Insurance carriers have accumulated massiveamounts of data over the years, which can present a daunting taskwhen it comes time to turn that data into business intelligence(BI). That's why Deloitte Consulting principal John Lucker believescarriers must conduct a proper data inventory if they haven't doneone already.

"It's not just a matter of what comes off the top of theirhead," says Lucker. "But looking throughout the organization fornon-traditional data and in particular in-house data they havepurchased or they have licenses for that might be useful forthem."

Carriers also have large amounts of manual data that Luckermaintains could be made electronic. For example, carriers want toperform BI or predictive analytics around MVRs, but very often thecompanies don't have that data in an electronic format.

Lucker believes the MVR reports are an easy thing to capture,though, and having the files in an electronic format providestremendous value.

Lucker also advises insurers not to obsess on data quality,either.

"This is a big topic with regard to embarking on BI projects,"he claims. "Typically, business intelligence is not a countingexercise. The phrase you hear often is 'good is often goodenough.'"

Lucker recommends performing an exercise in which you find datayou think is dirty and you design an analysis of the data beforethe data is cleaned. The company then cleans the data and performsthe exact same analysis on the data after it's been cleaned.

"What I've found almost every time I've done this with a clientis they've seen the cleaning exercise doesn't significantly changethe trends and pattern that they were setting out to see in thebusiness intelligence exercise," says Lucker.

Lucker believes there are various statistical reasons why thisoccurs.

"Very often the dirt in the data is random," he says. "If youthink of it like a bell curve, if there is dirty data on the rightof the bell curve, statistically speaking there would be anotherdirty data point to the left of the bell curve. If you plotted allthe dirty data around distribution you would see they average out.The statisticians on my team always say typically dirty datacancels itself out. There's some inherent bias in that dirtiness,you can understand that but you don't necessarily have to cleanit."

The Next Steps

Lucker maintains it's important for carriers to be thoughtfuland holistic in determining what they want to accomplish with thebusiness intelligence project. Once they design the docket of workto determine what specific BI findings they hope to discover, it'simportant to anchor that work to a cost-benefit analysis.

"Look for ways to create the best short, medium, and long termproject dockets so you can provide the organization with sometangible return on investment to help the executives and the restof the team realize value throughout a timeline," says Lucker.

Lucker finds that some companies—at the end of the two-yeareffort—hope they finally get something for their effort.

The project dockets enable insurers to accrue benefitsthroughout the course of the project and this gives them theopportunity to achieve business satisfaction and a return oninvestment.

The dockets also give the carrier the opportunity to alter theircourse, which is something a lot of companies need.

"They go so far along they make [the project] bigger than theyneed to," says Lucker. "If it doesn't go as well as they had hopedthere can be a tremendous emotional hurdle to overcome."

Follow the Rules

Sticking to the 80/20 rule is important, according to Lucker, toavoid scope creep, which inevitably takes place when carriers beginthese BI projects.

"I've been in project planning meetings and clients will saythey understand the 80, but what about focusing on a small amountof the business," says Lucker. "They end up focusing an inordinateamount of time on the 20 percent and completely lose track of thebusiness value and the value of time in accomplishing the 80percent sooner rather than later."

Organizing the staff is an important initial step becausecompanies are not always thoughtful around determining who theright people are to work on these BI or analytics projects.

"My experience is it takes a certain aptitude and a passion forBI and analytics," says Lucker. "Not everybody is good at themechanical aspects of working with data or working with thesoftware tools or passionate about the level of granularity that'srequired. Find out who the go-to people are and make sure they areinvolved from the onset."

Generic orIndustry-Specific

Lucker believes the term business intelligence is often misusedor overused.

"I think software vendors try to paint their tools to be biggeror broader and sometimes even overly specific," he says. "There aretools that are foundational for BI that help you organize data,populate data marts or data warehouses, but ultimately when you getto the data side there is a whole suite of agnostic data tools, BItools, and industry-specific tools that have differentpurposes."

For insurers, it depends on the type of people they expect to bedoing the business work and the level of flexibility they want toprovide those people.

If you are giving BI responsibility to business people who aretechnically oriented—like a really good business analyst—they aregoing to be confident with a tool that is flexible but morecomplex," says Lucker. "But if you are expecting a morebusiness-oriented desk-worker to be doing BI work or using BItools, you require a tool with a different level of ease ofuse—less programming and more clicking type of tool."

Lucker believes smaller carriers seem to be further along withbusiness intelligence and the larger carriers—because they arebigger and more complex—have some pockets that are struggling withBI.

"It's easier for smaller carriers to be more holistic," hesays.

Lucker maintains industry-specific tools are not all thatimportant for insurers.

"Companies sometimes pick tools that are highly specific at thatpoint in time, but their vision or their needs might change," hesays. "There's a real need to think seriously about the claims ofthe software industry to say this is good for this particularindustry versus this is a more robust tool. You need people who areexpert in using the tool and they can create specificity with amore generic tool."

Hampering the Efforts

Lucker believes BI has become universal throughout the insuranceindustry.

"Virtually every company would say they do it," says Lucker.Obviously there's a continuum of what that means, but I do think alot of companies are struggling to take business intelligence to ahigher level. Companies are struggling in how they get enoughpeople to understand what advanced analytics mean, what the art ofthe possible is."

Lucker continue to see significant organizational inertiaissues—a fear of change—in how companies can become moreinformation driven and fact based and less intuition driven andallowing things to happen to them by the market rather than beingmore forceful in the market.

"I'm seeing plenty of success stories," says Lucker. "The way Ialways think about success is not everything translates todollars—very often it does and should—so how do you articulate yourROI. That's a very basic question, but it's still a vexing problemfor insurers in terms of how they calculate the value. You have tobe comfortable with the idea you can't always measure everything indollars and cents."