LOS ANGELES -- Getting back to basics for business intelligence (BI) and analytics teams means revisiting the three R’s. But instead of resuming lessons in reading, writing and arithmetic, a Gartner analyst suggests
That was the theme of the opening remarks and keynote address at the 10th annual Gartner BI Summit. To a crowd of about 1,000 attendees, analysts from the Stamford, Conn., research group detailed how analytics and BI have become even more important in the last year with a growing number of use cases. In fact, earlier in the day, a Gartner press release announced that worldwide BI platform, analytic applications and performance management software revenue reached $12.2 billion in 2011, a 16.4% increase from 2010.
Gartner Business Intelligence Summit timeline
2011: Gartner BI Summit: Business intelligence benefits lie in orchestration
2010: Gartner analyst and users discussed new technology vs. old-school strategy
2009: While a priority for most businesses, Gartner looked at how BI was falling short
2008: Sessions at the summit investigated how to embed BI within business processes
2007: The summit’s keynote speech focused on redefining BI
But while BI and analytics have grown in popularity, so has the complexity of the data, the analysis and the business environment. Today, businesses are still at risk of creating uneven, fragmented programs, which could lead to uninformed and even bad decisions.
“It’s back to basics,” said Bill Hostmann, a vice president and Gartner analyst, in his keynote address. “No matter how long we’ve been doing this, this conference has always been about making better decisions.”
“Are you still relevant?” Hostmann asked attendees. “What is your role in terms of making information the powerhouse behind better decisions?”
These questions should be top of mind when designing new reports or models for data analysis. When done right, businesses should be able to create an iterative cycle: Analysis will churn up more questions, requiring more data. That means a “what” question -- or one that requires basic, descriptive analytics -- could trigger questions that will eventually require more advanced analytics, such as predictive or prescriptive.
“The more you go through the cycle, the better insights you have,” Hostmann said. “And the better able you are to answer questions for the people making decisions.”
Today, businesses face greater challenges when trying to answer the question of relevance. That’s due, in part, to changes in the industry and the advent of “big data,” or data growing in variety, velocity and volume. For example, no longer does data come from internal sources alone; now businesses are juggling external data as well, which could be of questionable quality.
“As we look at additional information sources, we’re seeing exponential noise,” Hostmann said. “This is a significant challenge, and it challenges our role.”
But that isn’t the only complication when defining relevance: The industry is seeing a bigger variety of buying centers as interest in BI and analytics grows. Businesses are also tasked with an increased organizational complexity and will need to determine appropriate points of integration, Hostmann said. That requires building an architecture to help align performance measurements across the business.
“Things are getting more complicated,” Hostmann said. “These issues -- the analytic hierarchy, the complexity inside the organization, the information and noise explosion, the diversity of the buying centers -- it’s really changing not only our roles, but our relevance.”
Defining relevance can help business stay focused and can mean keeping analytics and BI central to decision making, Hostmann said.
BI and analytics teams do not have to be enormous to get the job done, Hostmann said. Businesses can do well -- even thrive -- with a team of just two. The key, he said, is to think about what resources are necessary to achieve success.
“It’s about having the right resources and the right teamwork to make decisions and drive key changes,” Hostmann said.
In other words, businesses need to be willing to embrace BI as a team sport and encourage IT and their line-of-business counterparts to work together. Doing so brings challenges of its own, Hostmann said, as business goals are different from technology goals.
“We can’t be pointing in different directions,” he said. “We’ve got to have all resources aligned and accounted for. We have to have a common blueprint.”
To achieve this, Hostmann suggests businesses use a framework (he recommended the Gartner business analytics framework) that enables a way to look at people, process and platform.
“When developing the framework, I can’t stress enough that you start at the very top,” Hostmann said. “This is not about information looking for decisions. This is about decisions looking for information.”
Hostmann considers building the framework and finding resources that may be lacking a core business competency. That requires bringing new people to the table.
“That’s why it’s important to know what your role is,” he said. “What do you bring to the table? Who else do you need at the table to be successful?”
But based on businesses he’s talked to, only 33% are using this kind of framework.
From social networks and sentiment analysis to mobile devices, the landscape for BI and analytics is changing, which means businesses have to change as well.
“We’re calling this the information nexus,” Hostmann said. “It’s changing how we look at information technology and business. And it’s having a domino effect on the BI and analytics market.”
That change is being driven by three things: First, consumerization. Most information systems inside organizations are behind what’s available in the market today, Hostmann said.
“It’s hard to be credible when you’re delivering information on 10-year-old equipment,” he said.
Second, Hostmann pointed to a whole host of new tools and technologies that are now available -- from Analytics as a Service to collaborative platforms to nonrelational databases. And third, the ability to deliver analysis at the point of the decision by embedding analytics.
To help grasp how changes in the industry may affect businesses and how businesses should integrate technology to meet those changes, Hostmann suggested developing a scenario of how technology will play out in the organization. For example, he noted a shift away from business applications to analytical applications. But how will business change with the industry?
Hostmann suggests using the Pace Layer model, recommended by Gartner, when helping to build an application portfolio. One axis records change; the other measures the level of integration. The model will help businesses prioritize technologies that are core to the organization against those that don’t need to be as heavily integrated.
“If you get that whole point of analytical applications are going to be at the center, I’ve got to be able to manage the pace of change and level of integration,” he said. “And figure out how to put together a portfolio that fits this kind of model.”