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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
Plan, execute, and sustain a successful IT campaign with Sam Bansal's perfect scorecard approach
First came the dot.com bust, then the IT squeeze. Despite software being the tail that wags the dog in most corporations, the cham-pions of IT, the CIOs, are constantly under fire to justify and maximize their IT investments—past, present, and future.
Learn how to establish Key Performance Indicators and Value Scorecards for IT to ensure maximum value in your corporation with the step-by-step approach found in Sam Bansal's Technology Scorecards.
Drawing on Dr. Bansal's over forty years of field experience in the management of large and complex projects, Technology Scorecards shows you how to:
- Create Scorecards geared towards your organization's business goals
- Make quantum improvements in cost, value, and productivity using KPIs and Scorecards
- Increase your company's net by as much as 100% just by improving your supply chain management by 50%
- Impact your top line the most through product life-cycle management
- Develop a realistic strategy through Scorecards, which can then be used to drive IT investments that maximize your business performance
Enhance profitability. Streamline strategy execution. Lower costs. Learn how to align your IT plans with your business objectives and optimize your company's overall performance with the perfect scorecard approach found in Technology Scorecards.
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Table of Contents
Cover
Title
Copyright
Disclaimer
Acknowledgments
Acronyms and Abbreviations
PART I: Introduction
CHAPTER 1: Why Projects Fail, Scorecards, and How This Book Is Organized
Today’s Environment
Why Projects Fail
Harry’s Survey
Scorecards and SCOR Cards
Promise of Technology: Functionality, Key Performance Indicators, and Business Benefits
Deliver on Promises: Scorecard Methodology to Align Investments to Business Performance
Bibliography
PART II: Promise of Technology
CHAPTER 2: Strategic Enterprise Management
Introduction
Core Activities with Strategic Enterprise Management
How to Create a Strategy
Tools Supporting Strategic Enterprise Management
Essential Support from SEM Application Modules
Business Analytics
Key Performance Indicators
Bibliography
CHAPTER 3: Supply Chain Management
Introduction
SCM Domain
Advanced Planner and Optimizer
Solvers, Algorithms, and Simulation
Supply Chain Management Detailed
Supply Chain Execution
Supply Chain Coordination
Supply Chain Collaboration
Value Chains
Key Performance Indicators
Benefits
Bibliography
CHAPTER 4: Product Life Cycle Management
Introduction
Architecture of a PLM System
Detailed Component Descriptions
Product and Process Design
Change and Configuration Management
Asset Life Cycle Management
Life Cycle Collaboration and Analytics
Quality Management
Environmental Health and Safety
PLM: Why It Is So Important, What It Can Do, and How It Does It
PLM Features and Benefits in Details
PLM Key Performance Indicators
Five-Day Cycle with PLM Scenario
Mapping of PLM Feature (to Support High-Volume Parts Manufacturing from Concept to Release)
Significant Issues in PLM Implementation
Future Outlook
Bibliography
PART III: Scorecard Methodology to Align it Investments with Business Performance (Deliver on Promise)
CHAPTER 5: Strategy
Enterprise Strategy
Key Performance Indicators
Benchmarking
Value/Benefits Estimating
Business Process Reengineering
Bibliography
CHAPTER 6: Realization Phase
Solution Architecting
Gap Analysis
Roll-Out Planning
Configuration Planning
Bibliography
CHAPTER 7: Human Factors
Project Management
Project Champions
Business Case Development
Bibliography
CHAPTER 8: Umbrella Considerations
Change Management
Implementation Time Risk Analysis and Mitigation of Risk in Enterprise Systems
Quality Management
Communications Management
Test Plan and Test Procedures
Training
Bibliography
CHAPTER 9: Performance Management
Introduction
Principles of Performance Management
Preparing to Implement Performance Management
Generating the Corrective Signal
Bibliography
CHAPTER 10: Summary
References
Index
End User License Agreement
Pages
cover
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Guide
Cover
Table of Contents
Begin Reading
List of Illustrations
CHAPTER 1: Why Projects Fail, Scorecards, and How This Book Is Organized
FIGURE 1.1 Why Projects Fail
FIGURE 1.2 Harry’s Survey Summary
PART II: Promise of Technology
FIGURE IIA Overview of Development of Scorecard and Strategy
CHAPTER 2: Strategic Enterprise Management
FIGURE 2.1 Direction of Strategic Enterprise Management
FIGURE 2.2 Architecture of an SEM
FIGURE 2A Virtual Reality, Model, and Assumption-Based Simulations
CHAPTER 3: Supply Chain Management
FIGURE 3.1 Supply Chain Management Architecture
FIGURE 3.2 Systems Landscape Architecture
FIGURE 3.3 APO Functionality
FIGURE 3.4 SCM and APO Architecture
FIGURE 3.5 Basics of SCM Functionality
FIGURE 3.6 Workflow in SCM
FIGURE 3.7 Supply Chain Paradox
FIGURE 3.8 Solvers and Algorithms
FIGURE 3.9 Customer and Market Focus (Part I)
FIGURE 3.10 Customer and Market Focus (Part II)
FIGURE 3.11 Costs I
FIGURE 3.12 Costs II
FIGURE 3.13 Costs III
FIGURE 3.14 Costs IV
FIGURE 3.15 Profitability I
FIGURE 3.16 Profitability II
FIGURE 3.17 Profitability III
FIGURE 3.18 Profitability IV
FIGURE 3.19 Cash-to-Cash Cycle Time
FIGURE 3.20 Order Fill
FIGURE 3.21 Inventory Days of Supply
FIGURE 3.22 Capacity Utilization
FIGURE 3.23 Raw Material Inventory Turnover
FIGURE 3.24 Total Supply Chain Costs
FIGURE 3.25 Key Performance Indicators
FIGURE 3.26 Benefits—Causes and Effects
FIGURE 3A CIM Architecture
CHAPTER 4: Product Life Cycle Management
FIGURE 4.1 Overview of PLM System
FIGURE 4.2 Fundamental Components of a PLM System
CHAPTER 5: Strategy
FIGURE 5.1 Methodology (Road Map)
FIGURE 5.2 Business Goals to Business Solutions
FIGURE 5.3 SCOR Model Representation of a Business Environment
FIGURE 5.4 Total Supply Chain Costs
FIGURE 5.5 Results of Benchmarking Study
FIGURE 5.6 Overall Business Model
CHAPTER 6: Realization Phase
FIGURE 6.1 Full-Service Solution Architecture
FIGURE 6.2 Full-Service Manufacturing Solution’s Architecture
FIGURE 6.3 Configuring Activities
CHAPTER 7: Human Factors
FIGURE 7.1 Collapsing Overhead and Direct Labor
FIGURE 7A BCD Project Planning
FIGURE 7B Mapping Actionable Items of Methodology on BCD Major Activities
CHAPTER 8: Umbrella Considerations
FIGURE 8.1 Evolution of Risk Decision Making
FIGURE 8.2 Quality Management Processes in All Life Cycles of Software Implementations
FIGURE 8.3 V Model Testing in the Life Cycle of Software Development
CHAPTER 9: Performance Management
FIGURE 9.1 Principles of Performance Management
FIGURE 9.2 Performance Delivery Architecture
List of Tables
CHAPTER 4: Product Life Cycle Management
TABLE 4.1 PLM Features and Benefits
TABLE 4.2 KPIs and Their Explanations
CHAPTER 5: Strategy
TABLE 5.1 Customer Participants for SWOT Discussions with the Project Team
TABLE 5.2 The Delta
TABLE 5.3 Clustered KPIs Leading to Total Supply Chain Cost
TABLE 5.4 Client PC Company’s SCOR Card
TABLE 5.5 Calculations of Value Creation
CHAPTER 6: Realization Phase
TABLE 6.1 Value Creation and Value Drivers
CHAPTER 7: Human Factors
TABLE 7A Preliminary Questionnaire
TABLE 7B Activities for Business Case Development
TABLE 7C KPIs to Collect
TABLE 7D As-Is and Recast Supply Chain Costs
TABLE 7E Supply Chain Scorecard
TABLE 7F Summary of Improved Potential Benefits
CHAPTER 8: Umbrella Considerations
TABLE 8.1 Team Training Matrix
Technology Scorecards
Aligning IT Investments with Business Performance
SAM BANSAL
Copyright © 2009 by Sam Bansal. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.
No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400, fax 978-646-8600, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, 201-748-6011, fax 201-748-6008, or online at http://www.wiley.com/go/permissions.
Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
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Library of Congress Cataloging-in-Publication Data
Bansal, Sam, 1940- Technology scorecards : aligning it investments with business performance / Sam Bansal.
p. cm.Includes bibliographical references and index.ISBN 978-0-470-46456-4 (cloth)1. Strategic planning. 2. Business logistics. 3. Performance technology. I. Title.HD30.28.B3644 2009658.4’012–dc22
2008052098
Disclaimer
This publication contains references to the products of SAP AG. SAP, R/3, xApps, xApp, SAP NetWeaver, Duet, PartnerEdge, ByDesign, SAP Business ByDesign, and other SAP products and services mentioned herein are trademarks or registered trademarks of SAP AG in Germany and in several other countries all over the world.
Business Objects and the Business Objects logo, BusinessObjects, Crystal Reports, Crystal Decisions, Web Intelligence, Xcelsius and other Business Objects products and services mentioned herein are trademarks or registered trademarks of Business Objects in the United States and/or other countries.
SAP AG is neither the author nor the publisher of this publication and is not responsible for its content, and SAP Group shall not be liable for errors or omissions with respect to the materials.
Acknowledgments
The author is indebted to SAP AG for the knowledge gained on Advance Planner & Optimizer (APO), Supply Chain Management (SCM), and Product Life Cycle Management (PLM) while in tenure over there. Most of the information presented in these areas is based on the author’s own practice and knowledge of the SAP domain. To the best of the author’s knowledge, nothing discussed is of a confidential nature.
I also wish to acknowledge all those friends, relatives, colleagues, and associates without whose help, advice, and encouragement this book would have still remained in my head. Specifically, some people I want to thank for their help are:
Amrish Goyal, my friend, for his constant encouragement to complete this work.
Sneh Agarwal, my wife, for her continued enthusiasm and for encouraging me when I did not feel up to completing this work.
Sahil Bansal, my son, for editing the preface and sowing the seeds of confidence in this effort.
Suresh Mehta, my friend; as a CIO and project manager, he critiqued the preface and introduction with a high degree of enthusiasm.
Sanjay Jain, my friend and colleague, for his endorsement blurb. Sanjay has always encouraged and advised me on various issues. His review and critique of the entire book has proven invaluable. A professor at George Washington University, Sanjay is a subject matter expert.
Ajay Agrawal, my friend and erstwhile colleague, for his implicit faith in my claim that a high percentage of software projects fail the first time. His belief gave me the confidence to begin this project.
Mike O’Brien, my friend, mentor, and client, for his kind encouragement and for agreeing to review the book and give me an endorsement.
Mike Petrucci, my friend, mentor, and client, for agreeing to give me an endorsement.
Acronyms and Abbreviations
APO:
Advanced planner and optimizer
Avg:
Average
BBP:
Business blue print
BCD:
Business case development
BPR:
Business process reengineering
CAD:
Computer-aided design
CAE:
Computer-aided engineering
CAM:
Computer-aided machining
CAPE:
Computer-aided process engineering
CAPP:
Computer-aided process planning
CIM:
Computer-integrated manufacturing
CIMing:
Usually means tasks related to computer-integrated manufacturing
Collabn:
Collaboration
Config Mgmt:
Configuration management
CPG:
Consumer packaged goods
CPM:
Collaborative project management
CRM:
Customer relations management
CSF:
Critical success factors
DDC:
Direct digital control
DFA:
Design for assembly
DFM:
Design for manufacturing
EH&S:
Environment, health, and safety
Env:
Environment
ERP:
Enterprise resource planning
fabs:
Fabrication units; usually refers to chip-making plants
FI:
Finance
iPPE:
Integrated product and process engineering
IT:
Information technology
KPI:
Key performance indicator
LCM:
Life cycle management
MES:
Manufacturing execution system
MM:
Materials management
mySAP:
SAP’s software product begun in 1999
mySAP SCM:
SAP’s Supply Chain Management
OA:
Opportunity assessment
PM:
Project manager, also program manager
Psft:
Peoplesoft
R3:
SAP software system
SAP:
Software Application Products (usually refers to SAP Ag of Germany)
SCM:
Supply chain management
SD:
Sales and distribution
SEM:
Strategic enterprise management
SIS:
Semiconductor integration services; also strategic international services
SKU:
Stock keeping unit
SOA:
Supply chain opportunity assessment
Sr:
Senior
SRM:
Sourcing relations manager
SWOT:
Strength, weakness, opportunity, threat
WBDS:
Work break-down structures
WF:
Work flow
WFM:
Work flow modeling
PART IIntroduction
CHAPTER 1Why Projects Fail, Scorecards, and How This Book Is Organized
Today’s Environment
Since the dot-com bust in the year 2000, information technology (IT) and IT people have been under an unprecedented squeeze. Today’s high-tech industry has come close to being a $10 trillion behemoth, of which software is fully more than 25%. There was a time when software was a forgotten appendage to the mighty mainframe, but such is not the case anymore. Now software, even if only 25% of the total content, is the tail that wags the dog.
As paradigm after paradigm is changing in the high-tech landscape of our world, software is increasing in importance and is contributing more business benefits than ever before. But this is not enough.
It seems the honeymoon days for IT are over. The free rein that chief information officers (CIOs) enjoyed not too long ago are gone. Instead, we find ourselves in the midst of very tight operating conditions. In today’s software environment, CIOs must:
Reduce total cost of ownership.
Increase value to the corporation.
Contribute to improve bottom and top line.
And the normal things that CIOs were expected to do in addition to the top-level goals continue:
Decrease complexity in increasingly heterogeneous environment.
Contribute to creating a real, real-time enterprise.
Manage resources.
Do a lot with the little that is available.
Produce miracles without budget growth.
The champions of IT, the CIOs and their staffs, try to deal with these issues while the project world is delivering the other messages:
New technologies are being introduced at a more rapid rate than before.
There are too many vendors to choose from.
All claim to have practically the same offerings, so it is difficult to differentiate among them.
So-called neutral consultants are too eager to take your money without contributing much value.
Requirements are not understood. Promises are made to be broken later.
And to make matters worse, when projects are finished, chief executive and chief financial officers complain that:
Expectations are not met.
Too much money was spent for too little return.
They want to sue the vendor because it failed to deliver as promised.
When a new technology is first implemented by a group of trailblazer companies, success is far from guaranteed. Success and satisfaction are seldom found in this group of companies. However, as the technology gets old and commonplace, the success rate generally goes up. In fact, the larger the company and larger the project, the more likely project failure is. The frank reality is that larger projects (more than $3 million in application spend) routinely need harsh turn-around measures, or they get stalled and eventually killed by the weight of their own bureaucracy.
A survey published in 2001 in Chaos News Letter1 has shed light on companies’ success by taking the cumulative cost of failure, estimated by the Standish Group at $145 billion, and by the Meta Group figure at $180 billion. This amount, they believe, is the amount lost each year in the United States due to failed or challenged projects. The Chaos report is full of grim numbers, such as “for every 100 projects, there are 94 restarts” and “only 9% of projects for large companies come in on-time and on-budget.” However, the 2004 Chaos report,2 entitled “CHAOS Chronicles,” found a total project costs to be $255 billion, of which a total failure cost was estimated to be $110 billion. While this is an improvement over the previous estimates, it is still a large cost of failure. And compare failure or success of a project from the perspective of the stake holders as defined by the chief stakeholders who believe that their IT investments did not give them the desired returns from their perspective.
The question is: What are the promises of technology, and how can technology deliver on those promises?
Human nature is such that first we create problems, then we search for reasons behind them, and then we try to solve them. So, having seen the current complex and heterogeneous landscape of systems, let us examine briefly the reasons for widespread failures of software projects.
A cautionary note about failure is that systems may not necessarily have failed; in the eyes of the stakeholders, however, they may not have fulfilled expectations.
Why Projects Fail
These are the messages we are getting from the media:
Enterprise software at X Company failed to perform.
SCM software from Y vendor failed to perform.
Company Z is suing the vendor A for noncompliance.
Consulting Group A was thrown out of Company B.
Here are some basic causes of these problems:
Strategic alignment did not match the business goals.
There were communication breakdowns.
Up-front buy-in was not obtained.
User involvement was inadequate.
There were poor user inputs.
Stakeholder conflicts existed.
The requirements were vague.
User requirements were not firmly nailed down.
User requirements may have changed midway.
Poor cost and schedule estimates existed.
Skills did not match the job.
There were hidden costs of going “lean and mean.”
There was a failure to plan properly.
Poor architecture existed.
Failure warning signals came late.
Company financials may have changed.
Project manager may not have been skilled.
The project team may have been unacceptable to management.
The champion and executive sponsor was transferred, or left the company, or was not there.
Additional problems encountered in the field include:
Value is not understood.
Vendors bid without understanding the requirements well.
Goals are not clearly and succinctly defined.
Key performance indicators (KPIs) are neither defined nor understood.
Change management was not practiced.
Risk planning was not done properly.
Most projects get initiated as automation of as-is without due business process reengineering (BPR) or to-be views.
The quality of external consulting was poor.
It is not my intention to discuss the causes and cures here. Suffice it to say that the literature provides plentiful basic causes. The additional causes, just enumerated, constitute the main theme of this book. They will form the key factors to unleashing the quantum improvements in cost, value, and productivity. They will form the bulk of the chapters in Part II which will deal with the technologies—their features and benefits—and in Part III the complete step-wise approach to get the projects to succeed will be discussed.
Are we investing too much money in information technology and information systems? This is a question many of today’s CEOs and boards of directors ponder. Until recently, companies have made major investments in IT, trusting that this measure alone would increase productivity. Now decision makers are increasingly questioning whether IT projects actually create value.
Jurgen H. Daum, writing about adding value through IT investments,3 cited statistics from a survey conducted by CFO Magazine: Only 14% of executives state that their companies’ IT investments achieved the expected return on investment (ROI), whereas 74% were unsure of whether they had spent too much money on IT in the past three years. Similarly, in June 2007, as I was talking with Ajay Agrawal, a vice president of a financial services company, he mentioned that most IT projects fail the first time they are attempted. Clearly, doubts are being raised about the benefits of IT investments, and managers are becoming more careful about giving the go-ahead to IT budgets.
These reservations are apparently warranted. According to a study published by the Gartner Group in October 2008,4 of the $570 billion that flowed into IT investments worldwide, a high percentage was spent in vain. My estimate of this wasted spending is around $246 billion. Figure 1.1 summarizes the basic reasons for the failure.
FIGURE 1.1 Why Projects Fail
Numerous studies prove this failure in IT project in particular. One important study, however, set out to understand what the projects that did succeed contribute to business performance. The survey results are discussed in the next section.
Harry’s Survey
I collaborated with Harry Sakamaki of SITA Corporation to conduct a survey of companies in the United States to provide bottom-line KPIs. We selected 16 companies in the manufacturing sector representing a mix of small- to midsize and some large companies. We solicited data from their CEOs, heads of IT, and their staff. Figure 1.2 gives the highlights of this survey.
In Figure 1.2, rows 1–14 that are in the smallest type size give the KPIs with respect to systems infrastructure; KPIs in rows 15–25 represent the same of the business performance but specifically of the supply chain; the ones in rows 26–34 are the KPIs of the business performance representing the bottom lines. The improvements shown in the extreme right column are the improvement percentages of each row. Do not add these percentages; they must be looked at as the individual performance improvements.
FIGURE 1.2 Harry’s Survey Summary
Highlights from Figure 1.2 are that bottom-line performance improvements are in the 3% to 10% range. This is a very low number. In fact, it is lower than the earlier number, which said that fully 75% of firms do not fulfill stakeholders’ expectations. Whether the figure is 3% to 10% or 25%, it is clear that the success rate as measured by performance improvement is very low. I have tacitly recognized the sad state of affairs of low returns for a long time. My conversations in the field always confirmed that some regular culprits will raise their ugly heads whenever one’s guard is down. When I pondered why I often succeeded in delivering values via projects yet sometimes did not, a pattern emerged. This pattern was based on the best practices I employed by design or sheer luck. This is what I want to share with you. The rest of this chapter describes the scorecards and how the major parts of this book are organized. After reading the next section, you will understand the technologies and how to create scorecards that are based on aligning investments and can drive the achievement of business performance.
Scorecards and SCOR Cards
Scorecarding technology has been around since early 1980s. First there was the Balanced Scorecard methodology, where nonfinancial processes are measured based on their impact on company performance. The term SCOR card is based on the supply chain operations reference model that was introduced in the mid-1990s for measuring, monitoring, and thereby driving the performance of supply chains. In my practice, I used SCOR cards very successfully. However, I grew into SCOR cards using the Balanced Scorecard. The main difference between the two is that the SCOR card is geared more specifically around the KPIs of the supply chain operations whereas regular scorecards can be applied to all enterprise operations. And best of all, I could use either scorecard to impact the development of strategy to align the IT investments with business performance. An example of the potential power of scorecards comes from a conversation I had with the president of a major automotive company in India. I had redesigned his supply chain and presented him with his company’s scorecard. It would drive the implementation and huge reduction in his inventory cost. Upon hearing my presentation and reviewing the scorecard, he said, “Sam, I will hang it right behind my chair in my office so that every time any of my staff comes to see me, they see where we are, where our goals are, and who we have to beat to become the best-in-class business.” The scorecard had all of that information in it. Part II of this book describes knowledge essential to creating scorecards. Part III presents case examples that show how scorecards can be developed and can drive the development of a realistic strategy that then can be used to implement the IT investments and exploit the business benefits (i.e., the business performance).
Promise of Technology: Functionality, Key Performance Indicators, and Business Benefits
Part II explains the concepts behind the value drivers in the value chains from which KPIs can be extracted; they become the basis of functionality required and finally the planning for implementation and development of a business case to benefits exploitation. Thus Part II shows practitioners and stakeholders what is practical to get from the technology. It is divided in three chapters:
Chapter 2
Strategic Enterprise Management
This chapter examines the functionality of strategic enterprise management (SEM) in detail and discusses its benefits
Chapter 3
Supply Chain Management
This chapter examines the functionality benefits and KPIs of supply chain management (SCM). SCM impacts the bottom line the most. A 50% improvement in SCM can increase the net before taxes by as much as 100%.
Chapter 4
Product Life Cycle Management
This chapter examines the functionality, benefits and KPIs of product life cycle management (PLM). This is the application that impacts the top line the most.
Deliver on Promises: Scorecard Methodology to Align Investments to Business Performance
Part III describes scorecard methodology to align IT investments with business performance. The chapters describe all the areas and activities that have to happen to estimate the benefits and exploit them so that the promises are fulfilled. Note the activities are far more than mere project management. My 44 years of field experience in the management of large and complex projects serves as the basis for this part.
Chapter 5
Strategy
Enterprise Strategy
This chapter is about developing IT strategy that is responsive to business strategy. IT strategy formulation or synchronizing it with the enterprise strategy is based on business goals and strengths, weaknesses, opportunities, and threats (SWOT) analysis. This chapter is the driver for KPI, benchmarking and SCOR carding, as-is and to-be modeling, and business blueprinting. It drives planning for all the activities in the realization phase, such as solution architecting, gap analysis, roll-out planning and configuring, as well as the planning for change, quality, risk, and test management, training, performance measurement, and performance tracking.
Key Performance Indicators
Key performance indicators are the measure of a business goal. Unlike most projects, which concentrate on IT-oriented KPIs, these are the business goals as extracted from the key stakeholders of the project. Remember however that there are KPIs that are action/independent variables that impact the business goals or dependent KPIs.
Benchmarking
Here the comparison is done with the best in class and average in class and the targets the company chooses for KPI (business goal) improvements.
Value/Benefits Estimating
This section provides a succinct calculation of the value contribution as derived from the SCOR card.
Business Process Reengineering
Here the workflow modeling of the as-is and to-be views of the enterprise and processes is covered.
Chapter 6
Realization Phase
Solution Architecting
Translating the business blue print to the hardware, software and network structures creates solution architecture. This solution is entirely IT-centric.
Gap Analysis
This activity pertains to determining whether there is difference between the business requirement and the selected vendors’ technology functionality.
Roll-Out Planning
Various alternatives for rolling out solutions are considered. This planning is very important for a global project.
Configuration Planning
This section defines the activities of configuring processes and the ways to plan.
Chapter 7
Human Factors
Project Management
Here various models of project management are presented along with the characteristics of an ideal project manager. Critical success factors and how to do them are given. Also presented are the burning issues of the day in this discipline.
Project Champions
Project champions are the most essential people, the invisible reasons for a project’s success. This section discusses how to work with them and get them interested in the project.
Business Case Development.
This section discusses all the human and political aspects of taking the business case to the stakeholders and the board to sell the project.
Chapter 8
Umbrella Considerations
Change Management
This section demonstrates how to rigorously manage the change. Most projects fail because they were not done well enough to proactively manage the change that promotes success.
Implementation Time Risk Analysis and Mitigation of Risk in Enterprise Systems.
This section shows how to estimate and eliminate risk in the various phases of the project. Recovery models are also given.
Quality Management
This section discusses quality as applied to software and explains how to establish and enforce the quality regimen.
Communications Management
This section describes how to plan and enforce the proactive communication system.
Test Plan and Test Procedures
Here we discuss various aspects of the test plan, test procedure, and test methodology through the entire life cycle of the project. This section includes validation and reviews.
Training
This section explains who to train and how much to train. Without a successful graduation from a training program, the project will not succeed.
Chapter 9
Performance Measurement
This chapter explains how to do ongoing measurement and track the KPIs. It discusses where and when KPIs should be presented to the stakeholders in order to continue to buy their support.
Chapter 10
Summary
This chapter provides the overall summary of the book.
Bibliography
“Danger Signs on the Road to Success,” Chaos News Letter, August 17, 2001.
Daum, Jurgen H. “Strategy—A Holistic Approach: Adding Value Through IT Investments,” Sapinfo.net.
Gartner Group. “Most Business-Launched Virtual Worlds Fail,” May 16, 2008, www.informationweek.com/news/personal_tech/virtualworlds/showArticle.jhtml?articleID=207800.
Gartner Group. “90 Per Cent of Corporate Virtual World Projects Fail,” May 15, 2008, www.gartner.com/it/page.jsp?id=670507.
Gonsalves, Antone. “Gartner Backtracks on Earlier IT Spending Growth,” Information Week, October 13, 2008.
Krigsman, Michael. “Why IT Projects Fail,” August 10, 2007, www.softwaremag.com/L.cfm?doc=newsletter/2004.zdnet.com/projectfailures/?p=329.
PM Hut Admin. “Why Do Projects Fail?” August 30, 2008, www.pmhut.com/why-do-projects-fail.
Standish Group. “Project Success Rate,” Software Magazine, January 15, 2004.
PART IIPromise of Technology
This part serves as an introduction to three chapters: Chapter 2, Strategic Enterprise Management, Chapter 3, Supply Chain Management, and Chapter 4, Product Life Cycle Management. These chapters cover the promises of technologies and explain the broad functionality of each application. Also included is a description of the key performance indicators (KPIs) of each area, organized as KPIs that act as the value drivers and KPIs that measure the driven values. Taken together, these chapters provide a substantive knowledge base that will give the reader knowledge of how a bottom-line improvement can be achieved and what technology can be used as an enabler. Figure IIA describes the interrelationships between these concepts.
FIGURE IIA Overview of Development of Scorecard and Strategy
CHAPTER 2Strategic Enterprise Management
Introduction
Chief financial officers and chief information officers have long struggled to satisfy the strategic information requirements associated with managing in an organized, structured, and efficient manner. The promise of integrated enterprise resource planning (ERP) systems to fulfill these requirements has been only partially realized. Companies have reduced cycle times and costs while increasing service and customer satisfaction levels. Yet many fundamental strategic questions about customer, channel, segment, service and product profitability, and the financial and nonfinancial performance of key business segments remain unanswered. Strategic Enterprise Management (SEM) deals with the higher-level tasks to:
Measure business performance against simulations, targets, and benchmarks, using a Balanced Scorecard, value drivers, and management. Balanced Scorecard is a performance measurement technique; the SCOR card is similar but applies to the supply chain domain and is based on the supply chain operations reference model.
Automate and accelerate the entire business consolidation process.
Control and monitor business using value-based management principles.
Change static operational planning cycles into continuous, rolling forecasts.
Integrate business strategy with operations, planning, and employee goals and incentives.
SEM is a suite of tools designed to enable advanced cost management and performance measurement capabilities while allowing managers to focus explicitly on driving increased shareholder value.
SEM affords companies the opportunity to efficiently and systematically measure the performance of key business processes and the value they contribute to the business. SEM unlocks the complex array of data populated within the ERP environments, offering companies an effective way to utilize the full capabilities of these applications. Specific benefits include:
Improved strategic decision making
Improved tactical decision making
Increased organizational alignment
At the core of SEM is the principle that whatever is not automated but needs to be automated should follow a rigid discipline consisting of the following rules:
Focusing on value propositions and the development of a business case
Establishing clear objectives
Facilitating return on investment estimates
Considering continuous improvements to ensure stabilization and user satisfaction to ensure the most cost-effective approach through onsite/offshore deployment
The goal of Strategic Enterprise Management is the (re)definition and implementation of strategic goals and visions based on economic constraints gearing toward a competitive advantage of the corporation, while constantly improving and questioning strategic decisions. SEM also keeps future developments in mind. Because of the rapidly changing markets, it is very important that strategic decision processes are continuously accelerated and improved.
Core Activities with Strategic Enterprise Management
Strategy Definition
A future strategy cannot be implemented and validated immediately. Therefore, thorough planning is mission critical. Initially, the strategy is created, communicated, and discussed by using easy-to-understand graphical models. Simulation technology can be used for validation. Finally, the clear communication of the strategy is a key success factor for the implementation. This communication can be done by publishing the strategy to all relevant stakeholders and then deriving measurable performance indicators based on the abstract goals and visions.
FIGURE 2.1 Direction of Strategic Enterprise Management
Controlling
In addition to monitoring performance indicators, one main goal of controlling a process or the entire enterprise is to define and monitor early-warning indicators that look ahead of the current situation. All controlling results play an important role in redefining the corporate strategy.
Analysis
Data from past business processes are collected and consolidated. In some cases, this is required by law; even if it is not, data collection can help tremendously in evaluating and redefining corporate strategies. (See Figure 2.1.)
How to Create a Strategy
Initially an external consultant and corporate management carry out a strength, weakness, opportunity, threat (SWOT) analysis. During the analysis, the strengths, weaknesses, opportunities, and threats of the enterprise are identified.
Based on the SWOT analysis, the main areas of interest are identified and are further investigated. The analysis results in a redefinition of the areas identified, which are described by means of various models. The models for a process road map show process structures and interfaces as well as organizational units that are involved. In addition, critical performance indicators are identified. The strategic decision process may also be subject to redesign in order to implement faster decision processes and improve the support for strategic decisions.
All models created in this stage are communicated between the various stakeholders.
Tools Supporting Strategic Enterprise Management
Business Management Tools
Business management tools consisting of models embodying cause effect variables along with goals and limits, reports and dissemination methods support by creating meaningful and consistent corporate models. The models are the starting point for ongoing discussion, analysis, simulation, and optimization. In many cases, the tools support the publication of the models.
Portal Solutions
The best corporate strategy is worthless if no one knows about it and if the enterprise is not aligned with the strategy. Corporate portals can support you in publishing strategies and in delivering user-specific content. These portals also act as a single access point to all relevant corporate information, which helps to reduce the strategic decision life cycle.
Analytical Tools
Ideally, every strategic decision is based on up-to-date corporate information. Business Intelligence solutions can offer a highly valuable advantage to corporate management during the process of strategy (re)definition.
Collaboration Services
Especially in larger corporations, strategic decisions are based on complex and labor-intensive decision processes. Collaboration services can help to provide the common ground for these processes.
SEM enables companies to execute strategies quickly and successfully and to manage business performance throughout the entire organization. It supports integrated strategic planning, performance monitoring, business consolidation, and effective stakeholder communication, thereby enabling value-based management.
The listed business goals and objectives can be achieved through the implementation of these collaboration processes:
Improve customer service.
Offer 24×7 customer self-service.
Personalize customer interaction.
Raise competitive barriers to entry.
Improve product/service quality.
Improve forecast accuracy.
Increase revenue.
Extend market share.
Develop new markets.
Improve the sales lead generation and process.
Reduce time to market and volume.
Provide efficient campaign planning and management.
Gain market share.
Lower working capital requirements.
Improve capacity utilization.
Reduce operating costs.
Figure 2.2 is an architectural presentation of an SEM.
FIGURE 2.2 Architecture of an SEM
Essential Support from SEM Application Modules
Stakeholder Relationship Management
Stakeholder relationship management communicates strategies and investor information to major stakeholders and collects information and feedback via the Internet.
Strategy Management
Strategy management communicates strategies and objectives throughout the entire organization, using the Balanced Scorecard. It also supports value-based management, management by objective (MBO), and strategic initiatives.
Performance Measurement
Performance measurement monitors the performance of strategic key success factors and integrates external and internal benchmarks into the Balanced Scorecard and the Management Cockpit.
Strategic Planning and Simulation
Strategic planning and simulation supports strategic and business performance management through scenario planning, dynamic simulation, and integration of strategic and operational planning.1
Business Consolidation
Business consolidation consolidates actual and plan data supporting all aspects of legal and management consolidation.
Enterprise Management
Enterprise management integrates business processes and provides predefined, closed-loop business scenarios and predefined metrics to measure the effectiveness of business operations and enable immediate corrective action. Analytical applications (analytics) are built on consistent data stored in the data warehouse and are based on a variety of business areas. Business analytics are discussed in the next sections.
These business goals and objectives can be achieved through the implementation of these processes:
Improve customer service.
Offer better service levels.
Improve product/service quality.
Improved quality and accuracy.
Increase revenue.
Maximize profitability by customer.
Enable cross-sell/up-sell capability.
Improve customer retention and loyalty.
Improve sales lead generation and process.
Gain market share.
Provide efficient campaign planning and management.
Reduce time to market and volume.
Lower working capital requirements.
Improve cash management, minimize borrowing.
Increase visibility to vendor/supplier inventory.
Reduce inventory carrying costs.
Improve capacity utilization.
Reduce material and component obsolescence.
Lower work-in-process inventory.
Lead to fewer returns, more efficient process.
Lead to lower-cost procured goods and services.
Manage fixed assets.
Optimize capital equipment and asset utilization.
Reduce operating costs.
Business Analytics
Customer Relationship Analytics
Customer relationship analytics measures and optimizes customer relationships and include applications such as profitability analysis, market exploration, and customer-retention analysis. Customer relationship analytics allows you to analyze customer requirements systematically, enabling you to increase customer loyalty or acquire new customers by applying the results of your analysis and executing them in your customer management system.
E-Analytics
E-analytics analyzes the online customer experience, allowing companies to maximize their return on Web site investments, build one-to-one relationships with customers over the Internet, and improve competitiveness in the e-business and e-market world.
Supply Chain Analytics
Supply chain analytics measures and optimizes the value chain by supporting collaborative planning and forecasting, procurement analytics, and production efficiency analytics.
Financial Analytics
Financial analytics allows for business planning and forecasting, activity-based cost and profitability management, and working capital as well as investment management.
Human Resource Analytics
Human resource analytics analyzes and evaluates an organization’s workforce by supporting workforce planning and forecasting, benchmarking and reporting, and by aligning the personal scorecard to MBO goals.
Product Life Cycle Analytics
Product life cycle analytics measures and optimizes the life cycle of a product by supporting product portfolio management and various aspects of life cycle cost management.
Business Intelligence and Decision Support
Business intelligence integrates all your corporate information so you can turn information into insight, insight into action, and action into improved business operations.
Flexible Reporting
Flexible reporting provides reporting and analysis scenarios and enables users to evaluate information across company boundaries. It consists of decision support tools, such as query, reporting, and multidimensional analysis for collaborative decision making, including data exploration and data visualization tools.
Information Dissemination and Sharing
Information dissemination and sharing enable users to organize and share information according to their specific role and information needs within the enterprise portal. It combines structured and unstructured information, internal enterprise information with external data, and allows executives, knowledge workers, and business partners to use the Internet, intranet, or mobile devices to browse the enterprise’s data warehouse and business intelligence.
Performance Monitoring
Performance monitoring provides a complete view of all corporate business operations and information needed to make profitable decisions, set strategy, and measure the results of business tactics.
Planning and Simulation1
Planning and simulation link strategy with goals and simulate the impact of changes.
Ad Hoc Analysis
Ad hoc analysis allows users with specific information needs to create ad hoc queries, analyze data via a standard Web browser, and adjust strategy to meet changing markets and make immediate decisions.
Collaborative Decision Support
Collaborative decision support allows decision makers to collaborate, add comments to reports and key figures, and automate approval processes so that they can participate in decision making within the wider context of the enterprise.
Data Collection and Integration
Companies need to collect, organize, and analyze data quickly and efficiently to meet changing market needs. Data collection and integration enable the integration of data from multiple sources used to support the decision-making process based on a unified data model.
Content Management and Collaboration
Content management and collaboration help companies identify, manage, and share information.
Key Performance Indicators
Detailed key performance indicators (KPIs) given in Chapters 3 and 4 form the universe of KPIs applicable for SEM. The subset of these KPIs should be chosen based on the wishes and direction of management with respect to what they want to monitor and what they want to modulate for the desired result.
Case Example
Some time ago, in my work as a chief information officer, I oversaw the implementation of a full suite of enterprise software. Once the implementation was finished, I went to the executive team and requested a role related directly to the product and management of business processes. I was assigned an interesting task. It was not what I had requested, but it evolved precisely into product definition and product management, based on modeling and simulation. Before describing this role and how it evolved, a little bit of information about the company and product is useful.
This semiconductor company manufactured electronic packages, which are used as chip carriers. Its customers were the likes of Intel and Motorola.
My boss told me to study the requirements of the end users—in other words, the requirements of our customers’ customers (e.g., Intel’s customers, such as Dell or HP). In that context, the requirements were driven not only by Dell or HP but by those of their end users. Our company would have to furnish the packages to meet these new requirements in the future.
Based on a review of some published literature, I could determine impending requirements that we would have to be responsive to. However, the translation from one stage to the next was very much a guessing game, and this did not satisfy me. So I began toying with the idea of building a model that could predict the impact of end user requirements on the product characteristics of packages that we would have to manufacture. After I completed, tested, and verified the predictability and accuracy of this model, I was asked to include the impact of design features on manufacturing cost. With this model we could simulate the effect of design assumptions on product characteristics and product cost. Ultimately this cost performance study could be used with various input (customer requirements) scenarios to start new product initiatives or stop some that were already underway.
I call this model SLAM, for System Level Architectural Model. It includes detailed items such as concept, scope, concept chaining, physical model, model architecture, simplifying assumptions, model statistics, salient features, range of usage, and implementation. SLAM was developed as a software tool. It is comprised of 76 highly complex mathematical equations derived from the fields of device physics, material science, very large scale integration technology (VLSI), and design sciences. It has 76 independent variables (design rules, design requirements) and 76 dependent variables (product characteristics) in the performance domain alone. It can be categorized in the general domains of computer-aided design, computer-aided engineering, concurrent engineering design for manufacturing, predictive engineering, or computer aided product engineering (CAPE). This tool is a system-level, early-stage architectural design aid. Its area of application lies in electronic systems. It can be applied in the design of chips, their packages, printed circuit boards, and entire systems such as personal computers, work stations (WSs), servers, and all the way up to the supercomputers.
SLAM was used to develop a new paradigm of cost performance studies, described in Figure 2A.
FIGURE 2A Virtual Reality, Model, and Assumption-Based Simulations
In Figure 2A, the needs (input requirements) are fed to the performance models (SLAM). These models use design rules (input requirements) and produce performance parameters (output variables). Performance parameters are then input to the cost models along with the manufacturing rules and the like, and cost is in turn computed. The result is cost and performance information available simultaneously for a set of design rules (input requirements). Cost or performance can be optimized iteratively, in a closed-loop feedback manner. The interesting thing is that this can happen long before detailed design of the product or even the physical manufacturing process to produce electronic packages has been accomplished. It is done at an early architectural stage and with few details on hand. This model was used extensively2 in the management of the business with high predictability and accuracy, as testing by outside agencies confirmed. Specifically, this tool set has been used in these areas:
Printed circuit board manufacturing
Product line management
Electronic forecasting
Business plan and marketing management
Business development
New materials invention
Research and development strategy formulation
In each of these cases, there was a need to know certain facts without the detailed knowledge. These details usually come from having done a detailed design of the product, material, process or the technology, depending on the case in hand. The needed predesign stage knowledge—both design rules (input variables) and product characteristics (output variables)—to iterate successfully included:
Product footprint
Number of planes
Delay
Wirability
Power
Trade-off of cost with performance parameters
Cost/performance comparison of competing technologies
This effort was well received. It seemed to fulfill a long-felt need of various personnel who needed to know cost performance of new products, processes, technologies, and materials. People need this kind of information at very early stages in the life of new products. If they have it, fact-based decision making can take place, saving time, money, and costly mistakes. Working on SLAM was very fulfilling to me personally. The encouraging results reconfirmed my belief that model-based industrial virtual realities can be created successfully and be commercially useful.
Bibliography
Fahey, Liam. Competitors. New York: John Wiley & Sons, 1993.
Bansal, Sam. “Cost Estimation of Electronic Systems-Technical Cost Modeling,” Paper presented at Pemas 94 conference, Penang, Malaysia, May 1994.
Bansal, Sam. “Practical Applications of Models and Their Benefits, Evolution of a New Paradigm,” Journal of International Federation of Automatic Controls (October 1994).
Bansal, Sam. Simulation in the Life Cycle of Manufacturing Systems. Paris, France: Inria, 1995.
Bansal, Sam. “Trends and Methodologies in Business Consulting—KPI-based Performance Improvement,” Paper presented at the International Federation of Automatic Controls, Barcelona, Spain, July 2002.
Strategic Enterprise Management—Unlocking the Potential of ERP. CSC India, May 2006.
CHAPTER 3Supply Chain Management
Introduction
Advanced planning and scheduling (APS) is a new technology, a revolutionary breakthrough, and the greatest innovation since the assembly line. It aims to do optimized planning and scheduling of all the manufacturing resources and personnel, keeping in view the constraints (i.e., man, machine, material, and time). It may surprise you to learn that companies have benefited from APS techniques for over 30 years. APS is a collection of well-established solution methods made more accessible and effective by incremental improvements in a wide range of technologies. Thus, an experience base exists that companies trying to implement APS can draw on. In the 1990s, the APS market boomed and products proliferated. Consumer packaged goods companies like Procter & Gamble, Colgate, and Gillette started to use more APS at that time. Although there were some early adopters in this market segment, this industry as a whole was slower in using APS techniques. This is true of the paper industry as well, despite its sophisticated approaches for trimming paper and leftover materials.
A number of companies that had been able to implement relatively simple tools for manufacturing scheduling discovered they needed a more sophisticated approach to the number of SKU (stock keeping unit) and location combinations in their distribution networks and for their forecasting capabilities. The simple tools used to generate revenue forecasts choked on the number of SKU and location combinations needed to provide the level of detail required for operational decisions.
