As organizations increasingly view data as a valuable asset, more CDOs are being recruited to harvest, manage, protect and mine it. Gartner’s last Chief Data Officer survey revealed a 57 percent increase in CDOs in 2017 compared to 50 percent in 2016.
The CDO is one of a new breed of technical leadership roles like Chief Evangelist and Chief Data Scientist. Compared to traditional technical roles, these call for a mix of advanced communications skills like influencing and negotiation along with technical and analytical competencies. They require an eye for detail without losing sight of the big picture. They also must balance the needs of IT and the business.
Stakeholders across business and IT all have their own ideas about what the CDOs priorities ought to be. Sales and marketing want things like clean, reliable data that gives 360-degree views of customers and prospects and stats on campaign effectiveness. Legal and risk teams expect flawless governance, regulatory compliance and alerts to impending threats. The BI team wants the best tools for doing their jobs successfully. On day one the CIO will more than likely offload a huge stack of unresolved data-related issues on your desk.
It’s nice to feel loved, but at the same time, how on earth is the CDO supposed to prioritize?
Some CDOs will be tempted to launch straight into a high stakes data initiative, like that IoT use case the CEO is staking the future of the company on. Others might decide that rolling up their sleeves and putting out fires is the heroic way to get lots of different stakeholders on their side.
Both are errors that could prove fatal. The first is like building an expensive mansion on top of a shaky or non-existing foundation. When that high-stakes project invariably comes crashing down, many high-profile spectators will be watching. The second puts you in a defensive mode right out of the gate, making it increasingly elusive for you to deliver strategic projects that deliver sustainable value. These rookie mistakes explain why CDOs’ tenures are often problematic and brief – 2.4 years on average, according to the Second Gartner CDO Survey – The State of the Office of the CDO.
At the risk of stating the obvious, your first order of business must be establishing, getting buy in for and communicating your data strategy. This will give you a framework in which to prioritize (and also deflect) the many requests that will be coming at you. This should succinctly communicate your long-term vision and short to medium range priority tactics. Here are the top five areas I recommend focusing on in your data strategy:
1. Privacy and security
The Allianz Risk Barometer ranked the top UK business risks for 2018 as cyber incidents, changes to regulatory compliance and business interruptions. All these risks can be mitigated by good data management. No CDO wants the kind of negative publicity recently earned by William Hill and Rabobank, both of whose failure to spot potential money laundering risks in their transactional data landed them huge fines.
Since the CDO role was born out of concerns for regulatory compliance (the US banking crisis and European GDPR legislations), it follows that privacy and security are fundamental priorities. Your organization probably already employs people with tactical responsibility for privacy and security. As CDO your role is to ensure that safeguards are robust enough, enforced properly and prioritized above all else.
A first step is knowing which regulations impact your industry and business, even tangentially (as can be the case with GDPR). Then establish standards and guidelines, put your teams in place, and ensure that everyone at your company who works with data understands their role in keeping it safe.
Once your data is safe, the next step is to ensure it’s consistent. Governance is primarily about getting agreement to what your data should mean. For example, how many different definitions of “revenue” exist in your company? How many definitions of a “customer?” While both sound straightforward, it’s all too common for different departments to define what appear to be simple terms and metrics in different ways.
After you establish common, company-wide definitions for all measurable business terms, you need to get all stakeholders to agree and buy into them, then set up a process to maintain and enforce the whole thing.
Once that’s done, it’s time pull it all together.
3. Integrate silos
Data silos are the bane of many organizations. They tend to develop organically and unintentionally as businesses change and restructure.
Some data silos are source systems that grew in isolation, usually in a specific department. For example, marketing may have implemented a Customer Relationship Management (CRM) system without realizing that an enterprise-wide solution already exists. Or maybe they did, but just didn’t want to go through the effort of getting access.
Data silos are often crop up downstream of centralized systems. This is common where business intelligence and data warehouse functions are treated as a shared service, but where no mandate exists to use those services. One scenario I’ve seen a lot is a business deciding that it’s easier to get a feed from the data warehouse and build an isolated data mart than to go through centralized channels. This approach has some obvious advantages – faster turnaround, no competition for resources and more targeted tool selection. The disadvantages are greater, but often less apparent — decreased security, duplication of effort and poor governance.
When integrating silos, CDOs should take both of these types of silos into account and also develop a prevention strategy.
Once you’ve built a foundation in these three focus areas, the day-to-day firefighting and ad hoc data requests will be significantly reduced. This gives you the space to focus on the big ticket items.
4. Find opportunities to monetize
The expression “data as an asset” has been bandied about recently, but what does it really mean? On one level, it’s a reminder that data has intrinsic value and is not just a byproduct of a system.
The real point however, is that data can be key to growing top-line revenue. Using data to improve operational efficiencies is a great way to free up working capital, but there’s only one way to grow top-line revenue with data – monetize it.
Monetizing data should be a top concern of every CDO. If you’re not using data to create new revenue streams today start talking to business stakeholders about strategies to benefit your organization. Sometimes this involves analyzing data to make the case for diverting resources away from unprofitable business areas into new, more lucrative ventures.
Fortunately, there is a growing body of success stories in the public domain from your peers in the CDOs community who are successfully monetizing their data. If you need inspiration, attend and industry events, read blogs and join social networks. In my experience, leaders are more than willing to share their successes and lessons learned.
5. Evangelize data to the business
Gartner recently reported that 35% of CDOs regard poor data literacy as a major challenge in their organizations. As your team and its remit evolves, you play an active role educating and evangelizing to the lines of business, to the CEO, and to the front-line employees who will ultimately control the success or failure of everything on this list.
Don’t get me wrong. This isn’t about trying to make line managers literate in esoteric concepts like table joins and SQL scripting. It’s about showing people the wide range of insights possible to support everyday decision making. Most people don’t even know what questions they can ask of data, or how different sources can be blended to gain even deeper, more unique insights.
Above all, enjoy the journey! The role of CDO is still very new, and if you focus on these areas your success story might just inspire the next generation of data leaders.
As read on ThoughtSpot’s Data Chief blog – Written by Doug Bordonaro, Field CTO