sap xapp analytics - techtargetmedia.techtarget.com/searchsap/downloads/jan2007.pdf · sap xapp...

Ryan Leask, Mathias Pöhling

SAP xApp Analytics

A practical guide to implementing and using SAP xApp Analytics

Bonn � Boston

102.book Seite 3 Montag, 9. Oktober 2006 11:14 11

Contents at a Glance

Foreword by Henning Kagermann ..................................... 17

Foreword by Sanjay Poonen .............................................. 19

1 Why Analytics? .................................................................. 21

2 Introduction to SAP xApp Analytics .................................. 33

3 SAP NetWeaver Visual Composer ..................................... 43

4 Installation of the Visual Composer .................................. 69

5 Working with the Visual Composer .................................. 89

6 Administration and Transporting ...................................... 195

7 SAP xApp Analytics Composite Applications .................... 225

8 Managing SAP xApp Analytics Projects ............................ 303

9 Design Guidelines .............................................................. 333

10 Outlook for SAP xApp Analytics ........................................ 347

A Technical Prerequisites for Predelivered Analytics ............ 365

B Links ................................................................................... 393

C Glossary ............................................................................. 395

D Bibliography ....................................................................... 399

E Acknowledgements ........................................................... 401

F The Authors ........................................................................ 403

Index .................................................................................. 405


7

Contents

Foreword by Henning Kagermann .......................................................... 17Foreword by Sanjay Poonen ................................................................... 19

1 Why Analytics? .................................................................. 21

1.1 Starting from the Beginning ................................................... 211.1.1 Business Intelligence Overview ................................. 211.1.2 Challenges for BI ....................................................... 221.1.3 Resulting Artificial Wall Between Actions and

Insights ..................................................................... 231.2 The Analytics Gap .................................................................. 24

1.2.1 Why Does the Gap Exist? .......................................... 251.2.2 A Business Analytics Example .................................... 26

1.3 Closed-Loop Analytics ........................................................... 271.3.1 Embedding Analytics ................................................. 28

1.4 Business Intelligence or Business Analytics? ........................... 301.5 Benefits of Using Analytics ..................................................... 311.6 Summary ............................................................................... 32

2 Introduction to SAP xApp Analytics .................................. 33

2.1 Introduction .......................................................................... 332.1.1 Blocked Sales Orders Example ................................... 342.1.2 Other SAP xApp Analytics Composite Applications ... 36

2.2 Architecture for SAP xApp Analytics ...................................... 372.2.1 SAP xApp Analytics and SAP NetWeaver BI .............. 39

2.3 What's in a Name? ................................................................ 402.3.1 What Is a Composite Application? ............................. 412.3.2 What is an SAP xApp? ............................................... 41

2.4 SAP xApp Analytics in the Market ......................................... 422.5 Summary ............................................................................... 42

3 SAP NetWeaver Visual Composer ...................................... 43

3.1 Introduction .......................................................................... 433.1.1 Integration with SAP NetWeaver Portal .................... 443.1.2 Design Time Environment ......................................... 453.1.3 Consuming Services .................................................. 47


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3.2 Enterprise SOA and Web Services .......................................... 473.2.1 SOA Overview .......................................................... 483.2.2 Web Services ............................................................ 48

3.3 Visual Composer Architecture ................................................ 503.3.1 User Interfaces .......................................................... 513.3.2 SAP NetWeaver Portal .............................................. 513.3.3 Detailed Visual Composer Architecture ..................... 523.3.4 Authorizations and Delivery to End Users .................. 53

3.4 Kit Concept and the BI Kit ..................................................... 543.4.1 What’s in the BI Kit? ................................................. 55

3.5 Visual Composer in the SAP Environment .............................. 643.5.1 Visual Composer and SAP NetWeaver BI ................... 643.5.2 Web Dynpro and Visual Composer ............................ 653.5.3 Choosing the Right Tool ............................................ 67

3.6 Summary ............................................................................... 68

4 Installation of the Visual Composer .................................. 69

4.1 Introduction .......................................................................... 694.2 Prerequisites for Using the Visual Composer .......................... 69

4.2.1 Connecting to SAP NetWeaver BI (Optional) ............. 704.2.2 SAP NetWeaver 2004 Runtime (Optional) ................. 70

4.3 Sizing ..................................................................................... 724.3.1 Sizing Models ........................................................... 724.3.2 SAP Quick Sizer ......................................................... 73

4.4 Installation Process ................................................................ 754.4.1 Operating Systems and Databases ............................. 754.4.2 Usage Types .............................................................. 764.4.3 Updating the SAP NetWeaver 2004s system ............. 77

4.5 Client PC Software Installation ............................................... 804.6 Connecting to Backend Systems ............................................. 81

4.6.1 Creating a System Connection ................................... 824.7 Summary ............................................................................... 87

5 Working with the Visual Composer .................................. 89

5.1 Introduction .......................................................................... 895.2 Model Administration ............................................................ 90

5.2.1 Menu and Toolbar .................................................... 905.2.2 Workspace ................................................................ 925.2.3 Task Panel ................................................................. 925.2.4 Task Panel Toolbar .................................................... 935.2.5 Console Panel ........................................................... 93


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5.3 Working in the Visual Composer ............................................ 935.3.1 Packages, Pages, and iViews ..................................... 955.3.2 Navigating the Model ............................................... 965.3.3 Design, Layout, and Source ....................................... 975.3.4 Menu Options .......................................................... 101

5.4 Building a Visual Composer Model ........................................ 1035.4.1 Design of the Example Application ............................ 1055.4.2 Layout of the Application Example ............................ 1245.4.3 Deploy and Run ........................................................ 125

5.5 Connecting to Different Systems ............................................ 1275.5.1 RFC-enabled Function Modules (BAPIs) .................... 1285.5.2 SAP NetWeaver BI .................................................... 1295.5.3 Web Services ............................................................ 1355.5.4 Other Non-SAP Sources ............................................ 1375.5.5 SAP Query ................................................................ 141

5.6 Visual Composer Features and Functions ............................... 1425.6.1 Compose Model ....................................................... 1435.6.2 Actions and Events .................................................... 1715.6.3 Formulas ................................................................... 1765.6.4 Miscellaneous Features and Functions ....................... 186

5.7 Summary ............................................................................... 193

6 Administration and Transporting ....................................... 195

6.1 Administration ....................................................................... 1956.1.1 Monitoring ............................................................... 1956.1.2 Logging ..................................................................... 1986.1.3 Backup ...................................................................... 2036.1.4 Security ..................................................................... 2056.1.5 Languages and Decimal Notation .............................. 208

6.2 Transporting .......................................................................... 2096.2.1 Installing SAP xApp Analytics Models ....................... 2106.2.2 Transporting Models ................................................. 2166.2.3 Transporting Composite Applications ........................ 216

6.3 Summary ............................................................................... 223

7 SAP xApp Analytics Composite Applications .................... 225

7.1 Introduction .......................................................................... 2257.2 Financials and Human Capital Management (HCM) ............... 226

7.2.1 Consolidation ............................................................ 2277.2.2 Credit Monitor .......................................................... 228


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7.2.3 Early Warning List ..................................................... 2297.2.4 Blocked Order List .................................................... 2307.2.5 Line Manager: My Budget ......................................... 2317.2.6 Profit Center Accounting ........................................... 2327.2.7 Recruiting ................................................................. 2337.2.8 Headcount ................................................................ 2347.2.9 Learning .................................................................... 2357.2.10 Overtime and Illness ................................................. 2367.2.11 Line Manager: My Team ........................................... 2377.2.12 Corporate Governance .............................................. 238

7.3 Customer Relationship Management (CRM) .......................... 2447.3.1 Order and Lead Analysis of a Channel Partner ........... 2447.3.2 Order and Lead Analysis for a Channel Partner .......... 2457.3.3 Web Analysis ............................................................ 2457.3.4 Connection and Open Ticket Analysis ....................... 2467.3.5 Marketing Project Performance Analysis .................... 2477.3.6 Sales Pipeline Analysis ............................................... 2487.3.7 Competitive Win/Loss Analysis .................................. 249

7.4 Supplier Relationship Management (SRM) ............................. 2507.4.1 Category Management .............................................. 2507.4.2 Contract Management .............................................. 2517.4.3 Supplier Order Management ..................................... 252

7.5 Supply Chain Management (SCM) .......................................... 2537.5.1 Forwarding Agent Efficiency ...................................... 2537.5.2 Demand Supply Match .............................................. 2547.5.3 Forwarding Agent Requirements ............................... 2547.5.4 Global Capacity Utilization ........................................ 2557.5.5 Global Inventory View .............................................. 2567.5.6 Order Analytics ......................................................... 2577.5.7 Delivery Performance ................................................ 2587.5.8 Supplier Rating Monitor ............................................ 2587.5.9 Warehouse Stock Analysis ......................................... 2597.5.10 Warehouse Workload History ................................... 2607.5.11 Material Availability .................................................. 261

7.6 Manufacturing ....................................................................... 2627.6.1 Overall Equipment Effectiveness (OEE) ...................... 2627.6.2 Capacity Utilization ................................................... 2657.6.3 Inventory Overview ................................................... 2657.6.4 Material Consumption .............................................. 2657.6.5 Plan Realization ........................................................ 2657.6.6 Production Order Analysis ......................................... 265


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7.6.7 Material Utilization ................................................... 2667.6.8 Production Flexibility ................................................ 2677.6.9 Quality Problem Analysis .......................................... 2677.6.10 Scrap Quantity Analysis ............................................. 2687.6.11 Take from Stock or Buy ............................................. 2687.6.12 Quality of Purchased Parts ........................................ 268

7.7 Consumer Products & Apparel and Footwear ......................... 2687.7.1 AFS Analytics for Reseller .......................................... 2687.7.2 Brand Analytics ......................................................... 2697.7.3 Category Cockpit ....................................................... 2707.7.4 Category Sales Analysis ............................................. 2707.7.5 Category Promotion Analysis ..................................... 2707.7.6 Channel Performance YTD ........................................ 2717.7.7 Trade Marketing Analytics ......................................... 271

7.8 Logistics Service Provider ....................................................... 2727.8.1 Sales Manager Logistics ............................................. 2727.8.2 Transportation Manager ............................................ 272

7.9 Banking and Insurance ........................................................... 2737.9.1 Defaulted Exposures ................................................. 2737.9.2 Overview of Collaterals and Guarantees .................... 2747.9.3 Regulatory Capital Requirements .............................. 2747.9.4 Total Expenditure in an Overview ............................. 2757.9.5 Expenditure Detail .................................................... 2767.9.6 Total Expenditure as a Trend ..................................... 276

7.10 Retail ..................................................................................... 2777.10.1 Category Manager ..................................................... 2777.10.2 Store Manager .......................................................... 2777.10.3 Replenishment Planner ............................................. 278

7.11 Chemicals .............................................................................. 2787.11.1 Customer Profitability ............................................... 279

7.12 Aerospace & Defense; Engineering, Construction & Operations; Industrial Machinery & Components ................... 2797.12.1 Pilot Report .............................................................. 2807.12.2 Vendor Analytics ....................................................... 2807.12.3 Service Manager ....................................................... 2807.12.4 Facility Operations—Damage Analytics ..................... 281

7.13 Automotive ........................................................................... 2817.13.1 Alert Reporting Supplier Managed Inventory ............ 281

7.14 Environment, Health and Safety ............................................. 2827.14.1 Workarea, Exposure Log ........................................... 2827.14.2 1,000-Employee Quota ............................................. 283


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7.14.3 Waste Approvals, Quote of Already Released Quantities ................................................................. 283

7.15 Customer Financials Management ......................................... 2847.15.1 Credit Manager ......................................................... 284

7.16 Telecommunications .............................................................. 2857.16.1 Contract Analysis for Dealer Managers ...................... 2857.16.2 Contract Analysis for Channel Managers .................... 286

7.17 Healthcare ............................................................................. 2867.17.1 Hospital Contribution Margin .................................... 2867.17.2 DRG Monitor ............................................................ 2867.17.3 Hospital Material Management ................................. 2867.17.4 Occupancy Monitor .................................................. 287

7.18 Higher Education & Research ................................................. 2877.18.1 Admission Overview ................................................. 2887.18.2 Registration Overview ............................................... 288

7.19 High Tech .............................................................................. 2897.19.1 NPDI Projects Analytics ............................................. 289

7.20 Utilities .................................................................................. 2907.20.1 Meter Reading Administrator Utilities ....................... 2907.20.2 Sales Analyst Utilities ................................................ 2907.20.3 Process Manager Utilities .......................................... 291

7.21 Media .................................................................................... 2917.21.1 Entertainment Analytics—License Sales Contract ....... 2917.21.2 Key Account Manager Advertising ............................ 2927.21.3 PCP Analytics—By Title ............................................. 292

7.22 Mill Products ......................................................................... 2937.22.1 Revenue .................................................................... 2937.22.2 Profitability ............................................................... 2937.22.3 Sales ......................................................................... 294

7.23 Oil & Gas & Mining ................................................................ 2947.23.1 Tracking Bulk Shipments ........................................... 294

7.24 Public Sector ......................................................................... 2967.24.1 Funds Management .................................................. 2967.24.2 Tax and Revenues ..................................................... 2967.24.3 Grantee Management ............................................... 297

7.25 Service & Asset Management ................................................. 2977.25.1 Service Organization Performance Analysis ................ 2977.25.2 Maintenance Cost Monitor—Equipment View .......... 2977.25.3 Downtime Analysis ................................................... 2977.25.4 Maintenance Cost Monitor—Work View ................... 298


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7.26 New Product Development and Introduction ........................ 2997.26.1 New Product Development and Introduction

(NPDI) Analytics ....................................................... 2997.27 Summary ............................................................................... 301

8 Managing SAP xApp Analytics Projects ............................ 303

8.1 Introduction .......................................................................... 3038.2 Project Pre-Phase .................................................................. 3058.3 Planning Phase ...................................................................... 306

8.3.1 Project Goals and Scope ............................................ 3068.3.2 Stakeholder ............................................................... 3078.3.3 Timeline and Milestones ........................................... 3098.3.4 Resources, Roles, and Responsibilities ....................... 312

8.4 Realization Phase ................................................................... 3138.4.1 Project Kick-Off ........................................................ 3138.4.2 High-Level Process for Building Analytic

Composites ............................................................... 3168.4.3 Design ...................................................................... 3188.4.4 Development ............................................................ 3228.4.5 Additional Project Management Considerations ........ 323

8.5 Go-Live Check/Review Phase ................................................. 3258.6 Go-Live Phase ........................................................................ 327

8.6.1 Go-Live Procedure .................................................... 3278.6.2 Project Closure .......................................................... 329

8.7 Summary ............................................................................... 330

9 Design Guidelines .............................................................. 333

9.1 Introduction .......................................................................... 3339.2 Designing the Floor Plan ........................................................ 3349.3 Application Content .............................................................. 3389.4 Navigation & Design Elements ............................................... 3399.5 Form Views ........................................................................... 3419.6 Table Views ........................................................................... 3429.7 Chart Views ........................................................................... 3449.8 Summary ............................................................................... 346

10 Outlook for SAP xApp Analytics ........................................ 347

10.1 Introduction .......................................................................... 34710.2 Investment Approval (mySAP ERP) ........................................ 34710.3 Corporate Governance (mySAP ERP) ...................................... 349


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10.3.1 Assessment of Management Controls ........................ 34910.3.2 Validation of Internal Control Assessment ................. 35110.3.3 Design Assessments of Internal Controls at

Process Level ............................................................ 35210.3.4 Sign-Off of Internal Control Assessment .................... 352

10.4 Account Analytics (CP) ........................................................... 35310.5 Warehouse Stock Analysis (mySCM) ...................................... 35610.6 Expense Exceptions ............................................................... 35710.7 Treasury and Financial Investment Controlling (TRAFIC) ........ 35810.8 Best Practice Scorecarding ..................................................... 36110.9 Summary ............................................................................... 362

Appendix................................................................................... 263

A Technical Prerequisites for Predelivered Analytics ............................. 365A.1 Aerospace & Defense Engineering Construction &

Operations Industrial Machinery & Components .................... 366A.2 Automotive ........................................................................... 367A.3 Banking and Insurance ........................................................... 367A.4 Chemicals .............................................................................. 368A.5 Consumer Products & Apparel and Footwear ......................... 369A.6 Customer Financials Management ......................................... 370A.7 Customer Relationship Management (CRM) .......................... 371A.8 Environment, Health and Safety ............................................. 372A.9 Financials and Human Capital Management ........................... 373A.10 Healthcare ............................................................................. 377A.11 High Tech .............................................................................. 378A.12 Higher Education & Research ................................................. 378A.13 Logistics Service Provider ....................................................... 379A.14 Manufacturing ....................................................................... 379A.15 Media .................................................................................... 383A.16 Mill Products ......................................................................... 384A.17 New Product Development and Introduction (NPDI) ............. 385A.18 Oil & Gas & Mining ................................................................ 385A.19 Public Sector ......................................................................... 385A.20 Retail ..................................................................................... 386A.21 Service & Asset Management ................................................. 387A.22 Supplier Relationship Management (SRM) ............................. 388A.23 Supply Chain Management (SCM) .......................................... 389A.24 Telecommunications .............................................................. 391A.25 Utilities .................................................................................. 392


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B Links .............................................................................................. 393C Glossary ........................................................................................... 395D Bibliography ..................................................................................... 399E Acknowledgements .......................................................................... 401F The Authors ..................................................................................... 403

Index ...................................................................................................... 405


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Forewordby Henning Kagermann

Today’s world of business gets more and more complex. Analytical applica-tions are a key differentiator in the competition, because they give access tocomprehensive information about customers, prospects, suppliers, partners,employees, and overall business indicators. They enable strategic and opera-tional decisions to be made on an accurate, up-to-date, and consistent pictureof corporate performance.

SAP® xApp™ Analytics provide clear and deep insights into business pro-cesses. They supply the user with the information necessary to take theappropriate measures in real time in order to implement the company strat-egy, and to work in concert with other participants in the processes and inthe ecosystem. The application allows the user to look into the supply chainnetwork and to cover all disparate functions, departments, and even organi-zations. The analyses functions are harmonized with the requirements of theuser. They can easily be used, adjusted, and extended.

With SAP xApp Analytics, SAP demonstrates what a new generation of user-friendly User Interfaces (UI) looks like. SAP has partnered with Adobe Sys-tems, Inc. to incorporate their Flash technology into the SAP UIs. This part-nership has resulted in a new look and feel, which has been very wellreceived by customers and partners.

As part of the underlying SAP NetWeaver technology, SAP xApp Analyticsare simple to use and implement. The download and installation can now bedone in a matter of minutes; customers can implement and go live with SAPxApp Analytics within weeks, instead of spending months or years on devel-opment. Less complex applications can even be created from scratch inunder a minute.

Based on a strong technology foundation, SAP xApp Analytics demonstratethought leadership in the field of Business Analytics. In addition, SAP xAppAnalytics—being a part of SAP’s Enterprise Service-Oriented Architecture(SOA) roadmap—clearly show how the full potential of Enterprise SOA canbe used to create applications that were impossible to develop only a shorttime ago. I truly hope that this book not only helps you to find your way into


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SAP xApp Analytics, but that you also develop a sense of the possibilities thatare now within reach as a result of SAP delivering on its Enterprise SOAroadmap.

Henning KagermannCEO, SAP AG


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Forewordby Sanjay Poonen

Welcome to the world of SAP® xApps™ Analytics. Perhaps it is a differentworld from the one that you’re used to, but that's exactly the idea behind it!

I know it’s different, because even inside SAP, Analytics have always chal-lenged the norm. Initially, the concept of SAP xApp Analytics was conceivedearly in 2005, and in just twelve months, the vision had become a reality,and the first customers had successfully gone live. All of this is impressive inand of itself, but when you consider the speed with which a large companylike SAP moved to make Analytics a reality, that is a true testament to thecreditability and enthusiasm of the SAP xApp Analytics team.

I am also pleased to report that SAP AG was the first company to go live withSAP xApp Analytics. In 2005, we implemented six SAP xApp Analytics in ourinternal finance organization. As the test pilot for the new software, theimplementation of these models took just six weeks. Our early customerexperiences have been equally successful, even as the technology continuesto advance from release to release.

Another impressive feature that you’ll notice in SAP xApp Analytics is itsincredibly modern user interface. I always find it amusing to watch how inawe customers are when they first see the UI. The new user-interface para-digms of SAP xApp Analytics combine the latest in modern Web 2.0 userinterfaces, with robust backend infrastructure, to provide truly powerfulapplications.

SAP xApp Analytics are built on the SAP NetWeaver stack, and show theworld just how easy composite application development can be. For exam-ple, we have customers taking xApp Analytics and customizing these com-posite applications in a matter of days. The norm in the IT industry is for it totake months, and sometimes years, for analytic applications to be built andtailored to the needs of business users. Now, in a paradigm shift, powerusers can assemble an analytic application in a matter of hours and test itwith other business users, all without having to learn a line of code. Further-more, these applications can access both SAP and non-SAP systems, andallow the user to actually take action on the underlying data. Analytics have


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long been considered as read-only applications, but SAP is changing that per-ception by combining analytical capabilities with the operational executionof the business process.

Our vision is to make Analytics an integral part of every business process,that is, to make it so embedded that it is almost transparent to the user. Agreat analogy is the SimCity experience for a little kid. I watch my nephewsplay SimCity and wonder how it is that six-year-olds can build such complexcities? They actually simulate building cities with fairly sophisticated rules.They negotiate with a city planner, and while they’re engaged in doing this,a fire starts and they’re prompted to take action. We've got to make Analyt-ics for the user as simple as the SimCity experience is to a kid, so that peoplecan easily navigate through their decisions on a day-to-day basis in the con-text of their business process. Users should not even be thinking about Ana-lytics—they just know that the underlying technology is helping them makequicker, more accurate decisions by helping them take the appropriateactions. Think of Analytics embedded into the business process for an HRmanager or a supply chain manager. They see a few metrics, the system givesthem a few intelligent suggestions they can act on, they make their decision,and then they go on with their life. That's how mainstream we're seeking tomake Analytics. It’s a different way of thinking for sure, but that's whatmakes it exciting!

Mathias Pöhling and Ryan Leask have been two star contributors on the SAPxApp Analytics team. They have successfully implemented several of ourmost complex customer xApp Analytics projects, and have a clear passion forthe topic. I am excited to write a Foreword for the first book on this topic inthe market, and know that many of you will find it useful, because it isgrounded in practical experience.

Furthermore, not only do I trust that you will find this book practical anduseful, but even more importantly, I hope it allows you to appreciate andexperience in your own implementations the true potential that can beunleashed with SAP xApp Analytics.

Sanjay PoonenSVP and GM of AnalyticsSAP Labs, LLC


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1 Why Analytics?

1.1 Starting from the Beginning

Before delving into “Why Analytics?” the question we really need to ask is“What is Analytics?” First, we can narrow our focus to specifically examineBusiness Analytics (BA); however, even then, there is not one, all encompass-ing, and accurate definition. It is a topic that covers many different technol-ogies, and each vendor in this space will have their own definition of whatshould constitute Analytics. Another important distinction to examine iswhether Analytics is the same as or even a subset of Business Intelligence(BI). It is certainly not our intention to explore the intricacies of definingthese terms, but rather, to simply provide a clear understanding of how andwhere Analytics fits into an organization, especially when compared to Busi-ness Intelligence.

1.1.1 Business Intelligence Overview

Today the industry at large is generally referred to as Business Intelligence.Basically, Business Intelligence comprises applications and technologiesdesigned to gather, store, and analyze business data, with the goal ofenabling better decision-making, and thereby improving organizational effi-ciency and allowing a company to gain a competitive advantage. From atechnology perspective, Business Intelligence covers topics such as datawarehousing, querying and reporting, Online Analytical Processing (OLAP),data mining, alerts, and planning. Data Warehousing was the accepted indus-try term prior to Business Intelligence being coined. In 1990, Bill Inmoncoined the term data warehouse, and his definition follows:

“A (data) warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision-making pro-cess.”

This is quite a precise definition, and we don’t need to go into the semanticsof it; but, basically, data warehousing refers to the central collection, consol-idation, and storage of the huge volumes of data that an organization accu-mulates in multiple, disparate systems. Often, Business Intelligence software


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is thought of as the frontend tools used by the end users for querying, anddata warehousing is considered to be the backend supporting this.

The purpose of collecting business data into a data warehouse is to be able toanalyze consolidated results, and gain insights from this analysis (to enablebetter decision-making). But, it is possible to have too much of a good thing,and if there is simply too much data available, then users can become over-whelmed. A company collects a phenomenal amount of data, and findingjust the right information can be very challenging for a business. In fact, ifbusiness users cannot access the data because it is too hard to find what theyare looking for, then having too much information can be just as much of adisadvantage as having too little information. Essentially, BI software hastaken the analysis a step further, by providing more comprehensive and rig-orous software to search through the data, looking for patterns and trends.This means that BI software is really designed to assist users, by helpingthem to make sense of all the information that is out there, and presenting itin the clearest and most concise manner possible. As we mentioned earlier,BI still incorporates the technologies of data warehousing, but it also coversan even wider range of principles and applications.

1.1.2 Challenges for BI

Unfortunately, BI has generally not had a significant focus or investment inIT. As Neil Raden points out, this is due to historical technology limitationsthat forced Analysis and Operations apart. BI has always been considered tobe a totally distinct area from the operational execution of business pro-cesses. Consequently, companies have generally focused their attention onEnterprise Resource Planning (ERP) systems, which manage and optimize theday-to-day processes that enable the company to run efficiently. BI on theother hand, is thought of as after-the-fact analysis, where the data is accumu-lated and analyzed over time, and the insights gained from this analysis areeventually transferred back into the operational business to improve its effi-ciency.

Yet, even the managers in a company, who are there to specifically work at astrategic level (rather than at an operational level), may or may not use BIsoftware. Another reason why BI has been held back is the potential for com-plication. To begin with, it means one or more (depending on the companyand their objectives with BI) new pieces of software to learn. Furthermore,users don’t enjoy sifting through volumes of data, looking for the informa-tion they need. It can be far too time-consuming to perform an in-depth anal-


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ysis of the data; inevitably, what happens is that people will give up search-ing and continue to make decisions without all the necessary data.Dashboards have been used to address this issue. Dashboards are predefinedapplications, summarizing all the required information in a format that iseasy to read and understand (typically they present the information in a col-lection of table and graphs). They are often used to deliver information tomanagement, because they are an ideal way of summarizing all of the impor-tant information, and they enable the user to quickly comprehend the datawhile requiring little or no user interaction.

1.1.3 Resulting Artificial Wall Between Actions and Insights

Although BI applications play a very valuable role, and companies have beensuccessfully using these technologies to gain valuable competitive advan-tages, the broader definition of Business Intelligence is that its purpose is toimprove decision-making. Today, it is largely up to the analysts using the BIsoftware to drive the insights gained back into the business. But, BI softwareis not really designed to support this part of the process. Rather, the BI view-point is that by analyzing and presenting the data in such a way that insightscan be gained, it has done its job properly. But what good is it if opportuni-ties or weaknesses are identified for the business, but they cannot be con-verted into improvements at the operational level? Or, if by the time the ana-lyst is aware of the potential opportunity to benefit from these insights, theopportunity to do so has already slipped by.

Furthermore, we must consider the human factor (i.e., analysts are people,and therefore their skills at performing this task will vary; they can also justpick up and leave an organization and take their knowledge with them). So,there is a bit of a leap of faith that is going on here. That is, it assumes thatwhen users have the right information, they will make the right decisions.The people who are truly making decisions on a daily basis are those execut-ing the operational business processes. Yet, as already stated, BI software isnot really designed to support operational decision-making. This situationhas led to an artificial wall between the business insights gained by the busi-ness analyst and the actions taken by the business user, as depicted in Figure1.1.

Of course, not every operational step in a company would be better off withBI, but there are many, many processes that could really benefit from suchapplications. This problem of not having analytical applications for the oper-ational execution of the business is called the Analytics Gap.


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Figure 1.1 Artificial Wall Separating Insight and Action

1.2 The Analytics Gap

The analytics gap has materialized because the people who are executing theoperational side of the business are doing so without any analytical support.It is usually a select few analysts who have access to BI applications. They aregenerally performing more complex analyses of the data (i.e., slicing and dic-ing, creating ad-hoc reports, etc.), and really need the advanced offering of BIproducts. To learn how to use these applications can often require significanttraining and experience, as well as an understanding of the underlying datamodels. However, there are many steps in the business process where Ana-lytics could be used to gain operational insights. This situation is depicted inFigure 1.2.

The analytics gap is represented by the box in the top left corner of this fig-ure. It reflects the low overlap of traditional BI applications and the opera-tional side of a business.

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Business UserBusiness Analyst

Business ProcessAnalytic Steps


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Figure 1.2 The Analytics Gap

1.2.1 Why Does the Gap Exist?

So, you ask: Why does this gap exist? There are many factors contributing tothe current analytics gap.

To begin with, the way in which BI tools have evolved over time has cer-tainly been a major factor. Operational people generally need the most gran-ular data, on a real-time basis, in order to make decisions to run the businesson a day-to-day basis. Analytical people, on the other hand, generally needhistorical data, collected and analyzed over time, in order to draw insightsfrom it. BI systems have been built on exactly this premise. Therefore, thedata in the BI systems often doesn’t meet the requirements necessary to sup-port operational execution.

Note

This is not to say that data warehouses store only historical, aggregated data. Withever-improving hardware performance, many data warehouse systems do (andshould) contain granular data where it is needed. But, for the data to be truly effec-tive for operational needs, it often needs to be accurate up-to-the second, whichcannot be said for data warehouses.

Complexity

This is where the majority of decisions are made …

without appropriateanalytical support

TraditionalBI Applications


Why Analytics?1

26

Again, this is not a negative reflection of BI systems, but just a matter of hav-ing the right tool for the right purpose. BI systems have generally beendesigned to support analytical requirements, not operational ones.

Undoubtedly, another factor that has contributed to the analytics gap is cost.Trying to deploy very sophisticated BI tools to everyone in the organizationwould generally not be the most cost-effective approach. The functionalitythat is delivered and available in BI systems would often be excessive foroperational needs. It doesn’t make sense to pay for licenses of such systemsif the user is simply not willing or able to use this functionality. Additionally,costs are not just limited to licensing, as there are development, support,documentation, and training costs to be considered as well. Thus, cost isanother reason why we see a relatively low adoption rate of BI softwareacross a company’s entire workforce.

1.2.2 A Business Analytics Example

Many operational business processes could definitely benefit from analyticalinsights. An example of just one step in one operational business process,which could benefit from analytical insights, is that of a Credit Manager ana-lyzing blocked sales orders. This is where a customer placing an order to pur-chase some items may want to put the cost of the order on credit rather, thanpaying up front.

The company needs to the evaluate whether the customer is creditworthy.Therefore, the customer’s sales order will undergo an automated creditcheck. If the credit check is not definitive, the sales order will be temporarilyblocked where it can then be manually examined by a Credit Manager. It isthen the Credit Manager’s job to decide whether the order should bereleased (credit approved) or blocked (credit rejected). To make an effectivedecision, the Credit Manager needs an overview of the most important infor-mation about the customer.

This information needs to come from both operational systems (includinginformation such as the customer’s credit limit and current credit exposure),as well as analytical systems (information such as the trend of the customer’scredit score over the last several months). To collect and consolidate all ofthis information from the different systems can be a time-consuming pro-cess. What would ultimately enable the Credit Manager to do his job effec-tively would be to have a single application where the current list of allblocked orders is visible, and when an individual order to be processed is


Closed-Loop Analytics 1.3

27

selected, the Credit Manager would get all the necessary information, rightthere and then, to help him decide whether to release or block the order.

This sounds very similar to a dashboard that could be implemented to poten-tially achieve this result; however, what would really be useful is if the CreditManager could make his decision without having to leave the application. Allthe information would be in one place, so why not guide the Credit Man-ager’s decision-making and present her with a list of possible decisions fromwhich to choose. In this particular scenario, there are three possible deci-sions. The Credit Manager may first want to check the sales order again withthe most recent credit information to see whether the order still needs to beexamined. The other two options are to either release or block the order. TheCredit Manager now has everything she needs to carry out this operationalstep, without having to leave the application. As you can see, the analyticalapplication that we just described is clearly much more than a dashboard,since the ability to make decisions has been directly incorporated into theapplication.

1.3 Closed-Loop Analytics

This example of the blocked sales order application highlights how both ana-lytical information and decision-making can be embedded into a singleapplication. This situation is called Closed-Loop Analytics because the analyti-cal application can directly impact the outcome or action that is taken.

Figure 1.3 Closed-Loop Analytics

Figure 1.3 illustrates how a closed-loop scenario works. A business user (e.g.,a Credit Manager) has to perform an operational step in a business process


Why Analytics?1

28

(e.g., block or release sales orders that failed a credit check). To do this, shecan run the analytical application to help her analyze all the required data(e.g., analyze the customer’s credit score, credit limit, credit exposure, etc).By having all the required data in one place, the Credit Manager will be ableto gain valuable insight (e.g., the customer’s recent credit behavior indicateshis business appears to have cash flow problems). The Credit Manager willnow be presented with all of the available actions that she might want totake, so she can now decide what to do (e.g., the decision is whether torelease or block the order, and in this case, she decides to block the order).Arguably, the most important step is now for the Credit Manager to executeher decision (e.g., proceed with blocking the order in the system). This istherefore considered a closed-loop application, because the entire process—from analysis to execution—is completely driven inside one application.

1.3.1 Embedding Analytics

To achieve this closed-loop scenario, the analytics gap described in Section1.2 needs to be closed off, and analytical applications must be embeddedinto the operational execution of the business processes. The Credit Managerexample is just one step in one business process where this could happen.Analytics can really be used everywhere in an organization. This means thatanalytical applications should be deployed to most business users in an orga-nization, and not just to the business analysts. This way, the business userhas direct access to the analytical information. There are reasons this has notbeen done in the past, namely, because of course, as previously described,for additional costs, and training because business users just won’t have timeto sift through the masses of data searching for the right information. Often,their decisions also need to be based on real-time operational data ratherthan on typical analytical data. So what has changed that allows us to nowaddress these concerns?

Self-Intuitive Applications

First, it is imperative that the analytical applications are very self-intuitive.The business users should not be exposed to data models or complex OLAPcontrols. The goal here is for the application to help the business user do herjob faster and more efficiently, and not to take up more of her time! As wealready mentioned, users don’t enjoy tinkering with BI applications andlooking through data in search of the information they need. They simplywant to find the right information at the right time. To make the applications


Closed-Loop Analytics 1.3

29

truly self-intuitive this may mean a reduction in functionality. Although thisconcept can be hard to accept at first, reduced functionality does not neces-sarily mean reduced productivity! The data just needs to be displayed in theoptimal way as to convey it’s meaning to the user. Neil Raden states:

“Visualization of data is the quickest way to understand information, and it’seasy to use.”

We must also point out that we are in no way suggesting that BI tools shouldhave reduced functionality. What we’re saying is that business users don’tneed to be exposed to all the available functionality at once. Business ana-lysts, on the other hand, will continue to want and need the advanced func-tionality provided by BI tools, so nothing is changing in this respect. We arealso not saying that a business user can’t use sophisticated tools and algo-rithms to analyze data. There will still be situations where more advancedfunctionality would be helpful to a user. However, for most operationaltasks, if the analytical information that users want to see can be presented tothem in a logical, concise manner, then they won’t need the more advancedcapabilities. We cannot stress enough, the importance in understanding thebusiness processes when designing the analytical application. If users are notgoing to be searching through the data, then it is critical that they are pre-sented with the right data the first time around. This knowledge comes fromknowing the business processes. Furthermore, the application User Interface(UI) itself must be easy to understand and user friendly. There should be lit-tle or no training required to use the application, because it should be so log-ical that it is self-intuitive.

Hiding the Technicalities

Where the data that the users want to see is being sourced from should notcome into play for these applications. It should be transparent to the users.From their perspective, they don’t want to have to deal with “transactional(or operational) systems” and “analytical systems,” each of them having dif-ferent types of data, each with their own UIs. They just want the data,regardless of its source. The analytical applications should be able to sourcedata from whichever system is required. In other words, analytical data (i.e.,historical, aggregated data) and transactional data (i.e., real-time, granulardata) should be able to be combined seamlessly into one application.


Why Analytics?1

30

Taking Action

Finally, the user should be able to take action from within the analyticalapplication. When whole business processes are broken down into smallersteps, there are many operational decisions to be made and actions to betaken. To support the improved decision-making goals of BI tools, the abilityto act on the information should be an inherent part of the application.Merely giving users the information, but assuming that this automaticallyleads to the right decisions and actions will not suffice. When looking at theblocked sales order scenario, it is clear what is expected of the user of theapplication. The user must examine a customer’s credit history to determinewhether a sales order that is currently blocked should be allowed to gothrough. The user has all the necessary information to make an informeddecision, so she can act on that decision. Aside from the application’s afford-ing the user with more effective decision-making skills, this newfound abil-ity to take action based on informed decisions also enables her to becomemore productive. Not only does she no longer have to source data from dif-ferent systems, but she can act on the insights she gained without even leav-ing the application.

1.4 Business Intelligence or Business Analytics?

Is there really a difference between BI and BA? This is a heavily debatedquestion; however, in the authors’ opinions, there is a distinction. Let’sexamine this further.

Analytics are the business applications of the technology on which they arebased. These applications cannot be generic because they must be industry-specific, application- specific, and job-specific. Business Analytics can lever-age the strength of BI technology, but they are not confined to just BI sys-tems. They must be composite applications that can source their data fromwhichever type of system has the information that the user needs to performhis job. Therefore, BI is just one of many possible data services for analyticcomposite applications. Furthermore, Business Analytics are really designedto be embedded in the operational side of the business. To truly enable oper-ation execution, they must allow the user to directly take action on the data.BI systems, on the other hand, focus on the read-only, analysis of data. Thereare some aspects of BI where data might be changed (such as planning appli-cations), but on the whole, BI systems are not designed to allow the user to


Benefits of Using Analytics 1.5

31

take action. And unlike business analytic applications, BI applications are notembedded in the operational side of the business.

Despite the difference between BI and BA, Business Analytics in no waydetracts from the goals or methods of BI. The role of BI is just as critical asever, and BA and BI must work together in order to give a company a truecompetitive advantage. From a pure technology perspective, there are manypoints where BI and BA overlap, so whether the distinctions that we just out-lined become blurred and imperceptible, resulting in one technology plat-form is yet to be seen. Currently, however, there is still a distinction in thetechnology for BI and BA.

1.5 Benefits of Using Analytics

Hopefully, you can now see the benefits of using Analytics in your businessprocesses. Analytic applications are focused on the business users and theirspecific job roles in the context of the business process. To date these usershave generally had to manage without the aid of Analytics in their decision-making process. But, analytic composite applications can change this. By pro-viding accurate, comprehensive, timely, and actionable information to busi-ness users, they will be able to make faster and more informed decisions.The potential benefits to the operational side of the business are enormous.

Furthermore, the actions that the users take can now be much more closelydefined and monitored. That is, users are given a much more guided deci-sion-making process, leveraging the use of composite applications. This pro-vides management with a means to directly influence the way in which theoperational side of the business gets run. In this sense, management canalign the corporate strategy more closely with the daily running of the busi-ness. It also affords companies the opportunity to really adapt to change,when the key measures that users are relying on and the decisions that arebased on this information are both integrated into the same composite appli-cation. If a change arises in business conditions, then the metrics them-selves—how they impact the decision-making process and what decisionsshould be taken—can all be easily adapted. It becomes much clearer to usershow they need to act, and thus their actions can be more closely aligned withorganizational strategy and company expectations.

Yet for Analytics to really be able to achieve these goals, there is one impor-tant factor that still needs to be addressed: Total Cost of Ownership (TCO).


404

Index

Index

A

ABAP 66Accordian 156Account Plan 354Actions 171Administration 195Adobe Flash 81Adobe Flex 51, 67Adobe Flex integration 65Alert 188Alert Management 63Alerts 63Alias Manager 213Analytical Application 29Analytics 21, 24, 28, 30Analytics Project 303, 304, 305, 309Application Developer 313Appropriation Request 347Architecture 50, 52Area Chart 345Asset Class 360Audience 317Authorization 53, 206, 207, 326

B

Back End Development 322Backend Requirements 320Backend System 47, 207, 247Background colours 344Backup 203BAPI 128Bar Chart 345Basis/Technology Consultant 313Best Practice Scorecarding 361BEx Query Designer 140BI Integration Wizard 58, 140, 141BI JDBC System 82BI Kit 55, 56, 60, 61, 62, 63, 141BI Objects 83BI Query 323BI query 61Blocked Order List 36, 37Blocked Sales 34

Blueprint 307, 315, 326Budget Planner 296Business Analyst 312Business Analytic 34Business Content 33, 37, 39, 214, 225Business Intelligence 21, 23, 32Business Package 214, 225Business Process 26, 32, 318Business Requirements 305, 317Business Scenario 305

C

CAPEX 348Change Management 324Channel Manager 244Characteristic 133Chart Types 345Chart View 146, 344Closed Loop 27, 28Closed-loop Scenario 34Color 344Combine Element 170Combo Chart 345Component Overview 196Composite Application 30, 31, 37, 40,

216Composite Application Framework 66Composite Applications 41, 225, 333,

334Conditional Functions 181Config Tool 203Connection 81, 82, 86Connector 83Connector Framework 81Console Panel 94Corporate Governance 98, 349Corporate Governance Applications 347Create Deal 360Credit Manager 26, 35CRM 36Custom Actions 46Customer Service Manager 261


405

Index

D

Data Export 341Data Fields 178Data Flow 320, 321Data Service 128, 321Data Sevice 321Data Store 185Data Warehousing 21Date formats 339Date Functions 180Delta Link 217Design 333Design Guideline 333Design Process 316Design Tab 98Design Time 43, 326Design time 90Development 322Development Portal 86Distinct Element 165Documentation 315, 328Documentation Management 323Documenting 307Doughnut Chart 345Downtime Analysis 297Dynamic List 187

E

End Point 159End Uuser 328Enterprise Portal 6.0 71Enterprise Resource Planning (ERP) 347Enterprise SOA 47, 49Entry List 186Entry List Manager 186ERP 2005 system 35Event 113, 171Existing model 91Export 128, 204, 213, 221Expression Boxe 183Expressions Editor 177

F

Features 142Field Propertie 183File System 97

Financials 354Find Data 106, 129Flash 50, 67Flash Debugging Console 199Floor Plan 318, 319, 334Form View 144, 341Formula 176, 179, 182Functions 142Funds Management 296

G

Gap Analysis 320Generate Button 132Generic Modeling Language 52GML file 127Go or Submit 341Go-Live 328Go-Live Check 304, 325Go-Live Phase 304, 327Go-Live Procedure 327Grantee Management 297Group By Element 168Guard Condition 185Guided Procedure 153, 190

H

Help 90Hierarchical view 337Hierarchies 61HTML View 148Human Capital Management 233Hyperlinks 182

I

Image Manager 188Implementation 303Import 128, 210, 211, 213, 222Info Port 131InfoObject 208InfoSet 142Input 108, 130Input Form 109Installation 69, 75, 214Interaction 343Internal Control Assessment 351, 352Intersect Element 167


406

Index

Investment Approval 347Investment Management Module 349iViews 53, 65, 208

J

J2EE 51, 66Java Server Page 50Java Support Package Manager 80JDBC 56, 64JDBC Connection 137

K

Key Figure 134Key Performance Indicator 225Kit 54

L

Language 208Layer 152, 157Layout Tab 100, 124Legend 344Lessons Learned 329Line Chart 345Link List 156Link Tree 157Log Configurator 202Logging 198Logistics 354Logon Tickets 84

M

Macromedia Flash Player 50Maintenance Cost Monitor 298Manage Model 91Management Controls 349Mass Exporting and Importing 203Material Availability 261MDX Editor 58, 103, 140, 207, 208Measurement 339Messages Port 131Milestone 306, 307, 309Monitoring 195MyModels 92mySAP CRM 33, 47, 141, 247mySAP ERP 33, 105, 230, 349

mySAP PLM 33mySAP SCM 33, 281

N

Navigating 97Nested iView 148, 150NetWeaver 333NetWeaver Application Server 205NetWeaver BI 39, 67, 85, 231NetWeaver BI System 82NetWeaver Portal 38, 51, 69, 126, 205NetWeaver Portal Environment 225New Product Development 299Non-SAP Systems 38Numeric Functions 180

O

ODBO 56, 64, 70, 139Oil & Gas & Mining 294OLAP 56, 64, 67, 225, 333OLTP 64, 225Operational environment 33Operators 181OPEX 348Output 114Output Element 319Output Port 121, 131

P

Package 95PAR File 53, 200, 216, 218, 223Performance 135Permissions 84Pie Chart 345Planning Phase 303Popup Signal 160Portal Connector Framework 69Portal Content 44Portal Content Directory 81, 127Portal Deployment Folder 220Portal Page 53, 95Ports 108Post-Import Test 328Pproductive Ssystem Eenvironment 328Predefined Applications 305Pre-Phase 303


407

Index

Prerequisite 69, 70Print 341Print Page 341Procedures 314Product Availability Matrix 75Product Category 244Profit Center Accounting 232Project Budget 306, 307Project Closure 329Project Goals 306Project Kick-Off 313Project Management 303Project Manager 304, 312Project Plan 310Project Pre-Phase 305Project Progress 323Project Results 329Project Scope 306, 307, 309, 315Project Status 307Project Tasks 306Project Timeframe 306Promotions 354Prompt Message 174Public Models 92Pushbutton 111

Q

Quad view 335Quality Management 323Query View 135Quick Sizer 73, 75Quick Sizer Tool 73, 74

R

Realization Phase 303, 313Request Overview 196Request Summary 196Return on Investment 32, 42Review Phase 304, 325RFC 55, 64, 70, 128, 207RFC-enabled Function 105Role 215, 216Roles and Responsibilities 312Run 126Runtime 43, 44Runtime Patch 71, 223

S

SAP Application Benchmark Performance Standard 75

SAP Backend System 49SAP Customer Relationship Manage-

ment 55, 347SAP NetWeaver 37, 43, 44, 87SAP NetWeaver 2004 71SAP NetWeaver 2004s Portal 89SAP NetWeaver BI 60, 89SAP NetWeaver Portal 75SAP Query 64, 141SAP Strategic Enterprise Management

33, 361, 363SAP Supply Chain Management 347,

363SAP xApp Analytics 33, 305SCA 210Scientific Functions 181Scoping Document 306Screen Resolution 339SDN 61, 83, 91Security 205Segment Builder 141Select 119Selectable view 337Service Manager 297Service-Oriented Architecture 42, 47, 48Sigma Element 165Signal In 160Signal Out 160Single Screen 34, 339Single Sign-On 84Single View 334Sizing 72Software Deployment Manager 211Software Download Center 77, 213Sort Element 164Source Tab 101Split view 336SQL Editor 58SRM 335Stakeholder 307, 308, 309Start Point 158Static List 187Steering Committee 312Storyboard 45, 50, 93, 94, 98Successful Project 308, 309


408

Index

Supplier Managed Inventory 281Support Environment 330Support Package Stack 77, 80SVG Viewer 81System Action 46, 112, 119System Alias 85, 86, 212, 215

T

Table View 145, 343Task Panel 94, 97Technical Description 315Text Functions 179Thread Overview 198Throughput Based Sizing 72Time Functions 180Timeline 309Timer 162Timestamp 341Title 338Tool Tip 343Tracking Bulk Shipments 294Translation 208Transport Package 218, 221Transporting 195, 213, 216, 222Transporting iViews 209Transporting Models 209Travel Management 357Travel Manager 357, 358Treasury 358

U

Union Element 166Units 339, 343Universal Work List 63, 350Unlock 206Unlock model 91

Upper Element 165User Based Sizing 72User Interface 305, 316, 318, 327User Interfaces 51, 65User Management 83

V

Validation Rule 184Value Help 59, 188, 340Variables 130Visibility Condition 184, 185Visual Administrator 202Visual Administrator Logs 201Visual Composer 37, 39, 47, 51, 54, 55,

59, 85, 87, 88, 105, 141, 171, 195, 202, 207, 225, 323, 333

Visual Composer Patch 80

W

Warehouse Stock Analysis 259, 356Warehouse Supervisor 259, 356Warehouse Workload 260Web API 56, 62, 70Web Application Designer 65Web Dynpro 64, 65, 66Web Service 49, 56, 89, 135, 137Web Service System 83Web Services Description Language 135Window Dragging 191Window Splitter 191Wizard 57, 153Workspace 92, 94

X

XMLA 57, 64, 70, 139


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