Choosing the Right Governance Model for Your Data Strategy

We all know that Analytics teams are comprised of 3 main areas – Data, Tools and People.  How much time you spend organizing people and clarifying their roles and expectations will have a significant impact on the overall performance of your teams.

You may have listened in to our client talk about the work we did (check out this article about our work) supporting a major telecommunications carrier as they transformed their Global Supply Chain from decentralized reporting to a Center of Excellence Analytics model and thought – that sounds great – how do I get there?

First, let’s back up and determine if the Center of Excellence model is right for you.   Here are 5 common governance models covered in that summary, how they work and what you will realize when they are implemented.

Which of these most closely aligns with how you identify your analysts and data organization today? Which best describes where you strive to be?  This will determine the amount of change you will go through.  Having a well-planned, measurable and segmented program will ease the process and ensure you have results that last.

Okay, so here is what you need.

The core components, along with analyst alignment, that you should manage under your governance model are:

  1. Data access: Data architected to support business and technology goals while providing performance and flexibility for growth. Balancing the need for a Single Source of Truth (SSOT) and Multiple Versions of Truth (MVOT)
  2. Data quality:  Accuracy of information supports business decision making and user adoption. Not all data must be 100% accurate for every purpose but you must execute audits to ensure data is within your acceptable bounds.
  3. Leadership & Organization: Functional accountability by business leadership. Clear alignment and prioritization of strategic plan to tangible, impactful outcomes via data, tool and analytical support model improvements.
  4. Master Data Management (MDM): The application of definitions, ownership, and sources of critical information (i.e. customer, product, employee) across an enterprise. Through applying these holistically, enterprises gain alignment of metrics, definitions and transparency.
  5. Data Security: Creating and managing the proper roles and groups to ensure critical information is secure while still providing the right information to the right people in the right context.

The priority of these components becomes your strategy to implement, manage and evolve information management through Governance.  A tight control of each of these functions will certainly improve your time from question to answer.

It is an evolution, and the journey can begin top-down or via installing one component.  The key is to understand what components you are doing today and which you need to invest in.  This is the foundation for all your insights and must be a priority for the organization.

Interested in learning more? Connect with us.


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