Starting a new job is never easy, but chief data officers (CDOs) have it especially tough. Unlike traditional C-suite positions like CIO and CTO, where the roles are well-defined and come with a fair degree of repeatability, CDOs typically start from scratch. In fact, CDO is one of the only executive positions today that doesn’t have a well-established blueprint or roadmap to follow, which helps explain why the average tenure for a CDO today is a mere 24 months.
CDOs have a clear mandate: Create business value and competitive advantage with data. But where do you start? These days, I spend more time talking with CDOs than just about anyone else. Based on conversations with many, many CDOs over the years, here are a few of the strategies that seem to make for success.
1. Report to the right role
One of the first challenges CDOs face is sorting out where they sit in the organization. As an entirely new role, there are no standards set for where a CDO should be located in the traditional hierarchy.
Generally speaking, there are four common reporting structures: reporting to the CEO, CMO, CTO, or CIO. While it likely goes without saying, the best option in most situations is reporting directly to the CEO. That’s because analytics are paramount to an organization’s long term goals, and so CDOs need access and authority across departments.
Reporting to the CMO can also be effective – especially in organizations that are very marketing-focused like retailers. That’s because marketing departments are often the largest consumers of data in any company, and it always helps to be close to your constituents. (According to the latest Freeman Data Benchmark Study, 89 percent of corporate marketers currently use data to make strategic decisions, and two-thirds report plans to further increase spending on data and analytics in 2019.) CMOs are also responsible for top-line growth, which means they have a direct and vested interest in your success.
It’s also fairly common for CDOs to report to either the CTO or CIO. Both are usually mistakes. In most businesses, the CTO role is all about technology, whereas the CDO role is focused on solving business problems with data. Likewise, CIOs are predominantly focused on the management, governance, and compliance aspects of data. While important, it’s tough to juggle those foundational responsibilities while trying to effect a digital transformation cross the organization. These clashing approaches and mindsets are a recipe for over-indexing on managing the risk of data use (in the case of reporting to the CIO) or functionality (in the case of CTOs) – neither of which aligns with the purpose of the CDO role. And if there is misalignment between your leader’s goals and what you think needs to be done, you will never be effective enough or have the support you need to succeed.
2. Create a plan for culture change
Driving culture change across the organization is the single greatest challenge facing CDOs today. While almost everyone recognizes the inherent value of data, analytics efforts at most organizations are largely stuck in first gear. According to the latest research from Gartner, 87 percent of organizations are classified as having low levels of maturity when it comes to analytics.
The best CDOs approach the role from the perspective culture change – even more so than data itself – because that’s what ultimately makes or breaks any organization-wide data strategy. What’s more, the larger the company, the harder it will be.
Where do you start? With a listening tour. To succeed in driving culture change, you need two types of buy-in from your constituents inside the organization: One, for your existence in the first place, and two, for integrating data into their day-to-day work lives. A listening tour helps with securing both.
At the end of the day, your job as CDO is figuring out how to create business value and competitive advantage using data, so you need to understand what problems your business users face before you can start figuring out how to solve them. With that in mind, it’s important to understand that these conversations aren’t about data (at least not yet); instead, they are about the constituent and what they care about most. What is their mandate? What are they trying to accomplish? Where do they want their line of business to be 3-5 years from now? What does wild success look like? Start there. Later, once you have a better understanding of the people you exist to serve, you can start to talk with them about how data can help them accomplish their goals and objectives better and faster.
3. Focus on education
Intent and action are not the same thing. Even if you get the buy-in for your existence and succeed at expanding access to data throughout the organization, that doesn’t guarantee that anyone is actually going change their ways. This is where education comes into play. You don’t just have to teach people how to use the tools for interacting with data (in fact, that is getting easier by the day); you also have to foster basic data literacy and fluency.
Do people at every level of your organization understand key concepts like statistical significance, standard deviation, outliers, and so on? If not, start there with education efforts. Why? Simply put, if people don’t understand the basic nouns and verbs of a language, they are not going to use it effectively (or even at all).
Once the organization “speaks” data, the next piece of the puzzle is helping teams understand what data is available. The best way to do that is by training them to ask for it. Start with team leads: once they start showing the data behind their decisions as a leader – and make clear they expect the same from their teams – it will start to become reflexive for everyone.
Will you get to full data literacy and fluency in 90 days? Not likely. But CDOs that position themselves strategically within the organization, secure the necessary buy-in from their fellow leaders, and drive education at every level are the ones most likely to find success.
Doug Bordonaro is Chief Data Evangelist and Field CTO at ThoughtSpot. He has over 20 years of experience with BI and data warehousing solutions in his various roles at Netezza, AOL, and Disney.