Long Is the Road that Leads to BI and PM Excellence
BI and PM programs -- like that eternal city of proverbial renown -- aren’t just built in a day.
Business intelligence (BI) and performance management (PM) programs—like that eternal city of proverbial renown—aren’t just built in a day. In fact, says market watcher AMR Research, they frequently gestate over the course of five to ten years—and rarely mature without first encountering a hitch or two.
“Companies must crawl before they walk, walk before they run, and run before they run marathons. As in any maturation process, it takes time,” writes AMR analyst Jack Hagerty. “When BI/PM programs start, they are technology-centered. Then, at the highest level of maturity, they fuse culture, philosophy, and technology in a grand coalition to drive business by the numbers.”
The first phase in any BI and PM program is historical: companies need to know where they’ve been in order to know where they are, much less where they want to go. In this regard, Hagerty says, companies frequently start with the basics, reorganizing projects to help improve access to business data, reduce reporting cycle times, and increase visibility into line-of-business performance.
“It’s mostly about displaying what has happened in the last business cycle, providing details and status to support the given department,” Hagerty writes. “Technology adoption has been minimal up to this point. Firms depend heavily on desktop productivity tools and ad-hoc processes to execute and monitor analytic tasks. In some cases, it’s each person for themselves, with coordination minimal. Companies grab the low-hanging fruit, allowing them to realize benefits quickly.”
In many cases, organizations next seek to capitalize on the successes of phase one, pushing reporting and other BI capabilities out to more and more information consumers, making better use of existing tools, and investing in additional resources to drive user uptake. In this phase, Hagerty notes, BI and PM projects start to trend from the purely tactical to the more strategic. They’re also more visible within departments—although groups still for the most part work in silos.
“Data issues raise their heads at this step and increasingly dominate projects,” he explains. “Emphasis expands to include current performance data, and dashboards appear as the primary vehicle to inform workers what performance is now. Real-time or near real-time data plays a more prominent role.”
The next phase is one of increasing collaboration—call it a groupthink, of sorts, in which individual groups start to ask a single common question: where are we going? It’s in this phase that PM as a practice first rises to the fore, typically when organizations are able to identify a few clear operational and financial performance metrics that help drive the business, Hagerty indicates. “These [KPIs] … are mapped back to organizational strategies that give visibility into the health and future prospects of the business,” he points out. At this point, organizations typically make use of dashboards and scorecards to help align resources and objectives within and across groups, Hagerty says.
It’s at this stage that analysts and business power users start to come into their own, too. “Scenarios and models let analysts flex alternatives and recognize that decisions made in one part of the business will have an effect—positive or negative—on other constituencies in the firm,” he writes.
That’s as far as most companies have gotten—which actually amounts to quite a bit of progress.
Going forward, Hagerty says, organizations will focus on orchestration. “Few companies have reached [this level of] maturity. At this step, performance management is a cultural philosophy, not just a technology stack, with top-down goal setting cascading from executives through operations,” he writes. “The goal is to obtain a single, consistent, and streamlined view of the enterprise. Sense and respond becomes reality as companies adjust their model and execution to subtle shifts in dynamic markets. The business is truly run by the numbers, with expectations clearly set for all to achieve and incentives properly aligned.”
As organizations grow their BI and PM practices, their expectations change. So, too, do their patience levels. “Research now indicates that [BI and PM] maturity takes significantly longer [than three to five years]—closer to double the time—and is far more complex than companies originally thought,” Hagerty writes.
“This unanticipated complexity can be attributed primarily to data issues. Many firms originally expected to slap a BI tool or PM application onto their data architecture and then move on,” he continues, noting that once organizations try to capitalize on their initial BI roll-outs, “they immediately find that isolated, disparate, and overlapping data sources are a massive impediment to expanding BI/PM more broadly. In the words of one company, ‘It was time to stop the data insanity.’” Most companies—having reaped significant value from their initial BI investments—are undeterred. “Companies have been redoubling their efforts to address data infrastructure needs. This has [led] to more projects aimed at creating a solid foundation for future BI/PM growth.”
Stephen Swoyer is a Nashville, TN-based freelance journalist who writes about technology.