Like economics, there is a supply and demand factor that will govern a business analyst’s approach to managing and modelling requirements on a business intelligence project.
According to the International Institute for Business Analysis (IIBA) body of knowledge (BABOK, version 3), the “objectives and priorities of a business intelligence initiative can be based on the technical goals of improving existing information delivery systems (supply driven) or on the business goals of providing the appropriate information to improve decision-making processes (demand-driven)”.
I will explain these two methods a little bit better.
Think of data sources that exist right now in your company. Imagine they are scattered all over the place. The existing pool of data that lives in these data sources is what is called the supply. Supply driven business intelligence places the scope of analysis on the existing sources of data. So given this current pool of data, what value can the project team provide to the business when it comes time to extracting, transforming and loading the data into a business intelligence solution? That is the questions. Let’s use what we have and try to find the value in turning the vast expanse of data in spreadsheets, text files, databases and other sources into something that can help management make better decisions with that data.
Now to the demand side. Imagine if you will that after having workshops, focus groups and brainstorming sessions with executives, line managers and operational staff you discover that the data models and sources of data yield needs that cannot be covered by the existing pool of data. Where is the value going to come from in this case? Most likely, the company may need to obtain information from open sources of data that provide metrics for public consumption related to the BI needs or the business is forced to generate the data that is needed for their business intelligence objectives some other way.
In either approach, the business analyst will need to work with the business to understand decision making, develop logical data models and dig deep into data mining principles to assess upon which method a BI project will depend.
I hope this helps a little bit as we learn more and more about business analysis and how we can add tremendous value to any business intelligence initiative.
If you are interested in taking an online course on the methods, models and concepts for the business analysis on BI projects, check out our course offering.