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Business Modeling: Money Pit or Blueprint for Success?

The modeling death spiral, the modeling money pit, modeling for the sake of modeling – business executives familiar with these terms know how costly such scenarios can be not just in terms of financial commitments, but also time, people and other resources. While effective business modeling can facilitate streamlined operations and greater enterprise efficiency, ineffective modeling can wreak havoc on even the healthiest organization.

This article outlines several common pitfalls associated with business modeling and offers practical advice on how to avoid such situations. The article also contrasts the pitfalls with rationale for why business modeling is important.

1) Modeling in a Vacuum

Business models are designed to represent the requisite flow of information throughout an enterprise. To be effective, they must accurately depict not only the necessary data flows and business processes, but also relationships between various data groups, interactions of business processes, organizational implications, the information systems themselves and the overall architecture that supports the business. They must also show linkages with overarching strategies, goals, policies and regulations. Without such linkages and relationships, optimal value of the models won’t be realized.

Consider this example: A company launches a business process modeling initiative and completes a comprehensive model of its end-to-end processes. However, they don’t link these processes with their organizational model or strategies and goals. Nor do they link the models to their information systems architecture. In the end, what do they have? They have a great business process design that’s difficult to execute because they haven’t considered the organizational and transformation needs. Their strategies and goals may not be achievable because the process design was done in a vacuum; so their initiative becomes a money pit.

“If you do data modeling in isolation from process modeling, or the other way around, you’ll be in trouble, because one anchors the other,” says Brian Coleman, an independent data consultant who did extensive work with IBM throughout the 1990s. “I’ve seen process modeling go on and on without the benefit of data to balance it. That’s an example of the modeling death spiral.”

2) Comfort Zone Inertia

Karolyn Duncan is the principal consultant with Information Technologies, Inc. and is a frequent instructor for TDWI, an educational institute dedicated to business intelligence. A veteran of the data warehousing industry, she often encounters data modeling scenarios that are less than optimal. One phenomenon she's witnessed is reluctance on the part of client teams to move a project forward due to lack of experience in subsequent tasks.

Says Duncan, "I find with data warehousing, in particular, teams who are new to warehousing like to stay within their comfort zones. They may know how to do data modeling, so they'll continue to do that rather than moving on to designing ETL (extract/transform/load) maps, because ETL is different from what they've done before. They get hung up on what they know instead of moving forward."

One way to avoid this pitfall is to time-box project tasks: set a hard deadline for when the data modeling process will finalize. Then, stick to that deadline. "That's the hard part," says Duncan. "It's very easy to get caught up in trying to get the data model 100 percent finished, 100 percent correct. People want to go for 100 percent, but that's unrealistic. Sometimes, you need to encourage a mental shift to get past this 'it's not right enough' mentality."

Besides, data models can always be modified down the road as business circumstances change. Making such modifications usually isn't difficult or terribly time-consuming. But again, perception can be an issue. Duncan: "I've encountered certain perfectionists who view changing the models down the road as rework, which they consider wasted money.  You have to learn to accept a certain amount of rework."

3) Insufficient Requirements Gathering

Most practitioners would agree that requirements gathering rarely goes off without a hitch. Almost invariably, end users do not fully describe their needs and/or consultants don’t fully capture the articulated needs. Additionally, when versions or releases of a solution come online, users often discover possibilities that lead to new ideas which require expanded versatility (read: more data).

One way to address this is to prepare for it. Duncan describes a tactic she picked up from Michael Haisten, one of the dozen or so original data warehousing consultants and a pioneer of real-time data warehousing. “The idea is that when you go to the source file, look at all the data elements there and determine which others have business value. I’m not saying pull in everything from your ERP but definitely grab anything that could have business value. The cost in terms of time and resources is minimal because you apply this technique only to files or tables that you were going to anyway.”

“In one example,” she continues, “there was a field called Order Method Code – how was the order placed? Phone, fax, Web? At this company, most of the orders were phoned in. But they did a Web promotion, so they encouraged customers to place orders via their Web site. A couple weeks later, they wanted to analyze sales based on this Web promotion and needed the order method code, but they hadn’t asked for it originally. So, you have to prepare for change.”

4) Excess Detail

Of course, too much of any good thing can be bad. Coleman warns against providing reams of detail just because you can. “Detail takes time to model and that can be very costly. Focus on producing the detail your audiences need to achieve their objectives.”

In working to fine-tune your model, Coleman says to keep in mind the two aspects that comprise level of detail: depth (very detailed, less detailed, not detailed enough) and kind of detail (relationships with partners, customers, suppliers; quotations, orders, deliveries).

“Business models need to be very detailed in areas that address current issues, problems and the achievement of business objectives,” he says. “Managing depth and detail prevents audience wear and tear. Couple this with an understanding throughout the company that business models are important to operations and you get a much higher probability of audience buy- in, ownership and success.”

Consider also the model’s longevity. Is it a means to an immediate end? Or is there a commitment to maintain the model as an ongoing tool for management of business change? If the model life expectancy is short, temper content and design accordingly.

5) Unscrupulous Consultants

As many companies have discovered the hard way, some business modelers sink their teeth into their client’s pocketbook and model for the sake of modeling. When consultants arrive on the doorstep and can’t ever seem to finish the job but keep draining the bank account, it’s time to eject them.

A disciplined approach to the modeling process can preempt this type of scenario. Says Coleman, “Always have an explicit purpose or set of objectives that are directly linked to a realistic budget. With budgets and objectives clearly defined, realistic expectations will be established up front.”

Plan for Change

Business models help companies respond quickly and effectively to change. The models focus gap analysis; they expedite definition of “what is,” “what needs to be” as well as the vacancies and overlaps in between. A single business process change can impact the process model, organization model and possibly the information system(s) that support the process itself. However, changes are not always simple. Mergers, acquisitions, spin-offs or even just the introduction of new products or lines of business – all can prove to be mine fields of complexity. Reliable business models are essential navigation tools in these and other such scenarios.

A comprehensive set of business models are the road maps and blueprints for your business. Graphical process maps permit analysts to quickly see where wasted work is occurring in the business and which processes, subprocesses or set of activities need to be measured in order to gauge efficiency. Consider the implications of replacing legacy information systems with newly purchased systems. Without process maps and information system architecture models, the transformation process can be disastrous.

H. James Harrington wrote, “The only reason you should ever consider starting an improvement process is to generate more profits and make your organization more competitive. You need to look at the improvement thrust as a business investment that is going to either add to or detract from your long- term, net-favorable balance.” (Business Process Improvement, 1991)

Too much focus on profit can be dangerous, however, as author Peter Drucker notes, “To emphasize only profit, for instance, misdirects managers to the point where they may endanger the survival of the business. To obtain profit today they tend to undermine the future. They may push the most easily saleable product lines and slight those that are the market of tomorrow. They tend to shortchange research, promotion and other postponable investments. Above all they shy away from any capital expenditure that may increase the invested-capital base against which profits are measured; and the result is dangerous obsolescence of equipment. In other words they are directed into the worst practices of management.” (The Practice of Management, 1993)

View your investment in business modeling as long term. Make the models a critical component of your overall business management system. Weave into your ongoing operations a regimen of looking at the maps, analyzing them, tweaking them, sometimes doing considerable rework – whenever company needs and budget justify. Larger organizations may need more protocol than smaller ones, but each case is unique. Regardless, you won’t get value without continuous focus and action. Business process modeling is, after all, a process. By definition, the process continues…


With more than 38 years of experience in managing both business and IT environments, Steven Arbogast specializes in defining, mapping, integrating and changing corporate processes. A veteran of enterprise architecture design and maintenance, he understands both the technical and organizational components necessary for effective business change management. An internationally published author and presenter, Arbogast spent his first 31 years with IBM. In 1999, Arbogast formed Advanced Enterprise Services (www.advent-services.com), a professional services business focused on overall business change management. In 2001, he also assumed the role of president for enterprise software vendor QualiWare, Inc., a subsidiary of Denmark-based QualiWare APS, where he worked through 2005. Arbogast still provides management services to Qualiware (www.qualiware.com), while also providing professional services to a variety of businesses.



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