In the Aesopian fable of the one-eyed stag, the deer overcomes his visual handicap by grazing on a cliff near the sea with his good eye facing the land. This works well for a very long time – until he is killed by a hunter in a boat. Monitoring some metrics and ignoring others are choice we make based on our business insights. Failing to update your KPIs can make or break our business.
As companies deal with economic uncertainty as the new normal, competitive pressures are putting even greater demands on KPIs and performance management processes to stay updated with business changes. To stay competitive means measuring the right metrics and making better decisions more quickly. It means accelerating the “raw data -> clean data -> information -> insight -> decision cycle.”
Many CFOs, CEOs believe that IT is unable to deliver results where it counts. At the same time, IT organizations spend an incredible amount of time, money and resources simply reporting obvious data within their business process and workflows. A common refrain that we hear from IT directors is that they produce thousands of BI reports in response to requests from internal customers. They often feel that the usage of these reports follow the Pareto Principle with only 20% or less being used. The obvious question being asked is – “Do managers really need all this information to run their business? “.
A recent study by Gartner says that ”IT collaboration initiatives fail because IT leaders hold mistaken assumptions about basic issues… rather than making technology the starting point, IT leaders should first identify real business problems and key performance indicators (KPIs) that link to business goals.”
Business Analytics is more than sophisticated reporting technology. It is about actionable insight and supporting better decision-making to identify business opportunities and adapt to change. Being able to execute practical Business Analytics requires architects (both IT and Business) to go well beyond merely reporting the obvious data about business operations. Building a Business Analytics solution requires answers to questions such as:
1. What is the decision-making process? How can the BI implementation make that process better?
2. Is information required for awareness or is it required to take action? Is there a desirable Cycle Time to Information (CTI) and Cycle Time to Action (CTA) for the decision-maker?
3. What decision-making patterns are recurring, repeatable and supportable? Which business roles need what information to effectively monitor and manage performance?
4. What technologies and architecture are necessary to support those decision-making patterns? Is there need for a “single source of truth” or a federated model possible?
Jack Welch is known to have said, ” Too often we measure everything and understand nothing”. Enterprises are often quick to implement extensive business analytics solutions without KPIs which reflect business insights.
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