Data Governance Implementation

Ensuring operational success in every stage of data governance implementation

Your data governance journey needs a structured and repeatable approach, both from a strategic and a technological standpoint. Your goals are to tie the data governance initiatives business requirements and outcomes and implement a scalable and extensible platform architecture.

Each phase of your data governance journey requires tight synchronization between technical and business workstreams.

Plan

Your DG implementation needs accurate direction and areas of focus before it rolls out. The planning phase ensures it.

It involves an assessment of maturity, data leadership, resources, and technological capabilities of your organization. We identify the key business areas or use cases that drive the governance initiative. These use cases drive data governance adoption and acceptance.

Determining the metrics and measures for success, understanding the relationship between new governance tools and existing data driven capabilities, creating runbooks and operational guides, all take place in this phase.

Implement

The high-level roadmap created in the planning phase leads you to a series of business and technical activities in the implementation phase.

You need an overall charter for the programme that includes core processes, roles, and responsibilities involved in data governance. The metrics and measures for success determined in the previous phase will be defined in more detail.

This phase involves the development of an overall operating model for the data governance platform. This process is complemented by streamlined onboarding of stewards and nurturing them with training plans for various common tasks.

Monitor

DG implementation enables better access to insights, enhanced visibility, and streamlined processes. Monitoring ensures that the data is fresh; the stewards are active; and activities are performed efficiently.

The key metrics identified in the planning phase need to be monitored in this phase. Processes such as system onboarding, conflict resolution, and regulatory review are assessed and documented in this phase.

As your organization’s data governance programme grows, you will need repeatable techniques for monitoring and assessing performance and user adoption.

Optimize

Monitoring and process assessment leads to the understanding of what is working and what is not. Evaluation of the governance process in view of the business goals allows you to find new opportunities of achieving enhanced analytics capabilities.

Technology rollouts need to be aligned with business objectives. You want to identify the possibility of a quick win and manage change in accordance with that.

Having a strong feedback loop to continue to identify new opportunities for the program will be critical to streamlining the program over time.

Incept’s mission

We are bound by one goal: delivering operational success at each stage of the Data Governance journey.

Companies are investing in digital transformation and data analytics to gain competitive advantage through new strategies and operating model efficiencies. To be successful, companies must consider how they will help employees execute these strategies and transform the way they do business. They must enable data scientists and business analysts to access the data they need to discover new insights.

They must understand where their sensitive data is and implement the right measures to protect it. Executives need confidence in the data and analysis they're using to drive critical decisions and future targets. At Incept, we recognize that a solid data governance foundation is critical to any strategic initiative with data at its core – this is why we invest heavily in our people and processes.

We'd love to share our experience of overcoming
challenges and creating value through
DG implementation.

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