For example, consider the data collected for each item that is sold at a supermarket. Tens of thousands or even hundreds of thousands of transactions of raw data are collected at the checkout counter every single day. If one looks at this transactional data in its raw form, it will give basic information such as which item was sold, when it was sold, and its selling price. However, by implementing BI software, the supermarket can turn that raw product data into information and use that information to gain more profound insight into their business. So, in addition to determining how many containers of milk were sold on any given day, the supermarket can determine "bigger picture" insight such as how many dairy products were sold compared to canned goods; the supermarket's best and worst selling products by department; the top-five ranked retailers; etc.
Armed with this knowledge, the supermarket's management can better plan for the future. By tracking buying trends of the customers, the purchasing department knows which products to stock up on. Moreover, management can obtain such information as products that are commonly purchased together, such as hotdogs and mustard, so that they can better position them on the shelves, thereby increasing sales and revenue.
By providing this type of window into vital information, BI enables companies to improve the way they do business. Companies are empowered with the ability to offer products and services at the lowest possible cost and with the greatest amount of efficiency and productivity possible - while returning the highest revenues and profits. Companies implement BI effectively through a four-phase business intelligence improvement cycle (BIIC).
The Four Linked Components
A healthy BI strategy should be viewed as the sum of four major processes that fit together in a constant cycle. These four processes are measure, analyze, plan and improve (see Figure 1).
Figure 1: Business Intelligence Improvement Cycle
MeasureThe measure phase is by far the most widely deployed and far-reaching process of business intelligence. Think of the process of establishing a BIIC as blowing up a long thin balloon. As you blow up the balloon, the part of the balloon closest to your mouth expands first, then that expansion extends down the length of the balloon. If you wrote the words measure, analyze, plan and improve down the length of the balloon starting at the end you blow into, the measure section of the balloon would expand before you will see the other sections. Try to blow up any section of the balloon before the measure section and you will find it impossible. The same goes for the BIIC.
In the measure phase, companies "report" the current and historical status of key metrics used to manage their business. These measures tell a company the "what" (i.e., "What is the status or health of my business?"). Although most companies know which fundamental indicators to measure (e.g., sales, profit, etc.), it is not necessarily easy for them to obtain and distribute the status of these measures to the individuals throughout their organization. By employing an effective BI solution, an organization can successfully distribute this information to all the people who affect business inside and outside the enterprise. Through BI, an organization can uncover new ratios and metrics that provide even deeper insight and that could potentially modify or enhance that which is currently measured. Today, reporting and information delivery software used widely by IT departments provides the bulk of the aforementioned functionality in this initial phase of the BIIC.
During implementation of the measure stage, a stabilization of the company's overall BI infrastructure occurs. People viewing measures can determine inconsistencies with the aggregated measures and what is generally expected. This helps to uncover "glitches" in the collection processes. Determining problems with data collection and connecting them is a necessary evolution that takes place during the measurement stage. Without this weeding out of collection problems, companies cannot successfully move into the latter stages of the cycle because to base analysis and planning on a suspect measurement system makes no sense.
AnalyzeThe second phase in the BIIC is analyze. During this phase, analysts review and measure the data in new and different ways to see whether they can uncover hidden relationships that will help them answer "why" (i.e., "Why is this occurring?"). In the evolution of BI, several tools have emerged that simplify the analytical process - ad hoc query, online analytical processing (OLAP) and data visualization. It is not in the scope of this column to discuss the benefits of each; simply understand that these tools help people analyze data.
PlanAfter determining some of the reasons "why" things occur in the analyze phase, companies then try to determine the effects on outcomes should they implement changes. This is when the third part of the cycle, the plan phase, begins. In this phase, companies use tools to play "what if" games with their data (i.e., varying scenarios that target the process changes they may need to make to help steer the company in the right direction). Software for this segment of the BIIC has been categorized as planning, budgeting and forecasting. Using these kinds of tools, you can perform scenarios such as "expected measures from the budgeting process" and then combine them with historical measures and forecasting algorithms to determine potential future outcomes. You can then vary your inputs to see how different courses of action might affect these outcomes.
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