enterprise inventory and service level optimization analytics

Enterprise Inventory and Service Level Optimization Analytics

User Guideversion 6.10SP3P5

© 2016 SAP SE, All Rights Reserved.

This manual, as well as the software described herein, is furnished under license and may be used or copied only within the terms of such license. The content of this manual is furnished for informational use only, is subject to change without notice, and should not be construed as a commitment by SAP. SAP assumes no responsibility or liability for any errors or inaccuracies that may appear in this documentation. Except as permitted by license, no part of this document may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, recorded, or otherwise, without the prior written permission of SAP.

Revision 20161208

3

Table of contents

IntroductionAbout this guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Chapter 1: Getting StartedAccessing EIS Analytics through InfoView . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

EIS Analytics application overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Analytics Replenishment Workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Data Mart View . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Latest Successful Replenishment Run View . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Chapter 2: Working with Legacy EIS Analytics dashboardsUsing the analysis drop-down menu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Using attribute slicers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Viewing DIM outputs by Lag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Reviewing Analytics Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Demand Analytics data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Demand History data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Supply Analytics data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Reviewing Performance Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Reviewing Performance Overview data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Reviewing Target Performance data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Enterprise Inventory and Service-Level Optimization Analytics User Guide

4

Reviewing Scenario Comparison data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Reviewing inventory scenario comparison data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

Reviewing Cost Curve data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Reviewing Fix the Mix data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Reviewing Demand Scenario Comparison data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Chapter 3: Working with new EIS Analytics dashboardsUsing the analysis dashboards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Using attribute slicers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Viewing DIM outputs by Lag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Reviewing Analytics Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Demand Analytics data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Demand History data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Supply Analytics data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Reviewing Performance Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Reviewing Performance Overview data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

Reviewing Target Performance data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

Reviewing Scenario Comparison data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

Reviewing inventory scenario comparison data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

Reviewing Cost Curve data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

Reviewing Fix the Mix data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

Reviewing Demand Scenario Comparison data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

Chapter 4: Working with WebI ReportsReviewing the Demand Summary Report. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

Reviewing the Target Performance Report. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

Reviewing the Scenario Comparison Detail Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

Reviewing the Cost Curve Detail Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Creating a new WebI report from an EIS Analytics report . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Creating a new WebI from the EIS Analytics Universe. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

5

Introduction

he SAP Enterprise Inventory and Service-Level Analytics (EIS Analytics) application lets you monitor supply chain performance through intuitive visualizations of key product indicators and metrics derived from Enterprise Inventory and Service-Level applications.

With EIS Analytics, you can compare inventory targets based on your supply chain's global performance around key performance indicators. The EIS Analytics application design takes advantage of SAP's Business Objects Edge solutions to provide reporting tools, data-mining, filtering, aggregation and support for root-cause analysis.

About this guideThis document describes how to use the SAP Enterprise Inventory and Service-Level Analytics (EIS Analytics) application. This book accompanies the EIS Analytics software and provides an overview of this product and the procedures for performing key tasks.

This guide contains the following chapters:

• Chapter 1: Getting Started

• Chapter 2: Dashboard Fundamentals

• Chapter 3: WebI Fundamentals

T


6

Notation conventionsThis section describes notation and formatting conventions used throughout the documentation. These conventions have been defined and are used to provide consistency and clarity as well as to aid visual recall of information.

Convention Example

Any item that appears literally on the computer screen such as a text field label, a menu name, or a button label is printed in boldface.

Information that should be entered exactly as shown is also printed in boldface.

• click Go

• click LOGOUT

• Type 2 in the Factor by text box.

Keyboard keys are indicated by the text of the key face displayed in upper case and small caps.

Key combinations include multiple keys. A plus sign connects names of keys that should be pressed simultaneously.

• ALT

• SHIFT

• CTRL+ALT+DELETE

• SHIFT+S

Information you enter that is specific to your own circumstances, such as your user name or a specific unit cost, is designated by an italic variable name.

Italic text is also used to indicate a new term or concept.

• Type User Name and press ENTER.

• lead time, also called total lead time

This symbol indicates information that emphasizes or supplements important points of the main text.

This symbol indicates a note of caution. Items that warrant a note of caution include warnings that could protect against a loss of data or other undesired behavior.

Table 1: Notation conventions used in this document

7

Chapter 1: GettingStarted

ou can run the EIS Analytics module using the EIS portal interface to access the dashboard and WebI reports relating to your supply chain data. You can also run EIS Analytics directly through the InfoView application.

This section provides instructions on how to run EIS Analytics and an overview of the EIS Analytics dashboard functionality. :

Accessing EIS Analytics through the EIS portal.

To access EIS Analytics through the EIS portal, do the following:

1. Log on to the SAP EIS application.

2. From the Portal menu, select Analytics

Note: Refer to your SAP BusinessObjects documentation and associated online help for specific information on the functionality associated with the InfoView web interface.

Note: For releases after 6.10SP3, if you access EIS Analytics through the EIS portal, you will only be able to access the legacy dashboards. To use the updated dashboards, please Run EIS Analytics directly through the InfoView application.

Y


8

The EIS Analytics dashboard scenario selection screen appears, as shown in Figure 1-1.

Figure 1-1 EIS Analytics Scenario Selection screen

3. Select a scenario from the Scenario Selection screen.

4. Click Go.

The EIS Analytics dashboard appears, as shown in Figure 1-2.

Chapter 1: Getting Started

9

Figure 1-2 EIS Analytics dashboard

Accessing EIS Analytics through InfoViewTo access EIS Analytics through the InfoView application, do the following:

1. Log on to the InfoView portal.

2. Under Navigate, click Document List.

3. Expand the Public Folders.

4. Expand the EIS Dashboards folder.

There are three subfolders that contain the EIS dashbords:

• Analytics

•BIAS Dashboard, Bias_dashboard_perf.xlf

•Demand History Dashboard, DIM History_perf.xlf

•Forecast Error Dashboard, Forecast_Error_dashboard_perf.xlf

•Intermittency Dashboard, Intermittency_dashboard_perf.xlf


10

•Supply Analytics, Supply_Analytics_perf.xlf

• Performance

•Performance Overview Dashboard, Perf Overview_perf.xlf

•Target Performance Dashboard, Target_Performance_perf.xlf

• Scenario Comparison

•Demand Comparison Dashboard, AIM Demand Comparison_perf.xlf

•Cost Curve Dashboard, Cost_Curve_perf.xlf

•Fix the Mix, Fix_The_Mix_perf.xlf

•Scenario Comparison, Scenario_Comparison_perf.xlf

5. Double click the dashbord you want to view

The dashboard displays.

EIS Analytics application overviewThe EIS Analytics application consists of a series of dashboards and reports that support planners with analysis tools to supply chain data generated by SAP EIS. The EIS Analytics dashboards focus on three key areas:

• Improved demand analytics & reporting

• Inventory projections

• Scenario comparisons

The EIS Analytics reporting design includes additional data structures that facilitate reporting, sorting and filtering, association with attributes, drill-through, and aggregation of supply chain data. EIS Analytics includes a semantic layer on top of these data structures to allow end-users to create their own reports.

This layer was developed in the SAP Business Objects universe, which serves as the single point of access for business intelligence reporting. The EIS Analytics universe supports all WebI reporting needs, including EIS Analytics reports, ad-hoc reporting and dashboards data source reports.

Analytics Replenishment WorkflowEIS Analytics, in conjunction with MIPO, can be used as part of a replenishment workflow. When inventory depletes below a target level, EIS determines how much and at what locations the inventory needs to be replenished. Replenishment requires computing the total supply and demand at a stocking point and determining if the remaining stocking level triggers a reorder to replenish the stocking


11

point. EIS will recommend ordering up to the calculated total required inventory position, while respecting any batch size requirements for the item.

A high level overview of how replenishment functions is as follows:

Users run MIPO optimization scenarios and the results are transferred to Data Store. Once in DataStore, an ETL runs and transfers the scenario information to the Data Mart.

Several quality checks run on the data, and then the replenishment ETL runs, which calculates whether a replenishment order should be made, based on current and planned inventory and demand.

Data tables are updated and informational emails are sent, and then the order recommendations (if any) are ready to be retrieved from EIS Analytics by the user’s system. The orders can be for current or future dates.

Note: There are two replenishment batch jobs in EIS Analytics that provide the replenishment functionality. J_SmartOps_Replenishment is a job that can be scheduled to run every five minutes and ensures another instance of the job is not running and the or loading data into the Data Mart. J_SmartOps_Replenishment_Manual is a manual job that does not check to see if another replenishment job is running. In addition, you can configure the jobs to send email in the event of a successful or failed replenishment run. See the EIS Analytics Installation Guide for information.

New data moves into Data Mart

MIPO runs and Data Store is updated

Quality check on the data

Run Replenishment Calculation

Update tables

Send success or failure emails

PO recommendations ready for retrieval


12

Replenishment only runs for active item/location pairs. If an item/location is inactive for the base period of the run, replenishment orders will not be generated for that item/location.

If you have allocation configured (have the Is Allocation Enabled flag set to Y) orders are generated, regardless of the allocation quantity.

Data Mart ViewThe following information can be accessed through the associated Data Store table:

Latest Successful Replenishment Run View(VW_DM_REPLENISH_ORDERS_LATEST)

Note: You can examine the replenishment recommendations by reading the view VW_DM_REPLENISH_ORDERS_LATEST.

Column Name Description

IS_ALLOCATION_ENABLED Whether allocation is enabled. The flag defaults to N, unless specifically set to Y. (That is, any character, including null, except Y is considered to be N.)

Replenishment orders are generated in all cases, but this view will only display orders that have an allocation flag set to N.

RUN_NUMBER A unique number associated with the run.

RUN_DATE The timestamp for the run.

ORDER_ID A unique identifier for the order.

ORDER_QTY The order quantity.

ORDER_DATE The date of the order.

ITEM_NAME Unique value to identify an item in the supply chain.

ITEM_KEY Unique value for each item defined in EIS MIPO.

TARGET_LOCATION_NAME Target location name associated with the demand stream.

TARGET_LOCATION_KEY Unique value to identify the target location record associated with the demand stream.

Table 1-1 Latest Replenishment Run view


13

SOURCE_LOCATION_NAME Source location name associated with the demand stream.

SOURCE_LOCATION_KEY Unique value to identify the source location record associated with the demand stream.

PO_NUMBER Purchase order number.

PERF_TRCK_GRP Performance tracking group in the Data Mart scenario.

Column Name Description

Table 1-1 Latest Replenishment Run view


14

15

T

Chapter 2: Workingwith Legacy EIS

Analytics dashboards

his chapter provides instructions for using EIS Analytics dashboards to compare and approve inventory targets based on your supply chain's global performance around key performance indicators.

Using the analysis drop-down menuUse the analysis drop-down menu to select the specific dashboard you want to view.

EIS Analytics dashboards consist of three selections that focus on three key areas of supply chain analysis:

• Analytics

• Performance



16

EIS Analytics dashboards display data using gauges, histograms, and tables. Six customizable slicers, anchored at the top of the dashboard, let you filter data based on attributes defined in your supply chain.

Each section accessible from the analysis drop-down menu also contains tabs to allow you to access individual dashboards.

By default, the Demand tab on the Analytics dashboard displays; the other two dashboard sections and corresponding tabs can be accessed by clicking on the drop-down menu and selecting the corresponding sections, then clicking the desired dashboard tab.

Figure 2-1 Analytics dashboard

For all EIS Analytics dashboards, the selected scenario name is shown at the bottom, along with the total number of demand streams in the selected scenario.

Chapter 2: Working with Legacy EIS Analytics dashboards

17

Using attribute slicersYou can use the attribute slicers to analyze the overview data. The following slicers are available by default:

• Material

• Material Class

• Location

• Planner Code

• Business Unit

• Region

You can also customize your attribute slicers. Refer to Chapter 3: Maintaining the EIS Analytics Dashboard in the EIS Analytics Installation Guide for more information.

To filter scenario data using an attribute slicer:

1. Click on the slicer you wish to use to open its drop-down list.

2. Select an attribute category from the list

3. Repeat steps 1 and 2 for other slicers, if necessary.

4. Click Apply.

Viewing DIM outputs by Lag For scenarios with DIM outputs, you can view those outputs based on DIM’s lag calculation feature by clicking on the Lag drop-down and selecting one of the corresponding lags associated with the scenario.

Reviewing Analytics DataThe Analytics dashboards display analytics-related data to support sales and operations planning, including demand analytics and demand history.

There are two analytics-related dashboards available, via tabs on the top left of the dashboard:

• Demand Analytics

• Demand History

• Supply Analytics

Note: Clicking Reset Filters returns slicers back to their default settings of All and updates all gauges, histograms and tables to show all scenario data.


18

Demand Analytics dataThe Demand Analytics dashboard supports planner analysis through the review of Forecast Error, Bias and Intermittency data. This dashboard includes data drill-down capability by filtering scenario data based on specific item and location attributes, as well as demand stream-specific characteristics.

With the Demand Analytics dashboard, you can drill down to a specific forecast error, bias or intermittency range, all the way down to a single demand stream and its characteristics.

The Demand Analytics dashboard offers a graphic overview of the summed average for three indicators of demand analysis:

• Forecast Error

• Bias

• Intermittency

By default, the Demand tab on the Analytics dashboard displays when you open EIS Analytics. However, you can return to this dashboard any time by selecting Analytics from the analysis drop down menu and clicking the Demand tab.

Drilling down to Forecast Error detailsThe Forecast Error gauge displays the average CV value for the scenario demand streams. The bar graph in the associated histogram represent the demand stream groupings based on their CV range. You can mouse over the histogram bars to see tool tip information related to the number of demand streams within the associated CV range.

Figure 2-2 Forecast Error overview

Click >>View Forecast Detail view the Forecast Error Details dashboard. Use this dashboard to analyze forecast error details for the selected scenario. The dashboard includes the Forecast Error overview gauge and histogram at the top of the screen. The Item-Location table is located at the bottom left of the screen, while the Forecast vs. Sales chart appears on the bottom right of the screen.

Initially, the Forecast Error Details table and chart do not display data. Click the Show Top 20 link to see the 20 overall worst performing demand streams, based on forecast error, in the Item-Location table. Click on a demand stream record from the table to see its associated Forecast vs. Sales chart data. Click on the Demand Summary Report link to see all the data associated with the scenario.

You can also click on any bar in the overview histogram to drill down to its associated demand stream records in the Item-Location table, initially displaying the 20 worst performing demand streams


19

associated with the selected CV range. For scenarios with more than 20 demand streams, you will see a message to “Select the Demand Summary Report link below to see more data.”

Figure 2-3 Forecast Error Details dashboard

By clicking on any record in the Item-Location table, you will see its associated forecast vs. sales data. This information is initially displayed based on the lowest granularity of time-varying data in the scenario (e.g., 26 Weeks). You can change the display granularity by clicking the associated drop-downs at the top left of the graph. (Note: The numerical spinner arrows may be sensitive when large values are displayed. You can also type numerical values into the field).

You can use the Attribute slicers to filter scenario data. You also have the option of changing the Forecast vs Sales chart to display in Dollars by clicking Dollars.

For scenarios with multiple lags, you can click the Lag drop-down and select one of the corresponding lags associated with the scenario to see its associated Forecast vs. Sales chart data.

You can return to the Demand Analytics overview dashboard by clicking Close.

You have the option to change the current scenario by clicking Actions in the top right corner of the dashboard, and selecting Change Current Scenario.


20

Drilling down to Bias detailsThe Bias gauge displays the percentage of biased demand streams for the scenario. The bar graph in the associated histogram represent the demand stream groupings based on their bias determination. You can mouse over the histogram bars to see tool tip information related to the number of demand streams within the associated bias category.

Figure 2-4 Bias overview

Click >>View Forecast Detail view the Bias Details dashboard. Use this dashboard to analyze bias details for the selected scenario. The dashboard includes the Bias overview gauge and histogram at the top of the screen. The Item-Location table is located at the bottom left of the screen, while the Forecast vs. Sales chart appears on the bottom right of the screen.

Initially, the Bias Details table and chart do not display data. Click the Show Top 20 link to see the 20 overall worst performing demand streams, based on bias, in the Item-Location table. Click on a demand stream record from the table to see its associated Forecast vs. Sales chart data. Click on the Demand Summary Report link to see all the data associated with the scenario.

You can also click on any bar in the overview histogram to drill down to its associated demand stream records in the Item-Location table, initially displaying the 20 worst performing demand streams associated with the selected bias. For scenarios with more than 20 demand streams, you will see a message to “Select the Demand Summary Report link below to see more data.”


21

Figure 2-5 Bias Details dashboard

By clicking on any record in the Item-Location table, you will see its associated forecast vs. sales data. This information is initially displayed based on the lowest granularity of time-varying data in the scenario (e.g., 26 Weeks). You can change the display granularity by clicking the associated drop-downs at the top left of the graph (Note: The numerical spinner arrows may be sensitive when large values are displayed. You can also type numerical values into the field).






22

Drilling down to Intermittency detailsThe Intermittency gauge displays the percentage of demand streams for the scenario classified as Intermittent. The bar graph in the associated histogram represent the demand stream groupings based on their intermittent demand interval determination. You can mouse over the histogram bars to see tool tip information related to the number of demand streams within the associated intermittence data.

Figure 2-6 Intermittency overview

Click >>View Forecast Detail view the Intermittency Details dashboard. Use this dashboard to analyze intermittency details for the selected scenario. The dashboard includes the Intermittency overview gauge and histogram at the top of the screen. The Item-Location table is located at the bottom left of the screen, while the Forecast vs. Sales chart appears on the bottom right of the screen.

Initially, the Intermittency Details table and chart do not display data. Click the Show Top 20 link to see the 20 overall worst performing demand streams, based on intermittency, in the Item-Location table. Click on a demand stream record from the table to see its associated Forecast vs. Sales chart data. Click on the Demand Summary Report link to see all the data associated with the scenario.

You can also click on any bar in the overview histogram to drill down to its associated demand stream records in the Item-Location table, initially displaying the 20 worst performing demand streams associated with the selected intermittency data. For scenarios with more than 20 demand streams, you will see a message to “Select the Demand Summary Report link below to see more data.”


23

Figure 2-7 Intermittency Details dashboard

By clicking on any record in the Item-Location table, you will see its associated forecast vs. sales data. This information is initially displayed based on the lowest granularity of time-varying data in the scenario (e.g., 26 Weeks). You can change the display granularity by clicking the associated drop-downs at the top left of the graph. (Note: The numerical spinner arrows may be sensitive when large values are displayed. You can also type numerical values into the field).






24

Demand History dataThe Demand History dashboard supports planner analysis through a historical review of forecast error and bias. This allows you to determine whether forecast trends are improving over time.

This dashboard includes data drill-down capability by filtering scenario data based on specific item and location attributes, as well as demand stream-specific characteristics.

The Demand History dashboard offers a graphic overview of the history of two demand analytics, to show how they have changed over a period of a year:

• Forecast Error Improvement

• Bias Improvement

Note: To ensure that all EIO base scenarios are properly handled by the EIS Analytics performance tracking group feature, these scenarios must use the following naming convention:

<supply chain name>#<unique scenario name>

Ensure that your supply chain files follow this naming convention when they are transferred to the EIS application.

Supply chain names may contain spaces before the supply chain name or before the # symbol, but they are ignored by the system. As a result, a performance tracking group (supply chain/scenario pair) called abc #scenario is seen as being the same group as abc#scenario.


25

To view the Demand History dashboards, select Analytics from the analysis drop-down menu and click Demand History tab.

Figure 2-8 Demand History dashboard

Forecast Error Improvement detailsThe Forecast Error Improvement gauge displays the current average CV value for the scenario demand streams. The bar graph in the associated histogram displays the current and historical average CV value for the scenario, with the bar on the right representing the current average CV value.

The current bar changes color to indicate whether the trend is improving from one month ago or not. When the trend improves, the current bar displays green. When the trend worsens, the current bar

Note: The dashboard displays a year’s worth of historical data, in increments. If the scenario does not contain a full year’s worth historical data (or more), only the periods available will be displayed. If there is no historical data, the dashboard only displays current information.


26

displays orange. If there is no historical data for the previous month or no change in the average CV, the bar displays blue.

The first six months of historical data is displayed on a monthly basis. After six months, only the 9th and 12th month’s prior averages are shown. The oldest data displays on the left, with the newest data displaying on the right.

Figure 2-9 Forecast Error Improvement detail

Forecast Bias Improvement detailsThe Forecast Error Bias gauge displays the percentage of biased demand streams for the scenario. The bar graph in the associated histogram displays the current and historical bias percentage for the scenario, with the bar on the right representing the current bias percentage.

The current bar changes color to indicate whether the trend is improving. When the trend improves, the current bar displays green. When the trend worsens, the current bar displays orange. If there is no historical data for the previous month or no change in the average bias, the bar displays blue.


Figure 2-10 Forecast Bias Improvement detail


27

Supply Analytics dataThe Supply Analytics dashboard supports planner analysis through the review of Lead Time Error and Planned Lead time data. This dashboard includes data drill-down capability by filtering scenario data based on specific item and location attributes, as well as supply stream-specific characteristics.

The Supply Analytics dashboard offers a graphic overview of the summed average for two indicators of supply analysis:

• Lead Time Error

• Delta to Planned Lead Time

To view the Supply Analytics dashboards, select Analytics from the analysis drop-down menu and click the Supply Analytics tab..

Figure 2-11 Supply Analytics dashboard

Lead Time Error DetailsThe Lead Time Error gauge displays the average CV value for the scenario supply paths. The bar graph in the associated histogram represent the supply path groupings based on their CV range. You


28

can mouse over the histogram bars to see tool tip information related to the number of supply paths within the associated CV range.

Figure 2-12 Lead Time Error

Delta to Planned Lead TimeThe Delta to Planned Lead Time gauge displays the percent of supply chains with non-zero deltas to lead time. The bar graph in the associated histogram represent the supply path groupings based on their delta to planned lead time. You can mouse over the histogram bars to see tool tip information related to the number of supply paths within the associated delta to planned lead time category.

Figure 2-13 Delta to Planned Lead Time

Reviewing Performance DataThe Performance dashboards display performance-related data to support sales and operations planning, including changes in inventory targets, inventory performance, service level performance and target performance.

There are two performance-related dashboards available, via tabs on the top left of the dashboard:

• Performance Overview

• Target Performance

To view the Performance dashboards, select Performance from the analysis drop-down menu. By default, the Performance Overview dashboard displays.


29

Figure 2-14 Performance Overview dashboard


30

Reviewing Performance Overview dataThe Performance Overview dashboard (Figure 2-14) highlights the performance of the supply chain and identifies areas that may be of concern. The dashboard offers a graphic overview for three indicators of performance:

• Inventory Target Alerts

• Inventory Performance

• Periods of Coverage

You can return to the Performance Overview dashboard if you navigate to other Performance dashboards by clicking the Overview tab.

Use the Attribute slicers to filter scenario data, if necessary

You have the option to change scenarios by clicking Actions in the top right corner of the dashboard and selecting a new scenario from the Scenario Selection screen.

Inventory Target Alerts DetailsThe Inventory Target Alerts graphic identifies the largest changes in safety stock when comparing the current inventory with the previous inventory. The Inventory Target Alert gauge displays the percent of item-locations where the safety stock change percentage is above a threshold (15% by default).

Figure 2-15 Inventory Target Alerts






31

The table lists the top ten item-locations where safety stock inventory has changed, ordered from greatest amount of change to least amount of change. Each row contains the following information:

• Item – Item name

• Location – Item location

• Previous SS – First four-period average safety stock from previous period

• New SS – First four-period average of safety stock from current period

• SS Delta % – Percentage change in safety stock from previous period to current period

• Forecast – First four-period average forecast, in units

Inventory Performance DetailsThe Inventory performance graphic displays a historical overview of how well inventory targets have been met. The Inventory Performance gauge displays the percent of item-locations that are between the minimum and maximum inventory values in the performance tracking groups. The greater the percentage, the more item-locations were in range.

The associated histogram shows the past twelve periods and the percentage of inventory that was in range (green), in excess (yellow), or a shortage (red).


Periods of Coverage DetailsThe Periods of Coverage graphic displays a historical overview of the number of periods covered by the amount of inventory during that period. The Periods of Coverage gauge displays the average periods of coverage for the current period. The gauge needle points to green when the average periods of coverage is in-range (between six and ten periods, by default) and red when the average periods of coverage is too great or too small (less than six or greater than ten periods, by default).


32

The associated histogram shows the historical periods of coverage, with the bar on the right representing the current average periods of coverage.

Figure 2-17 Periods of Coverage

Reviewing Target Performance dataThe Target Performance dashboard supports the inventory planning part of sales and operations planning (S&OP). The dashboard was designed to provide demand, supply and inventory target data at a glance, at a single stocking point, or for an item across all locations, in both a tabular format and a histogram chart.

Click the Target Performance tab to access the Target Performance dashboard. You can shift between the histogram and tabular views by clicking the Chart tab and Table tab respectively.






33

This dashboard includes slicers for data drill-down capability by filtering scenario data based on specific item and location attributes, as well as demand stream-specific characteristics.

Figure 2-18 Target Performance chart

The Inventory Target Performance dashboard provides a graphic overview of the following target performance indicators:

• Total supply

• Net expected demand

• Minimum inventory target

• Ending on hand inventory

• Maximum inventory target

The performance tracking chart allows filtering by date. To filter, move the left or right endpoint of the slider that is located below the X axis of the chart. You can also “grab” the slider in the middle by holding down the mouse button and dragging the whole slider left or right.


34

The Target Performance dashboard also offers a table with the following time-varying Supply targets:

• Vendor-managed inventory

• Beginning on hand inventory

• Supply (actual)

• Supply (projected)

• Total Supply.

Figure 2-19 Inventory Target Performance table

The following time-varying Demand targets are also displayed for the selected scenario:

• Forecast

• Shipments

• Orders





35


• Inventory shortage

• Inventory excess

• Demand CV

You can mouse over a chart element to display associated definition content in the notification area at the bottom of the screen.

To adjust the Backward Planning Weeks or Forward Planning Weeks setting:

1. Click the associated value up arrow to increase the weeks value, or down arrow to decrease the value.

2. Click Go.

3. Use the Attribute slicers to filter scenario data, if necessary.

You have the option to change the current scenario by clicking Change the Current Scenario in the top right corner of the dashboard.

Reviewing Scenario Comparison dataThe Scenario Comparison dashboards supports what-if analysis of scenarios. These dashboard includes data drill-down capability by filtering scenario data based on specific item and location attributes, as well as demand stream-specific characteristics.

There are four Scenario Comparison dashboards:

• Inventory

• Cost Curve

• Fix the Mix

• Demand Analytics Comparison

To view the Scenario Comparison dashboards:

1. Select Scenario Comparison from the analysis drop-down.

Note: The inventory excess and inventory shortage values at a stocking point are summed separately (not netted) when aggregated across nodes to show how much excess and shortages exist at a particular time period.

Note: All target performance dashboard data can be viewed as either units or dollars by clicking Units or Dollars.


36

The Scenario Comparison selection screen appears, as displayed in Figure 2-20.

2. Select a scenario record from the table and click Compare.

Figure 2-20 Scenario Comparison selection screen

By default, the Inventory Scenario Comparison dashboard opens.

Reviewing inventory scenario comparison dataThe Inventory Scenario Comparison dashboard provides a summary stacked bar chart with side-by-side comparisons of the following key indicators:

• Safety stock

• Cycle stock

• Prebuild stock

• Pipeline stock

• Merchandising stock


37

You can mouse over the stacked bar graph segments to see associated data. Also, you can hide any key indicator bar graph segment by clicking its associated check box. Such a change may be reflected in the summary totals, as indicated by the Y axis unit values.

Figure 2-21 Scenario Comparison dashboard

The Scenario Comparison dashboard also displays a line graph chart with side-by-side comparisons of trending activity for the key indicators. By clicking a specific key indicator’s bar graph segment, you can see comparison data for the selected indicator in the trend graph.

Alternatively, you can switch to an inventory total data view by clicking on the Show Inventory Total check box.

The bottom of the Scenario Comparison dashboard consists of tabular data organized by the following tabs:

• Scenario Comparison Summary

• Inventory Total

• Safety Stock

• Cycle Stock

• Prebuild Stock


38

• Pipeline Stock

• Merchandising Stock

The Scenario Comparison Summary table provides an aggregation value for each key indicator in both the current scenario and the comparison scenario, along with the Delta value and percentage difference.

The individual key indicator tabs provide time-varying data for both scenarios in the same comparison format.

You have the option to change the current scenario or comparison scenario by clicking the corresponding links in the top right corner of the dashboard.

You can click Swap Scenarios to switch the selected scenario with the comparison scenario to quickly see the inverse of the comparison changes.

Reviewing Cost Curve dataThe Cost Curve dashboard is designed to quickly determine how potential inventory investment will change based on using up to five different service levels for a given data set. This dashboard provides the ability to evaluate service level changes before committing to an inventory investment in line with planning expectations.

The Cost Curve dashboard supports service level analysis for up to five scenarios. This dashboard includes data drill-down capability by filtering scenario data based on specific item and location attributes, as well as demand stream-specific characteristics.

Note: All scenario comparison dashboard data can be viewed as either units or dollars by clicking Units or Dollars.






39

Figure 2-22 Cost Curve Scenario Selection screen

To view the Cost Curve dashboard:

1. If you have not selected Scenario Comparison from the analysis drop-down menu, Select Scenario Comparison.

2. Click the Cost Curve tab.

The Cost Curve dashboard appears without any data.

3. Click Actions, then Select Cost Curve Scenarios from the drop-down menu.

The Cost Curve Scenario Selection screen appears (Figure 2-22).

4. From the list of Scenarios Available on the left-hand side of the Scenario Selector, select up to five scenarios.

If you want to select multiple scenarios at once, press the SHIFT or CTRL key while selecting the scenarios. The SHIFT key allows you to select a co-joined list of scenarios while the CTRL key allows you to select multiple separate scenarios.

5. Click the right arrow (>) button to move the scenarios to the Scenarios Selected list on the right-hand side of the Scenario Selector. Click the left arrow (<) key to remove scenarios.

You can also drag and drop individual or multiple scenarios from one side of the Scenario Selector to the other.


40

6. Click Go.

The Cost Curve dashboard shows line graphs for the following:

• EIO Target costs

• Projected Inventory costs

The EIO target cost value is derived from adding the scenario’s safety stock cost value and the cycle stock cost value for the selected time period

The projected inventory cost value is based on the scenario’s end on-hand (EOH) inventory cost value.

Note: You can reorder the scenarios in the Scenario Selector; however, the Cost Curve dashboard automatically sorts the first five listed scenarios based on service level, with Scenario 1 having the lowest service level and scenario 5 the highest. The scenario names are displayed at the top of the graph below the scenario number labels.

If you select more than five scenarios, only the first five in the list are used.


41

You can mouse over the line graphs to see associated data. Also, you can hide any line graph segment by clicking its associated check box.

Figure 2-23 Cost Curve dashboard

To adjust the Forward Planning Weeks setting:


2. Click Go.


You have the option to change scenarios by clicking Actions in the top right corner of the dashboard and selecting new scenarios from the Cost Curve Scenario Selection screen.

Click on the Cost Summary Report link to see all the data associated with the scenario. For more information about this report, refer to the section “Reviewing the Cost Curve Detail Report” on page 79.


42

Reviewing Fix the Mix dataThe Fix the Mix dashboard quickly identifies the biggest problem areas in your supply chain inventory. This dashboard graphically shows the top 20 item-locations in your supply chain that have more on hand/projected inventory than recommended by MIPO; it also includes the top 20 item-locations in your supply chain that have less on hand/projected inventory than recommended by MIPO.

To access the Fix the Mix dashboard:

1. If you have not selected Scenario Comparison from the analysis drop-down menu, Select Scenario Comparison. You may have to select a scenario and click Go.

2. Click the Fix the Mix tab.

The Fix the Mix dashboard appears.


The Fix the Mix dashboard shows a bar graph chart representing the top 20 areas for cost savings on the left, where the MIPO target values for the item-locations are less than current cost projections. The right side of the chart represents the top 20 areas for risk, where the current cost projections for the item-locations are less than the MIPO target values.





Note: For scenarios that have less than 20 item-locations either above or below MIPO's recommendations for on hand/projected inventory, the Fix the Mix dashboard only displays those item-locations.


43

The Fix the Mix cost value is derived from subtracting the item-location’s end on-hand (EOH) inventory cost value from the sum of the item-location’s safety stock and its cycle stock cost value.

You can mouse over any bar graph to see its associated data.

Figure 2-24 Fix the Mix dashboard



2. Click Go.

Note: If the item-location paring name is longer than 25 characters, the name is truncated to preserve proper scaling for the graph. First, the location name is truncated to 12 characters. If the result is still too long, then location name returns to its original length, and the item name is truncated to 12 characters. If the resulting name is still too long, both the item and location are truncated until the resulting name is 25 characters long. If the name has been truncated, you will see ... display in the item-location name.


44

You have the option to change the scenario by clicking Actions in the top right corner of the dashboard and selecting a new scenario from the Scenario Selection screen.

Reviewing Demand Scenario Comparison dataThe Demand Scenario Comparison dashboard allows you to compare two streams of forecasting information side by side to see which scenario produces more desired results. This dashboard is a companion to the Demand Analytics dashboard that allows you to compare Forecast Error and Bias data for two scenarios.

Figure 2-25 Demand Scenario Selection screen

To view the Demand Scenario Comparison dashboard:

1. If you have not selected Scenario Comparison from the analysis drop-down menu, Select Scenario Comparison.

2. Click the Demand tab.

The Scenario Comparison selection screen appears. (Figure 2-25).


45

3. Select a scenario record from the table and click Compare

The Demand Scenario Comparison dashboard appears.

Figure 2-26 Demand Scenario Comparison dashboard

The Demand Scenario Comparison dashboard offers a graphic overview of comparison data for two indicators of demand analysis:

• Forecast Error

• Bias

The bottom of the dashboard lists the two scenarios that are being compared.


For scenarios with multiple lags, you can click the Lag drop-down and select one of the corresponding lags associated with the scenario to see its associated data. The Lag drop-down for the current scenario is located on the left, while the Lag drop-down for the comparison scenario is located on the right. By default, these values are set to the lowest lag available for each scenario.

You have the option to change the scenarios by clicking the Actions drop-down in the top right corner of the dashboard.


46

Forecast Error Comparison DetailsThe Forecast Error Comparison section contains two gauges (one for each scenario) that display the average CV value for each of the scenario’s demand streams.

The side-by-side bar graphs in the associated histogram compare the CV range of the demand stream groupings. The blue bar graph is associated with the left-hand gauge (current scenario), while the red bar graph is associated with the right-hand gauge (comparison scenario).

You can mouse over the histogram bars to see tool tip information related to the number of demand streams within the associated CV range

Figure 2-27 Forecast Error Comparison detail

Bias Comparison DetailsThe Bias Comparison section contains two gauges (one for each scenario) that display the percentage of biased demand streams for each scenario. The side-by-side bar graphs in the associated histogram compare the demand stream groupings based on their bias determination. The blue bar graph is associated with the left-hand gauge (current scenario), while the red bar graph is associated with the right-hand gauge (comparison scenario)

You can mouse over the histogram bars to see tool tip information related to the number of demand streams within the associated bias category.

Figure 2-28 Bias Comparison detail

47

T

Chapter 3: Workingwith new EIS Analytics

dashboards

his chapter provides instructions for using EIS Analytics dashboards available after the 6.10SP3 release to compare and approve inventory targets based on your supply chain's global performance around key performance indicators.

Using the analysis dashboardsEIS Analytics dashboards consist of three selections that focus on three key areas of supply chain analysis:

• Analytics

• Performance


EIS Analytics dashboards display data using gages, histograms, and tables. Six customizable slicers, anchored at the top of the dashboard, let you filter data based on attributes defined in your supply chain.

Scenario selection is available from the top of the dashboards.

For all EIS Analytics dashboards, the selected scenario name is shown at the bottom, along with the total number of demand streams in the selected scenario.


48

Using attribute slicersYou can use the attribute slicers to analyze the overview data. The following slicers are available by default:

• Material

• Material Class

• Location

• Planner Code

• Business Unit

• Region

You can also customize your attribute slicers. Refer to Chapter 3: Maintaining the EIS Analytics Dashboard in the EIS Analytics Installation Guide for more information.

To filter scenario data using an attribute slicer:

1. Click on the slicer you wish to use to open its drop-down list.

2. Select an attribute category from the list

3. Repeat steps 1 and 2 for other slicers, if necessary.

4. Click Apply.

Viewing DIM outputs by Lag For scenarios with DIM outputs, you can view those outputs based on DIM’s lag calculation feature by clicking on the Lag drop-down and selecting one of the corresponding lags associated with the scenario.

Reviewing Analytics DataThe Analytics dashboards display analytics-related data to support sales and operations planning, including demand analytics and demand history.

Note: Clicking Reset Filters returns slicers back to their default settings of All and updates all gauges, histograms and tables to show all scenario data.

Chapter 3: Working with new EIS Analytics dashboards

49

There are five analytics-related dashboards available:

• BIAS

• Demand History

• Forecast Error

• Intermittency Dashboard

• Supply Analytics

Demand Analytics dataDemand Analytics supports planner analysis through the review of Forecast Error, Bias and Intermittency dashboards. These dashboards includes data drill-down capability by filtering scenario data based on specific item and location attributes, as well as demand stream-specific characteristics.

The Demand Analytics dashboards offers a graphic overview of the summed average for three indicators of demand analysis:

• Bias

• Forecast Error

• Intermittency

Bias DashboardThe Bias dashboard displays the Bias gauge and chart, as well as Item-Location table associated with the top twenty items, sorted by decreasing order of bias. The Bias gauge displays the percentage of biased demand streams for the scenario. The bar graph in the associated histogram represent the demand stream groupings based on their bias determination. Bias categories display as buttons at the top of the bar chart, and the count of items in each bias category are displayed at the top of each bar in the chart. Clicking the bar in chart or clicking a button above displays the top twenty items of the selected category.


50

If you click on the row in the Item-Location table, a drilldown of that item displays to the right of the table.

Figure 3-1 Bias Dashboard

By clicking on any record in the Item-Location table, you will see its associated forecast vs. sales data. This information is initially displayed based on the lowest granularity of time-varying data in the scenario (e.g., 26 Weeks). You can change the display granularity by clicking the associated drop-downs at the top left of the graph (Note: You can also type numerical values into the field).



Click on the Demand Summary Report link to see all the data associated with the scenario.


51

Forecast Error dashboardThe Forecast Error dashboard displays the average CV value for the scenario demand streams and the associated bar graph represents the demand stream groupings based on their CV range. A list of details associated with the top twenty items, sorted by decreasing order of CV value also displays. The Forecast Error categories display as buttons at the top of the chart and the count of items in each Forecast Error category are displayed at the top of each bar. Clicking the bar in chart or clicking a button above displays the top twenty items of the selected category in the Item-Location table. Click on a demand stream in the table to see its associated Forecast vs. Sales chart data.

Figure 3-2 Forecast Error dashboard

By clicking on any record in the Item-Location table, you will see its associated forecast vs. sales data. This information is initially displayed based on the lowest granularity of time-varying data in the scenario (e.g., 26 Weeks). You can change the display granularity by clicking the associated drop-downs at the top left of the graph. (Note: You can also type numerical values into the field).





52

Intermittency DashboardThe Intermittency dashboard displays the percentage of demand streams for the scenario classified as Intermittent, and the bar graph in the associated chart represent the demand stream groupings based on their intermittent demand interval determination. Also displayed is an Item-Location table containing the top twenty items, sorted by decreasing order of ADI value. The Intermittency categories are displayed as buttons at the top of the chart, and the count of items in each Intermittency category are displayed at the top of each bar. Clicking a bar in the chart or clicking the corresponding button displays the top twenty items of the selected category.

Click on a demand stream record from the Item-Location table to see its associated Forecast vs. Sales chart data.

Figure 3-3 Intermittency dashboard

By clicking on any record in the Item-Location table, you will see its associated forecast vs. sales data. This information is initially displayed based on the lowest granularity of time-varying data in the scenario (e.g., 26 Weeks). You can change the display granularity by clicking the associated drop-downs at the top left of the graph. (Note: You can also type numerical values into the field).



53



Demand History dataThe Demand History dashboard supports planner analysis through a historical review of forecast error and bias. This allows you to determine whether forecast trends are improving over time.

This dashboard includes data drill-down capability by filtering scenario data based on specific item and location attributes, as well as demand stream-specific characteristics.

The Demand History dashboard offers a graphic overview of the history of two demand analytics, to show how they have changed over a period of a year:

• Forecast Error Improvement

• Bias Improvement






54

To view the Demand History dashboard, in InfoView, select the DIM History_perf.xlf file.

Figure 3-4 Demand History dashboard

Forecast Error Improvement detailsThe Forecast Error Improvement gauge displays the current average CV value for the scenario demand streams. The bar graph in the associated histogram displays the current and historical average CV value for the scenario, with the bar on the right representing the current average CV value.

Note: The dashboard displays a year’s worth of historical data, in increments. If the scenario does not contain a full year’s worth historical data (or more), only the periods available will be displayed. If there is no historical data, the dashboard only displays current information.


55

The current bar changes color to indicate whether the trend is improving from one month ago or not. When the trend improves, the current bar displays green. When the trend worsens, the current bar displays orange. If there is no historical data for the previous month or no change in the average CV, the bar displays blue.


Figure 3-5 Forecast Error Improvement detail

Forecast Bias Improvement detailsThe Forecast Error Bias gauge displays the percentage of biased demand streams for the scenario. The bar graph in the associated histogram displays the current and historical bias percentage for the scenario, with the bar on the right representing the current bias percentage.

The current bar changes color to indicate whether the trend is improving. When the trend improves, the current bar displays green. When the trend worsens, the current bar displays orange. If there is no historical data for the previous month or no change in the average bias, the bar displays blue.


Figure 3-6 Forecast Bias Improvement detail


56

Supply Analytics dataThe Supply Analytics dashboard supports planner analysis through the review of Lead Time Error and Planned Lead time data. This dashboard includes data drill-down capability by filtering scenario data based on specific item and location attributes, as well as supply stream-specific characteristics.

The Supply Analytics dashboard offers a graphic overview of the summed average for two indicators of supply analysis:

• Lead Time Error

• Delta to Planned Lead Time

To view the Supply Analytics dashboards, in InfoView, select the Supply_Analytics_perf.xlf file.

Figure 3-7 Supply Analytics dashboard

Lead Time Error DetailsThe Lead Time Error gauge displays the average CV value for the scenario supply paths. The bar graph in the associated histogram represent the supply path groupings based on their CV range. You


57

can mouse over the histogram bars to see tool tip information related to the number of supply paths within the associated CV range.

Figure 3-8 Lead Time Error

Delta to Planned Lead TimeThe Delta to Planned Lead Time gauge displays the percent of supply chains with non-zero deltas to lead time. The bar graph in the associated histogram represent the supply path groupings based on their delta to planned lead time. You can mouse over the histogram bars to see tool tip information related to the number of supply paths within the associated delta to planned lead time category.

Figure 3-9 Delta to Planned Lead Time

Reviewing Performance DataThe Performance dashboards display performance-related data to support sales and operations planning, including changes in inventory targets, inventory performance, service level performance and target performance.

There are two performance-related dashboards available, via tabs on the top left of the dashboard:

• Performance Overview

• Target Performance

To view the Performance dashboards, in InfoView, select the Perf Overview_perf.xlf file.


58

Figure 3-10 Performance Overview dashboard

Reviewing Performance Overview dataThe Performance Overview dashboard (Figure 3-10) highlights the performance of the supply chain and identifies areas that may be of concern. The dashboard offers a graphic overview for three indicators of performance:

• Inventory Target Alerts

• Inventory Performance


59

• Periods of Coverage


You have the option to change scenarios by clicking Select Performance Tracking Group at the top of the dashboard and selecting a new performance tracking group from the dropdown list.

Inventory Target Alerts DetailsThe Inventory Target Alerts graphic identifies the largest changes in safety stock when comparing the current inventory with the previous inventory. The Inventory Target Alert gauge displays the percent of item-locations where the safety stock change percentage is above a threshold (15% by default).







60

The table lists the top ten item-locations where safety stock inventory has changed, ordered from greatest amount of change to least amount of change. Each row contains the following information:

• Item – Item name

• Location – Item location

• Previous SS – First four-period average safety stock from previous period

• New SS – First four-period average of safety stock from current period

• SS Delta % – Percentage change in safety stock from previous period to current period

• Forecast – First four-period average forecast, in units

Inventory Performance DetailsThe Inventory performance graphic displays a historical overview of how well inventory targets have been met. The Inventory Performance gauge displays the percent of item-locations that are between the minimum and maximum inventory values in the performance tracking groups. The greater the percentage, the more item-locations were in range.

The associated histogram shows the past twelve periods and the percentage of inventory that was in range (green), in excess (yellow), or a shortage (red).


Periods of Coverage DetailsThe Periods of Coverage graphic displays a historical overview of the number of periods covered by the amount of inventory during that period. The Periods of Coverage gauge displays the average periods of coverage for the current period. The gauge needle points to green when the average periods of coverage is in-range (between six and ten periods, by default) and red when the average periods of coverage is too great or too small (less than six or greater than ten periods, by default).


61

The associated histogram shows the historical periods of coverage, with the bar on the right representing the current average periods of coverage.

Figure 3-13 Periods of Coverage

Reviewing Target Performance dataThe Target Performance dashboard supports the inventory planning part of sales and operations planning (S&OP). The dashboard was designed to provide demand, supply and inventory target data at a glance, at a single stocking point, or for an item across all locations, in both a tabular format and a histogram chart.

You can shift between the histogram and tabular views by clicking the Chart tab and Table tab respectively.






62

This dashboard includes slicers for data drill-down capability by filtering performance tracking group data based on specific item and location attributes, as well as demand stream-specific characteristics.

Figure 3-14 Target Performance chart

The Inventory Target Performance dashboard provides a graphic overview of the following target performance indicators:

• Total supply





The performance tracking chart allows filtering by date. To filter, move the left or right endpoint of the slider that is located below the X axis of the chart. You can also “grab” the slider in the middle by holding down the mouse button and dragging the whole slider left or right.


63

The Target Performance dashboard also offers a table with the following time-varying Supply targets:

• Vendor-managed inventory

• Beginning on hand inventory

• Supply (actual)

• Supply (projected)

• Total Supply.

Figure 3-15 Inventory Target Performance table

The following time-varying Demand targets are also displayed for the selected performance tracking group:

• Forecast

• Shipments

• Orders





64


• Inventory shortage

• Inventory excess

• Demand CV

You can mouse over a chart element to display associated definition content in the notification area at the bottom of the screen.

To adjust the Backward Planning Weeks or Forward Planning Weeks setting:


2. Click Go.

3. Use the Attribute slicers to filter scenario data, if necessary.

You have the option to change the performance tracking group by clicking Select Performance Tracking Group at the top of the dashboard and selecting a new performance tracking group from the dropdown list.

Reviewing Scenario Comparison dataThe Scenario Comparison dashboards supports what-if analysis of scenarios and performance tracking groups. These dashboard includes data drill-down capability by filtering scenario and performance tracking group data based on specific item and location attributes, as well as demand stream-specific characteristics.

There are four Scenario Comparison dashboards:

• Inventory Scenario Comparison

• Cost Curve

• Fix the Mix

• Demand Analytics Comparison


Note: All target performance dashboard data can be viewed as either units or dollars by clicking Units or Dollars.


65

Reviewing inventory scenario comparison dataThe Inventory Scenario Comparison dashboard provides a summary stacked bar chart with side-by-side comparisons of the following key indicators:

• Safety stock

• Cycle stock

• Prebuild stock

• Pipeline stock

• Merchandising stock

You can mouse over the stacked bar graph segments to see associated data. Also, you can hide any key indicator bar graph segment by clicking its associated check box. Such a change may be reflected in the summary totals, as indicated by the Y axis unit values.

Figure 3-16 Scenario Comparison dashboard

The Scenario Comparison dashboard also displays a line graph chart with side-by-side comparisons of trending activity for the key indicators. By clicking a specific key indicator’s bar graph segment, you can see comparison data for the selected indicator in the trend graph.


66

Alternatively, you can switch to an inventory total data view by clicking on the Show Inventory Total check box.

The bottom of the Scenario Comparison dashboard consists of tabular data organized by the following tabs:

• Scenario Comparison Summary

• Inventory Total

• Safety Stock

• Cycle Stock

• Prebuild Stock

• Pipeline Stock

• Merchandising Stock

The Scenario Comparison Summary table provides an aggregation value for each key indicator in both the current scenario and the comparison scenario, along with the Delta value and percentage difference.

The individual key indicator tabs provide time-varying data for both scenarios in the same comparison format.

You have the option to change the current scenario or comparison scenario by clicking the corresponding links in the top right corner of the dashboard.

Reviewing Cost Curve dataThe Cost Curve dashboard is designed to quickly determine how potential inventory investment will change based on using up to five different service levels for a given data set. This dashboard provides the ability to evaluate service level changes before committing to an inventory investment in line with planning expectations.

Note: All scenario comparison dashboard data can be viewed as either units or dollars by clicking Units or Dollars.


67

The Cost Curve dashboard supports service level analysis for up to five performance tracking groups. This dashboard includes data drill-down capability by filtering performance tracking group data based on specific item and location attributes, as well as demand stream-specific characteristics.

Figure 3-17 Cost Curve Scenario Selection screen

To view the Cost Curve dashboard:

1. Select the Cost_Curve_perf.xlf dashboard from InfoView.

The Cost Curve dashboard appears without any data.

2. Click the Select Performance Tracking Groups button.

The Cost Curve Performance Tracking Groups Selection screen appears (Figure 3-17).

3. From the list on the left-hand side of the Performance Tracking Groups Selector, select up to five performance tracking groups.






68

If you want to select multiple performance tracking groups at once, press the SHIFT or CTRL key while selecting the performance tracking groups. The SHIFT key allows you to select a co-joined list of performance tracking groups while the CTRL key allows you to select multiple separate performance tracking groups.

4. Click the right arrow (>) button to move the performance tracking groups to the Performance Tracking Groups Selected list on the right-hand side of the Performance Tracking Groups Selector. Click the left arrow (<) key to remove performance tracking groups.

You can also drag and drop individual or multiple performance tracking groups from one side of the Performance Tracking Groups Selector to the other.

5. Click Apply.

The Cost Curve dashboard shows line graphs for the following:



The EIO target cost value is derived from adding the performance tracking group’s safety stock cost value and the cycle stock cost value for the selected time period

The projected inventory cost value is based on the performance tracking group’s end on-hand (EOH) inventory cost value.

Note: You can reorder the performance tracking groups in the Performance Tracking Groups Selector; however, the Cost Curve dashboard automatically sorts the first five listed performance tracking groups based on service level, with performance tracking group 1 having the lowest service level and performance tracking group 5 the highest. The performance tracking group names are displayed at the top of the graph below the performance tracking groups number labels.

If you select more than five performance tracking groups, only the first five in the list are used.


69

You can mouse over the line graphs to see associated data. Also, you can hide any line graph segment by clicking its associated check box.

Figure 3-18 Cost Curve dashboard



2. Click Go.

Use the Attribute slicers to filter performance tracking group data, if necessary

You have the option to change performance tracking groups by clicking Select Performance Tracking Groups at the top of the dashboard and selecting new performance tracking groups.

Click on the Cost Summary Report link to see all the data associated with the performance tracking group. For more information about this report, refer to the section “Reviewing the Cost Curve Detail Report” on page 79.


70

Reviewing Fix the Mix dataThe Fix the Mix dashboard quickly identifies the biggest problem areas in your supply chain inventory. This dashboard graphically shows the top 20 item-locations in your supply chain that have more on hand/projected inventory than recommended by MIPO; it also includes the top 20 item-locations in your supply chain that have less on hand/projected inventory than recommended by MIPO.

This dashboard includes slicers for data drill-down capability by filtering performance tracking group data based on specific item and location attributes, as well as demand stream-specific characteristics.

The Fix the Mix dashboard shows a bar graph chart representing the top 20 areas for cost savings on the left, where the MIPO target values for the item-locations are less than current cost projections. The right side of the chart represents the top 20 areas for risk, where the current cost projections for the item-locations are less than the MIPO target values.

The Fix the Mix cost value is derived from subtracting the item-location’s end on-hand (EOH) inventory cost value from the sum of the item-location’s safety stock and its cycle stock cost value.





Note: For performance tracking groups that have less than 20 item-locations either above or below MIPO's recommendations for on hand/projected inventory, the Fix the Mix dashboard only displays those item-locations.

Note: If the item-location paring name is longer than 25 characters, the name is truncated to preserve proper scaling for the graph. First, the location name is truncated to 12 characters. If the result is still too long, then location name returns to its original length, and the item name is truncated to 12 characters. If the resulting name is still too long, both the item and location are truncated until the resulting name is 25 characters long. If the name has been truncated, you will see ... display in the item-location name.


71

You can mouse over any bar graph to see its associated data.

Figure 3-19 Fix the Mix dashboard



2. Click Go.

You have the option to change the performance tracking group by clicking Select Performance Tracking Group at the top of the dashboard and selecting a new performance tracking group from the dropdown list.

Reviewing Demand Scenario Comparison dataThe Demand Scenario Comparison dashboard allows you to compare two streams of forecasting information side by side to see which scenario produces more desired results. This dashboard is a companion to the Demand Analytics dashboard that allows you to compare Forecast Error and Bias data for two scenarios.


72

Figure 3-20 Demand Scenario Selection screen

To view the Demand Scenario Comparison dashboard:

1. From the Scenario Comparison selection dropdowns, (Figure 3-20) select the scenarios you want to compare.

The Demand Scenario Comparison dashboard appears.

Figure 3-21 Demand Scenario Comparison dashboard

The Demand Scenario Comparison dashboard offers a graphic overview of comparison data for two indicators of demand analysis:

• Forecast Error

• Bias

The bottom of the dashboard lists the two scenarios that are being compared.



73

For scenarios with multiple lags, you can click the Lag drop-down and select one of the corresponding lags associated with the scenario to see its associated data. The Lag drop-down for the current scenario is located on the left, while the Lag drop-down for the comparison scenario is located on the right. By default, these values are set to the lowest lag available for each scenario.

You have the option to change the scenarios by clicking the Actions drop-down in the top right corner of the dashboard.

Forecast Error Comparison DetailsThe Forecast Error Comparison section contains two gauges (one for each scenario) that display the average CV value for each of the scenario’s demand streams.

The side-by-side bar graphs in the associated histogram compare the CV range of the demand stream groupings. The blue bar graph is associated with the left-hand gauge (current scenario), while the red bar graph is associated with the right-hand gauge (comparison scenario).

You can mouse over the histogram bars to see tool tip information related to the number of demand streams within the associated CV range

Figure 3-22 Forecast Error Comparison detail

Bias Comparison DetailsThe Bias Comparison section contains two gauges (one for each scenario) that display the percentage of biased demand streams for each scenario. The side-by-side bar graphs in the associated histogram compare the demand stream groupings based on their bias determination. The blue bar graph is associated with the left-hand gauge (current scenario), while the red bar graph is associated with the right-hand gauge (comparison scenario)

You can mouse over the histogram bars to see tool tip information related to the number of demand streams within the associated bias category.


74

Figure 3-23 Bias Comparison detail

75

Chapter 4: Workingwith WebI Reports

his chapter provides instructions for using EIS Analytics WebI reports to compare and approve inventory targets based on your supply chain's global performance around key performance indicators. T


76

Reviewing the Demand Summary ReportThe Demand Summary Report provides a graphical and tabular representation of the demand stream records associated with the scenario. The bar chart compares forecast data to sales data for each time period in the scenario, along with the associated demand CV for the period. The table displays the following information:

• Forecast units

• Sales units

• The delta between forecast and sales

• MAPE

• MAD

• Demand CV

Figure 3-1 Demand Summary Report

To view the Demand Summary Report:

1. Select Analytics from the analysis drop-down menu.

2. Click the Demand tab.

3. If desired, use the attribute slicers to generate specific data for Demand analysis.

Chapter 4: Working with WebI Reports

77

4. Click Demand Summary Report at the bottom of the dashboard.

Reviewing the Target Performance ReportThe Target Performance Report provides a graphical and tabular representation of the target performance details associated with the scenario. The bar chart compares supply inventory data to demand inventory data for each time period in the scenario.

Figure 3-2 Inventory Projections Report

To view the Target Performance Report:

1. Select Performance from the analysis drop-down menu.

2. Click the Target Performance tab.

3. If desired, use the attribute slicers to generate specific data for inventory projection analysis.


78

4. Click Target Performance Detailat the bottom of the dashboard.

Reviewing the Scenario Comparison Detail ReportThe Scenario Comparison Detail Report provides a tabular representation of the comparison metrics between the current scenario and the comparison scenario.

Figure 3-3 Scenario Comparison Detail Report

To view the Scenario Comparison Detail Report:

1. Select Scenario Comparison from the analysis drop-down menu.

2. Click the Inventory tab.

3. If desired, use the attribute slicers to generate specific data for comparison analysis.

4. Click Scenario Performance Detail at the bottom of the dashboard.



79

Reviewing the Cost Curve Detail ReportThe Cost Curve Detail Report provides a graphical and tabular representation cost records associated with the scenario. The line graph show the following information for the scenario:



The table displays the following information:

• Service Level

• Supply Chain name

• Scenario name

• EIO Target Dollar amounts for the period

• Projected Inventory Dollar amounts for the period

• Inventory Exposure Dollar amounts for the period

• Inventory Shortage Dollar amounts for the period

• Inventory for the period

• Demand sum for the supply chain

• Supply sum for the supply chain

Figure 3-4 Cost Curve Detail Report


80

To view the Cost Curve Detail Report:

1. Select Scenario Comparison from the analysis drop-down menu.

2. Click the Cost Curve tab and select the scenarios to compare.

3. If desired, use the attribute slicers to generate specific data for Cost Curve analysis.

4. Click Cost Summary Report at the bottom of the dashboard.

Creating a new WebI report from an EIS Analytics report

To create a new report based on a EIS Analytics WebI report:

1. Log on to the Infoview portal with an administrator account.

2. Under Navigate, click Document List.

3. Expand the Public Folders.

4. Expand the SmartOps folder.

5. Expand the AIM folder.

6. Select the Dashboards folder.

7. Navigate to the SmartOps report you want to copy.

8. Right-click on the WebI report, select Organize > Copy.

9. Navigate to a new location you will store the new report.

10. Rright-click in the white space in the right hand pane, select Organize > Paste.

You can open this copied file with your reporting application software to make any modifications.

Creating a new WebI from the EIS Analytics UniverseWhen creating a new WebI report using the EIS Analytics Universe, select the AIM Template as your Universe. This universe is linked to the AIMKernel and contains customer-specific customizations.

The Context names used in the EIS Analytics universe are as follows:

• Supply Chain Periods

• Actual and Projected Inventory and Supply

• Supply Chain Specific Data

• Demand Data and Characteristics

• Scenario Specific Data

Note: Do not edit a EIS Analytics WebI directly. These are used in dashboards and will be overwritten in EIS Analytics product updates


81

When choosing a data object for a new EIS Analytics WebI report, you may be prompted for the object’s context. Select the context name that best represents the data needed for the report.

Refer to the SAP BusinessObjects Web Intelligence application documentation for more information about creating WebI reports.

Note: When building customized WebI reports with EIS Analytics data, keep in mind that data dependencies exist which can yield unexpected aggregations. For example, a WebI report created with objects in the Demand folder must take lag into consideration for data sets with multiple lag data.


82

enterprise inventory and service level optimization analytics

Documents