Identify who your company’s best customers were, predict the amount of money they would be willing to spend over the next three months, and engage your best sales people to contact those customers;

 Predict energy consumption over the next two weeks based on average demand over similar time periods modulated by the different weather patterns so as to best negotiate energy generation, acquisition, and delivery contracts;

 Automatically assess global commodity prices and dynamically balance high net worth client investment portfolios to reduce risk while maintaining a high rate of return;

 Continuously review product profitability and eliminate the worst performing items from the catalog;

 Compare supplier performance based on credit-worthiness, product availability, compliance with contract terms, and product pricing to reduce the number of approved vendors;

 Figure out underserved geographic regions and the relative costs for entering local markets to identify best opportunities for expansion;

 Monitor key aspects impacting customer satisfaction among a collection of traditional sources coupled with social media streams to identify and correct issues in a rapid and effective manner; or

 Provide accurate audit trails demonstrating regulatory compliance to prevent fines and bad publicity.

Improving the Decision-Making Process

Almost every business process presents a situation in which information is collected, manipulated, and results are presented to help individuals make decisions. Some decisions are significant, driving broad organizational strategies; some are business-critical, but may be operational and narrower in scope, such as selecting the most cost-efficient containers that best accommodate the products within each customer’s order. Other decisions may be narrower, such as determining which product advertisements are to be placed in which positions on a web page served to a specific user.

Every business process has its associated measures of performance, and in a perfect world, each decision would be the optimal one—the decision whose results lead to the best overall performance. But those decision-makers are sometimes prevented from making the optimal decision because they are not provided with the information they need. Providing more information does not necessarily address the situation. When large amounts of unfiltered data are made available across the organization, overwhelmed individuals may be stunned into “analysis paralysis”—the compulsion to delay decision-making while waiting for just a little bit more data that can simplify (and perhaps justify) that impending decision.

This paralysis can be diminished if instead of delivering all the data, the information overload is reduced by distilling out the specific information needed to help make the optimal decision so that specific actions can be taken. Delivering trustworthy intelligence to the right people when they need it short-circuits analysis paralysis and encourages rational and confident decisions.

From the comprehensive strategic perspective, the senior management team can review overall company performance to consider any alternatives for adjusting corporate strategy for long-term value generation. From the immediate, operational perspective, day-to-day activities can be improved with specific pieces of intelligence suggesting adjustments for optimizing activities in real time. In the best scenario, business processes are augmented with the ability to incorporate information that is actionable—streaming the results of analyses directly into the process, tracking performance measures, and indicating when better decisions are being made.

In the best scenarios, reporting and business analytics contribute to a continuous virtuous cycle between operations, analysis of operations, modifications to business processes driven by the analysis, and then changes to the operational business processes and corresponding applications. Actionable information informs both strategic and operational processes, and its delivery to staff members up and down the organizational chart can facilitate a transition from reacting to what has happened in the past to streamline making the optimal decisions in the future.

Why a Business Intelligence Program?

What drives the desire for instituting a BI program? And more to the point, what are the primary drivers for business analytics and how can the benefits be effectively communicated to the important organizational stakeholders?

A straightforward approach for considering the value of a BI program looks at business processes, their source of derived or generated value, performance measures, and where the absence of knowledge impedes the complete achievement of business success. By categorizing dimensions of business value, we can then evaluate the ways that BI can contribute to increased performance along those dimensions. A high-level overview suggests at least these dimensions of value:

Of course, there are many other benefits to building a BI practice within an organization. Some benefits are focused on the ability to answer what might be considered the most basic questions about how a company does business. For example, it is surprising how few senior managers within a company can answer simple questions about their business, such as:

What is even more interesting is that in some organizations, not only can we not answer these questions, there may not even be a framework in which someone can even ask these questions. There is a critical point to be made here: Starting a well-conceived and comprehensive BI program that engages both the technical practitioners and the business consumers will not just provide the physical tools for answering these kinds of questions, but, more importantly, should be a catalyst for changing the way team members think about doing business and about how information is a critical catalyst for closing the loop by taking action and measuring the outcomes of those actions.

For example, before we can determine who the 20 best customers are, we must be able to articulate the difference between a “good” and a “bad” customer, as well as be able to identify a collection of metrics used to measure goodness, what data sets need to be collected for measurement, establish and integrate the methods for...