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Exploring ROI in Data Governance: A Call to Data Analytics Leaders Across Industries In my discussions with data analytics leaders across various industries, one common challenge frequently emerges: securing executive support for data governance initiatives. This difficulty often stems from the complex task of demonstrating immediate and clear financial returns from these initiatives. While the benefits of data governance—such as better data quality, operational efficiency, and enhanced compliance—are critically important, they can be intangible and develop over the long term, complicating efforts to quantify their direct financial impact. As leaders in data analytics, you likely encounter similar challenges. How do you quantify the indirect effects of robust data governance on other business areas, such as improved customer service or more effective risk management? Isolating the effects of data governance from other variables can be daunting in the multifaceted environments of modern businesses. I invite you to share your experiences and insights. How have you approached measuring ROI in your data governance projects? Do you rely more on qualitative benefits, such as increased organizational agility and stakeholder satisfaction, or have you developed methods to capture and quantify the direct and indirect financial impacts? Let’s discuss the metrics and strategies that have worked, the obstacles we’ve faced, and the lessons learned along the way. Your contributions are essential in painting a clearer picture of how data governance not only supports but drives business value across diverse industry contexts. hashtag #CDO hashtag #DataGovernance hashtag #DataAnalytics hashtag #BusinessIntelligence hashtag #Data hashtag #AI hashtag #Compliance hashtag #Data

Getting Executive Buy-In: Making the Case for a Data Governance Programme If you're in the data space, you know the struggle; convincing the CxO to invest in a full-scale data governance program. Let's not forget however, that data governance isn't merely a one off activity; it's a ongoing business imperative. Here are some tips to make a persuasive case to your executives: 1. Make It Relatable: Start by speaking their language. Show how poor data governance can have tangible business repercussions—lost revenue, regulatory fines, and reputational damage. 2. Use Past Incidents as Case Studies: Bring up instances where inadequate data governance led to challenges or missed opportunities. 3. Align with Business Goals: Demonstrate how data governance aligns with the company's broader business objectives. 4. Present a Pilot: Propose to start small. A successful pilot will not only show quick wins but also serve as a blueprint for governance at scale. 5. Risk vs. Reward: Provide a balanced view of the investment required against the potential benefits—cost savings, compliance readiness, and operational efficiency. 6. Stakeholder Involvement: Include testimonials or endorsements from internal stakeholders who understand the value. 7. Metrics and KPIs: Outline how the success of the program will be measured. The aim is to present data governance as a strategic business initiative that promotes organizational health. What else have you done to win executive buy-in? Looking forward to your stories and insights! #DataGovernance #ExecutiveBuyIn #DataStrategy

Don't overthink data! Data management can be complex, but keeping four key questions at the forefront can make the process much smoother. What data do you have and need? When are governance practices happening? Who is responsible for data ownership and stewardship? How will the data be managed? These questions apply to any industry or role dealing with #data. Don't know where to start? Start here! If you're struggling, feel free to DM me. Remember, without answers to these questions, everything is up for question. #data #datamanagement #governance #ownership #stewardship #custodianship #management

80% of Data Governance teams are obsessed with Data Quality. That's all they want to do. And they're making a mistake. Because by swearing by data quality, Data Governance : - Only assume part of their responsibilities - Postpone the realization of a clear roadmap - Forget about change and culture management - Don't understand risk on data I see several explanations: - Data Governance teams are influenced by Data Management literature - Concrete delivery is well perceived by Business - They prefer to execute rather than think - They avoid facing Top Management Being a Data Governance team member means setting up a framework for data AND implementing it through to the end. You can't have one without the other, that would be too easy. #data #datagovernance #business

Recently as an invited guest to an executive briefing on Data Governance, I sat and listened to one high-priced consultant after another present their take on the topic. In the end, very little value came out of the 2.5 hour meeting. The look on the faces of the executives in attendance reflected this fact. 😣 Waiting for the elevator, one of the CxOs asked me a simple, direct question: "So, Tim, what's critical to success in this Data/AI governance project?" As we stepped into the elevator, I knew I had the length of the ride down to the lobby to answer. Classic "elevator pitch." "RESPECT." It's always top of mind, and the first aspect to focus on when dealing with the issue of governance. "Respect for the policies and processes that you need to introduce. Respect of the data - what it will, and will not, deliver for you. And respect for your resources that you expect to implement this program for you - their time, talents, and the potential need for upskilling and expanding their capabilities." Respect. It's rarely addressed. It shouldn't be expected; rather, it should be incorporated into every aspect of a data governance program. Lead by example, and actively look for ways to help others emulate it. With it, your expectations regarding success are achievable; without it, you'll be chasing after success and never fully realizing it. #datagovernance #aigovernance #informationgovernance

The role of a #CDO should be that of a strategic business leader who helps create value from data, than being narrowly focused on governance and compliance. #Data

The role of the Chief Data Officer (CDO) has drastically evolved 🚀, becoming key to unlocking new revenue streams and enhancing regulatory compliance 📜. But what does it take to design an effective data strategy in today's volatile market? Our latest blog sheds light on how Chief Data Officers are navigating these obstacles, fostering a culture of innovation 💡, and ensuring compliance. To learn how to align your data strategy with your business goals for maximum impact, click the link to uncover the strategies that make data-driven transformation a reality: https://lnkd.in/gj8RMpi8   #datastrategy #datainsights #datastrategies #CDO #digitaltransformation

Data governance vs Data management: Which comes first? Gartner estimates that poor data quality costs organizations an average $12.9 million annually, primarily via introducing unnecessary complexity that hampers decision making, ultimately leading to lost business opportunities Data governance is defined as the ownership, stewardship and operational structures needed to ensure that you’re managing corporate data as a critical asset. Data management involves the coordinated activities to define, control, supervise and improve the entire data lifecycle. Let's check the difference between data management vs data governance in this blog: https://lnkd.in/diGfQxjM While data governance and data management are two separate entities, their goals are the same: to build a solid, trustworthy data foundation, contact us now: https://lnkd.in/d_YiNz7M #data #datacatloguing #dataexpert #datagovernancesolution #datastrategy #consultnow #businessexpert #nextgeninvent #founders #ceo #entrepreneur #usa #newyork 

Many businesses are struggling to effectively use data. A recent study found that most business leaders lack both the confidence and the qualifications to use data to make decisions. In fact, 72% of business leaders said that they have avoided making a decision because of too much data and a lack of trust in data.    Data professionals have long grappled with this problem. Business leaders don’t always trust data and prefer to rely on their personal experience when it comes to important decisions -- or what I like to call, “a sample size of one.”  Keep reading...

I find there to be disproportionally more conversations around “how to do data governance differently” than “how to do data governance well”. Guess what? There is no magic bullet for data governance. Is this really a surprise? Firstly somewhere along the line governance became synonymous with management, but I’ll table that for now. Speaking of which… There is also no magic bullet for management in general. Imagine if you followed the same 10 steps and your company was worth a billion dollars. Doesn’t exist, and few executives would believe that if they heard it. They know the truth. Management is hard and far from perfect because it’s about people, who are also far from perfect. Data governance takes tenacity, grit, will, teamwork, perseverence through conflict, accountability to hitting goals, patience with failure. If you’re in the trenches, don’t look for some magic methodology to ease the pain. Keep looking forward and fight, but most of all - know the struggle is real, but there are 10’s of thousands of professionals tackling it head on day in and day out. You’ve got this!