Harnessing the Power of Business Intelligence

Business intelligence software can translate masses of data into insights that drive better decisions—if you do it right.

November 12 2013 by CJ Prince

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A few years back, Greg Dickinson, CEO of Hiperos, realized he had a problem. As a software-as-a-service provider to Fortune 500 customers like AstraZeneca, T-Mobile and Microsoft, Hiperos needed to provide outstanding customer service. Unfortunately, the system the company used to manage open service tickets was manual and slow. Whenever a corporate customer called in to ask how many tickets were open and the status of each, the customer service rep was forced to look up each one manually. “A Fortune 500 company is bound to have numerous inquiries that result in tickets, and their need to understand status is very important,” says Dickinson.

The business intelligence (BI) solution they chose, powered by Birst, now allows customer service reps to monitor tickets in real time, proactively taking care of those that have been sitting the longest and to pull up a customer’s information in seconds when on a call. On his own dashboard, Dickinson personally monitors whether customer service reps are hitting their goals of closing tickets in a timely manner and is able to look at that progress any number of ways. “The analytics lets me look at it by hour, by week, by month, by severity, by department—you name it,” he says, noting that today’s fast pace in business doesn’t allow for long waits for IT to throw something back over the wall. “Business has changed. The line of business is now empowered to do more. They’re closer to their customers. I, as a business user, need to be able to go in and get my own information. I don’t have months and months to let IT do it.”

That is perhaps one of the biggest changes to Big Data since the early 1990s, when database deployment and data mining exploded on the scene, en masse. Until recently, projects were largely initiated by and implemented for IT departments, rather than business, and the focus was primarily on eliminating silos and moving from departmental to enterprise programs.

That focus has shifted and the shift has led to a $14 billion global market for BI software in 2013—one expected to eclipse $17 billion by 2016, according to Gartner estimates. “What we’ve seen over the past few years is that a large part of what’s driving that growth now is the business user. The buying influence has shifted back to the line of business,” says Rita Sallam, vice president of research and BI expert with Gartner Group.

Five Steps to Successful BI

  1. Align the technology with corporate strategy. Too often, CEOs become enamored with glitzy technology and fail to start with the key business questions, says Myron Weber, founder and managing partner of Northwood Advisors. A better way to approach it is to focus on the people you’re trying to empower. “Who is making decisions today but not able to make the decisions you want them to make because they don’t have the right information? Who is making fly-by-the-seat-of-their-pants decisions when you want them to make data-driven decisions? That way, you’re aligning the strategy with the business. The software can be just right, but it doesn’t mean it’s supporting the right activities.”
  2. Get your Key Performance Indicators (KPIs) in a row. Surprisingly, often, executives in an organization cannot agree on the definition of various metrics, says Cris Hadjez, BI practice director for itelligence, an SAP implementation partner. “They’ll talk about the ability to have a nice enterprise BI solution and how it allows for automation and allows them to get their information faster. But if your foundation is based on business rules that are incorrect, the only thing the BI solution does is help you arrive at an incorrect solution much faster.” Organizationally and culturally, the various business unit heads must agree both on what will be measured and how it will be measured. “How do you define revenue? How are you defining sales? Am I allowed to have two different definitions for margin—from a financial perspective vs. sales perspective? There are a lot of nuances to those definitions and they have to be decided upon up front.”
  3. Don’t rely solely on vendors for BI competency. “Have your own people, who are trained and well educated and knowledgeable about whatever BI solution you’re implementing, [consider your BI],” advises Steffen Kleinmanns, VP of business development for BI provider Cubeware. Ask your internal experts the high-level questions: Can these processes be measured? Which are the most important? Once we can measure, what are the appropriate targets we should be measuring going forward?
  4. Be disciplined. “Once people get religion, they want to boil the ocean,” says Birst CEO Brad Peters. “They think, ‘I could do this, this and this—and that reduces the odds of success. The companies who have the discipline to do it in pieces are the most successful.” TriCore’s Kevin O’Rourke suggests starting with a manageable project with clear goals and well-defined success metrics. “A quantifiable, quick win with minimal investment on the first phase,” he says. If a vendor tries to upsell you on the first phase, start shopping for a new vendor.
  5. Believe in your people. You hired smart, good employees. Now it’s time to trust them with more information. Too often, says Peters, lower level employees are seen as assets to be controlled rather than empowered by data and analysis. But with relevant, intelligent data, they can make better decisions more quickly. “That’s a problem particularly for very large companies. The more nimble, small or midsize organizations, that’s less of a fear for them. They’re trying to compete more effectively and trying to get [the] most out of their employees.”

At the same time, the cost of implementing BI solutions has dropped dramatically, particularly with the advent of cloud-based computing and software-as-a-service (SaaS) applications, both of which allow companies to invest in BI technology without building their own giant data-warehousing sites. “The cost factors have come down by a factor of six or seven,” estimates Brad Peters, CEO of BI provider Birst. The result is a more level playing field for smaller and midsize companies that could never before afford the enterprise data-mining solutions of their larger brethren. “There are newer tools out there and the expenses have come way down,” adds Peters. “A smaller organization can inherently be more agile and leverage these capabilities to have access to things that previously only the big guys had. The big guys may have as much analytics as you do; but if you have a more agile way of using them, you’ll be faster—and you don’t have to spend $20 million anymore.”

Birst was the first cloud-based BI provider to win a spot on Gartner’s Magic Quadrant rating of BI providers, and its high functionality and easy-to-use interface received high marks on the 2013 review. But Gartner’s Sallam notes that cloud adoption has been slow, primarily because of security concerns related to mission-critical types of deployment, particularly for financial services firms and other highly regulated industries. “There are always some security risks when you put data outside your firewall. How much of a risk? Can the risks be mitigated to the point where the value of the cloud outweighs that risk? Those are still open questions,” she notes. That uncertainty leads some CEOs to opt against cloud-based BI. For example, although Birst did offer the less expensive cloud option, Hiperos’ Dickinson chose the on-site implementation.

That cloud resistance will likely continue in the market for a time, acknowledges, Sallam. “I’m in the risk-management business, selling to large pharmaceuticals, financial services organizations, [which are] heavily regulated industries,” she says. “They need to know their data is secure in my data center. [However,] “as the gravity of data shifts to the cloud, you will probably see some of those attitudes change.”

The question of just how to quantify BI’s ROI is also partly unanswered. Like other technology adoption, some applications easily translate to ROI while others are more challenging at drawing a direct line from investment to return. But as business users see the value of making analytics more pervasive, accessible and flexible, it’s becoming easier to make the business case.