Measuring the Value of Intelligence in Business Intelligence

Published
  • November 06 2008, 12:10pm EST

Intelligence is the ability to solve problems. It is also commonly referred to as practical sense or the ability to get along well in all sorts of situations. People cannot see, hear, touch, smell or taste intelligence. On the other hand, the more intelligence people have, the better their ability to respond to situations around them.  

On a similar note, we can define intelligence in business intelligence (BI) as the ability to realize business success with easy access to actionable information through timely and accurate insight into business conditions. It is crucial to examine BI initiatives from the perspective of the value created. If decision-makers do not understand the economic benefit generated by BI, they may grow to distrust the recommendations it generates. They may return to strategy by intuition and prioritization based on a hunch.

 

How are data, information, intelligence and BI interrelated?

  • Data generated by business events is raw without context, like customer data, product data and transactions.
  • Information is data with context and meaning; for example, information about product purchases made by the specific customers.
  • Intelligence is actionable information insight and is used by various information consumers to achieve business objectives: Which group of customers buys which products? Is there a trend in purchases of these products by these customers? How can we use the trend to predict what will happen in the future?
  • BI is intelligence based on business information, past actions and strategies for the future.

BI is all about achieving greater profitability by analyzing huge amounts of data and numbers - presenting them, qualifying the assessments, finding trends and issues hidden in them, empowering action to resolve issues and providing actionable insights.

 

 

The economic benefit of BI is often complex and difficult to quantify. Several factors may contribute to the overall revenue or profitability statistics that an organization needs to measure. A common factor in determining economic benefit is ROI on BI strategies or other metrics that quantify the number of sales, number of new customers acquired, etc. These numbers tell us how many and how much. Other factors such as customer centricity, lifetime value and wallet share are also critical. Negative economic impacts like losses due to charge-offs and fraud should also be measured and considered. Additional pertinent questions include:

  • Are we doing the right things? What is proposed for what business outcome, and how do we know which initiatives within the program contribute to the achievement of business strategy?
  • Are we doing them the right way? What management and operational practices have we put in place to maximize our chances of success? Have we moved from intention to realization, and is the information accessible to the right people at the right time?
  • Are we getting them done well? Are we applying the defined practices in the optimal way and monitoring them to ensure that they remain effective?
  • Are we getting the benefits? How will the benefits be delivered? What is the value of the program? How do we measure it? What factors influence success or failure?

Answers to these questions lie in monitoring business operations, learning from past performance and then feeding the learnings back into transactional systems, thus forming a closed-loop performance measurement and optimization process. The output of BI applications (actionable analytics) gets routed to business users in the form of business alerts and recommendations (such as product pricing changes, marketing campaign modifications or identification of fraudulent transactions) for identifying and addressing specific business issues.

 

 

In order to do this, the BI system must provide easy-to-use self-service intelligence nuggets that enable rapid decision-making, ideally leading to decision automation through decision trees. There should also be a methodology (either formal or informal) to help organizations assign responsibilities to specific business users for handling BI applications and to define actions to be taken when the intelligence nuggets identify business problems that require urgent attention.

 

 

Accessibility to information and exchange of information across the enterprise provide early insight to business opportunities and disruptions, thus leading to business agility. Information architecture is a key component to achieving business agility, and it must underpin clear metrics measuring the impact of information to agility. How can organizations best evaluate information agility? While there is no easy answer, this does not mean that companies need to fall back on gut-feel decision-making.

 

 

After selecting and applying measurements meaningful to the organization, the final decision may come down to a single question. And that question is not, “What is the best way to evaluate the impact of BI initiatives?” Rather, the question is, “What is the best way for the organization to evaluate whether a BI initiative can help identify and move the organization toward the goals more rapidly or with a greater likelihood of success?”

 

Measuring Information Agility and the Intelligence Quotient

 

Business conditions are constantly changing, and opportunities are emerging more rapidly than ever. In this dynamic environment, information agility provides a distinct edge, enabling enterprises to:

  • Determine how changing conditions and competitive pressures affect their basic business strategies,
  • Identify strategic refinements and
  • Leverage technology to support and drive new or adapted strategies.

Enterprises have accumulated huge amounts of data about customer needs, market trends, the competition, regulatory requirements and their own business operations. The volume of data has been growing at an accelerating pace. This huge volume of data has made business analytics more important than ever. A major distinguishing factor that separates agile enterprises from their less successful counterparts is the ability to leverage the data they have amassed to make informed decisions by delivering the right information to the right people at the right time. This requires:

  • Delivering aggregate information on key performance indicators (KPIs) for decision-making purposes, continuous improvement and regulatory compliance.
  • Speeding the dissemination of information regarding business decisions throughout the enterprise and, when necessary, beyond.
  • Protecting this sensitive information from unauthorized access and personalizing its delivery.

Companies have employed popular ROI calculation principles to judge the value delivered by BI initiatives as a general rule. However, to measure the impact of intelligence, one needs to dig deep into the various dimensions of information exchange, beyond the dollar value calculated by traditional methods of ROI.

 

In meeting these challenges and requirements, information must have certain quality-based attributes, including: authenticity, reliability, accuracy, completeness, timeliness, security, availability, understandability, usability and relevance. Only by having high quality information to rely on can organizations achieve intelligence in decision-making throughout the enterprise.

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