Demystifying Data Governance

Data Governance Knowledge Series - Topic 2

Busting some common myths

The objective of data governance is for an organisation to have greater control over its data assets. Data governance is achieved by planning, monitoring and enforcing stringent policies, standards and procedures. However, exercising authority over large volumes of data can be a complicated process for an organisation and it may require other business departments, such as human resources, processes and technology to get involved, thereby causing misconceptions over data governance.

A few common misconceptions on data governance are discussed below.

For a successful data governance programme in an organisation , both business and IT departments should come together and share equal responsibility. A successful data governance model can only be implemented when it is owned by the business and enabled by the IT departments respectively, to reap benefits and create business value from processes and data assets. The Responsible, Accountable, Consulted and/or Informed (RACI) chart is an effective integrating mechanism which defines clear roles on data governance within an organisation to overcome any misunderstanding.

The perception that data governance is a one time activity arises because organisations tend to believe that exercising authority and control and defining data policies and processes for once will result in the organisation continuing to achieve the desired business objectives. Organisations tend to ignore the fact that organisational risks change with external parameters and need continuous monitoring, changes in data governance policies, standards, architecture, procedures and metrics.

Often, organisations miss out on the holistic purpose of data governance and perceive that regulatory compliance, improving data quality, having in place adequate data security measures, obtaining data lineage or documenting metadata are the only activities under the data governance programme. Underestimating the overall scope of data governance does not benefit the organisation.

It is often perceived that latest technologies are required for an effective data governance model to be operational. It is true that tools and technologies facilitate data governance programmes . However, to have a greater control over existing data assets, governance tools can also be integrated with existing technologies. Also, if the mitigation of data security issues is achieved in a cost effective manner by using new technology that fits with the current technology in use, the new technology can be adopted.

PwC’s Data Governance Framework and its scope

The above myths can be clarified by an industry accepted Data Governance framework that applies the data governance core principles across core data governance areas and their interaction with data management components and data lifecycle.

PwC’s Data Governance Framework encompasses the various layers around data for an organisation , including enterprise data architecture, enterprise data management, information lifecycle management and the complete governance layer comprising governance charter, governance core areas, governance measures, governance operations, governance strategy and vision to help clients adapt and comply with the continuously changing regulatory landscape of data. This framework helps an organisation’s transformation into a data driven enterprise and aids building data strategy, optimising the data infrastructure, processes and systems and creates a data governance culture by leveraging latest technologies.

PwC’s Data Governance Framework

Figure: PwC’s Data Governance Framework

Data management layer

For a successful data governance programme in an organisation , both business and IT departments should come together and share equal responsibility. A successful data governance model can only be implemented when it is owned by the business and enabled by the IT departments respectively, to reap benefits and create business value from processes and data assets. The Responsible, Accountable, Consulted and/or Informed (RACI) chart is an effective integrating mechanism which defines clear roles on data governance within an organisation to overcome any misunderstanding.

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Data governance enablers

For a successful data governance programme in an organisation , both business and IT departments should come together and share equal responsibility. A successful data governance model can only be implemented when it is owned by the business and enabled by the IT departments respectively, to reap benefits and create business value from processes and data assets. The Responsible, Accountable, Consulted and/or Informed (RACI) chart is an effective integrating mechanism which defines clear roles on data governance within an organisation to overcome any misunderstanding.

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Data governance charter, stewardship and core layer

The charter provides a holistic view of the data governance programme , with clearly defined vision, scope, responsibilities and goals. It is a blueprint of the entire data governance exercise. A data governance framework scope should consist of, but not be restricted to, the following core areas:

  • data governance operating model
  • team and operating structure
  • mission and vision
  • data access and control
  • metadata, business glossary and data lineage
  • environment management
  • data governance tools and technologies
  • change management and user adoption
  • data stewardship
  • innovation, monitoring and control.

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Governance strategy and vision

A foremost step for data governance includes defining how organisations evolve by utilising data for ‘growth’ and ‘control’. When combined, the two components bring operational efficiency and financial gains.

An operational model which clearly defines and understand various policies, ownership and accountability around data, along with programme and change management and data governance practices such as data stewardship can improve productivity, brand equity and performance of an organisation.

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Where to start

Data governance brings both tangible and intangible benefits to an organisation. Therefore, it is recommended that organisations enrol in a data governance programme soon. At PwC, we help our clients to achieve the data governance goal efficiently and seamlessly by bringing in the cultural change on data collection and utilisation , using our subject matter expertise. We help our clients to achieve this vision, first by helping them identify their needs and then guiding them through the processes by:

  • defining and strategizing
  • assessment and planning
  • designing and implementation
  • execution and monitoring.
Where to start

Acknowledgments: This knowledge series has been researched and authored by Saurabh Pramanick and Samiksha Wahi

Contact us

Sudipta Ghosh

Sudipta Ghosh

Leader, Data & Analytics, PwC India

Tel: +91 22 6669 1311

Mukesh Deshpande

Mukesh Deshpande

Data Management Leader, Consulting, PwC India

Tel: +91 98 4509 5391

Amit Lundia

Amit Lundia

Data Governance Leader, Consulting, PwC India

Tel: +91 98 3692 2881

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