Every project in which we have implemented the Decision Model has seemed to bring further proof that – in the world of business logic or business rules, it seems to create a frictionless environment. We see “Ah ha!” moments time and again when people realize the simplicity to which their complex logic or business rules may be reduced by applying the model.

We are often asked what you need to do to run a successful SOA Pilot. Based on our experience of dozens of pilots, I propose that the following characteristics are essential to success.

It is no surprise that organizations spend over $15B annually on business intelligence and data mining technologies. But despite this focus on infrastructure technologies, there is little emphasis on the art of analysis.

Analysts are being asked to assimilate increasing amounts of data into meaningful information that can be acted upon quickly. This is a daunting task as the volume of data that comes into play is staggering and crippling to most analytic tools. This article discusses three innovations in data analysis that empower analysts to explore expansive data sets and gain actionable intelligence.

It is no secret that our record of complex project performance is rife with failed and significantly challenged projects. This is true for virtually all types of projects. Examples abound – we offer just a few.

With business analysis projects, as with all endeavors, you have to know where you are going before you can chart your course to get there. In other words, before you can decide whether to take a train, bus, or plane, what time of day you will travel, and what you will carry, you have to decide where you are going.

So it is with requirements. Before you can chart how you are going to implement a solution, everyone involved in the development effort must agree on why you need it to start with and that it is the very best solution available. Business requirements are fundamental to any development effort because they define where you are going by articulating the business problem and its solution—why it is needed and how to measure its success.

I'm hearing the word "value" a lot lately. This is partly because the economic downturn has us looking to get the most for our money. But that's not all. More and more managers, business analysts, programmers and testers are talking to me about value. They are concerned that their products provide value for their end users. Many of them express a kind of process or tool fatigue. They are tired of being told that using a particular process or toolset is the key to their success. To them, value is a more important concept.

In a previous column, we looked at how Decision Models improved an actual project. Below, we explore why the Decision Model is the next logical (and simple) advance in process modeling and business rules. We do so by addressing five questions. How does the Decision Model improve a business process model? Where did the business rules go? Why did the business process model become simpler? How does the Decision Model transform a business? Finally, why should business analysts upgrade from a traditional business rules approach to Decision Modeling?

The Business Analysis Body of Knowledge (BABOK® 2.0) is the definitive guide to the profession of business analysis. Every business analyst can profit from it, and few analysts can afford to be without it.

Business rules should be externalized from processes and established as a separate resource. Rule Independence permits direct management of the business rules, so they can evolve at their own natural pace rather than that of the software release cycle. Other benefits include better process models, and much closer tie-in to the business side (a.k.a. business alignment). Business rules put your company on the road to true agility.

It is unfortunate, but not surprising, that the elegant and relatively simple view of SOA has become bloated with a bewildering array of methodologies and products, leading to confusion and bafflement by many of its proponents and potential converts.