5 steps you should follow to demonstrate the business value through a Data Governance initiative

Data governance is often seen as a complex and cumbersome, but it can yield significant benefits if approached correctly. Here is my 5-step approach for deriving tangible value from a data governance initiative:

Step 1: Identify Low-Hanging Fruit

Start by identifying the data pain points within your organization that can be addressed quickly. These are the low-hanging fruits that can serve as vehicles to demonstrate the value of data governance. Focus on specific business problems that stakeholders can easily relate to, such as poor data quality affecting customer satisfaction or inefficient data processes increasing operational costs. By solving a pressing issue, you not only demonstrate the effectiveness of data governance but also build trust and buy-in from stakeholders.

Example: An insurance company has inconsistent and inaccurate customer address information, leading to delays in claims processing. Data governance programs should establish data quality rules, validation, and cleansing processes to ensure accurate and consistent address information, improving claims processing efficiency.

Step 2: Measure the ‘Before Effect’

Quantify the significance of the data challenge you are tackling. Conduct interviews, collect metrics, grasp the scope of the problem, and assign a monetary value to demonstrate the tangible business impact of this issue. Emphasize the expenses linked to operational inefficiencies, erroneous business decisions, or lost prospects originating from inadequate data handling. 

There are different types of business impacts of a data issue:

External Impact: 

• Fines due to data breaches, mistakes, 

• Compliance or privacy violations affect company's reputation and eventually lead to lost business

Financial Impact: 

• Incorrect cost due to extra labor in the context of data management (e.g. remediation of data issues that are the root cause of regulatory fines or manual workarounds)

• Lost opportunity cost i.e. missed revenue due to not targeting the right clients

• Lost revenue opportunity due to being unable to monetize (sell) data due to its poor quality

• Lost revenue due to billing errors, lost sales, or unpaid invoices

Confidence Impact:

• Poor reporting and KPI tracking due to poor data leading to wrong decisions (such as: being unable to identify high net worth customers, inaccurate performance measurements for employees, etc.)

• Poor data affecting customer satisfaction and retention, NPS score, increased number of complaints eventually leading to lost business\

• We’re unable to improve the ease of interaction for customers

• Inability to provide unified billing to customers 

• Inability to improve ease of use for staff (sales, call center, etc.)

Productivity Impact:

• Decreased ability for straight-through processing via automated services

• Ineffective performance of the business process for which data is used (either due to additional steps taken to clarify the information, more people involved in checking, internal bottlenecks because of the reliance on other departments/teams to confirm, etc.)

• The business-as-usual process takes more time, resources, or effort than needed which eventually increases the company's costs

Example: If poor data quality is leading to ineffective marketing campaigns, calculate the lost revenue opportunity. Demonstrating that improved data governance can save or generate a significant amount of money will make your case compelling.

Step 3: Deliver the Improvement and Showcase the 'After Effect'

Implement the appropriate data governance solution needed to resolve the issue at a small scale. Sell it to the business as a proof of concept or a pilot approach. Then, once you've implemented your data governance solution, showcase the results. Conduct a demonstration to illustrate not only the problem that has been fixed but also the associated true business value gained from this exercise which you must translate into either: cost reduction, revenue increase, cost avoidance, FTE saving, or regulatory compliance. Business executives are interested in numbers that demonstrate tangible resources so you should be prepared to give them what they need to get their support. Use before-and-after comparisons to make the impact clear.

Example: After standardizing and cleaning the customer data, show how the customer reporting accuracy has improved and how this has led to better decision-making for marketing and increased the opportunity to generate more revenue you can even calculate the projected revenue from this data. Present these improvements in a visual format, such as dashboards or graphs, to make the benefits obvious to business stakeholders.

Step 4:  Repeat 

You should repeat this process as many times as you can to build a portfolio of success stories. Data governance is not a one-time project; it requires ongoing effort and engagement. Keep stakeholders informed and involved throughout the process. Regular communication and continuous delivery of business value (small or large) will ensure constant interest and will keep everyone excited!

Example: Organize regular meetings with key stakeholders to assess the progress of the data governance initiative. Share success stories and insights gained from enhanced data quality and processes. Plan demos, lunch & learn sessions, data governance roadshows, engaging videos, and publish infographics to maintain continuous communication across various channels, reaching audiences at all levels. This ongoing interaction through diverse channels will help cultivate a culture that appreciates data governance! Data Governance won't be dull anymore.

Step 5: Foster a Data-Driven Culture

Promote a value-first data-driven culture where data governance is seen as a critical component of business success. Encourage collaboration across departments and ensure that data management responsibilities are clearly defined and understood.

Example: Create data stewardship roles within departments to ensure that data governance is being adopted and adhered to. Provide training and resources to help employees understand the importance of data governance and how they can contribute to its success.

Conclusion

Implementing a data governance initiative might seem like a big task, but by focusing on quick wins, putting value first, measuring impact, and keeping stakeholders involved, you can show its worth effectively. Encouraging a data-driven culture and prioritizing data governance can bring significant benefits, improving decision-making, efficiency, and business outcomes. I'd say the value-first approach is key - if you don't show the initiative's value, how can you get others on board? We're all a bit self-centered, right? So, before you share an exciting opportunity, ask yourself: why should they care?

Feel free to connect with me for more insights on data governance and how to derive value from your data initiatives!