By: Bernard (Bernie) Boar
Information Technology Consultant
This white paper was commissioned by NCR's Communication Industry Line of Business.
Table of Contents
2.0 A Data Architecture Perspective of Data Warehousing
3.0 Data Architecture Choices
4.0 Strategy and Sustainable Competitive Advantage
5.0 Strategic Thinking
6.0 Data Warehousing and Strategic Thinking
7.0 Data Warehousing as a Rising Tide Strategy
8.0 Data Warehousing and Strategic Paradox
9.0 Data Warehousing and Manueuverability
This white paper discusses the relationship between data warehousing, and strategy and strategic thinking. As background, business application types and data architecture are also discussed.
Our strategic analysis of data warehousing is as follows:
When your strategy is deep and far reaching, then what you gain by your calculations is much, so you can win before you even fight. When your strategic thinking is shallow and near-sighted, then what you gain by your calculations is little, so you lose before you do battle. Much strategy prevails over little strategy, so those with no strategy can only be defeated. So it is said that victorious warriors win first and then go to war, while defeated warriors go to war first and then seek to win. (1)
It is obvious to anyone that culls through the voluminous information technology (I/T) literature, attends industry seminars, user group meetings or expositions, reads the ever accelerating new product announcements of I/T vendors, or listens to the advice of industry gurus and analysts, that there are four subjects that overwhelmingly dominate I/T industry attention as we move into the late 1990s:
The fundamental strategic logic of the first three are fairly well understood.
Table 1. Four key subjectsm dominate I/T landscape
I/T processing architecture
Knowledge and learning
Data warehousing is the last of the four dominant trends but the underlying strategic logic has not been well articulated. As shown in Table 2, numerous companies in multiple industries are committing to and achieving tremendous benefits from data warehousing. Typical reasons given are faster and better decision making, push down employee empowerment, leveraging of operational data, scenario analysis, customer intimacy, analysis of anything and everything, and process control. These are certainly good reasons but are they adequate motivations to maximize the return on data warehousing? What is the underlying deep and compelling logic of data warehousing? How are we to understand data warehousing strategically so that we may fully optimize the investment?
Table 2. Various Industry Uses of Data Warehousing (sample industries).
This white paper will attempt to answer those questions. We will demonstrate that to understand data warehousing strategically, we must first understand strategy and strategic thinking. Once we understand those concepts, the strategic logic of data warehousing becomes clear and the path to an optimum implementation emerges. We will demonstrate that data warehousing is best appreciated as a realization of the deep and far reaching strategic idea of a rising tide strategy. The maximum return from data warehousing occurs when it is conceptualized, implemented, managed, and evolved within that context. Before doing that, however, it is beneficial to level set and review the data architecture origins of data warehousing.
The business processes of the enterprise are automated in the form of business applications that collectively compose the business systems portfolio. Companies have innumerable processes requiring I/T capability. Typical applications include order realization, customer service, contract administration, product development, benefits administration, staffing, budget development and monitoring, and information sharing (E-mail, conferencing, team support, etc.). The list is seemingly endless.
As illustrated in Figure 1, the business practices can generally be partitioned into two broad classifications:
"The Business Applications" are often called On-line Transaction Processing Systems (OLTP) or Operations Support Systems (OSS) and have the following general attributes:
Business Performance is the payoff advantage from these types of applications. Consequently, they will often contain exception monitoring subsystems used to advise management when an abnormal situation has occurred or an undesirable pattern is developing.
"The About-The-Business Applications" are often called Information Center Applications (decision support, modeling, information retrieval, ad-hoc reporting/analysis, what-if, data warehouses, etc.). This class of applications are retrieval/analysis/report/information sharing oriented. The data sources are often triggered extracts from OLTP or OSS applications or public information services. These applications have the following attributes:
Better knowledge about the business and the development of superior business strategies is the payoff from this class of applications.
Applications are often continuous in capability and their functionality may not be discrete. Though an application will naturally migrate to one classification as its primary definer, it may have subsystems that are more aligned to the other type. Both "The Business Applications" and "The About-the-Business Applications" with all the endless variations are built on top of a data architecture and a processing architecture that jointly compose the I/T architecture for the business. (More and more, the emerging client/server architecture that is replacing the aging host centric processing architecture.)
Business applications are performed by programs that collect, create, modify, retrieve, and delete data, and programs that use, analyze, summarize, extract, or in other ways manipulate data. Data is the common thread that ties together the extensive corporate application portfolio. Data, as it is transformed into information as it flows between users, can provide current advantage in the form of superior operational systems and future advantage in the form of superior analysis for planning. How the data asset is positioned is of vital long-term importance to the health of the enterprise.
Increasingly, corporations are recognizing that the purposeful management and leveraging of the corporate data asset must take on increased attention in the 1990s. In the 1970s, management attention was focused on hardware cost. During the 1980s, management's attention shifted to software as both a growing element of the I/T cost structure and the source of advantageous applications. In the 1990s, management will increasingly focus on data exploitation as the path to improved customer service, cooperation with suppliers, and the creation of new barriers for competitors.
Data Engineering theory (Data Engineering is the discipline that studies how to model, analyze, and design data for maximum utility) indicates that there are four generic data environments on which to build business applications. For a variety of technical and architectural reasons they are not equally advantageous.
Dedicated File Architecture: Each application has a set of privately designed files. The data structure is tightly embedded with the application and the data files are owned by the application.
Closed Database Architecture: A database management system (DBMS) is used to provide technological advantage over file systems (exemplary advantages are views, security, atomicity, locking, recovery, etc.) but distinct, separate, and independent databases are still designed for each application. The DBMS is used as a private and powerful file system with the data remaining the proprietary property of the application. As is true with the Dedicated File Architecture, there is a high degree of data redundancy and frequently poor data administration. "Spaghetti-like" interfaces move data between the Closed Databases. Since these interfaces often have to convert, edit, and/or restructure data as it moves between proprietary definitions, they are often called "data scrubbers" or translators. "Data scrubbers" do not add value; they compensate for inadequate data administration.
Subject Database Architecture: Data is analyzed, modeled, structured, and stored, based on its own internal attributes, independent of any specific application. Data is administered as a shareable resource through a data administration function that owns the data for all potential users. Extensive sharing of data occurs through application sensitive views. Subject Databases run the day-to-day operations of the enterprise.
Decision Support Database Architecture: Databases are constructed for quick searching, retrieval, ad-hoc queries, and ease of use. The data is normally a periodic extract from a Subject Database or public information service. To minimize the number of extracts and to insure time/content consistent data, data is shared at the corporate, departmental and local levels-not extracted per user. Data definitions are kept synchronized with the source databases to insure the ability to inter-relate data from multiple subject database extracts without the need to resort to "data scrubbers." Decision Support Databases are used to analyze the enterprise.
The recommended data architecture is a mixture of the Subject Database and Decision Support Database environments. Subject Databases to support "The Business Applications" and Decision Support Databases to enable "The About The Business Applications." This dual database architecture is most advantageous for the following reasons:
Some data architects would prefer a single database environment where both OLTP and decision support needs are fulfilled concurrently against a single database and, thereby, eliminate duplication and extraction altogether. It is our assessment that the two user communities have fundamentally different and incompatible requirements that preclude this option. Table 3 summarizes the major points of conflict. These dichotomies present a formidable barrier to a single database environment.
Table 3. Subject Database and Decision Support Database Dichotomies. (Source: Implementing Client/Server Computing, Bernard H. Boar, Mc-Graw Hill, 1993)
When routine access of operational databases is given to decision support users, major problems can occur:
We may summarize our views on data architecture as follows:
Data warehousing is the modern term used to describe a mature and robust decision support database environment consistent with the model in Figure 3. It implies that decision support databases have been carefully selected and designed to provide maximum utility and that a powerful set of tools have been provided to users to maximize their ability to leverage and exploit the captured operational data.
While data warehouses today are primarily single, physical databases with staged replication to departmental and personal databases, it should be anticipated that with the emergence of industrial grade distributed database management technology, data warehouses will become logical databases that transcend physically distributed decision support databases.
From an academic perspective, the purpose of strategic planning is to provide direction, concentration of effort (focus), constancy of purpose (perseverance) and flexibility (adaptability) as a business relentlessly strives to improve its position in all strategic areas.
Strategy is mathematics and is equal to direction plus focus plus perseverance plus adaptability. At a very pragmatic level, strategy can be understood as finding a way short (the shorter the better) of brute force to accomplish one's ends. Strategy should be comprehended as the movement from a current position to a more desirable future position but with economies of time, effort, cost, or resource utilization. There is neither elegance nor insight in brute force but there must be both in strategy.
The eternal struggle of business is the struggle for advantage. The one with more advantage wins, the one with less advantage loses. The purpose of strategy is the building, compounding, and sustaining of advantage. Consequently, business strategy must focus on:
The lone purpose of business strategy is the nurturing of advantage. Advantage can be realized through infinite combinations of strategic moves.
While there are many ways to build advantage, all advantages can be classified into five generic categories:
So you win by being cheaper, more unique, more focused, faster, or more
adaptable than your competitors in serving your customers. At a minimum,
your advantages must satisfy your customers and, at best, delight or
excite them. Sun Tzu said:
If an action does not lead to the development of an advantage, it is of no strategic interest. The struggle always has been, and remains, the perpetual struggle for competitive advantage.
The culmination of advantage is the building of a set of sustainable competitive advantages (SCA) for the business. An SCA is a resource, capability, asset, process, etc. that provides the enterprise with a distinct attraction to its customers and a unique advantage over its competitors.
An SCA has seven attributes that are itemized in Table 4. Without a well designed set of sustainable competitive advantages, a business engages in a frantic life and death struggle for marketplace survival; after all, there is no compelling reason for consumers to choose that company's products or services.
Table 4: Sustainable Competitive Advantage (SCA).
The basic problem, of course, is to determine from where advantages emanate? How do we discover that which will be elegant and insightful so that we may win without using mindless brute force? The answer is that we postulate, analyze, and select strategic actions through strategic thinking.
Figure 4 illustrates three dimensions to thinking:
Most of the time, most of us, as illustrated in Figure 4, engage in mundane thinking to solve our daily problems. All we need to do, to meet our needs, is to think about one issue, in the present, and in the concrete, at a time. Anything more sophisticated would be overkill. This thinking pattern that we use to solve our daily problems is also referred to as point thinking because all our problem solving efforts converge on one point.
Figure 5 illustrates strategic thinking. A strategist uses the same dimensions as the mundane thinker but thinks dynamically within the thought bubble defined by those three dimensions. A strategist concurrently thinks about many issues in multiple dimensions at many levels of abstraction and detail over time (past, present, and future). Strategic thinking is a creative and dynamic synthesis that is the exact opposite of point thinking.
When looking at a problem, a strategist thinks about it in terms of certain established strategic ideas or themes. While new perspectives can always be developed, time and experience have demonstrated the power of looking at problems through certain enduring and tested strategic lenses. The following is a partial and representative list of powerful strategic ideas (see appendix for definitions):
All these themes, not surprisingly, converge on one grand strategic idea-the building, sustaining, and extending of advantage.
So a strategic thinker:
Since the combinations of strategic ideas is inexhaustible, strategic thinking is a very powerful way to develop insight about problems and solve them in novel, unanticipated, and creative ways. It is from this kind of thinking that advantage is born and nourished.
To understand data warehousing strategically, we should now appreciate that it is the consequence of strategic thinking, which means that it is the product (result) of some combination of strategic ideas. In this case, we must reverse-engineer strategic thinking. We know the result of the strategic thinking process, data warehousing, but what are the strategic ideas from which it emanated?
Data warehousing is an unusually rich strategic action. A strong case can be made that it is the product of numerous strategic ideas. If we argue, however, that data warehousing is the product of everything, we cloud our analysis. What are the key ideas that it realizes?
In Miyamoto Musashi's classical book on strategy, The Five Rings, he teaches that all weapons have a distinctive spirit. It is the challenge of a warrior to understand that spirit, master it, and become in harmony with it. In that way, there is perfect integration between the warrior and his weapon.
When I think about data warehousing's distinctive spirit, I think about time. More than any other strategic theme, I believe that what data warehousing does is permit one to compete across time. One competes across time as follows:
So the strategic ideas from which data warehousing emanates are the time-oriented ones:
These four strategic ideas are not just any set of strategic ideas; they are uniquely important. They are uniquely important because they overlay the time dimension of strategic thinking (Figures 4 and 5, lateral axis). Time is one of the three fundamental dimensions of strategic thought and data warehousing enables one to directly think in that dimension. Data warehousing is, therefore, not just another good result of strategic thinking, it is a very special result because it provides the tools to permit an organization, through the action of building data warehouses, to compete in the primary strategic dimension of time.
By giving your employees robust access to information about customers, markets, suppliers, financial results et al., you enable them to strategically learn from the past, adapt in the present, and position for the future. To the non-strategist, the mundane thinker, data warehousing is about spending (wasting?) money to let employees play with data. To the strategist, data warehousing is about winning the endless battle against time.
There is a special name given to certain strategic actions. This name is a rising-tide strategy. As the tide comes in, it raises all the ships in the harbor. The tide does not discriminate; it raises the dingy, the canoe, the yacht, the warship, and the ocean liner. The single action of the incoming tide raises all ships. All of them, by no action of their own, enjoy the effect of the rising tide.
A rising tide symbolizes the strategic notion of leverage. Leverage is what gives strategy muscle. Leverage means that you do one thing but multiple benefits derive from it. Typical words used to describe leveraged events are reuse, sharing, economies of scale, economies of scope, cascading, cloning, duplicating, layering, amplifying, and multiplying. Mathematically, the value of leverage equals individual payoff times instances of payoff.
Data warehousing supports a rising-tide strategy. By the single action of making information readily available to employees, we can bring benefits to all the employees as they go about their daily work. Hundreds of times everyday, employees solve problems, make decisions, control processes, develop insights, share information, relate to others, and attempt to influence others. All of these actions can be made more efficient and effective if better information is made available in a timely manner at the point of need. This is called informating your business. Data warehousing informates the business.
Rising tide strategies are cherished strategies. They are cherished because of the multiplier effect. So while it is excellent that data warehousing permits you to compete in time, what is remarkable about data warehousing is that it can permit all of your employees to compete across time. The single act of making information available creates distinct strategic leverage for the business. You have the ability to further increase your leverage by increasing the amount of data available and the number of employees to whom it is made accessible. Data warehousing is an awesomely powerful rising tide strategy. A strategy that is most effective when the tide is kept as high as possible and raises as many ships as possible.
In conducting our daily lives, purposeful opposition to our routine efforts does not exist. No one has the goal to deliberately and continually thwart our actions. We use what is called linear logic to solve our problems. Linear logic consists of using common sense, deductive/inductive reasoning, and concern for economies of time, cost, and effort to problem solve. One is commonly criticized, for taking a circuitous route when a more direct one is available. Daily life applauds the logical, the economic, and the application of common sense.
Business strategy, to the contrary, is executed against a background of hyper-conflict and intelligent counter-measures. Able and motivated competitors purposefully and energetically attempt to foil your ambition. Because of this excessive state of conflict, many strategic actions demonstrate a surprising paradoxical logic.
There are two types of strategic paradox:
Conflict causes strategic paradox to occur, bad logic becomes good logic exactly because it is bad logic, and the able strategist must learn to think and act paradoxically. Figure 6 updates our illustration of strategic thinking to extend the thought bubble to a fourth dimension of linear logic and paradoxical thinking. Paradoxically, strategists often have to recommend, to an unbelieving and astonished audience, that they should take actions that are directly contrary to routine business sense.
An example of reversal of opposites thinking is illustrated by the Kano Methodology: the Kano Methodology is an analytical method used to stimulate strategic thinking. The logic of Kano suggests that candidate strategic actions be divided into three types:
While this is solid linear thinking, the true brilliance of the methodology occurs next through paradoxical thinking. What is suggested is that after one has developed the excitement capability, that it be presented to the customer as a threshold attribute, i.e., paradoxically, the truly exceptional is most exceptional when it is the ordinary. What this does is position your capability as minimum ante to play the game. A customer may be willing to forgo the exceptional but will minimally expect and demand the ordinary. Since you can do it and your competitors can't, you create strategic distance between yourself and your competitors. While they struggle to do the exceptional as the norm, you raise the tempo of the game and work on converting another excitement attribute to a threshold attribute and ad infinitum. So the great insight of the Kano Methodology is not the linear thinking of excitement attributes, where most people would have stopped, but the recognition that maximum value and market disruption occurs when excitement capabilities are presented, paradoxically, as the ordinary (reversal of opposites).
Data warehousing also needs to be understood in terms of reversal of opposites. As shown in Figure 8 and characterized in Table 5, we are moving from the industrial society to the knowledge society (3). Knowledge becomes the premier weapon of advantage and business-to-business conflict migrates from competing on industrial age economies of scale to information technology fighting (I/T fighting). Key strategic information technologies such as client/server computing (4) and data warehousing, therefore, become subject to strategic paradox in their implementations.
Table 5. Comparative Ages. Knowledge is becoming the premier weapon of advantage and information technology is its basis.
The strategic paradox of data warehousing is that the strategist concerned about cost does not seek to use just enough means but an excess (5)of means to accomplish her end. Data warehousing achieves, paradoxically, its greatest value for the business when it is used in excess.
It is typical to observe customer teams engage in extensive and exhaustive cost justifications exercises (net present value, return on investment, cost/benefit justification, payback period, etc.) to convince cost conscious decision makers to approve data warehousing expenditures for a predetermined fixed set of uses. Their actions are linear logic, understandable but inappropriate because of reversal of opposites. When the weaponry shifts to I/T fighting, data warehousing becomes subject to strategic paradox and must be managed as such to achieve optimum results.
Consider a military commander who needs to engage his enemy. If he uses linear logic and deploys just enough resources, he will win but it will be an expensive (Pyrrhic) victory. If he applies a force far in excess of his opponent, he will achieve his ends with minor causalities. All the downstream costs of battle will be avoided (damaged weapons, confusion, wounded/killed soldiers, etc.) So at the point of conflict, the efficient commander does not seek to use just enough, but applies far in excess. He does not use accounting logic that holds in non-conflict situations but applies paradoxical logic, which rules at the point of battle.
In the information age, data warehousing is a key strategic weapon. As we have discussed, not only does it let you compete across time, it is a rising tide strategy that can elevate the strategic acumen of all employees. The attempt to cost justify such powerful weaponry in terms of net present value misses the whole point. When one invests in a national highway infrastructure, one does not cost justify or attempt to anticipate each event of commerce that will transverse the highway. Rather one has the strategic vision to understand that the strategic action is putting in place the enabling infrastructure and then you permit the marketplace to take care of the rest.
I believe the same is true with data warehousing. Once the infrastructure is in place, you have raised the tide for all employees. Your initial justifications are constrained by the limits of your imagination. How the data warehouse will ultimately be beneficial will emerge as your employees use it to respond to the dynamics of the marketplace and is exploited by their creativity. As they respond by using the excessive data warehouse, they will experience the same phenomena as the military commander. Though they will be spending in excess at the point of conflict, it will ultimately prove to be much cheaper because all the downstream business processes will be more efficient and effective. So while cost consciousness is always in vogue and a specific set of business needs to be addressed is welcomed, the absence of a priori adequate tactical savings should not dissuade you from the deep and far reaching strategic merits of an encompassing data warehousing initiative.
Unquestionably, it is easier to accept this paradox with regard to the military commander than data warehousing. This is because of the differences between cause and effect in the two situations. In the military situation, the cause and effect are tightly coupled in time and space. One can immediately see the results of the excess and correlate the success to that excess. In the data warehousing situation, the cause and effect are often dispersed across wide gaps of time and space. The use of excess data warehousing will have the desired effect but it will occur, perhaps, months later at a remote branch office.
The strategist must take solace in that she is engaged in deep and far reaching strategy, not tactical, short-term decisions. Things that are readily cost justifiable are things that are obvious and known to all. Strategic thinking is involved in seeing victory before it exists. How can anyone cost-justify the formless? (6) While cost conscious accounting methods are appropriate for sustaining wealth, strategic vision has always been the required ingredient to create it. (7)
So while it stretches and strains your business common sense, I believe that strategic paradox is an important dimension of the spirit of data warehousing. Ultimately, experience will prove that those who use it in excess, will achieve greater benefits then those who attempt to rigorously cost justify and constrain its deployment. They will learn that their approach is mathematically correct but strategically sterile. You do not want a rising tide, you want a permanent high tide of information with which you can win the battles for the past, the present, and the future.
Use data warehousing to position yourself so that you will surely win, prevailing over those who have already lost. Win through intelligence, not brute force. Cost justification is supposed to be a tool of strategy; not the reverse. Strategic paradox alters the rules; understand and justify data warehousing strategically.
Businesses must always be prepared to respond creatively to marketplace dynamics. The normal marketplace state is constant upheaval. It is, therefore, obvious that those companies that can navigate with greater alacrity, speed, and dexterity have a distinct advantage. In fact, with speed, dexterity, and alacrity as your allies, you can further exaggerate your advantage by deliberately promoting marketplace mayhem to the benefit of your customers and the detriment of your competitors.
Companies take two basic roles in engaging the marketplace:
There is now a global and fundamental marketplace transition occurring from national wars of attrition to global wars of maneuver and successful companies must adapt to this shift.
Sun Tzu described the eternal character of maneuver warfare when he
As advantageous as this is, it is not easy to do. It demands intelligence. Intelligence is both the sense of being smart and having knowledge about your competitors and customers. A maneuver fighter must continually zig and zag. The problem is to decide where and when to zig and zag. Done well, the maneuver fighter will delight customers and drive competitors crazy. Done poorly, the maneuver fighter will inadvertently zig or zag directly into the attrition fighter who will crush her.
Data warehousing is a prerequisite to a maneuver strategy. An infrastructure of knowledge must be available to engage in maneuver fighting. With a solid infrastructure of accessible information that can be manipulated as demanded by swirling times and circumstances, the maneuver fighter can make calculated judgments as to where and when to move. Without such knowledge, a maneuver fighter will make one guess too many and be cornered by the behemoth attrition competitor.
An instructive example of maneuver is happening in the retail industry. Historically, retailers engaged in push marketing where they purchased large volumes of an item from a supplier and then attempted to convince their customers to buy it. Retailers are now moving to pull marketing wherein they attempt to understand exactly what customers want to buy and provide a desired product assortment at ideal value points. The former doesn't require much knowledge about one's customers while the latter requires a great deal. The push retailer stands still and doesn't need much data while the pull retailer needs precise information to support continuous moving (zigging) and maneuvering (zagging) slightly ahead of customers.
So the final way to understand data warehousing strategically is to understand it as the necessary foundation for changing your business from being a slow and ponderous attrition fighter to an agile and quick maneuver fighter. Attrition fighters stand still. If you're going to stand still, of what value is knowledge to you? To the contrary, and as illustrated in Figure 9, a maneuver fighter is a business in constant motion. Maneuver fighters win through intelligence; not brute force. In this way, by virtue of knowledge-enabled maneuvering, you act sooner rather than later, you learn rather than repeat, you anticipate rather than react, you know rather than guess, you change rather than atrophy, you exceed rather than satisfy, and ultimately, through the accumulation of rathers, you win rather than lose.
Our strategic analysis of data warehousing is as follows:
Companies enter markets to win profits, not to engage in expensive and endless pitched battles with competitors. Data warehousing is of strategic value because it enables us to achieve the former while deftly avoiding the latter. This is the strategic spirit in which we should understand, implement, and manage data warehousing.
A very powerful introduction to a data warehousing business case said the following:
"The strategic intent of our data warehousing strategy is to enable the business to win in the marketplace every day, with every customer, and with every purchase. By repositioning our operational data and combining it with selected foreign data, we will empower our employees so that they can routinely delight and excite our customers. Through our unique appreciation of the value of our data assets, we will elevate our data warehouses to the point where they become a compelling and durable contributor to the sustainable competitive advantage of the business. In this way, data warehousing will enable the business to impress its attitude on the marketplace and prevail over its competitors who have already lost."
Have you implemented data warehousing with such a cogent strategic intent? Sun Tzu said:
"Strategy is important to the nation-it is the ground of death and life, the path of survival and destruction, so it is imperative to examine it. There is a way of survival which helps and strengthens you; there is a way of destruction which pushes you into oblivion." (9)
Data warehousing is a path to survival that helps and strengthens you. Our strategic understanding of data warehousing is complete.
1 The Art of War, Sun Tzu, Translated by Thomas Cleary, Shambhala Publications, 1988. The Art of War is generally recognized as the greatest treatise ever written on strategy. There are at least seven current English translations available; all with variant translations of the original Chinese. My strategic thinking is strongly influenced by Sun Tzu's teachings.
3 There are a growing number of popular synonyms for labeling the new era. As far as I can tell, if you take any of the following adjectives (cyber, information, knowledge, digital, networked, or virtual) and associate them with any of the following nouns (society, era, age, corporation, enterprise, or economy), you derive 36 alternative names. While they all yield a slightly different spin, they are all redundant attempts to name the newest era illustrated in Figure 8 and defined in Table 5. 36 names are sufficient and the gurus will cease to differentiate themselves by creating the same thing. Reuse is a virtue.
4 The strategic paradox of client/server computing is "To concentrate computing power, you must disperse it." See Cost Effective Strategies for Client/Server Systems by Bernard H. Boar, John-Wiley and Sons, 1996, for a complete analysis.
7 In a recent magazine interview (Industry Week: 11/20/95), Bill Gates, CEO of Microsoft, described the qualities of leadership as "vision, innovation, long-term thinking, and risk-taking." Maximizing your return on data warehousing requires these qualities. Blind adherence to net present value or any other economic justification method was not mentioned by Mr. Gates in the article.
Bernard H. Boar Biography
Mr. Bernard (Bernie) Boar is an accomplished author in the field of information technology. He has four published books on the critical topics of I/T strategy and architecture entitled "Cost Effective Strategies for Client/Server Systems," "Practical Steps to Aligning Information Technology with Business Strategy," "The Art of Strategic Planning for Information Technology: Crafting Strategy for the 90s" and "Implementing Client/Server Computing: A Strategic Perspective." His book "Application Prototyping: A Requirements Definition Strategy for the 80s" is now recognized as the seminal work on the subject.
Bernie has been published in CIO Journal, Computerworld, Journal of Systems Management, Journal of Business Strategy, Auerbach and Systems Development. He is a frequent speaker at leading industry conferences on I/T strategy, I/T management and client/server computing. He holds an MBA from the Baruch Graduate School of Business and a B.Sc. in Computer Science from the City College of NY. Bernie is a member of both the Strategic Planning Society and the Strategic Management Society. He has provided guest lectures at American Graduate School for International Business and Cornell University.
Bernie serves as an information technology strategist, architect, and consultant for NCR Corporation in Lincroft, New Jersey.
1. Cost Effective Strategies for Client/Server Computing, John Wiley & Sons, 1995
2. The Art of Strategic Planning for Information Technology: Crafting Strategy for the 90s, Chinese Mandarin Edition, 1995
3. Practical Steps to Aligning Information Technology with Business Strategy: How to Build a Competitive Advantage, John Wiley & Sons, 1994
4. The Art of Strategic Planning for Information Technology: Crafting Strategy for the 90s, John Wiley & Sons, 1993
5. Implementing Client/Server Computing: A Strategic Perspective, McGraw Hill, 1993
1. Understanding Object Oriented Technology Strategically, The Enterprise Systems Journal, 8/95
2. The Origins of Strategy: The Teachings of Sun Tzu and Machiavelli, The Journal of Business Strategy, 2/95
3. Application Prototyping, Managing Systems Development, 1/95
4. I/T - Business Alignment: A Strategic Perspective, The Handbook of Business Strategy, 12/94
5. Logic and Information Technology: Separating Good Sense from Nonsense, The Journal of Systems Management, 5/94