In this article, I explain a project completed in the financial services industry. A client asked me to lead a project to redesign a failed sub-process that had resulted in billions of dollars of backed up financial transactions. This particular financial process had a history of failed and abandoned process improvement projects. The pressure was on and, I must confess, I was not entirely sure that The Decision Model would be a good fit.
You are experiencing success with decision models even without the assistance of decision modeling software. Imagine the possibilities with proper software support!
Business requirements are usually captured in narratives and graphics that, regardless of how detailed, structured, cross-referenced and validated, are fundamentally imprecise. A data-driven approach to specifications has the potential to help avoid these problems and subsequently decrease the risk and increase the return on companies' IT investments.
Almost every business analyst uses diagramming software in their arsenal of analysis tools. According to BABOK 2.0, an analyst’s traditional purpose in using diagramming tools is to “support the rapid drawing and documentation of a model, typically by providing a set of templates for a particular notation which are used to develop diagrams based on it.” Diagrams not only make requirements clearer to stakeholders through modeling, they help clarify an analyst’s thinking on a project through the process of their very creation.
While most business analyst roles don't explicitly require static modeling expertise, developing a better understanding of static modeling concepts can be a measurable forward step for business analysts seeking to develop new competencies. Such skills can be useful in many aspects of the BA work, from obtaining a better understanding of stakeholders' information needs, to documenting those needs in unambiguous ways and communicating them more effectively to the technical team.
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.
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.
Like all professions, business analysis has its golden rules – rules that are fundamental to the design of successful business systems. They might seem like common sense but it’s surprising how often we forget them and get ourselves into hot water.
When ModernAnalyst asked me to propose an article for their issue on Enterprise Architecture, I thought about the question framework developed by John Zachman, that provides the basic building blocks of that practice. The primary function of a Business Analyst is to ask questions that uncover requirements then to document those requirements so they may be developed into a useful, useable system.
Business Analysts rely on input from a subject matter expert (SME) to help complete scoping and requirements documents. This simple truth is the reason ModernAnalyst has asked me to share an overview of the Data Management Association Body of Knowledge (DAMA-DMBOK). The purpose of the article is not to teach you data management, but to provide you with a general understanding of building blocks of the practice. It will describe the breadth of subjects that data management professionals may be able to address.
The BABOK includes data modeling in order for a BA to document data requirements; this overlaps with the skills a data management professional needs to do data development. It is an obvious point of collaboration. When we examine all of the facets in data management, you may find other opportunities for leverage.
If you can recognize requirements that indicate impacts to the data environment early in your project, you can draw on other resources more effectively. I have provided some sample ‘red flags’ to illustrate requirements that might benefit from collaboration with a data management professional.
I suggest you develop your own list with the data management professionals at your organization; it will become helpful tool for you to know when to include them.
Many people on our Business Analysis workshop ask why we use dataflow diagrams (DFDs). Why not Use Case…or even BPMN? After all DFDs have been around for 20 years, surely the world has moved on?
Well, has it? The primary purpose of a business analyst is to communicate – to stakeholders and to solution providers – and when it comes to communication we all know that pictures (diagrams) are much more effective and less ambiguous than words. Remember the phrase "A picture is worth a thousand words". The question is – which type of diagram best suits our needs? In this article, written by IRM's Training Services Manager Jan Kusiak, we’ll look at using diagrams for stakeholder communications.
Author: Jan Kusiak
Every area of practice in IT has a set of specific “tools” that supports the standard work of technology professionals. Data Analysis is the capture of data requirements, development of models that reflect those requirements and creation of design to store the data. You can accomplish this with a pencil, paper, and the right skill-set. But it can be done much more quickly and consistently if the process is automated. There are hundreds of individual software tools and tool-suites that support different facets of data analysis.
In the past I have discussed the need to manage data (and all information resources) as a valuable resource; something to be shared and reused in order to eliminate redundancy and promote system integration. Now, our attention turns to how data should be defined. Well defined data elements are needed in order to properly design the logical data base as well as developing a suitable physical implementation.
“The biggest risk to your company is not being able to change fast enough… Business Rules are the answer.” …Ron Ross I am a great appreciator of Mr. Ross. He has written extensively on the topic of Business Rules, offers excellent training on the subject, and is the keynote speaker at each year’s International Business Rules Forum. I would like to start my own article on Business Rules with an ‘icebreaker’ he used on a seminar I attended. Consider the sport of American Football. Some aspects of the game are very stable, some less so, and some not necessarily stable at all.
Author: David Wright
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