Adoption of Data Governance by Business

Information Management Magazine, December 1, 2008

Businesses have realized that enterprise resource planning (ERP) systems and data warehouses are insufficient to effectively tackle the problem of inconsistent, inaccurate and unreliable data. In particular, there is growing awareness that the processes that create and update corporate data need to be addressed if the data dragon is ever to be slain. This involves understanding, documenting and controlling the business rules that surround the creation of new business classifications (such as a new customer code, new product line or brand, updated hierarchy of engineering assets or organizational structure). This is commonly termed “data governance.”

Data governance is the process of establishing and maintaining cooperation between lines of business to establish standards for how common business data and metrics will be defined, propagated, owned and enforced throughout the organization. The prime function of data governance is to improve and maintain the quality of data in the business. To be successful, data quality should be continuously measured and monitored and the results fed back to the data governance process. Data quality is also a prerequisite for master data management (MDM), which is the management of data (such as customer, product, asset, location or contract) that is shared between computer systems. Indeed, both MDM and data quality are (or should be) key components of any data governance initiative.

A growing number of organizations have put a tentative toe into the waters of MDM and data governance, but there is scant concrete information relating to the business motivation, level of maturity and adoption of data governance by business. Against this background, The Information Difference has conducted a survey into the take-up and adoption of data governance by business.

A total of 233 fully qualified participants took part in the survey, 60 percent from companies with more than $1 billion in revenue. Twenty percent of respondents hold the job title of chief architect and 16 percent are CXOs or VPs. Sixty-four percent were from North America, 20 percent from Europe and the rest elsewhere. Thirty-eight percent were drawn from the business and the remainder from IT.

Significant Interest in Data Governance

There is currently considerable interest in and focus on data governance in business. Approximately 36 percent of companies have already implemented data governance in either limited areas or companywide (see Figure 1). Overall, 30 percent have started initial fact-finding investigations or some form of pilot program. An additional 13 percent already have plans to implement in the coming year. Two-thirds of companies are clearly already focused on instituting data governance, but only 8 percent indicated that they had implemented data governance throughout the organization. In contrast, data governance is not on the planning horizon for just 6 percent of responding organizations.

Currently, only 21 percent of organizations have either active MDM or data quality initiatives (or both), though an additional 44 percent have plans to introduce these within three years. Considering that MDM and data quality are key elements of a successful data governance program, it is clear that more organizations should implement MDM and data quality initiatives alongside data governance.

Failure to Count the Cost of Poor Data

Surprisingly, given that the problem of poor data is not new, more than 52 percent have made no attempt to estimate the costs of poor data, as shown in Figure 2. They should redouble efforts to estimate the cost to the business of poor data and data errors. This is key to building a business case for implementation of data governance and ensuring that it receives ongoing support and funding.