Get 'data' healthy!

As individuals enter the new year, they will often take time to reflect not the past year and create ‘goals’ for the upcoming year. Over 48% of individuals have a New Years resolution goal of getting healthy. Their goal could be weight loss, better diet or nutritional habits, building muscle, training for an Ironman race, etc. Each individual has a unique starting point and timeline, therefore, their plan for getting healthy must reflect their distinct baseline. Now if you consider how organizations need to get their data healthy, the same principles apply. Each organization may have similar goals to get their ‘data’ healthy for responsible democratization, but there are multiple factors that require a unique approach. No two organizations are created equal and therefore, their goals will reflect their current state. Just as individuals need a unique plan for getting their body healthy, organizations also require personalized plans.?

Now let’s imagine someone has this goal to get healthy and they sign up for a gym membership. This person has never exercised other than going on walks and has never belonged to a gym, it would be intimidating with all the equipment at their disposable. It is not enough to simply have access to the equipment. They will need personalized guidance on how to use all the gym equipment safely to get the most efficient workout and use of their time. If we take a moment to consider what could have been their obstacles before this point and establish clear goals, it will help create a fitness plan. If one person was getting back into exercising after a long period of time, they might need more accountability and some additional structure. Another person might have a goal of doing their first triathlon, they will need specific targeted advanced workouts. There are endless scenarios with various goals and targeted dates to reach that goal. Each person needs a personalized plan that includes exercises, dietary requirements, and frequency to help them reach their specific goals. Therefore, getting access to the equipment in the gym is not enough. Sure, they could do their own research to figure it out and experiment with various pieces of equipment. However, it would be much less efficient and often take longer to get the results they desire. By leveraging personal trainers, they can help coach the individual through not only the right exercise plan, but the complementary diet needed to speed up their body transformation.?

So how does this relate to data? Well, getting 'data' healthy is quite similar to the needs of someone getting physically healthy. As organizations evaluate how they will get their data healthy in order to be responsibly democratized, they will also need to take into account their unique goals and baseline. Acknowledging Data Governance must be practice-led and technology enabled is essential to the success of the transformation. Organizations need to take the same approach as getting physically healthy and evaluate solutions based on their current baseline. We must look to who not only can provide the technology, but be our coach in our data healthy journey. It isn't enough to receive gym equipment, we need a coach who will guide, inspire and get help us accomplish our goals. This is one of the most crucial elements of Data Governance. The practice of Data Governance is truly a change management conundrum and we are looking for the right guide.

Organizations should consider the following aspects to figure out what the current 'baseline' is and how you will get your organization healthy.

Existing operating model

The operating model is a framework that defines how an organization will manage its data by outlining key processes, roles, responsibilities, standards, and metrics to ensure data quality, consistency, and compliance across the entire company. There are three key models: federated, centralized or decentralized model? By knowing which model the organization is currently working under, it will make it easier to establish a method for implementing data governance and the associated tools. The operating model is imperative to understand as this influences how to apply data governance programs and tooling.?

Leadership interdisciplinary relationships

Interdisciplinary roles in leadership is one of the biggest barriers to success Data Governance practices. Understanding who holds the purchase power helps to establish the level of influence required to get the buy in from the board of directors. Is there a specific timeline in place for the CDO to demonstrate data value? In addition, if operating on decentralized or federated models, we must know how much stakeholder support from various domains exist.

Data Driven Maturity Model?

Every organization aspires to be data driven, but understanding the actual state is imperative. Having a cultural alignment on the importance and value of data is a crucial element to successful Data Governance. This is often indicated by the investment (monetarily by way of tools or people) the organization is making into their data practices. The maturity of the organization is a strong indicator of readiness and scope for a Data Governance practice to be applied.

Complexity of the data landscape?

Data continues to not only grow in size, but in its complexity of types of data and where it is stored. Having an understanding of the current data landscape is essential to what the needs will be for the organization to get the data healthy. This will shape where you start, how you begin, and what tools you need to get you there. Is data in multiple-clouds, on-prem, hybrid? How much data exists and how siloed is the data across the ecosystem??Answering some basic questions will be instrumental to a successful data governance practice.

After the above have been considered, you will have a stronger indicator of your baseline and needs to get your 'data' healthy. This would be no different than if you signed up of a gym membership with a specific fitness goal and the coach needed to understand your current baseline. After factoring in the above considerations, the organization will have a better understanding of the needs they have in how they approach their own Data Governance program and solution criteria. Most CDOs need to demonstrate business value from data within a specific window of time. When looking for solutions to help the organization’s data governance practice, consider who will get you a return on investment and help increase speed to insights. Find a partner that doesn’t just provide you a tool, but recognize the value in strategic partnership where you also receive the guidance and best-practices unique to your own distinct circumstances.?Now how will you get your 'data' healthy this year?