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
- 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.”
- 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.”
- 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?
- 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.
- 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.
Technology also has grown more and more user–friendly; with the ubiquity of mobile devices, smartphones and web-based computing, business heads formerly phobic of technology no longer see data as a four-letter word. “BI is about creating automated machines that churn out business-relevant information that you can use to drive decisions,” says Peters. “That’s been around a long time, but what’s different this time is that it’s come out of the closet to some extent.” Peters says that back when he attended Harvard Business School, if anyone had talked about slicing and dicing data as a business tool, there would have been a revolt. “CEOs don’t do that. People who live in caves, in dark corners, do that. It was, ‘you give me the data; and at the end of the day, I’ll make a decision.’ Data analysis was seen as more of an actuarial task than a strategic differentiator.”
To be fair, these tools were once only comprehensible to the “dataheads” in those dark corners. Today, user-friendly interfaces are making it possible for C-level executives on the business side, who have no background in technology, to explore the data, play with the numbers, create their own reports and make smarter decisions more quickly and efficiently. With new dashboarding technology, a CEO can quickly pull up regional sales data, rendered on a geographic map with visualization technology, and see anomalies and areas for potential growth, says Dwight deVera, senior vice president at arcplan, a BI solutions provider. The CEO might, for example, notice that the highest sales tend to be clustered in parts of the country that have regional distribution sites and can see that this trend has been going on for several years.
“If you know your product would have appeal in the Pacific Northwest, but you don’t yet have a physical site there, you may be able to quickly rationalize the decision to build one,” he notes. Alternatively, BI tools would allow the executive to see which 20 percent of the products are generating 80 percent of the sales and then which of those products falling outside the 20 percent are generating an outsized direct cost, as well. “The decision to sunset that one product ultimately comes from the top, and it’s one that can be made fairly quickly,” he says.
Because of the speed with which decisions can be made, the potential for cost control is considerable, even when the percentages saved appear small or incremental. Kevin O’Rourke, director and BI Solutions practice leader with tech consultancy TriCore Solutions, recently worked with a medical-device maker that manufacturers defibrillators. The executives had decent insight into the revenue of a particular product set, but they did not have as clear a handle on its cost—and those costs seemed to be rising 4 percent year over year. Their new BI solution allowed them to do ad hoc analysis on both the revenue and cost sides to see cause and effect.
“They had, in near real time, daily or hourly, a view into which product costs were going into particular items and were better able to make changes from a supply chain or vendor relationship, based on an understanding of these costs and of margins going up and down,” says O’Rourke. For example, when the cost of oil was at an all-time high, they were quickly able to see that fuel costs (needed to ship from a manufacturing facility in the Middle East) were driving up the expense side. The billion-dollar company was able to save $7 million over a six-month period. “You could do all that in an Excel-based world, but it takes so much time and energy. Your time to market is not going to be as useful,” says O’Rourke.
Being able to compare cost or revenue per employee to the ratios of competitors is another benefit of new data analysis. By comparing your company’s ratio to that of your nearest competitor, you can better see where you’re coming out, says deVera. “You could also be a small company and compare yourself to General Electric, if you’re in the same industry. Even if they’re bigger, you can see their ratios and yours and it’s an apples-to-apples comparison.”
One company has even dedicated itself to turning BI technology outward and mining the public Web for just such valuable content. “There is a lot of garbage out there, that’s for sure, but there is so much gold out there that you never had access to, as a company. Now is the time to pay attention to that data outside the firewall, as it relates to your business,” says Keith Cooper, CEO of Connotate. He recently worked with a large brand-name hotel that was getting negative feedback from guests, saying the rooms in its brand-new wing were too noisy. Management had determined that they would have to spend several million dollars to soundproof the walls and ceilings of the entire wing. Connotate mined the web for all reviews and customer comments from dozens of review sites, presented by topic and date. “In the next 60 days, they discovered that several guests had figured out the problem for them. The doors to the rooms were missing the rubber bottoms that keep out noise and light. The $5-per-room solution was all that was needed.”
On the revenue side, CEOs can use BI analysis to spot new opportunities that would require minimal capital investment to realize. “It takes [bits of] information that are typically scattered around the company and brings them together to reveal opportunities,” explains Wayne Simmons, CEO of The Growth Strategy Company. Simmons worked with a high-tech client that discovered a new niche in an emerging market for a legacy product they’d had for years but that had leveled off sales in the U.S. “They were able to connect the product portfolio with the market analysis, so they had a finished product they could get to market very quickly.”
Another client, a consumer-product company, had the goal of globalizing as quickly as possible. Their primary metric for evaluating new market opportunities was GDP; high-growth countries were first priority to penetrate, and India was at the top of that list. But when they drilled down to look at other variables, such as market access, political dynamics and regulatory environment, “that painted a very different picture,” says Simmons. “The highest growth markets were the most expensive to go into and operate in. That fundamentally altered their strategy.” After all the analysis, Colombia came out near the top of the list, where previously it had not been on the radar screen at all.
Done right, BI can conceivably provide every person in the organization, from C-suite to front line, with information that makes it easier for each to make better decisions on the job. A customer service rep, for example, can pull up a customer’s entire purchase history, favorite products, most recent orders and complaints and be armed with that data when speaking with that customer—ideally leading to better service and retention. There are a host of other potential applications. Comcast, for example, rolled out an interactive reports application for call center reps to do what-if scenarios, designed by OpenSymmetry. The reps were able to view, in real time, how many services they’d sold in a month, and how many more they’d need to reach a certain threshold for reward. “It gives the initiative to the people who otherwise wouldn’t know what they’re going to make. Now they know that if they sell these two additional items, they’ll be eligible to get X,” says Todd LeBaron, CEO of OpenSymmetry.
Although the opportunity to have useful information remains the ideal, in practice, the actual number of employees getting their hands on BI, or opting to use it, is still quite low across companies, says Gartner’s Sallam. “Despite companies’ spending [collectively] $14.4 million on these tools, when we actually survey companies about what percentage of [their] people use the tools, that percentage is below 30 percent. So the challenge is, how do we get analytics in the hands of more and more users?”
To reach that goal, large vendors, such as SAP, Oracle, IBM and MicroStrategy have to adapt their enterprise solutions to be more flexible and accessible, and smaller players like Birst, Tableau and Tibco need to continue building their brands as providers of user-friendly interactive data exploration applications at a price point even small firms can afford. In the meantime, it seems that no CEO can afford to ignore the BI wave, regardless of company size or industry. As Peters points out, those who recognized data as a competitive weapon a decade ago are reaping rewards today. “There is no way Walmart would be what it is today if it had not embraced data warehousing the way it did back then. The ones able to get their fingers on the right information to tweak and manage business to a level of performance that takes them above their peers over time—they win.”