Taking Out the Guess Work


A few obstacles need resolution before any company can get started with modeling and impact analysis:

The most obvious is the common perception that the time it takes to develop a model during the design stage is better spent on implementation. This is due, in part, to previous experiences with models that were frighteningly inaccessible to all but the most die-hard experts.

Since non-specialists (a group that frequently includes managers and other authority figures) couldn’t experience their value first-hand, they assumed that the models were a waste of time. The shorthand solution to this is to make the modeling environment friendly enough for a broad range of people to pick it up and experiment according to their own level of comfort. A good example to point back to here is a financial model whose inner workings may be exceedingly complex but whose overall purpose is clearly communicated to a non-technical audience.

In extreme cases, modeling can be a waste of time. This happens when people get stuck in an endless design loop; by continuously tweaking the model in the quest for a perfect solution, they never get around to actually implementing what they’re working on. The way to counter this impulse is by linking a system of real-time monitoring to metrics, goals and objectives that are established at the beginning of the project. This implies a link to both project and performance management that is crucial to any type of modeling.

The other obstacle that stands in the way of modeling and impact analysis is the gaps that exist between multiple models and between models and the real world. These gaps are referred to as white space, and they’re familiar culprits in cases where modeling hasn’t been successful. Typically, the tools that are available to technology employees to model the business, processes, and technology are disjointed, and so they tend to exacerbate rather than overcome the white space problem.

Most tools are geared either to a particular task (process modeling, object modeling, or knowledge management) or to broad horizontal activities (word processing, drawing or spreadsheets). A consequence of these disjointed offerings is that companies tend to use multiple tools and environments to develop their models.

When changes are made in one environment (say a process diagram) they aren’t automatically reflected in other areas (a requirements document or business strategy memo). Without integrated tools, decision-makers must proactively anticipate ripple effects to keep their models aligned.

Once the current business model is understood, enterprise executives can begin to create the business scenario models that form the basis for end-to-end impact analysis. Each scenario represents a “to-be” alternative for accomplishing the firm’s goals. The structured and visual nature of models makes it easy for the team to compare these scenarios and eventually combine the best of each, and that equates to what’s best for the organization overall.

Faisal Hoque is an internationally known entrepreneur and author, and the founder and CEO of BTM Corp. BTM innovates business models and enhances financial performance by converging business and technology with its products and intellectual property. His previous books include Sustained Innovation and Winning The 3-Legged Race. His latest book, The Power of Convergence, is now available.