By Alan Radding Published on 06/11/2007
Clients engaged consulting firms repeatedly for everything from building the data warehouse to populating it to maintaining it. They would do enterprise data modeling, data cleansing, data normalization, and more.
Seeing is Believing
Throughout the 1990s, large enterprises spent hundreds of millions of dollars to build data warehouses, data marts, OLAP (online analytical processing) capabilities, ad hoc query and reporting, data mining, and more. Clients engaged consulting firms repeatedly for everything from building the data warehouse to populating it to maintaining it. They would do enterprise data modeling, data cleansing, data normalization, and more.
Into this century the work continued, as companies turned to consulting firms to develop Balanced Scorecards, key performance indicators, visual executive dashboards, and decision support systems. For a while people referred to these as executive information systems. Today all of the above and more, such as predictive analytics and forecasting, form part of what is now referred to as business intelligence (BI).
Despite pouring billions of dollars into BI initiatives, top executives still seem to be wandering lost in the corporate BI jungle. "I have a client who spent $150 million on an ERP system and has it working perfectly. Still, he doesn’t know what is happening in his business. He has to produce information manually," says Scott Songnefest, U.S. practice leader for business intelligence and data warehousing at Deloitte Consulting.
That client isn’t alone. In a published report, AMR Research predicts that North American companies will spend $23.8 billion on various business intelligence technologies in 2007, an increase of 9 percent over the previous year.
"Companies have been collecting a ton of information, but not a lot of people have been able to unlock it and bring it to solve specific business problems," says Gregory Molley, managing director, BI and performance measurement, within the Oracle practice at BearingPoint. This corporate inability to leverage previous investments in BI technology or arm top executives with the information they need to compete effectively promises to be a boon for consulting firms that can find the BI Promised Land and lead clients there.
Executives Discover BI
In recent studies, corporate executives continue to identify management information for decision-making as their number one priority. "In a study we did last year, 53 percent of the executives surveyed wanted better information for management decision-making," reports Jeanne Harris, director of research at the Accenture Institute for High Performance Business and coauthor of Competing on Analytics (Harvard Business School Press, 2007). A more recent Gartner study, she notes, confirms the Accenture finding of BI as the top executive priority.
Executives at least appear to have a good handle on their financial information — 86 percent of respondents to a recent Deloitte study report that their companies are good or excellent at reporting financial performance indicators. However, when it comes to reporting nonfinancial performance measures, 40 percent rated their company at best as average while 23 percent gave their company fair or even poor marks.
So, after nearly two decades of effort by companies to capture, report, mine, and analyze their data, both financial and nonfinancial, and the expenditure of untold billions of dollars, the majority of executives still think that they lack the information necessary to compete effectively, especially when it comes to nonfinancial performance metrics.
Another Songnefest client "spends $700 million to $800 million to produce management information that they don’t trust." This client invested in a data warehouse and now employs 100 people in a monthly process to produce financial information. With regulations now requiring C-level executives to sign off on this information, it is no wonder that BI finally has become a top management priority.
"BI has been successful for very specific measurements at the lower levels of the company. A line manager will query a database and get answers, but executives won’t do that. They still need people to build a special tool for them," says Eric Berridge, cofounder of the Bluewolf Group and coauthor of Iterate or Die: Agile Consulting for 21st Century Businesses, due to be published later this year. Much of the BI news recently has focused specifically on efforts to deliver BI to C-level executives.
Until recently, the BI market was highly fragmented. There were big database vendors and then a slew of small vendors who fill in the database ecosystem with specialized query, reporting, analysis, and data management tools and applications.
In March, Oracle announced plans to acquire Hyperion Solutions, a specialized financial pure-play BI player. Oracle will have to merge Hyperion’s BI capabilities with its own BI functionality and sort out its existing customers from among Hyperion’s 12,000 customers, many of which, reportedly, are customers of Oracle rival SAP.
Also in March, Accenture teamed up with SAS, another pure-play BI analytics vendor. Specifically, the two companies plan to work together to enhance Accenture’s SAS capabilities and also enhance SAS software by leveraging Accenture’s industry expertise, according to Accenture. In short Accenture will be able to use SAS’s vaunted analytics to bolster its own Accenture Information Management Services (AIMS) organization, while SAS gets access to the huge global Accenture sales and customer network. Of course, Accenture also maintains partnership and alliance relationships with Oracle and Hyperion.
BI clearly remains a big opportunity for consulting firms. Every top-tier consulting firm and most second-tier firms maintain alliances with the big BI database vendors and with various BI tool vendors. BearingPoint is typical "We have relationships with Oracle and also with IBM, SAP, Google, and Microsoft," says Molley.
Tools or Vision?
Although the latest news has focused on BI tools, BI consultants question whether the problem with BI is not tools but the lack of BI vision on the part of corporate executives. A number of factors have contributed to the failure of BI in the executive suite. "BI was never a top business problem, until now," says Harris.
First came the technology excuses. "They didn’t have the data available or they didn’t have the processing power," says Harris. Certainly, the complicated database joins did require considerable computer processing horsepower, which was a costly and carefully rationed resource as recently as a decade ago. Big queries could bring even the beefiest mainframe to its knees. "But now the power is there," she notes. With multicore, multiprocessor, scale-out, and scale-up systems, technology definitely is not a BI constraint today.
Another obstacle was computer-phobia among C-level executives. "The previous generation of C-level executives didn’t use computers," says Harris. They expected admins and secretaries to use the computers for them. Many couldn’t even type a letter on their own, never mind search a file system or query a database. However, "now there is a new generation of leaders in the C-suite, and they all use laptops," she continues. You can’t get out of B-school today without mastering PowerPoint, Microsoft Access, Google search, and other sophisticated tools.
But having the computer skills and using the computer to access and analyze information for decision-making are two different things. The challenge today is the vast amount of data that must be captured, processed, aggregated, and presented. "Managers are looking at mountains of information. To make sense of it, they need linkages to the broader enterprise view. They need to come to agreement around measurements and metrics and definitions," Molley continues. That’s a vision and strategy thing, not tools.
For example, Molley cites the situation of the large bank in which different business units all keep data on their customers. In effect, the customer is owned by the business unit. The same person, however, often is a customer of different business units, which complicates the BI picture. Each stores, manages, and analyzes the data in different ways. "The challenge is really at the enterprise level," he says, which will require BI vision and strategy to solve.
The New BI
The old BI sought pretty simple answers. How much of a particular product did we sell in this region in this time frame? How did this region compare to that region? If a manager was particularly BI-savvy, he or she might try multidimensional OLAP, in which you compare multiple factors with other factors in a complex matrix, cutting it into different views by this factor or that factor, "dicing and splicing," as it was often referred to. At that point, however, the call usually went out for the Ph.D. statisticians to interpret the results.
Then there was the now apocryphal data mining story about diapers and beer, which drove data mining to become the BI rage for a while. Somebody looked at sales data, moved displays around, looked at the data again, and discovered that the store would sell more beer on Friday afternoon and Saturday mornings if it displayed the beer next to the diapers near the checkout counter. Eureka! Operational managers suddenly saw a tool that they could use to boost the performance of their business unit.
The new BI is moving beyond ad hoc querying, reporting, and even data mining as it makes a play for the executive suite. The latest BI hot button, aimed to grab the attention of a new generation of executives versed in information-driven decision-making, is analytics, the subject of Harris’s book. Even more than just analytics, the goal is predictive insights — the notion that you can model and analyze data to predict future behavior, such as how a group of customers will respond to a subtle change in product pricing and packaging.
"By analytics we mean the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions," writes Harris. Predictive analytics are not exactly new. They have fueled lending processes such as credit scoring, in which a credit provider tries to predict the likelihood that a borrower will default. Financial institutions use it to predict churn in their customer base and to identify likely fraud. Harris takes analytics even further: "Analytics can support almost any business process," she writes.
More than just analytics, executives need their BI to be forward-looking. "Now executives want a new BI that is predictive," says Sanjay Sehgal, principal, CFO advisory services practice, Archstone Consulting. However, for most organizations, BI will end up delivering a blend of historical and predictive analysis as executives try to understand what has happened, what is happening now, and what they could change to get different results in the future.
In its own survey, InfoWorld magazine found that 62 percent of respondents report using predictive analysis now or plan to do so within the year. Of those, most were applying it to sales, finance, and marketing. Fewer were applying it to logistics/materials management or customer service/call centers.
Not only does the new BI have to be more predictive, but also it needs to be real-time. Relying only on data that is months, weeks, or even days old won’t cut it. "Companies need to move away from historical data to real time. They need the analytics embedded right into the business process," says Molley.
Finally, to date, BI has focused primarily on structured data from databases and various applications. The next frontier for the new BI may be unstructured data. For example, what insights can executives glean by applying analytics to such unstructured data as call center or help desk records?
There remain a number of obstacles to BI, although technology isn’t one of them any longer. Rather, the obstacles today, surprisingly, continue to revolve around many of the same issues that have troubled BI since its earliest days: data availability, data quality, and agreement on the meaning of the data.
"The number one complaint I hear from executives is that the information doesn’t match," says Sehgal.
This problem has been aggravated by the growth of the global economy. "With acquisitions, companies have grown globally. Now there are multiple instances of systems. Companies are pulling information from many more places," Sehgal continues.
The solution is as obvious as it is old: "Companies must strive to get to one version of the truth," says Sehgal, a refrain consultants have been repeating since BI began. Yet even now, companies have difficulty agreeing on such basic numbers as what constitutes sales revenue. Is anyone surprised that often the numbers don’t match?
Organizational silos continue to frustrate BI efforts. "Companies have to connect the dots across all functions," says Molley. C-level executives will continue to remain in the dark as long as the data they need sits in each individual department. Or, they will have to spend a fortune, as Songnefest points out, to pry that data out of each department and normalize it before they can learn anything from it.
While the trend toward information-driven BI analytics in the executive suite, propelled by books like Harris’s, appears inevitable, there remain a large number of diehard decision makers who prefer the from-the-gut approach. Downplaying analytics, these executives will make their decisions in an instant based on their gut instincts.
These from-the-gut decision-makers have found support in Malcolm Gladwell’s book titled Blink (Little Brown, 2005), which promotes decision concepts around what Gladwell refers to as the adaptive unconscious. His message: "Decisions made very quickly can be every bit as good as decisions made cautiously and deliberately."
The two approaches, Harris’s and Gladwell’s, may not be as contradictory as they initially appear. Actions taken in a blink, it turns out, often are based on years of experience that had been thoroughly digested before that seemingly instantaneous decision.
If so, BI and analytics in the executive suite may simply be a way to systematize and leverage the aggregation and digestion of the organization’s collective, adaptive, unconscious experience.