Over the last 20 years through my involvement in the world of data and analytics, a few key challenges continue to repeat themselves over and over.

As drastically as our business needs and supporting technologies have evolved over these years, the way data leaders, consultants, and analysts approach these recurring problems largely has not. As a result, we fail to make progress toward our goals — and more importantly, we often fail to legitimize the transformational role that data can, but often doesn’t, play in companies today.

How do I know this is true? In the spirit of being data-driven, I’ll let the numbers speak for themselves: only 24% of companies characterize themselves as being ‘data driven’; only 30% of CDOs say they are meeting objectives on the ROI from data and analytics; and only 44% of data and analytics leaders report that their team is effective in providing value to the organization.

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An Evolution of the Modern Data Leader 

This prolonged inability of CDOs to deliver business value has led us to what I believe is a turning point in the evolution of the role. Will data leaders finally figure out how to overcome their challenges, or will the role of CDO slowly fade into corporate oblivion? 

When you analyze these numbers to understand the core drivers (or inhibitors) of CDO success, you see a recurring lack of traction on some of the same core deliverables, over and over, survey after survey.

These include things like a failure to: 

• provide tangible business value through investments in data management and governance 
• build and promote a data culture 
• and define and implement a data governance framework – to name a few.

For most, these very failures are the core responsibilities of the CDO. So it should be no surprise that CDO tenures remain half of their CIO counterparts – even as the CDO role is now present in over 80% of all companies.    

While a Gartner analyst, it was my job to help CDOs succeed and overcome their challenges. In this role, I spoke with multiple data leaders daily and advised over a thousand of them on what we’ve come to accept as the demonstrated best practices in the discipline. As much as I sincerely wanted my clients to succeed – many did not – which caused me to spend the better portion of the last two years trying to understand why.

Leadership Takeaways from Thousands of Consultations 

When I reflect on my thousands of data leader, consultant and analyst conversations over the last four years – many of which happened over prolonged periods with the same people and companies – a few notable things stand out: 

• A significant portion of data leaders largely ignored many of the steps that we know could help improve data management. There are many possible reasons as to why, but this happens often. This is particularly the case with building business cases and quantifying business outcomes.
• Many data leaders acknowledged a need to improve their capabilities, but even after repeated engagements with analysts and expensive consultants (most of whom all advocate for established ‘best practices’), they were largely unable to operationalize what was being recommended.
• There’s a palpable sense of frustration with data leaders (especially those trying to do the ‘right’ things). In turn, there’s a growing trend to point fingers at forces or people outside the data organization as the root cause for their difficulties. The ire of data leaders, analysts and consultants tends towards the business stakeholders who both create (through their interactions in business applications) enterprise data or consume the data products of the CDO organization in the form of analytical insights.
• Data leaders’ frustration is being echoed by analysts, consultants and other ‘thought leaders’ in the industry – most of whom are equally perplexed as to why only marginal progress is being made to CDO goals when utilizing their recommended best practices.   This leads many – some with extremely influential platforms, such as Gartner analysts –  to validate the idea that forces outside the data organization are playing a significant role in blocking CDO success.
• The combination of finger-pointing, frustration and ongoing lack of traction toward goals is helping to exacerbate the already problematic divide between producers and consumers of data that creates a negative feedback loop that’s only making the problem worse. As an analyst, I often heard what could best be expressed as animosity (if not outright contempt) – from data leaders, consultants, and even my peer analysts – towards the business stakeholders outside the data organization constantly.
• The animosity and frustration were often expressed in phrases like ‘the users just don’t get it’, or ‘you can lead a horse to water’ (when trying to understand why data products weren’t being used), but perhaps the best example of this frustration is around data quality. In many organizations, business stakeholders are repeatedly reminded on how poor a job they’re doing in cultivating data assets in the eyes of the data organization – even while they may be meeting every conceivable business performance metric. Over and over, published soundbites like ‘80% of data scientist time is wasted due to poor data quality or ‘only 3% of enterprise data meets minimum quality standards reinforce the narrative that CDO struggles to deliver value are partially, if not completely, a function of problems emanating from outside data organizations.

What has become abundantly obvious to many, is that when measured by three of the biggest yardsticks of job success (fulfillment of job responsibilities, value delivery, and adherence to best practices), excellence in data leadership is sadly lacking at a time when it’s arguably needed the most.

This naturally leads to the question of why?

Modern Data Leaders Need to Shift Their Mindset

The answer, I believe, is one of mindset. In the world of data and analytics, many of our leaders have adopted a toxic mindset that creates a culture within data teams that is completely antithetical to the stated mission of most Chief Data Officers.

This mindset blames others outside the data organization for a failure to become ‘data– driven’, while at the same time endorsing the idea it’s impossible (or impractical) to measure how better data improves business performance.

This mindset blames a lack of user skills as a primary reason for low product adoption, while at the same time overlooking the very basics of good product design. This mindset clings to old and outdated approaches to data management and governance that clearly fail to promote meaningful change, at a time in business when transformation matters the most. 

And on, and on.  

Do all data leaders endorse this mindset? Of course not, but if this mindset is the reason for low data leader performance, this suggests aspects of this highly toxic mindset are widespread – and have been for a long, long time.

So where do we go from here? One thing is for certain:  – What data leaders, and those who advise them, have been doing is not working, and it’s time for some major changes.