

3099 POS DAILY SALES

4.2.2 Setting the Goods Processing Time in Hours

Context

You can set the processing time for goods receipts manually in Maintain Location Products (transaction /FRE/MASS_MATLOC) or as part of a mass maintenance in Mass Maintenance in Background (transaction /FRE/MASS_BACKGROUND).

However, you first need to define the field and make it available for editing. Proceed as follows:

Procedure

1. Open transaction SM30.

2. Open table /SCMB/MDL_AT_DEF.


3. Add the table name /SCMB/MDL_LOCPROD and the field name /FFIS/GRPTH.

4. Save your entries.5. Open the SAP Implementation Guide.

6. Navigate to Forecasting and Replenishment Master Data Define Maintainable Attributes .7. Add a new row and enter the table name and field name that you created in transaction SM30.

8. Select the Maintenance Only Using Dialogs autonomy option.9. Save your entries.

4.2.3 Assigning the Qualifier to the Time Series Interface

Context

You have already defined the internal qualifier but you now have to assign it to the time series for fresh product consumption data. To assign the qualifier to a time series, proceed as follows:

Procedure


2. Navigate to Forecasting and Replenishment Interfaces Maintain Time Series Interface .3. Make the following settings:

Time Series Interface Settings

Qualifier DirectionKey Figure Parameter LIME Relevant TS Relevant FRP Trigger

3099 0 0: output /FFIS/CONS_DATA

X


4.2.4 Maintaining Time Series Settings

Context

For the four time series introduced with SAP Forecasting and Replenishment, add-on for fresh products, you need to define the time series parameters in the standard Customizing for SAP Forecasting and Replenishment. The following key figure parameters are available:

● /FFIS/CONS_DATA Fresh Product Additional Consumption Data● /FFIS/FCST Calculated Fresh Product Forecast● /FFIS/PROJWASTE Calculated Projected Waste● /FFIS/SHRINKAGE Calculated Shrinkage

Proceed as follows:

Procedure


2. Navigate to Forecasting and Replenishment Time Series Maintain Time Series Profiles .3. Assign the key figure parameters to time series profiles as follows:

Time Series Profiles

Time Series Profile Key Figure Parameter

TSPR_STORE /FFIS/CONS_DATA

TSPR_STORE /FFIS/FCST

TSPR_STORE /FFIS/PROJWASTE

TSPR_STORE /FFIS/SHRINKAGE

4. Set the Primary Granularity to daily and the Secondary Granularity to weekly.

RecommendationWe recommend that you make sales data for fresh products available with a daily granularity for two years.

NoteIf you reorganize data in time series with the SAP Forecasting and Replenishment standard transaction /FRE/TS_DELETE, SAP recommends creating a new variant for the add-on time series. For the add-on time series data, schedule the transaction to run regularly in a separate job.


4.2.5 Exceptions

SAP Forecasting and Replenishment, add-on for fresh products creates and passes exceptions into the standard SAP Forecasting and Replenishment. The following types of exception can occur:

● Business exceptions indicate that a validation check found unexpected or problematic data patterns in a real-world object, such as a store or item, or in time series or master data, for example. When business exceptions occur, it is important that you investigate them thoroughly in order to avoid making poor business decisions as a result of erroneous data. Business exceptions always occur at item-level.

● Technical exceptions can occur when hardware or software does not behave as expected, for example, if the software cannot handle certain situations during processing, or when configurations are inconsistent or invalid. Technical exceptions may occur at store-level and item-level.

For detailed information about managing different types of exception, see Managing Exceptions [page 21].

4.2.5.1 Managing Exceptions

You manage high-level and low-level exceptions in the standard Customizing for SAP Forecasting and Replenishment (transaction SPRO).

Context

SAP Forecasting and Replenishment, add-on for fresh products provides both high-level and low-level exceptions. To use these add-on specific exceptions in the exception workbench, you need to create an entry in the exception Customizing for each message. There is a separate Customizing activity depending on whether you want to create entries for high or low-level exceptions.

NoteThe entries contained in this documentation are valid at time of publication. In the future, there might be additional exceptions delivered in the form of an SAP Note.

NoteMake sure that all available exceptions are included in your installation so that your system works properly.

Procedure


2. To manage high-level exceptions, navigate to Forecasting and Replenishment Exception ManagementMaintain Configuration Data for High Level Exceptions .


3. Make the following entries:

High-Level Exceptions

Application Area Message Number Message Text

/FFIS/MSG 001 Exception occurred during forecasting for fresh product

/FFIS/MSG 007 Could not read from file &2 for location &1

/FFIS/MSG 010 Could not find suitable optimization run schedule for location &1

/FFIS/MSG 011 Error while generating DIF assignment file

/FFIS/MSG 012 Error while processing logs; no auto. repl. for loc &1 for fresh products

/FFIS/MSG 013 Error occurred while generating JSON file for fresh products

/FFIS/MSG 014 Exception occurred in &2 module for location &1 for fresh products

/FFIS/MSG 018 Exception occurred while generating file &2 for location &1

/FFIS/MSG 029 Error occurred; no update of &2 data for location &1

/FFIS/MSG 057 Location &1/FRP run at planning date &2: Errors during splitting OP-items

/FFIS/MSG 058 OP number &1: Errors during splitting OP-items quantity

/FFIS/MSG 059 Plan. GR for loc. prod. &1/&2 shifted from avail date &3 to &4

/FFIS/MSG 067 Selling profile could not be found for location: &1

/FFIS/MSG 068 Location: &1 opening hours could not be found

/FFIS/MSG 075 Plan. GR for location product &1/&2 at avail. date &3 has been deleted

/FFIS/MSG 207 New listing forecast method used for &2/&1



/FFIS/MSG 216 No valid consumption data for &2/&1

/FFIS/MSG 218 Effect of DIF unknown for &2/&1

NoteRaise Unknown DIF Exception only once: If flagged, this exception is created only once per location product and Boolean DIF. If the exception was already created once before, the exception is not created again.

/FFIS/MSG 245 Metric DIF &3 was dampened for &2/&1

/FFIS/MSG 246 Very high forecast for &2/&1

/FFIS/MSG 247 CTP effect has been considered in sales forecast for &2/&1

/FFIS/MSG 300 Discrepancy between stock and goods receipts for &2/&1

/FFIS/MSG 301 Projected waste calculation not possible for &2/&1

/FFIS/MSG 302 Exceptionally high waste calculated for &2/&1

/FFIS/MSG 402 Sched. data for fresh prod. not maint. for Trg. &1, Src. &2 and S.Grp &3

4. To manage low-level exceptions, navigate to Forecasting and Replenishment Exception ManagementMaintain Configuration Data for Low Level Exceptions

5. Make the following entries:

Low-Level Exceptions


/FFIS/MSG 023 Error occurred while calling &2 module for location &1 for fresh products

/FFIS/MSG 055 Error during splitting quantity for product &1: OP quantity < 0



/FFIS/MSG 132 Invalid combination of Location Number &1 and Location Type &2

RecommendationSAP recommends assigning the high-level exceptions that are specific to the add-on to Business Area 7 (Forecast) in Assignment of Business Areas to F&R Exceptions. You should also adjust Validity Period of F&R Exception (Days) to the same number of days as you configured for the SAP Forecasting and Replenishment standard exceptions.

4.2.6 Maintaining Dispatcher Profiles

Context

NoteOnly adapt the dispatcher profile if the dispatcher is activated and used as the F&R Processor.

The extended dispatcher profile can be used for fresh products as well as non-fresh products.

To use the add-on-specific functionality for fresh products, you need to add new tasks that provide data for enhanced forecast, projected waste, and shrinkage calculations for the dispatcher profile. You also need to add modules to the dispatcher profile that allow the calculations to be performed and imported as time series data. This involves replacing the task SAFRUN_CRIT in the SAP Forecasting and Replenishment standard dispatcher profile with the new function to be executed.

To edit the dispatcher profile, dispatcher sequences, and dispatcher tasks, proceed as follows:

Procedure


2. Navigate to Forecasting and Replenishment F&R Processor Maintain Dispatcher Profiles . The following tasks are available:


Task Description Function to be executed Restriction

/FFIS/SAFRUN_LOC_ACTIVATE

Fresh product-specific environment checks and actions

/FFIS/FU_CL_FRP_SAFRUN_LOC_ACT

Call this task in a non-critical time window, for example, before SAP F&R standard task SAFRUN_CALIB

/FFIS/SAFOUT_CONFIG_FILES

Creates add-on specific CONFIG-/WORK.INI files

/FFIS/FU_CL_FRP_SAFOUT_UPD_INI

Call this task after task /FFIS/SAFRUN_LOC_ACTIVATE but in a non-critical time frame, for example, before SAP F&R standard task SAFRUN_CALIB

/FFIS/SAFOUT_CLOSED_DAYS

Creates a file with information about closed sales days

/FFIS/FU_CL_FRP_SAFOUT_STCLOSE

Same as for standard SAP Forecasting and Replenishment

/FFIS/SAFOUT_FEAT_PARAM

Creates a file with parameters for forecast calculation features

/FFIS/FU_CL_FRP_SAFOUT_FT_CONF


/FFIS/SAFOUT_CALIB_ITEMS

Creates a file with location products relevant for new fresh product-specific calibration

/FFIS/FU_CL_FRP_SAFOUT_CALIB


/FFIS/SAFOUT_FCST_ITEMS

Creates a file with location products relevant for new fresh product-specific forecast calculation

/FFIS/FU_CL_FRP_SAFOUT_FORECAS


/FFIS/SAFOUT_PRED_DATA

Creates files with fresh product-specific information about DIF parameters and assignments

/FFIS/FU_CL_FRP_SAFOUT_PRDCTR


/FFIS/SAFOUT_PROJ_WASTE

Creates files with location products relevant for projected waste as well as provision of parameters for calculation

/FFIS/FU_CL_FRP_SAFOUT_WP


/FFIS/SAFOUT_DAILY_SALES

Provisides consumption data from additional fresh product time series

/FFIS/FU_CL_FRP_SAFOUT_DAYSALE

Directly before task /FFIS/SAFRUN_CRIT (see next row)

/FFIS/SAFRUN_CRIT Calls the modules in a critical time frame enhanced with additional calls of new fresh product-specific calculations or steps

/FFIS/FU_CL_FRP_SAFRUN_CRIT

This task replaces the SAP Forecasting and Replenishment standard task SAFRUN_CRIT with call of /FRE/FU_CL_FRP_SAFRUN_CRIT

/FFIS/SAFIN_FRESH_PROD_FCST

Imports calculated fresh product forecast from file as time series

/FFIS/FU_CL_FRP_SAFIN_EXT_FCST

After task /FFIS/SAFRUN_CRIT (see above) and just before the cleanup tasks



/FFIS/SAFIN_PROJECTED_WASTE

Imports calculated projected waste and shrinkage from file as time series

/FFIS/FU_CL_FRP_SAFIN_PW_RESLT

After task /FFIS/SAFRUN_CRIT (see above) and just before the cleanup tasks

/FFIS/SAFRUN_CLEANUP Cleans up fresh product-specific data

/FFIS/FU_CL_FRP_SAFRUN_CLEANUP

Final task or directly before SAP F&R standard cleanup task

/FFIS/DELETE_SPLIT_ITEMS_BEGIN

Deletes data from /FFIS/SPLIT_ITEM for the current location and planning date at the start of the FRP run

/FFIS/FU_CL_FRP_DEL_SPLIT_1

Execute at the beginning of the FRP run

/FFIS/DELETE_SPLIT_ITEMS_END

Deletes data from /FFIS/SPLIT_ITEM for the current Location & Planning Date at the beginning of the FRP Run

/FFIS/FU_CL_FRP_DEL_SPLIT_2

Execute at the end of the FRP Run (after the creation of Order proposals)

/FFIS/SAFOUT_ENHANCE_DSX_FILES

Enhances FRP Standard DSX files with additional used fields for fresh products

/FFIS/FU_CL_FRP_SAFOUT_DSX

Execute after creating the standard DSX files

/FFIS/SAFOUT_ENHANCE_DATADICT

Enhances file DATADICT.xml

/FFIS/FU_CL_FRP_SAFOUT_DDICT

Execute after creating the standard DATADICT.xml File

/FFIS/SAFOUT_DELIVER Deletes file DELIVER.saf and renames Z_FFI_DELIVER_AVAILTIME.saf to DELIVER.saf

/FFIS/FU_CL_FRP_SAFOUT_DELIVER

Execute at the end of SAFOUT and before SAFRUN (sequence /FFIS/OUTBOUND)

/FFIS/SAFOUT_OPENORDER

Deletes file OPENORDER.saf and renames Z_FFI_OPENORDER_AVAILTIME.saf to OPENORDER.saf

/FFIS/FU_CL_FRP_SAFOUT_OPORDER


/FFIS/SAFOUT_SALESITEMS

Deletes file SALESITEMS.saf and renames Z_FFI_SALESITEMS.saf to SALESITEMS.saf

/FFIS/FU_CL_FRP_SAFOUT_SALESIT


/FFIS/SAFOUT_INTMORATES

Creates the file IntradayMovementRates.saf

/FFIS/FU_CL_FRP_SAFOUT_INTMORT

Execute in sequence /FFIS/OUTBOUND

/FFIS/TIME_BASED_SCHEDULING

Sets the value of class attribute /FFIS/CL_IM_SCHEDULING=>GV_FRP_RUN to ABAP_TRUE

/FFIS/FU_CL_FRP_INTRADAY_SCHED

Execute at the beginning of the FRP Run



/FFIS/SAFOUT_DP Resets the detailed timestamps of the Intraday Solution back to dates to ensure a right data access during the standard order forecast function

/FFIS/FU_CL_FRP_SAFOUT_DP


/FFIS/SAFRUN_CALIB Calibration in non-critical time frame

/FFIS/FU_CL_FRP_SAFRUN_CALIB

Execute in a non-critical time frame

3. See the following sections for detailed information.

Related Information

Dispatcher Profile /FFIS/DEFAULT [page 27]FRP Sequence /FFIS/MD_AND_TECH_SYNCH [page 29]FRP Sequence /FFIS/ACTIVATION [page 29]FRP Sequence /FFIS/OUTBOUND [page 30]FRP Sequence /FFIS/AUTO_REPL_AND_OPRM [page 31]FRP Sequence /FFIS/INBOUND [page 31]FRP Sequence /FFIS/CLEANUP [page 32]FRP Sequence TD_DATA_SYNCH [page 32]

4.2.6.1 Dispatcher Profile /FFIS/DEFAULT

FRP Sequence /FFIS/DEFAULT

Dispatcher Profile Sequence Order FRP Sequence Dispatcher Profile Text

/FFIS/DEFAULT 0 UPDATE_SUBSTITUTIONS Default Fresh Product Dispatcher

/FFIS/DEFAULT 1 /FFIS/MD_AND_TECH_SYNCH

Default Fresh Product Dispatcher

/FFIS/DEFAULT 2 /FFIS/ACTIVATION Default Fresh Product Dispatcher

/FFIS/DEFAULT 3 /FFIS/OUTBOUND Default Fresh Product Dispatcher


Dispatcher Profile Sequence Order FRP Sequence Dispatcher Profile Text

/FFIS/DEFAULT 4 /FFIS/ID_DATA_SYNCH Default Fresh Product Dispatcher

/FFIS/DEFAULT 5 /FFIS/AUTO_REPL_AND_OPRM

Default Fresh Product Dispatcher

/FFIS/DEFAULT 6 ORDER-FORECAST Default Fresh Product Dispatcher

/FFIS/DEFAULT 7 FC_AND_MD_SYNCH Default Fresh Product Dispatcher

/FFIS/DEFAULT 8 NON_EXC_ANA Default Fresh Product Dispatcher

/FFIS/DEFAULT 9 /FFIS/INBOUND Default Fresh Product Dispatcher

/FFIS/DEFAULT 98 /FFIS/CLEANUP Default Fresh Product Dispatcher

/FFIS/DEFAULT 99 FRP_CLEANUP Default Fresh Product Dispatcher

SAPDEFAULT 0 UPDATE_SUBSTITUTIONS SAPDEFAULT

SAPDEFAULT 1 MD_AND_TECH_SYNCH SAPDEFAULT

SAPDEFAULT 2 TD_DATA_SYNCH SAPDEFAULT

SAPDEFAULT 3 AUTO_REPL_AND_OPRM SAPDEFAULT

SAPDEFAULT 4 ORDER FORECAST SAPDEFAULT

SAPDEFAULT 5 FC_AND_MD_SYNCH SAPDEFAULT

SAPDEFAULT 6 NON_EXC_ANA SAPDEFAULT

SAPDEFAULT 99 FRP_CLEANUP SAPDEFAULT


4.2.6.2 FRP Sequence /FFIS/MD_AND_TECH_SYNCH

FRP Sequence /FFIS/MD_AND_TECH_SYNCH

FRP Sequence Task Order FRP Task

/FFIS/MD_AND_TECH_SYNCH 10 CREATE_LOCATION_ENVIRONMENT

/FFIS/MD_AND_TECH_SYNCH 20 /FFIS/TIME_BASED_SCHEDULING

/FFIS/MD_AND_TECH_SYNCH 30 /FFIS/DELETE_SPLIT_ITEMS_BEGIN

/FFIS/MD_AND_TECH_SYNCH 40 CREATE_OUTBOUND_FILES_ON_DEM

/FFIS/MD_AND_TECH_SYNCH 50 CREATE_OUTB_FILES_NO_CRIT_MD

/FFIS/MD_AND_TECH_SYNCH 60 CHECK_FOR_UPDATES

/FFIS/MD_AND_TECH_SYNCH 70 /FFIS/SAFEOUT_ENHANCE_DATADICT

/FFIS/MD_AND_TECH_SYNCH 80 /FFIS/SAFEOUT_ENHANCE_DSX_FILES

/FFIS/MD_AND_TECH_SYNCH 90 /FFIS/SAFEOUT_SALESITEMS

/FFIS/MD_AND_TECH_SYNCH 100 SAFRUN_NONCRIT

FRP Task Function to be executed Dispatcher Task Text

/FFIS/TIME_BASED_SCHEDULING /FFIS/FU_CL_FRP_INTRADAY_SCHED FP: Time Based Scheduling/Intraday Sol.

/FFIS/DELETE_SPLIT_ITEMS_BEGIN /FFIS/FU_CL_FRP_DEL_SPLIT_1 FP: Reorganization for split item table

/FFIS/SAFOUT_ENHANCE_DATADICT /FFIS/FU_CL_FRP_SAFOUT_DDICT FP: Enhance DATADICT.xml

/FFIS/SAFOUT_ENHANCE_DSX_FILES /FFIS/FU_CL_FRP_SAFOUT_DSX FP: Enhance DSX Files

/FFIS/SAFOUT_SALESITEMS /FFIS/FU_CL_FRP_SAFOUT_SALESIT FP: Cr. SALESITEMS.saf file

4.2.6.3 FRP Sequence /FFIS/ACTIVATION

FRP Sequence /FFIS/ACTIVATION


/FFIS/ACTIVATION 10 /FFIS/SAFRUN_LOC_ACTIVATE


Task Function to be execute Dispatcher Task Text

/FFIS/SAFRUN_LOC_ACTIVATE /FFIS/FU_CL_FRP_SAFRUN_LOC_ACT FP: Module call for location activation

4.2.6.4 FRP Sequence /FFIS/OUTBOUND

FRP Sequence /FFIS/OUTBOUND


/FFIS/OUTBOUND 10 /FFIS/SAFOUT_CONFIG_FILES

/FFIS/OUTBOUND 20 /FFIS/SAFOUT_CLOSED_DAYS

/FFIS/OUTBOUND 30 /FFIS/SAFOUT_FEAT_PARAM

/FFIS/OUTBOUND 40 /FFIS/SAFOUT_CALIB_ITEMS

/FFIS/OUTBOUND 50 /FFIS/SAFOUT_FCST_ITEMS

/FFIS/OUTBOUND 60 /FFIS/SAFOUT_PRED_DATA

/FFIS/OUTBOUND 70 /FFIS/SAFOUT_PROJ_WASTE

/FFIS/OUTBOUND 80 /FFIS/SAFOUT_DELIVER

/FFIS/OUTBOUND 90 /FFIS/SAFOUT_INTMORATES

/FFIS/OUTBOUND 100 /FFIS/SAFOUT_DP

/FFIS/OUTBOUND 110 /FFIS/SAFRUN_CALIB


/FFIS/SAFOUT_CONFIG_FILES /FFIS/FU_CL_FRP_SAFOUT_UPD_INI FP: Cr. specific CONFIG-/WORK.INI-files

/FFIS/SAFOUT_CLOSED_DAYS /FFIS/FU_CL_FRP_SAFOUT_STCLOSE FP: Cr. closed days file

/FFIS/SAFOUT_FEAT_PARAM /FFIS/FU_CL_FRP_SAFOUT_FT_CONF FP: Cr. feature parameters file

/FFIS/SAFOUT_CALIB_ITEMS /FFIS/FU_CL_FRP_SAFOUT_CALIB FP: Cr. calibration items file

/FFIS/SAFOUT_FCST_ITEMS /FFIS/FU_CL_FRP_SAFOUT_FORECAS FP: Cr. forecasting items file

/FFIS/SAFOUT_PRED_DATA /FFIS/FU_CL_FRP_SAFOUT_PRDCTR FP: Cr. pred. assignment and parameter files

/FFIS/SAFOUT_PROJ_WASTE /FFIS/FU_CL_FRP_SAFOUT_WP FP: Cr. PW items, parameter and data files

/FFIS/SAFOUT_DELIVER /FFIS/FU_CL_FRP_SAFOUT_DELIVER FP: Cr. deliver file with AVAIL times

/FFIS/SAFOUT_INTMORATES /FFIS/FU_CL_FRP_SAFOUT_INTMORT FP: Cr. IntradayMovementRates.saf file



/FFIS/SAFOUT_DP Fill /FRE/FRP_DP for Intraday Reset the detailed timestamps of the Intraday Solution back to dates to ensure a right data access during the standard order forecast function.

/FFIS/SAFRUN_CALIB /FFIS/FU_CL_FRP_SAFRUN_CALIB FP: Calibration in non-crit. time frame

4.2.6.5 FRP Sequence /FFIS/AUTO_REPL_AND_OPRM

FRP Sequence /FFIS/AUTO_REPL_AND_OPRM


/FFIS/AUTO_REPL_AND_OPRM 10 CREATE_OUTBOUND_FILES_CRIT

/FFIS/AUTO_REPL_AND_OPRM 20 /FFIS/SAFOUT_DAILY_SALES

/FFIS/AUTO_REPL_AND_OPRM 30 /FFIS/SAFRUN_CRIT

/FFIS/AUTO_REPL_AND_OPRM 40 SET_DIF_DELTA

/FFIS/AUTO_REPL_AND_OPRM 50 RESET_LOCATION_ENVIRONMENT

/FFIS/AUTO_REPL_AND_OPRM 60 CREATE_AND_RELEASE_OPS

/FFIS/AUTO_REPL_AND_OPRM 70 /FFIS/DELETE_SPLIT_ITEMS_END


/FFIS/SAFOUT_DAILY_SALES /FFIS/FU_CL_FRP_SAFOUT_DAYSALE FP: Cr. daily sales (cons. data) file

/FFIS/SAFRUN_CRIT /FFIS/FU_CL_FRP_SAFRUN_CRIT FP: Module calls in critical timeframe

/FFIS/DELETE_SPLIT_ITEMS_END /FFIS/FU_CL_FRP_DEL_SPLIT_2 FP: Reorganization for split item table

4.2.6.6 FRP Sequence /FFIS/INBOUND

FRP Sequence /FFIS/INBOUND


/FFIS/INBOUND 10 /FFIS/SAFIN_FRESH_PROD_FCST

/FFIS/INBOUND 20 /FFIS/SAFIN_PROJECTED_WASTE



/FFIS/SAFIN_FRESH_PROD_FCST /FFIS/FU_CL_FRP_SAFIN_EXT_FCST FP: Import fresh prod. specific forecast

/FFIS/SAFIN_PROJECTED_WASTE /FFIS/FU_CL_FRP_SAFIN_PW_RESLT FP: Import projected waste & shrinkage

4.2.6.7 FRP Sequence /FFIS/CLEANUP

FRP Sequence /FFIS/CLEANUP


/FFIS/CLEANUP 10 /FFIS/SAFRUN_CLEANUP


/FFIS/SAFRUN_CLEANUP /FFIS/FU_CL_FRP_SAFRUN_CLEANUP FP: Specific cleanup module call

4.2.6.8 FRP Sequence TD_DATA_SYNCH

FRP Sequence TD_DATA_SYNCH


TD_DATA_SYNCH 1 CREATE_OUTB_FILES_NO_CRIT_TD

TD_DATA_SYNCH 2 SAFRUN_CALIB

TD_DATA_SYNCH 3 /FFIS/SAFOUT_OPENORDER


/FFIS/SAFOUT_OPENORDER /FFIS/FU_CL_FRP_SAFOUT_OPORDER FP: Cr. OPENORDER file with AVAIL times

4.2.7 Activating Main and Supplementary Scheduling Types

The add-on supports the main and supplementary scheduling types that are included in the standard solution.

Context

You activate the main and supplementary scheduling types in table/FRE/XPRA_CTRL. These scheduling types allow you to configure main and supplementary order days, which you can use to optimize the requirement


calculation. By default, the system aims to order stock on main order days only. However, if you set up supplementary delivery days, the system can order more stock when necessary, for example, if there is a sudden increase in demand.

In addition to defining main and supplementary scheduling days, you can also specify the minimum and maximum coverage periods, which determine how many days the ordered stock should last for.

To activate the scheduling types, proceed as follows:

NoteIf you have already activated this feature for the standard solution, you do not have to perform this task.

Procedure

1. In Maintain Table Views (transaction SM30), open table /FRE/XPRA_CTRL.

2. Choose New Entries.3. In the Calling Application column, select FRP Forecast &Replenishment Processor.4. In the Fieldname column, choose Main and Supplementary Schedule Types.5. In the Function Status column, select Function Active.6. In the Upgrade Field , select Upgrade Outstanding.

Results

The system activates the feature when one of following events occurs:

● During the next FRP run when you run report /FRE/FRP_MID_BASIC● When you next start and stop the FRP dispatcher either by using transaction /FRE/FRP_DISP_ACT or

running report /FRE/FRP_DISP_START_STOP

When activated, the system automatically generates all required configuration files. In table /FRE/XPRA_CTRL, the system automatically populates column Upgrade Field with the value Upgrade finished.

Related Information

SAP Note 2486548SAP Note 2558381SAP Note 2599433





4.2.7.1 Defining Main and Supplementary Days

After activating main and supplementary scheduling types, you can define main and supplementary order days.

The process of defining main and supplementary days, as well as the business requirements and considerations, are explained in the following SAP Note:

● Main and supplementary schedule types (2468391 )

4.3 SAP Forecasting and Replenishment, add-on for fresh products Customizing Settings

You need to make various settings to configure the SAP system for some of the additional features provided by SAP Forecasting and Replenishment, add-on for fresh products. There are dedicated Customizing activities for these add-on-specific steps.

NoteWhen you install this add-on, no default profiles are created. You have to create your own default profiles.

The following Customizing activities are not transported to additional systems because they contain master data:

● SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh productsMaster Data Fresh Product Identification Assign Business Rule to Location

● SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh productsF&R Processor Assign Optimization Frequency Profile for Fresh Product to Location

Therefore, any changes you make using these activities need to be manually changed in each system.

The following sections each correspond to a node in the add-on specific Customizing settings in which you perform the various activities:.

Related Information

Master Data [page 35]Demand Influencing Factors [page 41]Interfaces [page 42]Intraday Functions [page 68]



4.3.1 Master Data

This section describes the activities you perform in the following Customizing node:

SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh productsMaster Data

This Customizing node contains general activities to define weekday groups, weekday group profiles, and resolution groups. This data is used to determine the permitted values in other Customizing activities.

4.3.1.1 Fresh Product Identification

SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh productsMaster Data Fresh Product Identification

This Customizing node contains several activities that you need to perform so that the system can automatically identify whether existing location products or new location products entered on the interface are fresh products.

New location products entered on the interface are automatically identified. Otherwise, you need to run the existing location products report /FFIS/INIT_NEW_FRESH_PRODUCTS as part of the step Identify Fresh Products. If a location product has been identified as a fresh product, the default forecasting profile that you defined in the following activity is assigned:

SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh products F&R Processor Customizing Enhance Attributes for Forecasting Profile .

NoteAutomatic identification of new products as fresh products is optional. If you do not want to use this functionality, you do not need to make any of these settings.

4.3.1.1.1 Defining Conditions for Identifying Fresh Products

In this Customizing activity, you can define one or more conditions to identify fresh products.

Context

You define conditions that the system will use to automatically identify that an incoming product is a fresh product based on the value of specific fields.


Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data Fresh Product Identification Define Condition for Identifying Fresh Products .

3. Enter a condition number and a condition description to help you identify the condition later.4. Select the field name using the input help in order to determine whether an item is a fresh product.5. Select the relevant condition, for example Equals, Between ... and … , etc.6. Define a low value and a high value for the condition.

ExampleTo set up a condition that will automatically identify items with a remaining shelf life of between 1 and 5 days as fresh products, you would enter the following values:

Field Name Condition Low Value High Value

SHLFLFEREQ_MIN Between… and... 1 5

4.3.1.1.2 Assigning Conditions to Condition Sets

In this Customizing activity, you assign the defined condition for fresh product identification to the condition sets.

Prerequisites

You have defined the conditions for identifying fresh products in the Customizing for SAP Forecasting and Replenishment under Define Condition for Identifying Fresh Products.

Context

You define the conditions in the Customizing for SAP Forecasting and Replenishment, add-on for fresh products.

Procedure



2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data Fresh Product Identification Assign Condition to Condition Set .

3. Select a condition set from the list to which you want to assign new conditions, or create a new set.4. Double-click Business Condition Set Assignment in the dialog structure.5. In the Condition Number column, specify the condition that you want to assign to the set.6. Save your entries.

Results

The selected condition is now assigned to the condition set.

4.3.1.1.3 Defining Business Rules for Identifying Fresh Products

In this Customizing activity, you define a business rule and business rule assignment.

Context


Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data Fresh Product Identification Define Business Rules for Identifying Fresh Products .

3. Select a business rule from the list, or create a new business rule.4. Double-click Business Rules Assignments in the dialog structure.5. In the Condition Set column, specify the condition set that you want to assign..6. If required, select the checkbox to set this business rule as the default.7. Save you entries.

Results

The condition set is now assigned to the business rule.


4.3.1.1.4 Assigning Business Rules to Locations

In this Customizing activity, you assign the business rule to a specific location.

Prerequisites

You have defined a business rule in the Customizing for SAP Forecasting and Replenishment, add-on for fresh products in the Define Business Rule for Identifying Fresh Products activity.

Context


Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data Fresh Product Identification Assign Business Rule to Location .

3. In the Location Number column, specify the location to which you want to assign the business rule.4. In the Business Rule column, specify the business rule that you want to assign to the selected location.5. In the Business Rule Description column, add a description to help you identify the business rule later.6. Save your entries.

Results

The business rule is now assigned to the selected location.

4.3.1.2 Weekday Group

SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh productsMaster Data Define Weekday Groups / Define Weekday Group Profiles

This Customizing node contains several activities that you need to perform to determine how certain calculations are made based on weekday groups. For example, you specify whether safety amounts and the


delta sales-price effect should be calculated differently for specific weekday groups, or even for each weekday individually.

To activate the safety stock regime, you need to activate the relevant parameter in SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh products F&R Processor Fresh Product Forecasting Parameter Profiles .

To determine different delta sales-price effects based on weekday groups, you first define the weekday group in the demand influence settings for delta sales price in SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh products Demand Influencing Factors Enhance Attributes for DIF .

4.3.1.2.1 Defining Weekday Groups

In this Customizing activity, you define weekday groups.

Context

Safety stock can be calculated for several periods within one week based on weekday groups. As a basic example, you might have one group for weekdays (Monday - Friday) and another group for the weekend (Saturday and Sunday). In this Customizing activity, you can assign one or more weekdays to a group.

You define weekday groups in the Customizing for SAP Forecasting and Replenishment, add-on for fresh products.

Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data Define Weekday Groups .

3. Enter the an ID and description for the weekday group.4. Select the weekdays that you want to include in this group.5. Save your entries.

ExampleWeekday Group 1: Monday

Weekday Group 2: Tuesday, Wednesday, Thursday

Weekday Group 3: Friday, Saturday


4.3.1.2.2 Defining Weekday Group Profiles

In this Customizing activity, you define weekday group profiles and assign weekday groups to them.

Prerequisites

You have defined the weekday groups in Customizing in activity Define Weekday Groups.

Context

You can use weekday group profiles during safety stock calculation. You define the profiles in the Customizing for SAP Forecasting and Replenishment, add-on for fresh products.

Proceed as follows:

Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data Define Weekday Group Profiles .

3. Enter a weekday profile ID and a weekday profile description.4. Assign weekday groups to your weekday profile.

NoteThe combination of weekday groups contained in a profile must contain at least one unassigned day. That is, you cannot assign a weekday group that contains every single day of the week.

5. Save your entries.

4.3.1.2.3 Season Resolution Group

SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh productsMaster Data Define Season Resolution Group for Fresh Products

In these Customizing activities, you define the number of season dummies that exist for a year. Season dummies are artificial data curves that are used for forecasting seasonal data. The number that you choose in this activity determines how many of these curves are generated. Therefore, the higher the value, the finer the granularity with which seasonal fluctuations are modeled. Season resolution 1 means that the forecast does not contain any seasonal predictions, that is, the entire year is modeled on a single curve.


A season dummy must be observed for at least half of its total period to accurately detect effects of seasonal demand-influencing factors (DIF). For example, if you set a season resolution of 6, there are potentially 6 separate seasons throughout the year consisting of 2 months each. Therefore, each season must be observed for at least 1 month before you can make accurate forecasts.

To activate this seasonality function, you need to activate the relevant parameter in Fresh Product Forecasting Parameter Profile.

4.3.1.2.3.1 Defining Season Resolution Groups for Fresh Products

In this Customizing activity, you define the number of seasonal demand influencing factors (DIFs) to be used.

Context

You make these settings in the Customizing for SAP Forecasting and Replenishment, add-on for fresh products.

The resolution defines how many seasons can potentially exist. Therefore, a season resolution of 1 means that the no seasonality is considered in the forecast, that is, the entire year is modeled on a single curve.

If you have activated the seasonality function in Customizing for SAP Forecasting and Replenishment, add-on for fresh products in activity Define Fresh Product Forecasting Parameter Profiles, resolution groups are required as a parameter for the fresh product profile.

Proceed as follows:

Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data Define Season Resolution Groups for Fresh Products .

3. Specify a new season resolution group or select one from the list by double-clicking it.4. Use the checkboxed to select the season resolutions that you want to assign to this group.5. Save your entries.

4.3.2 Demand Influencing Factors

SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh productsDemand Influencing Factors


This Customizing node contains activities for defining the relevance of the demand influencing factor (DIF) identifier for fresh products and editing it afterward.

4.3.2.1 Enhancing Attributes for DIF

In this Customizing activity, you define fresh product-specific attributes for demand influencing factors (DIF) based on the fresh product-specific DIF type you enter.

Prerequisites

● You have defined the DIF in standard Customizing for SAP Forecasting and Replenishment under Define Demand Influencing Factors.

● You have set the DIF relevance for fresh products to 1 Only relevant for Fresh Products or 2 DIF Relevant for Fresh and Non-Fresh Products.

● You have set the DIF relevance as instructed for additional fresh product-specific attributes to be maintained.

Context


Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data Demand Influencing Factors Enhancing Attributes for DIF .

3. Select a DIF ID and specify whether it is relevant for fresh products only, non-fresh products only, or both using the dropdown provided.


4.3.3 Interfaces

SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh productsInterfaces


This Customizing node contains activities that you can use to make settings related to interfaces. These are general settings considered during outbound processing within an FRP run but are also relevant for inbound processing of consumption data. For fresh products, you can make different settings from the SAP Forecasting and Replenishment standard to retrieve historical consumption data during the initial transfer from BI.

Define the interface settings as follows:

● Define General Configuration Parameters for Fresh Products: Define the FRP parameter Tools.SalesBuffer.Weeks with the value defined in Time Series Past Period for Second Granularity of an /FFIS/ time series.

Define General Configuration Parameters for Fresh Products

Configuration Parameter Name Configuration Parameter Value

Tools.SalesBuffer.Weeks 110

● Define Source Qualifier for Fresh Product Time Series: Assign all fresh product-relevant qualifiers for consumptions to the new qualifier 3099 in SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh products Interfaces Define Movement Type Qualifiers .

Define Source Qualifier for Fresh Product Time Series

Qualifier Qualifier Name FP Qualifier

3000 POS INFORMATION 3099

● Define Fresh Product Settings for Transfer of Consumption from BI: You can overwrite the standard parameters with parameters that are relevant for fresh products to retrieve consumption data from BI. Define all required parameters for transferring the consumption data from BW on a daily basis, as opposed to on a weekly basis.

4.3.3.1 Defining General Configuration Parameters for Fresh Products

In this Customizing activity, you define configuration values that are specific to fresh product forecasting.

Context

Similar to the SAP Forecasting and Replenishment standard forecast calculation, the fresh product forecast calculation receives configuration settings from the configuration file. For most parameters, you can use the same values as in the standard CONFIG.INI configuration file. However, you do need to make some changes to parameters to enable fresh product calculation. You make these settings in the Customizing for SAP Forecasting and Replenishment, add-on for fresh products.


Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data InterfacesDefine General Configuration Parameters for Fresh Products .

3. Add configuration parameter Tools.SalesBuffer.Weeks and set the value to 110.

4.3.3.2 Defining Source Qualifiers for Fresh Product Time Series

In this Customizing activity, you can determine the qualifier that is saved along with the incoming and duplicated data.

Prerequisites

● You have defined qualifiers in standard Customizing for SAP Forecasting and Replenishment under Define Movement Type Qualifiers.

● You have defined the time series interface for source qualifiers and for the fresh product time series qualifiers in standard Customizing for SAP Forecasting and Replenishment under Maintain Time Series Interface.

Context

Consumption data for fresh products is saved in both SAP Forecasting and Replenishment time series and fresh product-specific time series. In the time series for fresh products, data is saved for a longer duration and at a higher granularity. In the add-on, for example, data is saved for two years on a daily basis, whereas in SAP Forecasting and Replenishment consumption data time series, it is saved for 30 days on a daily basis and then at a lower granularity for longer periods.

To save consumption data for fresh products in two separate time series, the incoming consumption data with a specific qualifier is duplicated when data is posted to a buffer table for time series data, for example, /FRE/BIF_TSD.

With interface processing, the consumption data is written into two different time series.

Procedure



2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data InterfacesDefine Source Qualifiers for Fresh Product Time Series .

3. Add the following entry:

Qualifier Qualifier Name FP Qualifier

3000 POS INFORMATION 3099

4.3.3.3 Defining Fresh Product Settings for Transferring Consumption Data from BI

In this Customizing activity, you can define all required parameters for transferring the consumption data from the business warehouse on a daily basis, instead of on a weekly basis.

Context

This is necessary for fresh products because it allows you to overwrite the standard parameters with parameters that are relevant for fresh products in order to retrieve consumption data from BI.

On this Customizing screen, you cannot create or delete profiles. You can only maintain additional fresh product parameters. You can only define exact one profile, which is valid for all locations.

Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data InterfacesDefine Fresh Product Settings for Transfer of Consumption from BI .

3. Enter the required information and select the options that you want for the profile.4. Save your entries.

4.3.4 F&R Processor

This Customizing node contains settings that control the FRP run.

You can set parameters used in the enhanced forecast, projected waste, and shrinkage calculations. In addition to generally activating the fresh products forecast and waste calculations for SAP F&R standard forecasting profiles, you can activate and deactivate the individual enhanced forecast features. You can also define the parameters used for the calculation.


The default profile for fresh products can also be defined in the Condition Set and will overrule the default profile in Master Data F&R Processor Enhancing Attributes for Forecasting Profiles .

During these activities, you make the following settings:

● Define parameter profiles for fresh product forecasting● Define projected waste parameter profiles in which you configure the logic for projected waste calculation,

activate and configure shrinkage calculation, and select how the system deals with back orders when calculating the projected waste.

● Enhance the F&R standard forecasting profiles● Define a default frequency for how often you want to perform parameter optimization for fresh forecasting.

If you are using the dispatcher for the F&R processor,you can also can define whether the parameter optimization is performed in critical time window.

● Assign the optimized frequency profile to specific locations

NoteThese Customizing activities determine whether the main functions of the add-on are activated. When activating the fresh product forecast or projected waste calculation for a forecasting profile, the functions are activated for all location products that are already assigned the forecasting profile.

4.3.4.1 Defining Fresh Product Forecasting Parameter Profiles

You define parameter profiles for the F&R processor that determine how the system performs the automatic forecast for fresh products.

Prerequisites

● You have defined a weekday group profile in the Customizing (transaction SPRO) under SAP Forecasting and Replenishment, add-on for fresh products Master Data Define Weekday Group Profiles .

● You have defined a resolution group profile in the Customizing under SAP Forecasting and Replenishment, add-on for fresh products Master Data Define Resolution Group Profiles .

Context

To enable the F&R processor for fresh products, you have to create parameter profiles for fresh product forecasting and assign them to standard forecasting profiles.

In this activity, you define the parameter profiles for fresh product forecasting that you later assign to SAP Forecasting and Replenishment standard forecasting profiles. If a fresh product profile is assigned to a forecast profile, the system applies the new forecast calculation logic for fresh products only.


By default, when you create a new parameter profile, all of the fresh-product forecasting functions are active, for example, the collinearity and zero stock filters. If required, you can deactivate these features.

RecommendationWe recommend keeping at least one profile for fresh product forecasting with the SAP default settings.

Procedure

1. Open the SAP Implementation Guide

2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data F&R ProcessorDefine Fresh Product Forecasting Parameter Profiles .

In the table, you can add, edit and delete parameter profiles. To edit a parameter profile, double-click the parameter name.

3. To add a new parameter profile, choose New Entries.4. In the FP FCST Parameter Profile fields, enter a name in the left field and a description for your parameter

profile in the right field.5. Make the relevant settings as follows to suit your needs:

Section Field Description

General Parameters

Forecast Horizon Enter the forecast horizon for fresh products in days. A normal forecast horizon for fresh products is about 30 days.

Order Forecast Horizon Enter the forecast horizon for orders in days. The forecast horizon for orders cannot exceed the forecast horizon for fresh products.

To deactivate the order forecast, enter the value 0.



Past Horizon Enter the past horizon in days. This determines how many days' worth of historical consumption values are considered by the forecast calculation when calculating the forecast value.

RecommendationWe recommend entering 770 days.

Maximum Optimization Loops How many optimization loops can be performed during the forecast.

Value Range: 0-255

Default Value: 1

Safety Stock Regime

Activate Safety Stock Regimes When active, the safety stock is calculated for several periods within one week. The system assigns one or more weekdays to one group. Afterwards it assigns one or more weekday groups to one profile. The system uses these profiles during safety stock calculation.

Weekday Profile ID Enter the ID of the weekday profile to use when calculating the safety stock regime.

Seasonality



Activate Fixed Seed Detection When active, the system considers seasonal variations of a product.

Seasonality combines all aspects that consider seasonal variations of a product. Together with the intercept (base forecast) and other influencing factors, seasonality ensures accurate forecasting. The system automatically detects seasonality at product level.

When configuring the seasonality parameters, you can specify the sensitivity of the season detection. Sensitive means that even small deviations are detected as seasons.

Forecasting Contrast for Fresh Products

A value that is subtracted from season dummies to avoid that DIF occurrences have an endless extension.

Validity Threshold for Fresh Product Seasonality

Considers seasonal patterns by using special internal demand influencing factors (DIF) in the calculation.

A certain number of such DIFs are added to the model during optimization. These seasonal DIFs are tested for sufficient statistical base. If their historic observation is incomplete and does not achieve a certain extent, they are not included in the positive list of DIFs.

Resolution Group ID Defines how many season DIFs are used.

Outlier Detection for Sales Data

Outlier Detection Automatically detects outliers. An outlier is a sales value that is exceptionally high or low compared to the values in the sales time series of an item. Those sales values are ignored during forecast calculation. Outlier detection prevents the occurrence of extremely high or extremely low forecasts.



Outlier Detection Factor (Low/High) A date is considered to be an outlier date if the actual sales value on a particular day is smaller or higher than model fit minus the "Lower Detection Factor" standard deviation or plus the "Higher Detection Factor".

Zero Stock Correction The system can detect days with zero stocks based on a configured setting in Forecasting Profile of the standard forecast calculation. The daily sales for detected days with a zero stock automatically will be discarded in the fresh product forecast calculation.

In opposite to the standard forecast, detected zero stock days are not corrected by a local mean value, but these days are discarded. No correction reason is displayed in the time series.

Zero stock days for daily sales values from a reference cannot be detected.

Outlier Detection for Metric DIFs

Activate Outlier Detection for Metric DIFs

Dampens the effect if future metric DIFs exceed the range of the historic observations.

Forecast calculation determines the DIF effect and the value range of the past DIF values. It applies the DIF effect to future DIF values. The system treats these future values differently depending on the value range:

○ Future values within the past value range will influence the forecast without being dampened.

○ Future values outside the past value range (outliers) will influ-ence the forecast but will first be dampened using a dampening factor.



Dampening Factor for Metric DIF Outlier Detection

Avoids extreme forecasts and forecast errors by weakening the effect of values.

You can use the dampening factor in the forecast calculation.

○ Factor = 0: The system strictly limits the value to the highest historic value of the metric DIF.

○ Factor = 1: The system takes the value as it is.

○ Factor < 1: The system dampens future metric DIF values if they exceed the highest/lowest historic value.

Inactive Periods

Activate Inactive Periods Detection Automatically determines inactive periods along with detecting phantom sales.

An inactive period is a time period during which a product is typically not available for sale.

An example for a phantom sale is when the EAN code of a product was accidentally scanned despite not being available for sale at that time.

The system considers the (manually maintained) delisting data for fresh product to determine inactive time periods.

This allows you to identify periods in which items are probably not available for sale. In addition, it prevents an influence of the observations in such periods on the calculation results. You want to avoid that these periods that (mainly) consist of zero sales will reduce the forecasts if considered.



Probability Threshold for Detection of Inactive Periods

Identifies a sequence of low sales periods as an inactive period if the probability for this sequence of low sales is lower than the probability threshold. This means, the higher the value, the more inactive periods are detected.

Phantom Sales Detection Threshold for Inactive Periods

Controls which weeks are regarded as zero-sales weeks even if the sales are above zero. The bigger the value, the more values are regarded as zero.

Phantom Sales Quantile for Detection of Inactive Periods

Defines which quantile to use as sales quantile. The resulting quantile value is the observation value for which the "PhantomSalesQuantile" percent of the values is smaller than this.

Minumum Number of Successive Low Sales Weeks

Specifies the minimum number of successive low sales weeks needed to define an inactive period. This value forms an additional restriction.

At least n low sales have to occur consecutively to form an inactive period. To switch off this additional restriction, set n = 0.

Use Daily Refinement Parameters for Inactive Periods

Defines if in the weeks before and after detected inactive periods partly also should be ignored: There might be days at the end of the week before a detected inactive period which also is affected by the inactive period. In addition, there might be days at the beginning of the week after a detected inactive period which are affected by the inactive period.

Switch this additional detection on or off on a daily level.



Daily Refinement Factor for Detection of Inactive Periods

Defines the threshold below which weeks are regarded as "almost zero" and the threshold below which daily sales are regarded as "almost zero". The daily threshold is determined as the weekly threshold divided by the DailyRefinementFactor.

Inactive periods are detected by optimization and stored. Estimation uses the dates so they can be excluded from calculation.

Current Tendency Predictor

Activate Current Tendency Predictor Enables or disables the function to react to particularly high or low values at the beginning of the week.

Percentage of Weeks Threshold for Sporadic Sales

Specifies which percentage of weeks is allowed to be sporadic in order to use the current week DIF.

Maximum Active Days Detection of Sporadic Week for Current Week

Specifies up to how many days of sales >0 a week is regarded as sporadic week.

The system uses a current week DIF to adapt the forecast for the rest of the week. This current week DIF is only used if it regards the analyzed product as non-sporadic. This is required to avoid the extrapolation of rarely occurring sales that are coincidentally located on the first day(s) of the week.



Past Horizon for Check Number of past days with valid sales before current calculation date in which one of the two situations appears:

○ For all days with valid sales particularly high values have been observed which are above the configurable upper threshold.

○ For all days with valid sales particularly low values have been observed which are below the configurable lower threshold.

Days with valid sales are if no correction was applied for the daily sales value.

In addition, per DIF it can be config-ured that a DIF occurrence skips Current Tendency Predictor for time period of occurrence plus configured pre and post days. This has an impact on the detection of a current tendency predictor situation: The detection terminates if during the checks in the last days a current tendency predictor situation could not be detected before the period should be extended to a day which has an impact due to the DIF occurrence.

2 is recommended value. Parameter range x >= 1.

Past Horizon for Calculation Number of past days which are checked for valid sales before current calculation date. Current Tendency Predictor is skipped in case the configurable number of days for past horizon for check is bigger than the number of days with valid sales in past horizon for calculation.

7 is recommended value.



Future Horizon for Prediction Number of days starting counting from calculation date in which a determined effect due to Current Tendency Predictor is considered in forecast.

The effect consideration can be stopped earlier or can be blocked in general in case it overlaps with an occurrence for a Boolean DIF or the config-ured pre and post period. This is relevant only if for the DIF it is configured that Current Tendency Predictor has to be ignored in case the future horizon for prediction is overlapping with an occurrence for this DIF or the configured pre and post period.

7 is recommended value.

Upper/Lower Threshold A past day is considered to have a particularly high value if the daily sales value is higher than model fit plus upper threshold used as factor for the standard deviation.

The standard deviation is determined based on variance calculation in estimation. That means it is based on all daily sales values which have not been discarded due to Ignore DIF, not-listed time periods, outlier detection or inactive period detection.

Detection of Newly Listed Products

Activate Detection of Newly Listed Products

Detects newly listed products automatically during forecast calculation and determines the scope of optimization in the new fresh product forecasting engine based on the number of existing observations.

The system performs at least basic optimization for newly listed products. To distinguish between full and basic optimization, you define a minimum number of observations that the product must have in order to fully optimize.



Observation Limit Intercept Only Specifies the number of observations.

○ If the number of observations is less than or equal to the Observation Limit Intercept Only parameter, the system executes only basic optimization for this product.

○ If the number of observations is greater than the Observation Limit Intercept Only parameter but less than or equal to Obs. Limit Intercept and Weekdays, the system also performs only basic optimization but additionally considers weekday DIFs.

Observation Limit Intercept and Weekdays

Specifies the minimum number of observations.

○ If the number of observations is less than or equal to the Observation Limit Intercept Only parameter, the system executes only basic optimization for this product.

○ If the number of observations is greater than the Observation Limit Intercept Only parameter but less than or equal to Obs. Limit Intercept and Weekdays, the system also performs only basic optimization but additionally considers weekday DIFs.

Global Adaptivity

Activate Global Adaptivity You use the function of global adaptivity to assess most recent values higher than older ones. The higher the adaptivity, the more weight is put on the most recent observations.

Adaptivity for Products with Few Sales Greater 0

Defines adaptivity for products which are selling in few numbers according to the threshold comparison.

Adaptivity for Products with Many Sales Greater 0

Defines adaptivity for products which are selling in great numbers according to the threshold comparison.



Threshold for Few/Many Sales Greater 0

Defines which percentage of the observations must be non-zero before using the adaptivity value for high sales.

Minimum Value for Global Adaptivity Ensures that each observation is weighted at least at the minimum value that you have specified. The outcome will be affected in relation to the minimum value that you have defined.

Weekday Influence

Activate Weekday Effect Considers the impact of a weekday.

Forecast calculation can determine whether a weekday has an influence on product sales. It sets a corresponding internal DIF for that day. There are seven DIFs, that is, one for each weekday. When this feature is enabled with corresponding parameters, forecasting automatically inserts weekday DIFs for the product on all relevant days. One weekday DIF must be configured as a reference weekday.

One or more weekday(s) can be assigned to a new variance group. These variance groups are considered during forecast calculation. Each weekday can only be assigned to one variance group.

Reference Day for Weekday Effect Determines the weekday reference day.

DIF Consideration



Activate DIF Insignificance Check Excludes non-significant DIFs to reduce the number of random forecast effects. It removes insignificant DIFs that return results with a sign that has not the intended direction.

You can remove DIFs that are less significant than specified in the threshold parameter from the list of DIFs that are considered during optimization.

Minimum threshold value is 0.0. This means that all DIFs are considered during optimization.

DIF Insignificance Threshold You can remove DIFs that are less significant than specified in the threshold parameter from the list of DIFs that are considered during optimization.

Minimum threshold value is 0.0 This means that all DIFs are considered during optimization.

Collinearity Filter In some cases, problematic forecast values can be found to be caused by collinear DIFs, that is, DIFs whose effect cannot be determined properly because they occur in a very similar way as other DIFs.

You can improve the quality of the forecast by eliminating collinear DIFs from the forecast model.

Exceptions



Threshold for Exception Forecast Too High

An optional exception is provided in order to warn you about high forecasts and possible overstock situations ahead of the order proposal generation:

A daily forecast value of the forecast w/o safety amount exceeds the highest consumption peak threshold. This is checked for the whole forecast horizon and if used, the exception is raised on order as well as non-order dates.

The threshold is calculated based on highest consumption peak (in the complete past) multiplied with a factor configured in this parameter value.

Define this field only if you are interested in the exception Forecast Exceeds Consumption which warns you of possible overstock situations. If you do not want to use the exception leave the field empty or set it to 0.0. In this case the exception is not generated.

When making use of the exception in case of scenarios with a DC where observation values are high it is recommended that the value defined for this field is greater than 1.0.



Horizon analyzed for Unknown DIF Exception (in days)

An optional exception is provided to warn about the first occurrence of a Boolean DIF in the forecast horizon. The system could not determine an DIF effect because for the Boolean DIF no occurrence appeared in the valid past horizon. In case of fresh forecast the system generates exception /FFIS/MSG 218.

To avoid that the exception will be created for a DIF occurrence which is too far away in the future (e.g. calendar event which is many months in the future) in this parameter a maximum detection horizon in days can be set for this exception. The exception only will be created if the system detects an unknown DIF occurrence in the defined detection horizon.

If no value or a value of 0 is set, the Unknown DIF Exception will not be created.

The detection horizon must not be longer than the configured sales forecast horizon. Please consider that the sales forecast horizon in days starts with day 1 on first week day of current week. The detection horizon for unknown DIF exception starts with day 1 on calculation date.



Raise Exeption for Unknown DIF only once

A Demand Influencing Factor describes the basic properties of certain events or values that influence the demand for a product in a typical manner. They may reoccur over time or may change their value. It is essential that the occurrences of a particular DIF have the same causal influence on the demand for the product or its sales behavior, so that the demand forecast can calculate/predict the influence of future occurrences based on past occurrences.

If the system detects an 'unknown boolean DIF' on location product level, it generates the exception 218. An 'unknown boolean DIF' describes the first occurrence of such a boolean DIF. The DIF itself must be defined in Customizing first.

If the system detects that a future metric DIF value exceed the range of the historic observations, based on parameters below "Outlier Detection for Metric DIFs" in the Fresh Product Forecasting Parameter Profile, it dampens the effect of the metric DIF and it generates the exception 245.

This parameter describes whether exceptions 218 (unknown DIF) and 245 (metric DIF value dampened) should be raised only once per location product and DIF, or whether it should be raised with every FRP run as long unknown DIF situation is detected or as long the metric DIF is dampened.

The period to be checked is defined by the number of future days in parameter Horizon analyzed for Unknown DIF Exception (in days).

6. Select whether you want to activate the safety stock regime. This calculates safety stock for several periods within one week. It assigns one or more weekdays to one group. Afterwards it assigns one or more weekday groups to one profile. The system uses these profiles during safety stock calculation.


4.3.4.2 Defining Projected Waste Parameter Profiles

Context

In this activity, you define the projected waste profile, which you can later assign to a forecast profile in the activity Enhancing Attributes for Forecasting Profiles [page 64]. In each projected waste profile all the parameters needed for a projected waste calculation are collected. Only when a profile is assigned to a forecast profile, projected waste calculation will be executed.

When defining the profile, you configure the logic for projected waste calculation, activate and configure shrinkage calculation. and select how the system deals with back orders when calculating the projected waste. For example, you can choose to determine valid back orders based on the shelf life of the product. If the back order is so late that the product's shelf life has been exceeded, the system will stop considering the products as planned goods receipts.

Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products F&R Processor Define Projected Waste Parameter Profiles .

3. Choose New Entries to create a new profile.4. Enter a name for the profile.5. Define the parameters to suit your needs:

Field Description

Projected Horizon Definition of the projection horizon in days. A value of 0 or leaving the field blank restricts the projection horizon to the current calculation date. A value of greater than 0 counts the days after current calculation date.

Threshold Total Waste Too High Exception With this parameter, you configure a percentage of the delivered quantity of the relevant goods receipts. The calcuated percentage of the delivered quantity will be used as a threshold.

Distribution Factor Past/Future Sets the percentage for the past and future to control the daily distribution on the basis of the following factors: 0% means that FIFO applies, 100% means LIFO applies, 50% means both factors apply.

Back Order Handling Fresh Products Here you can select how the system handles shelf life. Outdated, planned goods receipts are treated as open orders, availability dates can be shifted to current planning datges for outdated goods receipts or a minimum shelf life can be taken into account.

Shrinkage Percentage This option defines the percentage (0% - 100%) by which the stock is reduced due to shrinkage.


Field Description

Disable Waste Activating this option prevents the system from using spoilage to calculate projected waste.

Distribute Overstock Activate this checkbox to handle the calculated overstock as available until the end of the day. Deactivate this checkbox to handle the calculated overstock as already expired.


Results

The profile is created and ready to be assigned.

4.3.4.3 Projected Waste Module Execution Timing

Context

In this activity, you configure exact time when the stock reduction due to projected waste calculation and/or daily shrinkage has to be considered in the Requirements Calculation

First, it has to be selected if the stock reduction must be considered at the next morning (the day after calculated best-before date) or at the end of day (the day of calculated best-before date) as well as at which time.


Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products F&R Processor Projected Waste Module Execution Timing .

3. Choose Evening or Morning from Date selection.4. Enter Waste time.5. Define the parameters to suit your needs:


Field Description

Date selection In morning mode, the projected waste module assumes that waste and shrinkage occurs at the beginning of the next (calendar) day. In evening mode, the projected waste module assumes that waste and shrinkage occurs at the end of the day.

Waste time The time that should be used for generating negative open orders for waste or shrinkage. The default is 00:00 in morning mode and 23:59 in evening mode.


Results

The projected waste module execution timing is set.

4.3.4.4 Enhancing Attributes for Forecasting Profiles

After you have created your parameter profiles, you can begin assigning them to your F&R standard forecasting profiles.

Prerequisites

● You have defined standard forecasting profiles in the Customizing (transaction SPRO) under SAP Forecasting and Replenishment F&R Processor Maintain Forecasting Profiles .

● You have defined parameter profiles for fresh product forecasting in the Customizing under SAP Forecasting and Replenishment, add-on for fresh products Master Data F&R Processor Define Fresh Product Forecasting Parameter Profiles .

● You have defined parameter profiles for projected waste in the Customizing under SAP Forecasting and Replenishment, add-on for fresh products Master Data F&R Processor Define Projected Waste Parameter Profiles .

Context

In this Customizing activity, you assign the forecast profiles defined in your F&R standard solution to fresh-product-specific parameter profiles. This assignment enhances the standard profiles with the fresh-product functions. In addition, you activate the features of the add-on for each profile and specify which profile is the default for fresh products.



TipIf you do not want certain location products to be considered in the fresh product calculations but they are already assigned to an F&R foreecasting profile that is enhanced, create an identical forecasting profile in the SAP Forecasting and Replenishment Customizng. If you do not activate the fresh-product features for this profile, you can assign it to the desired location products, and they will not be included in the fresh-product calculation.

Procedure

1. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data F&R ProcessorEnhance Attributes for Forecasting Profiles .

The activity opens and you see a table that contains all of the parameter profiles that you defined as part of your F&R standard solution.

RestrictionIn the activity, you cannot edit the DC Default and ST Default columns. These values determine which profile is used by default for stores and distribution centers.

In the activity, you cannot edit the Description column. This field allows you to provide a description that helps users to identify the profile.

You can edit these fields in the Maintain Forecasting Profiles activity. For more information, see the prerequisites.

2. (Optional) For each parameter profile, activate the fresh product forecast.a. In the FP Fcst On (Activate Fresh Product Forecast) column, select the checkbox.b. In the FP Fcst Prof (Fresh Product Profile for Forecasting Fresh Products) column, enter the technical

name of a parameter profile for fresh product forecasting. Alternatively, select one from the value help.3. (Optional) For each parameter profile, activate the projected waste calculation.

a. In the PrjWasteOn (Activate Projected Waste) column, select the checkbox.b. In the PrjWasteProf (Projected Waste Profile) column, enter the technical name of a parameter profile

for projected waste. Alternatively, select one from the value help.4. In the Store FP (Define Profile as Default for Fresh Prod. for Store) column, select one parameter profile that

you want to be used as the default for all stores.

NoteThe system uses this as the default value for stores and location products that meet the following criteria:

○ They are identified as having or being fresh products.○ There is no parameter profile defined in the master data.



Results

The selected features of the add-on are active for all distribution centers and stores that are assigned to the confuigured standard parameter profiles.

4.3.4.5 Defining the Optimization Frequency Profile

Context

In this activity, you define a profile that determines how often parameter optimization for fresh forcasting is performed. You must create at least one profile to be the default profile. You can also specify that the optimization should be performed during a critical time window, for example, if you are using the dispatcher for the F&R processor.

The optimization is an iterative process that involves the following steps:

● Determination of the DIFs to be considered● Determination of adaptivity● Determination of season description (resolution)● Outlier detection● Determination if the current week DIF is used● Detection of inactive periods

During forecast calculation, the parameters for the forecast model ensure that the most recent estimates are the best fit for the model. For newly listed product, a basic optimization is performed to ensure more reliable results for products with a short time series. To distinguish between full and basic optimization, you specify a minimum number of observations that are required for a full optimization run.

Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products F&R Processor F&R ProcessorDefine Optimization Frequency Profile for Fresh Products .

3. Choose New Entries to create a new profile.4. Enter a name and description for the profile.5. Select whether you want the optimization process to run Daily or Weekly. If you select weekly, you also

need to specify the day of the week on which the process should run.


6. Select whether you want the optimization process to run in a critical window.7. To set this profile as the default, select the Is Default checkbox.8. Save your entries.

ExampleIf you wanted to create a profile for daily fresh

Field Value

Profile Name DAILY

Profile Description DAILY FRESH PRODUCT OPTIMIZATION

Frequency Type Daily

Parameter Optimization in Critical Window x

Is Default x

4.3.4.6 Assigning the Optimization Frequency Profile to a Location

Prerequisites

You have defined the optimization frequency profile for fresh products in the Customizing for SAP Forecasting and Replenishment, add-on for fresh products under Forecasting and Replenishment, add on for Fresh Products F&R Processor F&R Processor Define Optimization Frequency Profile for Fresh Products

Context

In this activity, you assign the optimization frequecy profile you defined to specific locations.

Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products F&R Processor F&R ProcessorAssign Optimization Frequency Profile for Fresh Products to Locations .


3. Choose New Entries.4. Specify the location to which you want to assign the profile.5. Specify the profile.6. Save your entries.

4.3.5 Intraday Functions

SAP Implementation Guide SAP Forecasting and Replenishment for Retail, add-on for fresh productsIntraday Functions

This Customizing node contains the settings required to enable intraday functions. These functions enable you to provide scheduling data for multiple order and delivery times and import intraday selling profiles for different locations to help calculate demand for products with shorter shelf lives. These functions rely on data imported from an external system and override the dates generated by procurements cycles.

This section provides information about the database tables provided with the intraday functionality and provides detailed information about each of the Customizing activities that you must perform.

You use Display Selling Profiles (transaction /FFIS/DISPLAY_SELLING_PROFILES) to view the intraday selling profiles that are currently in the system. To delete intraday selling profiles that are no longer necessary or to import new intraday selling profiles, you use Manage Intraday Selling Profiles (transaction /FFIS/IMP_SELL_PROF).

4.3.5.1 Database Tables for Intraday Functions

SAP Forecasting and Replenishment, add-on for fresh products provides the following database tables that you have to fill with data from your master data system:

Name Technical Name Description

Scheduling data table /FFIS/SCHEDULES This table contains all of your scheduling data. After the data is imported into the BIF tables, you must execute Process Fresh Produce BIF Data (transaction /FFIS/BIF_PROC) to copy the data to the database tables

Location opening hours table /FFIS/LOC_OPENHR This table contains the opening hours for all of your stores. After the data is imported into the BIF tables, you must execute Process Fresh Produce BIF Data (transaction /FFIS/BIF_PROC) to copy the data to the database tables


Name Technical Name Description

Selling profiles table /FFIS/SELLPROF This table contains all your selling profiles. You import profiles by implementing and calling BAdI /FFIS/BD_SELLING_PROF

4.3.5.1.1 Scheduling Data Tables for Intraday Functions

SAP provides a table for scheduling data.

In SAP Forecasting and Replenishment, add-on for fresh products, the scheduling data table has the following structure for which you can provide data:

Component Component Type Short Text / Comment

KEY_TST /FRE/BIF_KEY_TST Key time stamp for BIF records

.INCLUDE /FFIS/BIF_SCHED_KEY_STY Key Fields of BIF Scheduling Data

LOCATION_TO /FRE/LOCNOTO Target Location

LOCATION_TO_TYPE /FRE/LOCTOTYPE Location Type of the Target Location

LOCATION_FROM /FRE/LOCNOFR Source Location

LOCATION_FROM_TYPE /FRE/LOCFRTYPE Location Type of a Source Location

SCHED_GROUP /FFIS/SCHED_GROUP Scheduling Group

ORDER_DATE /FFIS/ORDER_DATE Order Date

ORDER_CUTOFF /FFIS/ORDER_CUTOFF Order Cutoff Time

DELIVERY_DATE /FFIS/DELIVERY_DATE Delivery Date

DELIVERY_TIME /FFIS/DELIVERY_TIME Delivery Time

AVAIL_DATE /FFIS/AVAIL_DATE Availability Date

AVAIL_TIME /FFIS/AVAIL_TIME Availability Time

FUNCTION /FRE/BIF_FUNCTION Function code

SAP Forecasting and Replenishment, add-on for fresh products provides the following data elements for this structure:

Data Element Domain Short Text / Comment

/FFIS/AVAIL_DATE DATS Availability Date

/FFIS/AVAIL_TIME TIMES Availability Time

/FFIS/DELIVERY_DATE DATS Delivery Date

/FFIS/DELIVERY_TIME TIMES Delivery Time

/FFIS/ORDER_CUTOFF TIMES Order Cutoff Time

/FFIS/ORDER_DATE DATS Order Date


Data Element Domain Short Text / Comment

/FFIS/SCHED_GROUP /FFIS/SCHED_GROUP Scheduling Group

New domain:

Field Value

Name /FFIS/SCHED_GROUP

Format CHAR (000040)

Output 40

Value Range

This data is imported using the RFC module /FFIS/BIF_SCHED_INBOUND.

4.3.5.2 Performing Basic Settings

In this Customizing activity, you select a distribution method and availability moment calculation method.

Context

Availability moments are derived from the scheduling data table and are calculated based on the processing time of goods receipts.

The forecast distribution method can be equal, which means that the forecast value is calculated as being the same during your store opening hours, or it can be based on intraday selling profiles. You need to import selling profiles from an external system using BAdI (/FFIS/BD_SELLING_PROF).


Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data Intraday Functions Perform Basic Settings .

3. Select a calculation method for availability moments.4. Select a distribution method.5. Select the fallback option.6. Save your entries.


4.3.5.2.1 Availability Moment Calculation

The availability moment calculation method specifies how the system calculates when an ordered product is going to be available for sale. The default option is to calculate based on the goods receipts processing time. To use this option, table /FFIS/SCHEDULES must contain the relevant data. To copy the data into the BIF tables, you need to configure RFC module /FFIS/BIF_SCHED_INBOUND. You can then execute Process Fresh Produce BIF Data (transaction /FFIS/BIF_PROC) to copy the data to the database tables.

The following options are also available:

Derive based on Scheduling Data Table

If you use this option, the system uses the data stored in the scheduling data table, which contains the availability date and time for specific combinations of target location, source location, and scheduling group. The availability moment is defined as the availability time on the availability date.

Calculate Based on Goods Receipts Processing Time

If you use this option, the availability moments are calculated based on the delivery dates and times defined in table /FFIS/SCHEDULES and the goods receipts processing time in hours as maintained in the location product table. The system then calculates the availability moments as Delivery Moment + Goods Receipt Processing Time in Hours. The delivery moment is defined as the availability time on the availability date. Using this option, the system can differentiate between goods receipts processing times on a location product level.

To use this option, you first need to define the goods receipts processing time in hours in SAP Forecasting and Replenishment, add-on for fresh products. The system cannot import this data from your master data system, for example, SAP ECC.

4.3.5.2.2 Fallback Option

If time-based scheduling is active and no time-based scheduling data has been defined at least for the current and the next order date, the fallback option defines whether standard procurement cycles will be used as scheduling or Requirements Calculation will be skipped for relevant location products.


The following options are available:

Field Description

Use Standard Scheduling as Fallback If you select this option, the standard scheduling based on the relevant procurement cycle is used in case no time-based scheduling data has been defined at least for current order date and next order date.

Do Not Use Standard Scheduling as Fallback If you select this option, in Requirements Calculation no demand can be determined in case no time-based scheduling data has been defined at least for current order date and next order date. Optionally, exceptions can be triggered to inform about the scheduling error.

4.3.5.2.3 Distribution Methods

The distribution method specifies how the system distributes forecast values throughout the day. By default, Equal Distribution is selected.

Equal Distribution

If you select this option, the system assumes that the forecast values are equally distributed throughout the whole day.

To change the period of time over which the forecast values are distributed for specific locations, you import your location opening times into the database table /FFIS/LOC_OPENHR. When transferring location data from the master data system to the SAP Forecasting and Replenishment system, the add-on automatically stores the location opening hours in a BIF table. You then execute Process Fresh Produce BIF Data (transaction /FFIS/BIF_PROC) to copy the data to the database tables.

ExampleIf a location's opening times are defined in the table as being 08:00 to 20:00 daily, the system calculates the daily forecast values as being equally distributed over the 12 hours. If you have not imported store opening times, the system calculates the forecast values as being equally distributed over 24 hours.

Imported Intraday Selling Profiles

If you select this option, the system can distribute forecast values based on selling profiles that are imported from an external system. The intraday selling profiles will then define how your forecast values are distributed throughout the day. The data provided in intraday profiles overrides any data that you have imported for location opening hours.

To use this option, you need to implement and call BAdI /FFIS/BD_SELLING_PROF to import intraday selling profiles. SAP provides an example implementation /FFIS/BD_SELLING_PROF_IMPL for the BAdI. For more


information, see BAdI /FFIS/BD_SELLING_PROF. If you do not provide intraday selling profiles, for example, for a specific merchandise category or product, the system defaults to the equal distribution option.

This option can be used in combination with the Define Time Clusters and Merchandise Categories activity in the Customizing (transaction SPRO) under SAP Forecasting and Replenishment for Retail, add-on for fresh products Intraday Functions .

ExampleYou have a selling profile for a particular merchandise category or product, which defines the following forecast value distribution:

Time of Day Percentage of Daily Sales Sold at this Time

08:00 to 11:00 40%

11:00 to 14:00 15%

14:00 to 17:00 15%

17:00 to 20:00 30%

After importing this data into the system and selecting the Import Intraday Selling Profiles option in the Customizing, the SAP Forecasting and Replenishment system will use these values to calculate the forecast value distribution for this merchandise category or product. The system calculates the forecast value distribution for other merchandise categories and products by using equal distribution.

4.3.5.3 Activate Intraday Functions

In this Customizing activity, you activate the available intraday functions. This section contains information about the functions and their requirements.

The following functions are available:

Function Description

Time-based scheduling If this function is active, the system uses the order, delivery, and availability dates and times that are stored in table /FFIS/SCHEDULES instead of determining them from procurement cycles as in the standard solution.


Function Description

Time-based replenishment By using availability times and store opening times within SAP Forecasting and Replenishment, the system can consider intraday movements. Demand calculation is based on availability times instead of availability days only. The daily forecast values are distributed based on predefined intraday movement rates.

If this function is active, in addition to using the order, delivery, and availability dates stored in the table, the system also uses the time that is assigned to the order, delivery, and availability moments in the table.

Order proposal split This feature allows you to see a time component to the order proposal process allowing you to specify order moments rather than just order dates. Order moments are a specific time on a specific date.

If this function is active, the system will generate more than one order proposal if there are multiple order, delivery, or availability times for the same date. However, the system only allows a split of up to 2 order moments per date. The end user can see the times for order and delivery moments in the Replenishment Workbench rather than just the dates. This means you can have multiple order proposals per planning day for the same product.

The daily demand forecast is split-based on the distribution method and the availability moment is calculated based on the calculation method, both of which you select in Perform Basic Settings.

Time-Based Scheduling Requirements

You need to define scheduling groups for internal and external replenishment in the Customizing (transaction SPRO) under SAP Forecasting and Replenishment for Retail, add-on for fresh products Intraday FunctionsDefine Attributes for Scheduling Groups .

The table /FFIS/SCHEDULES must contain the relevant data. To copy the data into the BIF tables, you need to configure RFC module /FFIS/BIF_SCHED_INBOUND. You can then execute Process Fresh Produce BIF Data (transaction /FFIS/BIF_PROC) to copy the data to the database tables.

Time-Based Replenishment Requirements

You need to activate time-based scheduling and perform the necessary setup for the function. Depending on the distribution method you chose, you can either import your selling profiles into the SAP Forecasting and


Replenishment system by implementing and calling BAdI /FFIS/BD_SELLING_PROF or you can import your location opening hours. For more information, see BAdI /FFIS/BD_SELLING_PROF.

You also have to select a distribution method and availability moment calculation method. You do this in the Customizing (transaction SPRO) under SAP Forecasting and Replenishment for Retail, add-on for fresh products Intraday Functions Define Attributes for Scheduling Groups . Depending on your requirements, you could also import location opening times and define time clustering for your merchandise categories. For more information, see Perform Basic Settings.

Order Proposal Split Requirements

You need to activate time-based replenishment and perform the necessary setup for the function.

4.3.5.4 Defining Attributes for Scheduling Groups

Context

The system uses scheduling groups to classify location products that are ordered and delivered together. The groups are a technical key used to store scheduling data at an aggregated data level. You define a scheduling group by specifying a combination of master data attributes from your product, location product, and lane data. The system concatenates these fields to form the technical key and aggregate products.

In this Customizing activity, you select which master data attributes are used to define the scheduling groups in the table /FFIS/SCHEDULES and the order in which the system concatenates the attributes. You specify one combination of attributes for internal replenishment and a different one for external replenishment.

To define a scheduling group, you can use any combination of attributes from the following structures:

● /FRE/MATKEY● /FRE/MATLOC● /FRE/SOS_STY

NoteAs the content of scheduling groups is part of the key definition of the database table /FFIS/SCHEDULES, you must perform this Customizing activity before you use the groups productively.

After you have used a scheduling group productively, you must not edit this Customizing activity. If you need to change the scheduling group definition, you first need to reorganize the database content and you will probably need to migrate it.


Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data Intraday Functions Define Attributes for Scheduling Groups .

3. Select whether you are defining a group for internal or external replenishment.4. Create a new entry and specify the table and field that you want to use in the scheduling group definition.5. Specify the position of the field value in the concatenated string.6. Save your entries.

4.3.5.5 Defining Time Clusters and Merchandise Categories

In this Customizing activity, you can set time clusters for specific merchandise categories at different locations. The system uses these time clusters to determine how the forecast is distributed across a location's opening hours.

Context

NoteThese settings are used in combination with the Imported Intraday Selling Profiles distribution method that you can select in the Customizing (transaction SPRO) under SAP Forecasting and Replenishment for Retail, add-on for fresh products Intraday Functions Perform Basic Settings . If your imported selling profiles do not already specify time clusters, you can use the values you have specified here to apply them to the data that you import from your external system. The settings you make here are passed to BAdI /FFIS/BD_SELLING_PROF so that you can use them in your implementation.

Define Time Clusters

You can select how to cluster your hours by either specifying the size of the clusters for individual locations, by specifying a unique location number and location type, or by specifying one cluster size for all locations. If you want to define time clusters using this activity, you have to at least perform this activity for the All Location entry.

The number in the field represents how many hours are in one cluster. Based on this value, the system divides the business hours of a location into clusters of hours. These different clusters are used to assign a different value for each intraday movement rate of fresh products.

Any locations that do not have a specific Single Location entry use the cluster size from the All Locations entry by default.

Define Merchandise Categories

You can either define merchandise categories for all locations, or define them for individual locations by specifying a unique location number and location types.


To specify a merchandise category, select a location from the Maintain Cluster Size for Locations node and choose the Maintain Merchandise Categories for Locations node. Any merchandise categories you now specify will only be relevant for the location that you selected from the first node.

Only the merchandise categories maintained in the Maintain Merchandise Categories for Locations node consider the cluster size value stored for that location. For all other merchandise categories, the system uses equal distribution based on store opening times for the forecast distribution.

Procedure


2. Navigate to Forecasting and Replenishment, add on for Fresh Products Master Data Intraday Functions Define Time Clusters and Merchandise Categories .

3. Specify the cluster size as an integer.4. Specify a merchandise category (maximum 9 characters).

4.4 BAdI Implementations

BAdI implementations are used for SAP Forecasting and Replenishment, add-on for fresh products. In this section, the implemented BAdIs are listed, as well as some technical information and a short description of the process related to the BAdI implementation.

4.4.1 BAdI /FRE/IF_CON_BADI_007

This BAdI imports location opening hours handled by the standard location interface. The default BAdI implementation selects a WRF1 location opening hours from the system that is assigned to the Order message type in database table /FRE/BIF_MSGTP. To import any other location opening hours, you need to perform your own BAdI implementation.

Attribute Value

Enhancement Implementation /FFIS/BIF_LOC_HRS

Implementation Short Text Implementation for Interface table - location hrs

Definition Name /FRE/IF_CON_BADI_007

Interface Name /FRE/IF_EX_IF_CON_BADI_007

Method IF_CON_BADI_007_ENR_LOCATION

Implementing Class /FFIS/CL_IM_BIF_LOC_HRS


4.4.2 BAdI /FRE/UI_RWB_BADI_004

This BAdI is implemented to enhance the configuration of the Replenishment Workbench. In this BAdI, you can only add the new fields to be displayed.

This BAdI adds the following columns to the Order Item sub screen:

● Availability Time● Release Time● Order Time● Delivery Time

Attribute Value

Implementation Name /FFIS/UI_RWB_BADI004

Implementation Short Text Implementation for Intraday solution additional fields

Definition Name /FRE/UI_RWB_BADI_004

Interface Name /FRE/IF_EX_UI_RWB_BADI_004

Method GET_OPTIONAL_ORDERITEMS_FIELDS

Implementing Class /FFIS/CL_IM_UI_RWB_BADI004

4.4.3 BAdI /FRE/UI_RWB_BADI_002

This BAdI is implemented if you need to show additional fields within the Order Item subscreen of the Replenishment Workbench.

This BAdI is implemented to display the following columns on the Order Item sub screen

● Availability Time● Release Time● Order Time● Delivery Time

Attribute Value

Implementation Name /FFIS/UI_RWB_INTRDAY

Implementation Short Text BAdI Implementation for Intraday Solution for RWB

Definition Name /FRE/UI_RWB_BADI_002

Interface Name /FRE/IF_EX_UI_RWB_BADI_002

Method GET_ADDITIONAL_DATA

Implementing Class /FFIS/CL_IM_UI_RWB_INTRDAY


4.4.4 BAdI /FRE/FU_TS_BADI_007

Due to the fact that SAP Forecasting and Replenishment, add-on for fresh products allows you to calculate planned goods issues based on projected waste and shrinkage, you need to adjust the way the time series of stock projections are displayed. You make this adjustment using method GET_STOCK_PROJECTION of BAdI /FRE/FU_TS_BADI_007.

Attribute Value

Enhancement Implementation /FFIS/FU_TS_BADI_007_DEF

Implementation Short Text Customer stock projection (providing end of day stock)

Definition Name /FRE/FU_TS_BADI_007

Interface Name /FRE/IF_TS_BADI_007

Method GET_STOCK_PROJECTION

Implementing Class /FFIS/FU_CL_TS_STOCK_PROJ

4.4.5 BAdI /FRE/FU_FRP_BADI016

The two methods of this BAdI definition are used to filter DIF occurrences on a location level, as well as on location product level. This BAdI ensures that DIF occurrences that are only relevant for fresh products are not written into the SAP Forecasting and Replenishment standard files. Fresh product-specific occurrences are provided in add-on specific outbound files.

Attribute Value

Enhancement Implementation /FFIS/FRPDIF_FILTER

Implementation Short Text Filter DIFs for fresh product solution

Definition Name /FRE/FU_FRP_BADI016

Interface Name /FRE/IF_FRP_BADI016

Method FILTER_EVENTS + FILTER_PREDICTORS

Implementing Class /FFIS/CL_IM_FRPDIF_FILTER

NoteBAdI definition /FRE/FU_FRP_BADI016 is only available after importing or installing SAP Note 2080084

(Add-on for Fresh Product Forecast: BAdIs to Filter DIFs)




4.4.6 BAdI /FRE/FU_FRP_BADI_002

The method CHANGE_PARAMETERS of this BAdI is implemented to eliminate DIF identifiers from the equation parameters in the SAP Forecasting and Replenishment standard configuration file, that is, the CONFIG.INI if the DIF identifier is set as only relevant for fresh products in Customizing.

Attribute Value

Implementation Name /FFIS/FRPROD_FILTER

Implementation Short Text Filter out DIFs for CONFIG.INI only relevant for fresh products

Definition Name /FRE/FU_FRP_BADI_002

Interface Name /FRE/IF_EX_FU_FRP_BADI_002

Method CHANGE_PARAMETERS

Implementing Class /FFIS/CL_IM_FRPROD_FILTER

4.4.7 BAdI /FRE/FU_CON_BI_BADI2

If you initially transfer consumption data from BI using the SAP Forecasting and Replenishment standard process, you maintain the data source from which historical consumption data is retrieved in the SAP Forecasting and Replenishment Customizing (Alternative Transfer of Consumption from BI - Profile). To maintain the divergent data source for fresh products, add-on specific Customizing activities are required. You use methods RETRIEVE_CONSUMPTION and CHANGE_TS to overwrite the SAP Forecasting and Replenishment standard setting for the provision of BI data with fresh product-specific settings. This is also used to duplicate the received data with the new qualifier (similar to BAdI /FRE/IF_CON_BADI_003).

Attribute Value

Implementation Name /FFIS/IMP_TS_DIRECT

Implementation Short Text Import consumption data into time series appl. table

Definition Name /FRE/FU_CON_BI_BADI2

Interface Name /FRE/IF_EX_FU_CON_BI_BADI2

Method RETRIEVE_CONSUMPTION + CHANGE_TS

Implementing Class /FFIS/CL_IM_IMP_TS_DIRECT


This BAdI is called when time series data is received and before the data is entered in the buffer table. In SAP Forecasting and Replenishment, add-on for fresh products, this implementation is used to duplicate received


entries with the new qualifier before updating the buffer. The Customizing settings control which dataset with which qualifier are duplicated with the new qualifier.

Attribute Value

Implementation Name /FFIS/IMP_TS_BUFFER

Implementation Short Text Import consumption data into time series buffer



Method IF_CON_BADI_003_TSD

Implementing Class /FFIS/CL_IM_IMP_TS_BUFFER


The BAdI implementation of the method IF_CON_BADI_009_ENR_MATLOC is executed if location product data is received from the sending system. In this implementation, this determines whether new location products should be handled as fresh products based on predefined conditions and rules maintained in Customizing. For location products identified as fresh products, the default forecasting profile for fresh products is set.

Attribute Value

Implementation Name /FFIS/FRESHITM_IDENT

Implementation Short Text Identifies whether a product is a fresh item



Method IF_CON_BADI_009_ENR_MATLOC

Implementing Class /FFIS/CL_IM_FRESHITM_IDENTIFY

4.5 BAdI Definitions

BAdI definitions are used for SAP Forecasting and Replenishment, add-on for fresh products. In this section these BAdIs are listed, as well as some technical information and a short description of the process related to the BAdI implementation.


4.5.1 BAdI /FFIS/BD_SELLING_PROF

To import intraday selling profiles from an external system, you must be able to configure the interface between the SAP Forecasting and Replenishment system and the external system. You use this BAdI to pull selling profiles from the external source system. This BAdI is called by the report /FFIS/INTRADAY_IMP.

Attribute Value

Enhancement Implementation /FFIS/BD_SELLING_PROF_IMPL

Implementation Short Text PPF selling profile BAdI import

Definition Name /FFIS/BD_SELLING_PROF

Interface Name /FFIS/IF_BD_SELLING_PROF

Method IMPORT_SELL_PROFILE

Implementing Class /FFIS/CL_SELLING_PROF_IMPL


5 Security Information for SAP Forecasting and Replenishment, add-on for fresh products

SAP Forecasting and Replenishment, add-on for fresh products is based on SAP Forecasting and Replenishment. Therefore, the related guides also apply to this software.

For more information about security-related topics, see the following resources:

Topic Link

General and F&R Security https://www.sap.com/corporate/en/company/security.html

https://help.sap.com/viewer/product/security_guides_for_scm_products/scmsecurity/en-US

SAP Notes http://service.sap.com/notes

http://service.sap.com/securitynotes

SAP NetWeaver Security https://help.sap.com/viewer/p/SAP_NETWEAVER_SECURITY

NoteNo new authorizations or roles are used by SAP Forecasting and Replenishment, add-on for fresh products.

SAP Forecasting and Replenishment, add-on for fresh products Administrator GuideSecurity Information for SAP Forecasting and Replenishment, add-on for fresh products P U B L I C 83

http://help.sap.com/disclaimer?site=https%3A%2F%2Fwww.sap.com%2Fcorporate%2Fen%2Fcompany%2Fsecurity.html

http://help.sap.com/disclaimer?site=https%3A%2F%2Fwww.sap.com%2Fcorporate%2Fen%2Fcompany%2Fsecurity.html



http://help.sap.com/disclaimer?site=http%3A%2F%2Fservice.sap.com%2Fnotes

http://help.sap.com/disclaimer?site=http%3A%2F%2Fservice.sap.com%2Fsecuritynotes

https://help.sap.com/viewer/p/SAP_NETWEAVER_SECURITY

https://help.sap.com/viewer/p/SAP_NETWEAVER_SECURITY

6 Operating SAP Forecasting and Replenishment, add-on for fresh products

Designing, implementing, and running your SAP applications at peak performance, 24 hours a day, is vital to ensure business success. This chapter contains important information about the operation of SAP Forecasting and Replenishment, add-on for fresh products.

The add-on is based on SAP Forecasting and Replenishment. Therefore, the general operations information in related operations guides also applies to SAP Forecasting and Replenishment, add-on for fresh products.

The operations information specific to SAP Forecasting and Replenishment, add-on for fresh products is described in the following chapters. The following areas are covered:

● Monitoring● Administration and Management

6.1 Monitoring

6.1.1 Alert Monitoring

Messages raised in add-on-specific steps when running FRP are displayed in the SAP Forecasting and Replenishmentstandard exception workbench. To be able to display messages in the exception workbench, you need to make the Customizing settings as describe in Managing Exceptions [page 21].

6.1.2 Error Logs

Log files with errors and information about what occurred when executing the modules as part of FRP are written to folder./frp/<client>/<site-GUID>/log/ffi.

You can configure the log level with the following files:

● logback-cleanup.xml● logback-enhancedforecast.xml● logback-projectedwaste.xml

All add-on relevant log files are located next to the standard FRPs in /sapmnt/<SID>/global/frp/bin/FFI/lib.


Operating SAP Forecasting and Replenishment, add-on for fresh products

The valid log levels are:

LEVEL Description

ERROR The ERROR level designates error events which may or may not be fatal to the application.

WARN The WARN level designates potentially harmful situations.

INFO The INFO level designates informational messages highlighting the overall progress of the application.

DEBUG The DEBUG level designates informational events of lower importance.

TRACE The TRACE level designates informational events of very low importance.

6.1.3 Background Job Monitoring

There is no background job monitoring specific to the add-on. You can also use theSAP Forecasting and Replenishment standard transaction Check of Location Status (/FRE/FRP_LOC_STATUS) to monitor the status of the FRP run.

6.2 Administration and Management

6.2.1 Starting and Stopping

With SAP Forecasting and Replenishment, add-on for fresh products, the FRP run is executed with additional fresh product-specific steps. If you are using the dispatcher for the F&R processor, you need to enhance the relevant dispatcher profiles in Customizing with additional tasks. If the FRP dispatcher is deactivated and the SAP Forecasting and Replenishment standard report /FRE/FRP_MID_BASIC is used for the FRP run instead, you must use the add-on report /FFIS/FRP_MID_BASIC. This report also executes the fresh product-specific steps during the FRP run.

6.2.2 Daily Consumption Load and Data Initialization

Report /FFIS/INIT_NEW_FRESH_PRODUCTS allows you to initialize existing location products when someone has manually assigned a fresh product-relevant forecasting profile. Therefore, you need to activate change

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documents for location products in the Customizing (transaction SPRO) Advanced Planning and Optimization Master Data Product Activate Change Documents .

In the Location Product dialog, select Location Product.

All other details about the technical configuration are described in the installation notes mentioned in Required SAP Notes [page 5].

The report /FFIS/INIT_NEW_FRESH_PRODUCTS in the step Process Change Documents loads the daily consumption history and initializes the data.

You can also use the step Delete Change Documents for reorganizing change documents.

6.2.3 Load Balancing and Scalability

SAP Forecasting and Replenishment, add-on for fresh products does not replace any steps of the FRP run. Instead, with the add-on, additional data needs to be stored and processed by the calculation modules. For example, you should store daily consumption data for about two years. In addition, the calculation of the fresh product-specific forecast, as well as the calculation of projected waste and shrinkage, is added to the standard FRP run. As a result, you need to consider load balancing and scalability when installing this add-on. Using this add-on may require an increase in system resources.

NoteSizing information related to this add-on is available in the sizing guide for SAP Forecasting and Replenishment.


Operating SAP Forecasting and Replenishment, add-on for fresh products

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