Data Governance Step by Step: Month 2 Week 2

Month 2 Week 2:

1. Identify key data assets and systems: Which data assets are most critical to your business? Which systems are used to collect, store, and manage these data assets?

2. Data Quality Assessment: Evaluate the quality of your data to identify issues like inaccuracies, duplication, and inconsistency. This will be impactful to get buy-in from the executive committee.

3. Identify Project Management Approach: Do you have a PMO (project management office)? Assess project management process used and specific project 'gates' that gates data activities. Identify gaps.

4. Categorize Business Needs and Key Challenges: Based on the surveys and assessments conducted during the previous month, build out use case priority and impact matrix.

5. Establish a data governance framework: This framework should define the roles and responsibilities of key stakeholders, as well as the policies and procedures that will govern the use and management of data.

6. Define Data Governance Roles & Responsibilities

7. Define the scope and goals of your data governance program: What do you want to achieve with data governance? Do you want to improve data quality, enhance compliance, or optimize data utilization? Once you know your goals, you can tailor your implementation plan accordingly. What problems are you trying to solve, and what benefits do you expect to gain? Set clear objectives by defining the goals and objectives of your data governance program. Note, this is at a draft stage at this point. You'll need to review with the governance steering committee to finalize.

8. Data Governance Charter: Develop a draft data governance charter, stakeholder map and policy outline. Review it by the leadership influencers.

9. Data Catalog: Begin developing a data dictionary/catalog.

10. Identify members for Executive Steering Committee

​Identify Project Management Approach

​Identify Project Management Approach: Do you have a PMO (project management office)? Assess project management process used and specific project 'gates' that gates data activities. Identify gaps.

My goal for this assessment is to assess the role of the PMO office, the project management discipline, assess the culture of getting things done (for instance, I've run into inflexible organizational process where it takes forever to get a small change done), how project management process holds project members accountable, mandated project artifacts, project gates to ensure critical data related activities (such as data architecture artifacts) are enforced.

1. How easy it is to learn the project management process at the organization? Is the process published and broadly available and accessible? Are there training associated with it? Are there document templates available that assists the project team every step of the way?

2. Level of data related questions answered in the process at the project concept level. Are there questions on the type of data assets involved, impact of data on the business value etc.

3. Is there clarity on the data requirements?

4. Specificity on the application architecture, data architecture, data dictionary, metadata involved, data interfaces captured at the appropriate project gate?

5. What level of testing/validation does the PMO oversee to ensure data requirements are satisfied?

Categorize Business Needs and Key Challenges

​Categorize Business Needs and Key Challenges: Based on the surveys and assessments conducted during the previous month, build out use case priority and impact matrix.

• At this point, you should have outcomes from the data influencer reach outs, business area leader reach outs (e.g. Sales, Marketing, Legal, CRM, HCM, Business Operational Leaders)

• As I'd mentioned in my previous post, it is important to do the assessments in a structured way where the data gathered could then be helpful to be further assessed.

• Expect to have the following information to work with

• Key data assets that business cares about

• Key business processes and workflows

• Business categorization and process areas; How does the business organizes itself?

• Key data assets, technology associated with business process areas

• What data means to each business area and what is their perception of its value?

• Who are the subject matter experts?

• Leadership contacts and an initial stakeholder list

• What insights and intelligence are they seeking from data?

• What is their perception of how our customers perceive us for data delivery

• Process, People and Technology challenges

• Data related challenges, history on attempts to address the challenges, guestimate on effort involved in addressing them [note, you might need IT's feedback for this]

• Quotes about data challenges; Also, seek quantifiable information even if its a guestimate.

• Gather guestimate on efforts involved in potentially addressing the challenges; All you need is a breakdown of low, medium and high effort designations

• Gather top-level business use cases, key services we offer to our clients, the level of business impact or value for the use cases, products and services we offer

​Next steps,

• Prepare a summarization of your findings

• Group and categorize information

• Group key business process areas

• Group key data assets

• Group and category key challenges such as Data Quality Issues

• Prepare the information to be presented to senior leadership and get the buy-in for the data governance program

• Use business leader's quotes on the value of data and some of the key challenges they're facing. Ensure you have wide coverage for finance, sales, marketing, operations, customer experience etc.

​Read my blog post on 'Prioritization Methods for Strategic Implementation"

• This post will provide an insightful approach on how to assess, identify priorities, assess impact to the business and how it should be presented for buy-ins

• Impact Effort Matrix is the one that I recommend for inclusion for presenting the data governance proposal. You'll likely consider additional prioritization approaches as well depending on the complexity of the problem as well as your audience.

• Data Governance Framework, roles & responsibilities are the additional areas you'll tackle and prepare presentation materials for senior audience. I'll cover these in my next posts.

Sash Barige

May/01/2022