TDWI | Training & Research | Business Intelligence, Analytics, Big Data, Data Warehousing

Thinking Outside the Box Enterprise Information Management Box

Just because you can buy off-the-shelf EIM software doesn’t mean you can also buy an off-the-shelf EIM practice.

• By Stephen Swoyer
• April 8, 2009

Just because you can buy off-the-shelf enterprise information management (EIM) software doesn’t mean you can also buy an off-the-shelf EIM practice.

Beware the promise of EIM-in-a-box says industry veteran Philip Russom, senior manager with TDWI Research. EIM isn’t a technology category, Russom counsels; it’s an overarching practice. Moreover, EIM is best pursued in an iterative fashion: you build up an EIM practice -- painstakingly, in some cases -- by using many of the same data management (DM) best practices that you’ve honed in your data warehouse (DW) and business intelligence (BI) practices.

For this reason, Russom says, a lot of shops are probably at least part of the way along the bumpy road toward EIM. “EIM unites related information management tools and their best practices into a unified practice and infrastructure. Organizations use information management tools and techniques in implementing their EIM strategies, and organizations need these to achieve their EIM goals,” Russom writes in Enterprise Information Management: in Support of Operational, Analytic, and Governance Initiatives, a TDWI monograph published last month.

“Most organizations already practice unconnected pieces of EIM at a minimal level, although they may call it something else. True EIM is a well-thought-out strategy of orchestrated phases,” Russom continues. “Iteratively working through the EIM process increases the degree to which it is practiced.”

According to a recent TDWI survey, enterprise shops are both taking EIM more seriously and taking more substantive steps in the direction of full-blown EIM practices. On the strategic front, a combined two-thirds of respondents -- principally attendees at last month’s TDWI Winter World Conference in Las Vegas -- indicated that holistic EIM is at least “highly strategic” to their primary business goals. (Significantly, 20 percent of this group went so far as to describe holistic EIM as “very highly strategic” to their primary business goals.)

Collaboration-wise, enterprise shops are starting to get their acts together: a full 20 percent of respondents rated the level of formal coordination in their information management practices as “high” or “very high;” another 45 percent described their internal coordination levels as “moderate.”

That’s another reason why shrink-wrapped EIM is -- in the vast majority of cases -- a non-starter. Information management on an enterprise scale requires an unprecedented degree of collaboration between and among business units and technology domains.

“[G]etting there demands a number of adjustments to current technology solutions and business processes. For example, truly holistic enterprise information management has many organizational and technical requirements. EIM is inherently collaborative and cross-functional,” writes Russom. For this reason, he counsels, the cultivation of a successful EIM practice requires significantly more in the way of inter-departmental collaboration: call it new and previously unrealized collaboration.

“[M]any organizations manage data in isolated silos strewn across the enterprise, using a variety of tools and teams. A certain amount of coordination among these teams is inevitable, because their solutions interact,” Russom writes, citing the inevitability of collaboration -- of what might be called necessary or pragmatic collaboration -- in any modern data management practice. “[D]ata integration tools regularly call data quality tools, data federation tools connect to operational databases, and data quality and master data management solutions often require changes to other, related data management solutions.”

Again, he cautions, pragmatic collaboration just isn’t enough. “[T]his is a good start, [but] EIM demands much more. Ideally, the combination of all data management solutions involved should form a recognizable architecture -- even if it’s loosely federated -- that’s held together by agreed-upon methods for the deep tool and platform interoperability that EIM assumes,” Russom indicates. “Getting to this point usually demands the creation of a new, broader team structure, like a central competency center, a data stewardship program, or a data governance board.”

EIM isn’t a technology problem, per se, although it obviously has its technological components. When IT and business leaders grapple with technology problems, they tend to focus on interoperability, particularly when they expect to be using a heterogeneous mix of tools. Interoperability is important in any EIM project, Russom says, but it should not be treated as the sole criterion by means of which an organization chooses its EIM tooling, much less develops an EIM strategy.

Put another way, you probably aren’t going to get complete interoperability right out of the box, so it’s pointless to quibble over what might be called “degrees” of interoperability. If you can get close to -- but not quite -- 100 percent interoperability with a mix of EIM tools that both addresses your business needs and is consistent with your alignment priorities, don’t let that deter you.

“Acquiring a long list of tool types for an organization’s EIM portfolio is important, perhaps even a base requirement. Equally important is that each piece of the portfolio integrates and interoperates with others appropriately,” Russom writes. “To set the proper expectation, don’t assume 100 percent interoperability; tool integration should be selective, based on prominent business and technology needs.”

Finally, although adopters shouldn’t lose sight of the “E” in EIM, they must also guard against the (understandable) urge to try to shoot for an enterprise-wide “big bang” right out of the gate, Russom advises. “EIM is inherently broad, involving some definition of ‘enterprise scope.’ But don’t start by addressing the entire enterprise. That would be a risky ‘big bang’ project,” he writes, noting that “some organizations begin by deepening the integration and interoperability of the information management tools in their existing BI and data warehousing infrastructure. Others do the same with platforms for ERP or CRM. Still others begin with EIM for financials or the supply chain.”

The most important takeaway, Russom concludes, is that EIM is both an iterative, and -- to a degree -- an organic process. “As diverse pockets of EIM develop from these starting points, the next step is to connect the dots and unify them at a depth that is appropriate to enterprise goals.”

The full monograph is available here.