Thinking back on last week’s Gartner Business Intelligence Summit in Barcelona, I’m struck by how important context is to what we take away from conference presentations.
For example, one of the Gartner keynoters drew the analogy between cars on the road 30 years ago and analytics today.
“Remember how back before the mid-1980s cars wouldn’t always start when you needed them to? Then the auto manufacturers applied technology and innovation to ensure that their products always started up as a matter of course, he said.
“Analytics solutions are a lot like that today,” he added. “We are just getting to the point where BI technology is consistently reliable so we can really accomplish what we need to accomplish.”
On one level, the context of which country you lived in during the 1980s made that car analogy more poignant for some in the mostly European audience than others.
Yet, his point resonated on a deeper level. That’s because you only needed to recall how a faulty starter or spark plugs once made you late to underscore that, likewise, earlier business intelligence solutions are not reliable and efficient enough to cope with 21st century business problems.
And ultimately, context itself is really the greatest innovation that has now finally matured analytics and BI solutions, allowing them to achieve productivity gains for enterprises around the world.
A few minutes later, one of Gartner’s data-guru analysts drove the point home. He noted that today most analytics software provides only quantitative analysis, but lack the means to deliver context for data to determine its true relevance and value to solving the problem at hand.
“There is a major difference between getting a report on the number of customers that will be lost to churn in the next quarter, and getting one that defines the types of customers that will be lost, and prescribing what steps can be taken now to prevent them from moving to a competitor’s product,” the analyst said.
He was referring to sentiment analysis.
“The enrichment of data with sentiment analysis can provide major revelations, and can allow you to create programs to address reasons why customers are leaving you,” he added. “However a narrow focus just on structured data can lead to informational tunnel vision, providing only a partial view of the situation.”
The Gartner keynote speakers also explained that to improve business performance, companies need four types of analytics: descriptive, diagnostic, predictive and prescriptive.
“Today, however, only thirteen percent of organizations use predictive analytics to drive decisions, and Gartner shows even smaller numbers, less than three percent, of organizations apply prescriptive analytics, though prescriptive is growing as C-level executives are demanding it,” the keynote speaker said.
With a nod to Master Data Management (the Gartner Summit co-located with the BI Summit), the BI keynoter said that while prescriptive analytics have been siloed until now, there is an increasing appetite to link all four of these analytic categories together.
“You need to focus on sharing information, not keep it siloed, so you can connect the dots across those analytic styles,” according to the speaker. “Metadata needs to be readily available across all of those categories. That’s why MDM is a requirement for connected analytics. You’ll never get all of the stake-holders to speak the same semantic language if you don’t connect that metadata.”
Yet another huge opportunity for data-rich enterprises lies in what Gartner has termed “infonomics,” or the monetization of all that data piling up within enterprise systems.
“A form of analytic alchemy is also possible where informational analytics can improve businesses’ top lines, as well,” noted one analyst. “We can turn our data into revenue by developing customer facing information data products.”
Of course, that requires applying the correct levels of security and controls on data, which spans ethical and sometimes moral decisions as to whether such data can or should be monetized, he cautioned.
However, Gartner predicts that by 2014, 20% of companies who attended the BI Summit will be selling such data-based products. All of this speaks to what Gartner terms “The Nexus of Forces,” which simultaneously challenges 21st century enterprises and presents major opportunities to create and profit from competitive advantages.
The forces that are converging are information (aka big data), social, mobile and the cloud.
Full-fledged analytics that span traditional with predictive and prescriptive tap into the torrents of data that are exponentially increasing each year from millions of mobile and billions of social feeds via the cloud into enterprise systems and data warehouses.
Analytics become the means by which businesses can pan for digital gold. And those companies that dismiss analytics as unnecessary risk the same fate as car companies that continued to sell unreliable vehicles some 30 years ago.
Paul Labelle, Guest Blogger
LaBelle is a marketing and corporate communications executive with deep experience in the software industry. A former journalist, LaBelle lives outside Boston, Massachusetts.
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