This company’s approach to data governance was well designed and consistent. Data stewards assigned to create and harvest data for the BPM system defined detailed business terms and managed metadata. Simultaneously, IT people analyzed the data in the local systems to assess its quality. The two tracks merged to implement the enterprise BPM strategy in short phases to deliver value to stakeholders quickly. Together, they determined the cost to build the required data and struck the perfect balance between the most meaningful KPIs and the ones they could develop quickly.

The next activity was to install a plan and tools for ongoing data quality assurance (DQA), such as automatic testing for data and cross-referencing of data. The last step was to make an implementation plan, as mandated by the BICC, for continually delivering education and support, selecting the implementation champions, identifying the management routines for decision-making, and incorporating the system into those routines. The implementation plan also facilitated communication with the entire organization.

The end result: A comprehensive BPM system, adopted by all of the business units, that accurately measures all aspects of the enterprise, enabling the organization to make decisions based on the right KPIs and the right data.

Teamwork Demolishes the Silos

A leading pharmaceutical company faced problems of data integration, teaming, and coordination. The company stored data in multiple unintegrated systems that prevented cross-functional analysis and reporting.

One of the key steps the company took to address these issues was to form a team to develop and implement a data governance program which outlined business rules (policies, standards, data definitions, and compliance requirements), decision rights, and accountabilities for governing the use of data. The team set control mechanisms as well as governance metrics and success measures. A data facilitator introduced checks and balances for business, IT, and compliance.

The focus on data governance was instrumental in enabling the company to implement a successful BI solution to integrate the data and make it usable for analysis, reporting, and decision-making. The organization also achieved increased agility in responding to requests for information from business stakeholders and external agencies (such as the U.S. Food and Drug Administration), enhanced ability to provide BI as an enterprisewide service in a consistent and compliant manner, and reduced redundancy through streamlined and centralized development.

A strong data governance program can help your company measure the right things, and measure them right. It’s certainly not a one-off deal; it must be a part of an ongoing process that’s custom fit to your organization’s size and position in the BPM life cycle. But if you do it right, the benefits are rock solid: You can improve your organization’s responsiveness to requests from decision-makers; reduce resistance to performance measurement; and minimize the resources you’ll need to define, process, and manage data over time.

Guy Greenberg is the global business intelligence practice leader for Ness Technologies. He can be reached at guy.greenberg@ness.com.

Maya Gal is a consulting practice leader for Ness Technologies and specializes in business performance management and business intelligence. She can be reached at maya.gal@ness.com.

Ziva Slonimsky is a senior consultant for Ness Technologies and specializes in data modeling, business performance management, and business intelligence. She can be reached at ziva.slonimsky@ness.com.