In the IT landscape, the only constant seems to be change – that and the never-ending growth in the amount of data...
By submitting your personal information, you agree that TechTarget and its partners may contact you regarding relevant content, products and special offers.
organizations need to manage.
Now, though, there’s also a growing recognition of the business value of all that data, and of the need to better manage it. That’s the focus of the still-evolving discipline of enterprise information management (EIM), which is aimed at optimizing the use of data as a corporate asset while breaking down organizational barriers that can result in compartmentalized information and disparate data management processes.
But that’s often easier said than done. Leslie Owens, an analyst at Forrester Research Inc., said EIM can be hard for organizations to get their arms around because it’s so broad in nature: Typically, an enterprise information management program involves structured as well as unstructured information and encompasses functional areas such as data quality, data governance, master data management (MDM), and data retention and disposal.
To be successful, Owens advised, you must avoid overreaching and develop an EIM strategy that’s realistic and attainable – though with an eye to longer-term ambitions. “It must be a multiyear, multiphase program, but you also have to have some kind of big, hairy, audacious goal that you want the effort to mature into over time,” she said.
As with any business-oriented program, a company embarking on an EIM initiative should first reach consensus on its goals and the problems it wants to solve, according to Owens. There also must be an agreement that the organization will have a single enterprise-wide data management strategy: What can derail EIM efforts, she said, is when “you have multiple projects operating and being managed and governed without a lot of coordination.”
Horse before cart on an enterprise information management program
Owens suggested starting the EIM deployment process by building some shared information management capabilities and objectives into existing programs or functions, such as business intelligence and MDM initiatives, in order to create recognition internally that they are “all moving parts of a larger program.” Another key to EIM success “is to not start with technology,” she added. “People that try to build a strategy around the tool are putting the cart before the horse.”
Fred Hargrove, leader of the EIM practice at MorganFranklin Corp., a consulting and professional services firm based in McLean, Va., recommended that an enterprise information management program begin with an evaluation of current data management capabilities against a best-practices maturity model. That can help facilitate discussions about existing shortcomings and aid in laying the foundation for an EIM strategy, Hargrove said. He noted that guides to data management best practices are available from a variety of credible sources, such as Forrester, Gartner Inc., DAMA International and The Data Warehousing Institute.
But Hargrove cautioned that EIM doesn’t exist in a vacuum: There are numerous subsidiary issues that he said must be considered as part of developing an EIM plan. For instance, it’s important to focus on data quality processes and the software tools that are being used to manage and monitor the “fitness” of information to support business decisions, Hargrove said. Likewise, he added, proper data governance is needed to provide oversight and ensure that common data management practices are adopted enterprise-wide.
Despite the potential data management and business benefits of an EIM program, getting management support and funding can be problematic, according to Hargrove. He said EIM processes tend to be perceived as just “overhead” within an organization if their true value isn’t well articulated. Even if an EIM effort is approved and gets off the ground, ensuring that a return on investment (ROI) is realized and demonstrated should be a priority for the program managers, Hargrove said.
Gartner analyst Lyn Robison said corporate executives might not feel the immediate need for EIM programs unless their companies are operating under regulatory-compliance requirements or have other clear business needs for unified data management processes. However, he predicted that EIM will “become compulsory” in the years ahead because of the business problems that can result from inconsistent or uncoordinated data management.
In EIM’s absence: the fallout of ineffective information management
As an example of those problems, Robison cited the Wall Street meltdown in 2008 and 2009, in which the failure of one company often led others to collapse as well. “When Lehman Brothers failed, some of the other companies that were affected didn’t recognize the extent of their exposure because they handled information in so many disparate ways – that was an EIM issue,” he said. Similar exposures can exist in supply chain relationships, yet existing reporting structures often don’t provide clear views of those issues, Robison added.
In practice, EIM might not be for everyone, warned Jason Wisdom, president and principal of New York-based Wisdom Consulting Inc. “A lot of companies implement enterprise-wide solutions only to find out at the end that it caused more harm than help,” Wisdom said. Other EIM projects never reach that point, he added: “There are horror stories of millions of dollars spent, with no new system going live.”
To determine whether EIM is right for an organization, Wisdom recommended steps such as identifying business requirements for improved data management and defining both the expected ROI of an EIM program and the required budget. He said that process should also include an assessment of how complex the data environment is and whether internal resources have the necessary skills and expertise to manage an EIM implementation.
Seth Earley, president and CEO of information management consulting firm Earley & Associates Inc. in Stow, Mass., said another typical feature of successful EIM programs from a data management lifecycle perspective “is getting information into common structures using consistent metadata and controlled vocabularies.”
With the broad view of data enabled by that and the other components of a well-designed EIM strategy, Earley and other analysts said that EIM can become an all-encompassing approach to better data management and more effective IT systems – provided you can convince corporate and business management to get on board.
Alan R. Earls is a Boston-area freelance writer focused on business and technology.