Barnaby would like to thank Peter Graham of Palladium Group, Inc. for his contributions to this month's column.

The pressure on CIOs today has never been stronger. Demands from the CEO are requiring IT to take an enterprise view of its information assets and the tools it provides decision-makers. An organization's information platform, including data management and analytic tools, plays a vital role in enabling management processes necessary to execute strategy. Organizations that have recognized analytic capabilities as a core competency are allocating IT resources and initiatives to support analytics. They are also increasing their ability to provide consistent information to the organization for improved decision-making. These organizations are creating efficiency within information management through a scalable analytic architecture that supports the enterprises' needs and, thus, they are aligning the IT function with the strategy of the enterprise.

However, many organizations struggle to take an enterprise view of their information assets. Many continue to maintain redundant information sources as well as numerous analytic tools to meet decision-makers' query, reporting, dashboard and planning needs. Why isn't everyone linking their information architecture and data assets to support strategy execution? Our research indicates that many organizations suffer from four key barriers that hinder their ability to leverage their data assets.

Information strategy. Is IT meeting performance management needs, and is the analytic architecture scalable? Is IT aligned to organizational strategy? To sustain strategy execution, technology needs to be addressed as an enabler for the organization. A company's analytic platform plays a vital role in enabling management processes necessary to execute strategy. To support the analytic needs of the enterprise, a scalable information architecture is required, which includes a set of distinct layers that facilitate turning data assets into corporate information. Alignment of the organizational elements to support the analytic platform is critical. By optimizing ease of deployment, data and information assets, usability, richness of analytics and scalability, organizations can help turn data assets into critical decision-making information.

Analytic capabilities. Are users satisfied with their analytic tools? Are current IT investments being realized? Organizations struggle with the proliferation of reporting and analytic tools. The number of available tools has more than tripled in recent years. And, according to TDWI research, 42 percent of companies still allow departments to purchase their own solutions.1 However, the challenge is not necessarily standardizing on one analytic tool - the challenge is providing the best-of-breed analytic tools that will facilitate improved decision-making across the enterprise. Further, IT must be able to support all of these tools, translate the tools into an analytic platform and provide the necessary resources to realize the organization's investments.

Information silos. Is critical data redundantly stored and manipulated within different departments or divisions? What level of trust in the data do decision-makers have? The entire industry has experienced data warehousing projects that often fail due to long development cycles, poor information quality and the inability to adapt to quickly changing business conditions and requirements. Most organizations suffer from the information silo barrier. To meet the information needs of the business, organizations will typically make shortsighted decisions to build one-off solutions. As these tactical solutions evolve and grow, data proliferation and redundancy expands until the point where data integrity is sacrificed. To address this proliferation, there is extreme pressure on IT to establish a data architecture strategy that centralizes data into an enterprise model that represents the business. The data strategy must be aligned with the business and analytic needs of the organization.

Data integration. Do you have standards in place across business rules, hierarchies and attributes? Do you share information across different functional applications via scorecards and planning processes? Performance management master data is becoming a critical issue for organizations. Government and industry compliance requirements are the primary drivers for organizations to address master data. In addition, there is internal pressure to provide consistent and accurate data across information systems. Organizations need to start addressing the master data management (MDM) process to establish ownership and accountability across the entire enterprise. Standardization of business definitions, calculations and hierarchies is critical to create an enterprise view of the organization. Finally, a technology platform that centralizes MDM and provides synchronization capabilities to source and target systems will create a sustainable solution for enterprise data integration.

While the challenges and pressures on today's CIO are many, the rewards of leveraging their data assets to support strategy execution include re-engaging IT with the business community, adding critical value to the organization by aligning IT to corporate strategy and becoming the leader in the market.

Reference:

  1. Wayne Eckerson and Cindi Howson. "Enterprise Business Intelligence: Strategies and Technologies for Deploying BI on an Enterprise Scale." TDWI Report Series, August 2005.

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