T E R R Y M 0 R I A R T Y
T E R R Y M 0 R I A R T Y
December, 1997
Another interesting year has passed. When I reflect on the events of the last year, I see the hopes of a new beginning for those of us who believe that information is a strategic resource. Many organizations are investing their IT dollars in only two initiatives: correcting the Year 2000 date problem and implementing a robust data warehouse for their business decision makers. The Year 2000 crisis has placed IT management business practices under some unwanted scrutiny. Likewise, data warehouse projects are floundering as the problems associated with delivering high-quality integrated data to management become evident. These projects require an enterprisewide, datacentric examination of the application portfolio.
To a great extent, management ignored those of us who for decades have tried to convince them that a project approach to application development doesn't meet the business's need for access to shareable data. Now we're seeing the ramifications of years of application development without a common data architecture, and we must be ready to step forward with viable solutions for enabling enterprisewide information sharing. I believe that the business rules approach will prove to be a key component in those solutions.
The business rules approach is now at the toddler stage of development. It's standing up and walking around, but it's not quite ready to take off running. As its "parents," we still have time to foster its development before turning it loose in the information management world. Id say we have about two years, because I believe that once the Year 2000 crisis has passed, our industry will be ready to embrace new ways of managing information. And business rules hold the promise of moving us to the next stage: knowledge management.
The books I've selected for this year's review support the theme of getting ready for business rules. Peter Senge's The Fifth Discipline provides a business case for why organizations preparing for the future need the business rule approach. David Hay's Data Model Patterns: Conventions of Thought continues the theme of the learning organization by providing data model templates that are common across many industries. Finally, Peter Aiken's Data Reverse Engineering. Slaying the Legacy Dragon provides practical advice on approaches for recapturing the data knowledge embedded within your existing application portfolio.
The Fifth Discipline: The Art & Practice of the Learning Organization, Peter M. Senge. Doubleday, 1990.
The Fifth Discipline discusses a business management concept fostered by the Massachusetts Institute of Technology called the "learning organization." According to Senge, a learning organization is one in which "people continually expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspiration is set free, and where people are continually learning how to learn together."
The five disciplines necessary to achieving a learning organization are systems thinking, mental models, personal mastery, shared vision, and team learning and dialog. Systems thinking is a set of techniques that help to identify, clarify, and change patterns of behavior. Mental models are "deeply ingrained assumptions, generalizations, or even pictures or images that influence how we understand the world and how we take action." Personal mastery is "the discipline of continually clarifying and deepening our personal vision, of focusing our energies, of developing patience, and of seeing reality objectively ... the essential cornerstone of the learning organization-its spiritual foundation." A shared vision is "the capacity to hold a shared picture of the future we seek to create." By rallying around a shared vision, an organization binds its people together so that they "excel and learn, not because they are told to, but because they want to." With team learning, an organization raises its overall IQ through the collective knowledge of the group. Senge explains each of these disciplines in great detail, using analogies and examples from organizations and communities that have applied them.
One of this book's primary themes is the need to look at the big picture, to see how things interrelate. While Senge recognizes the need to break a problem into manageable pieces, he argues that, in so doing, "we can no longer see the consequences of our actions: we lose our intrinsic sense of connection to a larger whole." He describes how most organizations tend to concentrate on "snapshots of isolated parts of the system, and wonder why our deepest problems never seem to get solved." He could be describing the application portfolio of almost any organization.
I believe that we apply the concepts of system thinking when we develop enterprise models. We discover the patterns of structure and processes that determine the framework for the organization's behavior.
These models are components of the mental models that need to become part of an organization's shared vision. Therefore, if an enterprise decides to adopt the learning organization principles, our models can become enablers of that strategy.
The objectives of the business rules approach and learning organization are the same. Consequently, you can expect to encounter many of the same obstacles when attempting to establish either discipline within an organization. In Senge's words: "Part of the problem is cultural. There seems to be a particular lack of appetite in many American corporations for the hard work of articulating our mental models conceptually. Developing explicit systems models of complex issues, both conceptual models and formal computer simulations to test alternative policies and strategies, strikes many action-oriented managers as too theoretical ... If we cannot express our assumptions explicitly in ways that others can understand and build upon, there can be no larger process of testing those assumptions and building public knowledge."
Disciplines of the learning organization are a business rules analyst's most important ally in the quest to incorporate a business rules approach into the information management practices of our organizations.
Data Model Patterns. Conventions of Thought, David C Hay. Dorset House, New York, 1995
If your organization has decided to become a learning organization, you can get a jump start on developing those mental models by using the models in this book as a starter set. Hay has applied system thinking to many of the processes any business must perform and developed a cohesive set of data models. Even if your company has never encountered the learning-organization ideas, this book is a valuable reference for developing data models.
Why would you want to start your modeling effort using an industry template rather than starting from scratch? Hay provides some excellent insights. In many cases, your subject-matter experts (SMEs) may know their business so well that they forget to describe the obvious. According to Hay, "the essential facts are the things that 'go without saying'-so they don't get said." Furthermore, your SME's only context for understanding the business is how the business systems are implemented within the current technology. So the SME may not be able to distinguish between what is essential to the business and what is baggage required to cope with constraints imposed by technology. You must be able to strip away the constraints of your current business system to examine the business's true essence.
A model template can be very helpful when used as a straw man to address much of the essential information components required by any organization competing within a specific industry. When properly used, such industry models can prime the pump in generating discussions with your business stakeholders. Furthermore, if your modeling team is new to the specific business industry, models such as the ones Hay presents can be invaluable training aids. You won't have to spend quite so much of your business users' time educating your team in the basics of your company's business.
Hay has added value to the modeling community by presenting examples of how models should be documented. Each diagram is accompanied by a narrative describing the business area being modeled. This narrative is not merely a regurgitation of the statements asserted through the diagram but provides an overview of the business area in whatever detail is required to convey the model's purpose fully. I found Hay's narrative on basic bookkeeping to be one of the best synopses of accounting principles I have encountered. Hay also illustrates the iterative nature of modeling by illustrating how a model's structure changes as additional business rules are considered and as generalization and abstraction analysis are applied.
For years, I have been an advocate of the "universal business model," which can be used as the basis of most enterprise models. I find it easier to customize than to always start modeling from a clean slate. Hay has increased my arsenal of model templates by sharing his wealth of experience in his book.
Data Reverse Engineering.- Slaying the Legacy Dragon, Peter Aiken. McGraw-Hill, 1996.
Today, one of the greatest stumbling blocks we face when migrating to a new business vision is the organization's data. Nowhere is the lack of systems thinking more evident than in the disparate data that has been designed to be optimal for a specific business function but falls to support the entire business process. Much of business reengineering involves restructuring data to enable all business processes. But before we can do this, we must know what data is available, how it is used, and what each data item means. Aiken's book focuses on this process.
The book opens with several case studies that illustrate the problem many organizations face when they encounter business opportunities that require data sharing. For example, one case study describes a frequent flier program that lets members accrue mileage points from business partners (such as long-distance phone or credit card companies) whose systems are outside the airline's control. The airline's alliance partners provide data about their customers' product usage. While this data should enhance the airline's business system, its impact on the information systems proved quite devastating: The only way to get the data into the frequent flier system was to enter it manually, an error-prone approach. As a result, statements reported incorrect or incomplete data about a customer's mileage.
As Aiken stresses, "the major impact of organizational data problems is that they aren't recognized as such. Lack of organizational awareness of data as either an asset or a potential problem often results in situations where resources are spent solving organizational data problems without recognizing them as such or applying the correct solution procedures to the problems." This hidden organizational resource consumption manifests itself in wasted or missed production, diagnosing and fixing problems, missed system development, and inefficient systems.
Aiken argues that to achieve enterprise integration, we need active enterprise models that "are revised to reflect the changes in the organization or the environment, so that new behavior patterns can be understood. Once validated in that they effectively predict aspects of future organization performance, the models can be used as a strategic weapon to evaluate alternate courses of action."
Aiken also looks into data reverse engineering activities from a project manager's perspective and provides a template project plan that includes detailed descriptions on the activities and the stakeholders involved.
Anyone charged with developing a migration strategy from one application environment to another will find this book useful. Aiken's approach-grounded on the Zachman Information Systems Architecture-applies to any data migration effort, whether its objective is to source the data warehouse, merge two data portfolios together after a merger or acquisition, or convert to a purchased software package
Terry Moriarty, president of Inastrol, a San Francisco-based information management consultancy, specializes in customer relationship information and metadata management. Her common business models have been used as the basis of customer models for companies within the financial services, telecommunication, software/hardware technology manufacturing, and retail consumer product industries. You can reach her at terry@inastrol.com.