4 bad data habits that devour value

4 bad data habits that devour value

Many organizations skip the strategic decisions around data - paving the way for bad habits that keep data’s value trapped

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July 30, 2019

When I’m asked to provide a list of data-related issues that organizations should address to “solve” their data problems, my feedback is often much different than what my clients expect. That’s because they’re typically expecting a list of very tactical things they can quickly knock out to mark off some tasks from a to-do list. 

While that would be a nice easy approach to solving bad data issues within organizations, that’s not where the majority of time should be spent. For most companies, their data problems reside at the strategic level and require senior leadership involvement. Tactical fixes will do little good if you don’t solve underlying strategic and cultural issues.

[ Read more from Eric Brown: 4 big data myths, busted. ]

I’m always surprised at how many times these best practices are ignored and these bad habits are allowed to persist.

This requires breaking a few bad data habits. These bad habits are really nothing more than best practices for proper data governance and data management. Yet I’m always surprised at how many times these best practices are ignored and these bad habits are allowed to persist. The bad data habits are:

  •     Data governance
  •     Data silos
  •     Data hoarding 
  •     Data access

Let’s discuss each of these habits in a bit more detail:

Conflating data governance and data management

During my career, I’ve asked countless clients to describe their approach to data governance. After a few minutes of discussion, nine times out of ten they walk me through their data management systems. 

This is the first habit we need to break. We must stop treating data governance and data management as though they are the same thing. 

We must stop treating data governance and data management as though they are the same thing. 

Data governance does not equal data management (and vice versa). For reference, data governance is the rights and policies for data, while data management is the tactical execution of those policies. Think of data governance as “strategy” and data management as “tactics.” They require different approaches and different mindsets. 

You can’t just turn on a system to “do” data governance. Data governance requires high-level thinking as well as continuous executive-level involvement. It isn’t something that should be delegated entirely. CxO-level leadership is required to ensure that the proper strategic thinking around data and data management processes is in place. This support from the executive level emphasizes that data governance is indeed an organization-wide focal point rather than a small, departmental issue.

Data silos, data hoarding, and data access

I’ve combined these three bad habits because they always seem to go together. When you find data silos, you find data hoarding and data access issues (and vice versa).

I’ve long observed one particularly hard-to-break data habit: Silos – and the data hoarding and access issues that come with them.

I’ve long observed one particularly hard-to-break data habit: Silos – and the data hoarding and access issues that come with them.

I recently had a friend ask for some help understanding the data landscape within her company. She’s the CEO of a mid-sized services organization with offices and people spread across North America. She asked me to help her understand how her organization uses data, where data lives, and who has access to whatever data exists.  

What I found within this company was a serious data hoarding and data access issue due to data silos. Each department had a process for data collection and access, but the silos they created prevented the larger organization from tapping into the value departmental data might hold. 

[ Read also: 3 reasons data hoarding may not pay off. ]

Here’s the thing: People get in the habit of collecting data that makes sense for their job, their team, and/or their department. But what often happens is these data sets sit hidden among departments. That’s why it’s important to have strong data governance and data management practices in place. As an old boss of mine used to say: “Many companies don’t know what they don’t know.” This is especially true when it comes to an organization's data. Without having the full picture of their data, many organizations are leaving tremendous value on the table.

Breaking this bad habit requires a leadership team willing to put effort into creating the anti-hoarding culture – a culture where employees default to sharing data. With a proper culture, these silos, hoarding, and access issues fall away and are quickly replaced with open access and knowledge transfer across the organization.

The good news is that breaking these data hoarding and data access habits isn’t difficult, once leaders at the highest level of the organization mandate openness. With that new direction in place, it merely takes each person and department to pause and think about how the data that they use might be useful to others. 

Foster a culture of data transparency

To break a bad habit (or build a new good habit), the experts usually tell you to start small and take one step at a time. Over time, the bad habit will be broken and the new habit will be formed. That works great for individuals, but organizations need to take a much more strategic approach to break organizational bad habits. 

Breaking bad habits (and forming new ones) at an organizational level requires enacting cultural change. In the case of data, that means fostering a culture of openness and transparency. You won’t see the tactical changes you desire until you can form such a culture. The mistake many organizations make is skipping the strategic thinking process around data. But unless these bad habits are broken, your ability to take full advantage of your data will be extremely limited. 

[ How can automation free up more staff time for innovation? Get the free e-book: Managing IT with Automation. ] 

Eric D. Brown, D.Sc. is a consultant specializing in the intersection of data, marketing and IT. In his consulting practice, Eric works with organizations around the world assisting them in understanding how to find value in data and technology. You can read more about Eric and his work on his personal blog.

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