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The ability to recognize and understand what you don't yet know is, in my opinion, one of the best predictors for long-term success. And it is the ultimate prerequisite for a business intelligence (BI) initiative.

Successful BI initiatives begin with the simple recognition that an enterprise doesn't have sufficient knowledge about important aspects of its business.  Without that knowledge, decision making is compromised and may result in adverse consequences.

Making decisions "in the dark" is difficult for any executive and this is especially true for utility executives who are being asked to make important decisions about issues related to energy supply, reliability, smart grid initiatives and a host of other important issues that have long-term impacts. BI solutions that incorporate enterprise views of information are more valuable than those that only capture silos of information.

In my post last week, I cited the results of a survey that was conducted last year by Sierra Energy Group, a division of Energy Central. That survey indicated that utilities are still struggling to effectively use intelligence about their own business when making decisions. We are currently running a similar survey and although the results are not yet final, we do have some interesting preliminary information to share about how utilities are currently using BI software and solutions.

The results of the survey indicate that utilities are somewhat evenly distributed across four different levels of BI implementations. More specifically, respondents indicated that:

• 27 percent of responding utilities do not use BI solutions
• 25 percent of responding utilities only use BI solutions for operational data
• 23 percent of responding utilities only use BI solutions for back office data
• 25 percent of responding utilities report that BI solutions have been implemented for all enterprise data

Keep in mind that these results are preliminary and may change before the survey officially closes. But they do indicate that about 73 percent of utilities are using BI in some form, which is generally consistent with what we are currently hearing from chief information officers (CIOs).

Earlier this week, I had the pleasure of visiting with Jodie Heflin from Lucrum Inc.  Heflin has spent a considerable amount of her career working in the business intelligence space and much of that time has been focused on utility companies.  She knows a great deal about effective BI solutions and provided some interesting observations. Among other things, she commented that many utility companies use BI solutions within particular "silos" of their operations, but that more value is achieved if BI solutions are broadened to include more information.

Heflin's comments seem generally consistent with the preliminary survey results that indicate 50 percent of utilities have BI for just back office or just operational data. While this is encouraging on one level, it is also an indicator of the long journey ahead. BI solutions increase in value in proportion to the amount of meaningful data that is encompassed in the solution.

Consider this simplified example. I live in Minnesota and the temperature right now is approximately zero degrees. Anyone who lives in the Midwest, though, knows that temperature is only one indicator of how a person should dress when working outside.  Zero degree temps with no wind and no precipitation are somewhat tolerable, but zero degree temps with 25 mile per hour winds and blowing snow are difficult to tolerate and can be quite dangerous. In other words, the data points of wind speed and precipitation could be the difference between a tolerable day for someone who works outside and a debilitating day.  Knowing those two additional data points would certainly change how an individual dresses and prepares for the day. In a more drastic example, those data points, if not properly heeded, could be the difference between life and death for someone working outside.

Similarly, within a utility business, a silo of information only tells part of the story and provides only partial benefit because it is often missing several related data points. For example, a silo of information related to location, maintenance history and failure rates of transformers is made more valuable when joined with information related to location and aptitude of available resources, customers affected and supply/inventory of equipment needed to repair or replace those transformers. Joining those data sets in a meaningful and easy to use way can positively influence outage duration, cost to repair and customer satisfaction.  All are desirable outcomes for utilities, customers and regulators.

BI solutions continue to grow in popularity and although they are often used for only partial data sets, we should expect that utilities will continue to broaden their reach. This is good news for all constituents.

I enjoy discussing industry issues with you. Please feel free to share your thoughts in the comments section, or reach me directly at bthielbar@energycentral.com