Data Culture and Digital Transformation

One of the key success factors for organizations to thrive today is adopting modern self-service business intelligence tools and transforming their businesses to become more agile, more automated, and more data driven. For years technology vendors and industry analysts have thrown around the term “digital transformation” to broadly describe this phenomenon, and technology has matured to catch up with the hype.

Cheesy graphic of zeroes and ones - Image by Gerd Altmann from Pixabay

I use the term “hype” here deliberately. In my experience the term “digital transformation” has been thrown around in the same way as the terms “cloud” and “big data” were thrown around, just a few years later. The cynical part of my brain initially categorized it as “marketing bullshit,” but the intervening years have shown me that this wasn’t actually the case. Digital transformation is real, and it’s a key driver for a successful data culture with real executive support.

Over the past few years I’ve had hundreds of conversations with executives, decision-makers, and business and technical leaders from hundreds of enterprise Power BI customer organizations. These are real people working to solve real problems, and they come from a broad range of industries, geographies, and levels of maturity. I learned a lot from these conversations, and have done my best to help Power BI improve based on what I learned[1], but when I step back and look at the bigger picture there’s a significant trend that emerges.

Stakeholders from organizations that adopt Power BI[2] as part of a digital transformation describe more mature data cultures, and a greater return on their investments in data and analytics.

As you can probably imagine, once I saw this correlation[3], I kept seeing it again and again. And I started looking more closely at digital transformation as part of my ongoing work around data culture. Two of the most interesting resources I’ve found are articles from the Harvard Business Review, which may not be the first place you think to look when you’re thinking about Power BI and data culture topics… but these two articles provide important food for thought.

The first article is almost six years old – it’s from 2015, and focuses on The Company Cultures That Help (or Hinder) Digital Transformation. In the article, author Jane McConnell describes five of the most difficult obstacles that prevent organizations from adopting the changes required by a digital transformation:

(Please feel strongly encouraged to click through and read the whole article – it’s well worth your time, and goes into topics I won’t attempt to summarize here.)

I suspect these challenges sound as depressingly familiar to you as they do to me. These obstacles weren’t new in 2015, and they’re not new now – but they’re also not going away.

Jane McConnell goes on to identify what characteristics are shared by organizations that have overcome these obstacles and are succeeding with their digital transformations. The alignment between her conclusions and this blog’s guidance for Building a data culture with Power BI is striking[4]:

  • A strong, shared sense of purpose alleviates many obstacles, especially those of internal politics. When an organization has a clearly defined strategy, it is easier for everyone to align their work towards those strategic goals, and to justify that work in the face of opposition.
  • Freedom to experiment helps people prioritize, make decisions, and rethink how they work. Having a culture where data governance takes the form of guardrails and effective guidance, not roadblocks, is key to driving meaningful positive change.
  • Distributed decision-making gives people at the edges of organizations a voice in digital transformation. Although there is a need for centralized decision-making and control for some aspects of a data culture (data sources, applications, policies, etc.) the real power of managed self-service BI comes from letting IT do what IT does best, and letting business experts make informed business decisions without undue governance.
  • Organizations that are responsive to the influence of the external world are more likely to understand the value digital can bring. My customer engagements don’t provide any insight to share on this specific point, but I suspect this is significant too. Organizations that are not responsive to external factors are unlikely to make it onto my calendar for those strategic conversations.

In her conclusion, Jane McConnell suggests that readers who see these obstacles in their way should “find ways to transform your work culture using digital as a lever.” In the context of the Harvard Business Review’s target audience, this advice makes a lot of sense.[5] If you are a senior business leader, shaping the work culture is something you are empowered and expected to do. If you’re not, this is where having an engaged and committed executive sponsor will come in handy. If you don’t already have that sponsor, framing your conversations using the vocabulary of digital transformation may help in ways that talking about data culture might not.

The second HBR article I found valuable and fascinating in the context of digital transformation and data culture is written by Randy Bean and Thomas H. Davenport and titled Companies Are Failing in Their Efforts to Become Data-Driven. This one is more recent, and focused more closely on the data side of things.

(As with the article discussed above, please feel encouraged to click through and read this one too. Both articles are written by professionals with significant experience, and an informed strategic perspective.)

This article starts off with a excellent statement of fact:

Whether their larger goal is to achieve digital transformation, “compete on analytics,” or become “AI-first,” embracing and successfully managing data in all its forms is an essential prerequisite.

It then goes on to inventory some of the ways that organizations are failing to deliver on this essential prerequisite, including “72% of survey participants report that they have yet to forge a data culture.”[6]

I’ll let you read the source article for more numbers and details, but there is one more quote I want to share:

93% of respondents identify people and process issues as the obstacle.

If you’ve attended any of my “Building a data culture with Power BI” presentations, you’ll know that I break it down into two main sections: the easy part, and the hard part. Spoiler alert: The easy part is technology. The hard part is people.

The article by Bean and Davenport includes a lot of insights and ideas, but not a lot of hope. They’ve talked to senior data leaders who are trying various approaches to build data cultures within their enterprise organizations, but they all see a long march ahead, with hard work and few quick wins. Technology is a vital part of the transformation, but people and culture is necessary as well.

Building a successful data culture requires top-down and bottom-up change. If you’re in a position of authority where you can directly influence your organization’s culture, it’s time to roll up your sleeves and get to work. If you’re not, it’s time to start thinking about the changes your can make yourself – but it’s also time to start thinking about how using the vocabulary of digital transformation might help you reach the senior leaders whose support you need.


[1] This is your periodic reminder that although I am a member of the Power BI Customer Advisory Team at Microsoft, and although I regularly blog about topics related to Power BI, this is my personal blog and everything I write is my personal perspective and does not necessarily represent the views of my employer or anyone other than me.

[2] I assume that this holds true for other modern BI tools, but since I’m only talking to Power BI customers I can’t really say. And since Power BI continues to increase its lead over the competition…

[3] Not causation.

[4] The bolded text in this list is taken from the HBR article; the rest of the text is from me.

[5] Even if the use of “digital” is sooooo 2015.

[6] Now I wish that I had found this article before I started my data culture series, because I definitely would have used “forge” instead of “build” as the verb everywhere.

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