One Size Does Not Fit All---A Contingency Approach to Data Governance

Abstract

Enterprizes need Data Quality Management (DQM) to respond to strategic and operational challenges demanding high-quality corporate data. Hitherto, companies have mostly assigned accountabilities for DQM to Information Technology (IT) departments. They have thereby neglected the organizational issues critical to successful DQM. With data governance, however, companies may implement corporate-wide accountabilities for DQM that encompass professionals from business and IT departments. This research aims at starting a scientific discussion on data governance by transferring concepts from IT governance and organizational theory to the previously largely ignored field of data governance. The article presents the first results of a community action research project on data governance comprising six international companies from various industries. It outlines a data governance model that consists of three components (data quality roles, decision areas, and responsibilities), which together form a responsibility assignment matrix. The data governance model documents data quality roles and their type of interaction with DQM activities. In addition, the article describes a data governance contingency model and demonstrates the influence of performance strategy, diversification breadth, organization structure, competitive strategy, degree of process harmonization, degree of market regulation, and decision-making style on data governance. Based on these findings, companies can structure their specific data governance model.

Challenges for Value-driven Semantic Data Quality Management

“…A survey of the literature on data governance, management and lifecycles finds that while data quality is widely regarded as critical (Brous, 2016, Khatri, 2010, Tallon, 2013, Weber, 2009), that most current processes are human rather than machine oriented (Aiken, 2016, Mosley, 2010. In part this may be because there are a wide variety of data lifecycle models but no clear standards (ISO, 2014).…”

Preparing Law Students for Information Governance

“…and Lib., DLA Piper, to AALL Association for Legal Information Discussion List (Jan. 11, 2016) (on file with author). 9 Michele Lange, Back to (Law) School: Ediscovery Education by the Numbers, EDISCOVERY BLOG (Sept. 3,2014), http://www.theediscoveryblog.com/2014/09/03/back-law-school-ediscovery-education-numbers/ [http://perma.cc/2J6U-93PZ]. Kroll's research found that 69 law schools were offering some level of instruction on ediscovery outside the typical Civil Procedure class.…”

“…8 This article explores how academic law librarians can seize opportunities to help prepare law students for information governance. Many law schools have responded to the rapid development of e-discovery by offering specialized courses, 9 but only a few address the larger topic of information governance. Information governance's relationship to e-discovery and other legal concerns such as regulatory obligations and business practices makes familiarity with information governance vital for lawyers advising clients in these areas.…”

“…Sometimes this term is used to mean essentially the same thing as information governance. 61 At other times, the term is used more narrowly, focusing on the nature and integrity of the data artifacts themselves rather than the knowledge they represent.…”

Critical Factors In Data Governance For Learning Analytics

“…General data management is defined as "the set of processes that ensures that important data assets are formally managed throughout the enterprise" (Otto, 2011). Weber, Otto, andÖsterle (2009) define general data management and governance as the entire life cycle of decision rights and responsibilities regarding the management of data as information assets (See also Petersen, 2012). These definitions of general data management and governance converge on the need to define the (human and systems) entities that supply data, those that input data, those that process data, those that output data, and those that consume data.…”