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Featured - 4 items
In the global digital economy, companies everywhere face a growing challenge: how to use vast amounts of data they now gather to create greater value for their business and their customers without crossing the line into unethical, unlawful or unwanted use. Organisations not only need to take note and re-assess their data strategies but also incorporate governance measures to sustain this growth.
The rise of incidents of data breaches, theft and leaks has ignited the focus of Governments and regulators to draft stringent laws to prevent misuse of data and hold key executives accountable for any incident which compromises the interests of citizens. Organisations today also realise the need to govern the information life-cycle and prevent data swamp by focusing on data-use governance.
For companies to effectively balance opportunity and risk, they must develop strategies that facilitate transparency, traceability, ownership, ethical and secured data use and overall collaboration with its data citizens to build a culture of data trust.
PwC’s Enterprise Data Governance (EDG) framework offers an inside-out perspective to gauge the key data governance capabilities of an organisation and design a comprehensive data governance roadmap to fast track the adoption of key governance initiatives to achieve synergies between growth and control.
Our Services
- Enable organisation to strategically govern their data and set-up operational Data Governance Council
- Help build and transform data trust for an organisation
- Drive discovery, transparency and traceability of data (e.g. automated report to source traceability)
- Drive data ownership and accountability framework along with data access governance
- Define operational architecture for data privacy, protection and data-use governance
- Assist in development of sustainable framework and KPIs to manage data quality
- End-to-end data life-cycle governance (best practice, policy, process, rules and template design)
- Accelerating data implementation programmes (prevent data swamp, data migration governance, etc.)
- Third party data monetisation impact and usage optimisation
- Implementation and managed service support of data governance CoE
Case studies
Leading Indian Private Sector Bank - Enterprise Data Governance Transformation Strategy
- Challenge
- Approach
- Outcome
Challenge
The client was looking to set up the Enterprise Data Governance Council that will focus on building data trust, ownership, accountability, accessibility and traceability. They wanted to set up a comprehensive data governance operating model to drive a ‘Governance for control’ and ‘Governance for growth’ vision.
Approach
PwC utilised the PwC Enterprise Data Governance Framework 2.0 (EDG) that helped the client drive the vision of ‘Governance for control’ and ‘Governance for growth’. The following approach was undertaken:
- Defined Enterprise Data Governance Charter, Operating model, Team structure and RACI as per the PwC EDG framework
- Defined data access policy and created a role-based, profile-based and attribute-based data access entitlement framework
- Designed governance policies, rules and process-flows for Glossary, Metadata, Lineage, Stewardship and Environment Management
- Provided best-practice guidance on DG tools and provided a detailed phased implementation approach and roadmap for Data Governance initiatives
Outcome
- Role and profile-based data access entitlement defined for 14 business functions
- 70+ tools assessed across core data governance areas
- 140+ client’s system inventory assessed for enterprise data governance
- 40+ data governance process workflows defined across lineage, metadata, glossary, access and stewardship
Oil and Gas services company - Enriching the CDO office function with enterprise wide DQ dashboard
- Challenge
- Approach
- Outcome
Challenge
The client was losing out on revenue due to incorrect information being present in their systems. The inconsistencies were present in the master data for the vendor, customer, asset etc., leading to incorrect transactions. The client also wanted an automated method of identifying the erroneous data in their systems and highlighting it to specific users for correction.
Approach
PwC worked with the client to develop a data quality HUB under the data governance programme and following were the approaches undertaken:
- Manual effort was eliminated by setting an automated process of identifying data issues at near-real time
- An enterprise-wide awareness campaign was executed by the project stakeholders on DQ awareness and adoption
- The value delivered to the client included timely and accurate reporting of data quality issues, leading to a significant improvement in critical daily operations, which were impacting the client’s revenue.
Outcome
- Data quality hub to govern DMAIC process was developed
- 1150 data quality rules are being executed on a daily basis
- Increase in data quality index in six months from 63% to 94%
B2B telecommunications company - Implementation of the Data Governance model to address organisation wide data integrity challenges
- Challenge
- Approach
- Outcome
Challenge
The client embarked on a data quality management initiative (DQMi) with an objective to discover, measure, analyse, and control data across 14 data domains.
Approach
PwC conceptualised the DaGov function and the framework for linking DaGov KPI to the KRAs of business and data domain leaders. The following approach was undertaken:
- Data quality hub was setup for identification of data quality issues. The governance policy was setup to cleanse the data at source based on the DQ hub dashboard
- Defined data governance model - team roles, job description and responsibilities were defined
- DQ KPI index were defined for the source systems data. Index values were linked to the KRAs of the application leads and business unit heads
Outcome
- Business leaders and data domain leaders’ KRAs were linked to the DaGov DQ KPIs
- Established DaGov council and DaGov working committee responsible for publishing data quality KPIs on monthly basis
Global FMCG - Global Strategic Reporting and Governance
- Challenge
- Approach
- Outcome
Challenge
The client is considered as one of the largest FMCG company with global headquarters in Belgium. Through our engagement the Company wanted to ensure uniformity of data across different countries, offices, functions and point of consumption.
Approach
The PwC team is primarily responsible for financial and operational data governance, process compliance and performance management of a system that is used to report on private equity portfolio investments. Following are the activities being undertaken:
- Continuous auditing and review of systems and processes involved for governance standards and regulatory compliances
- Streamlined and successfully managing the data life-cycle and MIS reporting of portfolio companies
- Designed DQ framework for data validation, profiling, standardisation, accuracy and completeness
- Created an Innovation COE model for testing new ideas based on emerging technologies for monetisation such as – RPA, bots, cloud, etc.
Outcome
- A uniform robust high performing data and analytics solution
- Various checks, authentication and authorisation designed to maintain data security
Global Private Equity Firm - Portfolio Data Management and Governance
- Challenge
- Approach
- Outcome
Challenge
The client is a leading global alternative asset manager and private equity firm. Through our engagement, the client wants to measure performance of the portfolio companies and comply with regulators to demonstrate better control, governance and management of their data.
Approach
PwC utilised the PwC Enterprise Data Governance Framework 2.0 (EDG) that helped the client drive the vision of ‘Governance for control’ and ‘Governance for growth’. The following approach was undertaken:
- Defined Enterprise Data Governance Charter, Operating model, Team structure and RACI as per the PwC EDG framework
- Defined data access policy and created a role-based, profile-based and attribute-based data access entitlement framework
- Designed governance policies, rules and process-flows for Glossary, Metadata, Lineage, Stewardship and Environment Management
- Provided best-practice guidance on DG tools and provided a detailed phased implementation approach and roadmap for Data Governance initiatives
Outcome
- The solution covered the integrated governance of the functions - Portfolio Management, Finance and Treasury, Regulatory Compliance and Operations and Governance
- 91% productivity gains in operational reviews (from two hours to 10 minutes)
- 75% reduction in DQ errors, due to validation rules
- New company onboarding process TAT reduced from 4-6 weeks to 5-7 days
- Incorporation of 2-3 new initiatives every year within the programme for enriching data visualisation
Insights
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