The Case for Data Stewardship
Information Management Magazine, February 2005
The Sarbanes-Oxley Act of 2002 (particularly Section 404), has created a sense of urgency for senior executives to take an active interest in the accuracy, consistency and timeliness of their data. Now more than ever, corporate compliance, audit and governance issues must be efficiently resolved. Yet it is widely believed that less than half of large companies have a formal data stewardship or data quality program that protects and leverages their unique strategic asset of data. Smart businesses are proactive, not reactive; they comprehend the business need for quality data. Aside from compliance and governance agendas, having first-class data (and the ability to unlock it) significantly helps all aspects of your organization's business - helping to effectively gauge and manage risk, avoid redundant work loads, increase customer satisfaction (on the front and back ends) and provide for better business intelligence and decision making support. Conversely, poor data quality will have injurious consequences across all enterprise operations - negatively impacting the most critical customer service obligations (such as billing and remittance processing), skewing decisions and fulfillment obligations, and creating a host of other tactical problems. Numerous hidden business costs such as revenue leakage and higher capital expenditures may all be maladies that stem from lack of data integrity. While there are tools that can help with and augment your formal methodology, capable data stewardship requires the symbiotic merging and integration of the automated (technology) with the manual (people). For many organizations, data problems remain secreted or hidden until issues are uncovered that result from a formidable event of costly business impact, such as an external audit, fraudulent activity, subpoena or valued customer satisfaction issue. A prolific variety of complex legacy data (which may go through many iterations of manual reconciliation on its way up to senior management's eyes) lingering in cloaked and "siloed" structures will always be poised to wreak havoc when least expected. Today, with the advent of widespread Internet and e-commerce applications, the data problems of an enterprise can be exposed to the entire consumer world. If you have bad data on your customers (e.g., not recognizing them across accounts), they will know - often long before you catch on. The time to establish a formal data stewardship program is now!
When implementing a formal stewardship program or policy for your organization, it will be important to appoint the right person as the lead steward and assign the steward an appropriate title. This person will understand and approach duties from the perspective that data quality is a collaborative business and IT matter as he/she champions high-quality data across all multinational systems - from repositories to reports. The most effective stewards will be familiar with core business values and practices but should also be able to understand data models, tech-speak and data storage topics from a high and low level. (A systems analyst background with relevant industry understanding and outstanding communication skills will be ideally suited to bridge this sometimes giant gap between technology and the business.) A strong leader and a people person, the lead steward will educate and expand many people's horizons about proper data governance and the consequences of unreliable data on business objectives; the steward will make others accountable for continuous improvements in the caliber of data. Lead stewards should be visible senior-level people who are respected and well liked in the organization, with the ability to motivate and envision change from a high level. They should be empowered by senior management and steering committees to directly address issues and manage standards-based implementations from both a business and technology-centric view, brandishing their "data police badge" when staff members resist data standards and the added responsibility or loss of control that come with such regulations. A VP-level title of data steward is not out of the question.
Stewards must have specific and measurable goals for data quality, making sure that public data helps enforce and promulgate vital business rules and processes. A viable formal stewardship policy will be rooted in ongoing standards that identify goals, priorities and quality metrics within all systems infrastructure elements (from data warehouses to OLTP applications) and business functions that touch or affect data. The steward will tie business strategy to data strategy, applying generally accepted qualitative metrics and heuristics (risk management, cost benefit analysis, change management, etc.) to the measuring and enforcement of data quality. With increasingly aggressive life cycle timelines and rapid application development (RAD) paradigms, organizations should not have to keep worrying about the veracity of data from conversion to conversion, re-inventorying and re-reconciling data elements piecemeal every time a new systems integration project is tackled. Without ongoing business driven tools and touchstones for data assessment and improvement, your data stewardship program is doomed to fail. Only a continuous and structured methodology will bring long-term benefits, not a sustained culture of quick data fixes. For larger enterprises, this methodology will have functions that leverage time-honored calculations, derivations curves and benchmarks for measuring quality. The business rules of the corporation should be documented and maintained alongside data models, data dictionaries, meta data repositories, etc., so that a spirit of common responsibility, knowledge and ownership is cultivated. The formal stewardship policy will reside in a public place (corporate intranet) along with other operating policies so that employees who create, use and own the data develop a sensitivity to issues of data rectitude.
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If data quality improvements are to continue to be the norm, the impetus must come both through technology architecture and business requirements. It must be understood and evangelized throughout the company that many times business continuity is data continuity: data problems invariably turn into business ones, increasing a firm's exposure to various unanticipated risks. In contrast to purely technical issues, a data steward will sometimes have to address and analyze data problems that are attributable to business routines that have a large human/manual element, and thus cannot be changed easily. The steward will need to have a business understanding and the wherewithal (support of senior management) to carry out the reengineering of various business processes. This may necessitate that they have a cursory understanding of various types of unstructured data (such as that found in electronic document management systems) and data that is not stored digitally, as well as the integration challenges associated with them. In such cases, a steward may have to help engineer a balance between the manual processes - routing paper requests, bar-coding, manual archiving - of a company's information center and records management databases and software.
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