Data Governance is a crucial agenda in organizations that want data-driven business decisions and operations. Data-driven enterprises offer excellent digital experiences to their audience groups, and increase CSAT, employee satisfaction, revenues, productivity, and profitability.
The crucial question is how to implement effective enterprise-wide Data Governance (DG) and what benefits to expect from it in the medium to long-term. DG, as most practitioners would readily agree, is a complex long-term program encompassing people, new roles and responsibilities, virtual organization, organizational policies, data standards (global, regional and local), operating processes, procedures and last but not the least, the implementation and adoption of multiple platforms, systems and tools.
To rollout a new DG program or optimize an existing DG program across all its dimensions, following questions need to be deliberated.
1. What can an organization expect to gain from the rollout of a DG program?
DG initiatives can combine with analytics modernization initiatives to offer integrated high-quality data discovery. This will lend capabilities to data scientists, data analysts, business analysts to ask questions, formulate hypothesis and get answers that can be trusted as a single version of the truth.
This evolution will enable efficiencies like:
1.1 What are the steps to rollout a DG organization?
The above set of activities need to be plotted on a Gantt chart showing parallel activities, dependencies and estimated timelines leading to go-live of the enterprise DG program.
1.2 When can the expected benefits from the DG program accrue?
Stabilization Phase: lasts 9-12 months after the go-live
3 months after the go-live following benefits can start accruing (based upon the 4hr/week time allocation mentioned)
2. How to incentivize the DG organization members?
Upon go-live, considerations of additional remuneration should come into effect. These considerations can work at two levels - BUs and individuals.
2.1 At the level of BUs
2.2 At the level of Individuals
DG roles should be calibrated based on the extent of their engagements in slabs of 50-100%, 25-50%, and less than 25% of their available time for DG work. The slab of 50-100% will need new head count, who will need to be assigned with additional work by the respective BU, slab of 25-50% will also need new head count with more diversified work, and individuals in the lowest slab should be offered a package that includes a premium on top of current CTC.
For any analytics program implementation to succeed and yield business value, optimum data quality is a pre-requisite. Enabling data quality at enterprise scale requires multi-faceted approaches, enablement and technologies that make up the enterprise-wide Data Governance program. Therefore, well conceptualized and executed DG organization and program are essential to enable high-performance analytics to deliver insights that will be trusted as single version of the truth and will support business decisions and actions across the enterprise.
Rahul K. Srivastava
Lead Consultant- Information Management Data, Analytics & AI Wipro Limited.
Rahul has over 19 years of work experience including Enterprise Data Strategy & Governance, Master Data Management, Business Intelligence & Analytics, and Cloud platforms. He has built and run successful business transformation programs in these domains for diverse sectors. He holds a B.Tech degree from Indian Institute of Technology Varanasi (IIT BHU), India and MBA in Marketing (Research).