Chief Data Officer: The Challenges of a Challenging Job
“Nobody knows what the role of a Chief Data Officer is, and if they did, they would not take the job!” –as told to Roger Nolan
So, what’s going on with this emerging role of chief data officer?
Gartner recently published estimates that 25% of large global organizations have chief data officers (CDOs), a number that will rise to 90% within the next two years.
In a survey of 564 executives I helped write in late 2015 as part of my work with Forbes Insights and EY, we found that 59% of organizations already have a CDO in their ranks.
The rise of CDOs “represents a much deeper change occurring throughout most organizations,” according to Ted Friedman, research vice president and distinguished analyst at Gartner. “Practitioners of distinctive data and analytics disciplines will need to broaden their understanding, and work more closely with others to realize the benefits of using data and analytics to capture transformative business opportunities and mitigate risks.
Data industry experts have spelled out the challenges of this challenging job. Roger Nolan, for one, observes that “the challenge before a CDO is to manage data on an enterprise-wide basis. The obvious risk is in trying to boil the ocean and failing to deliver business results quickly.” Nolan recommends “Ruthless prioritization of all the business’s data and analytics projects,” along with “extreme diplomacy to collaborate across the CEO, business unit leaders, CIOs, architects and data owners.”
In addition, Nolan states, CDOs are charged with “dealing with the fact that data is fragmented, siloed, and pouring into the organization from outside sources in many formats, data quality levels, and with limited business context to understand what it means.” And, oh by the way, “let’s not leave out security concerns.”
Fortunately, there is a roadmap budding or current CDOs can follow, which Bill Schmarzo spells out in a recent CIO post.
Identify the targeted business initiative: Know the fundamentals.
Estimate financial value of business initiative: “Calculate a rough order estimate of the financial value of that business initiative,” Schmarzo says. “It is a sufficient starting point in driving conversations between the CDO and the key business stakeholders in order to gain consensus on the estimated financial value of the targeted business initiative.”
Identify use cases that support target business initiative: “Identify the use cases, or clusters of decisions, that support the targeted business initiative,” Schmarzo recommends. “Interview the key business stakeholders to identify the key decisions that need to be made in support of the targeted business initiative, and then group those decisions into common subject areas or use cases.”
Group decisions into common use cases: These may include items such as “increase store traffic via local events marketing, increase store traffic via customer loyalty program, increase shopping bag revenue,” and so on. “This is also the point in the process where the business and IT leaders need to prioritize the use cases based upon relative financial value and implementation feasibility over the next 9 to 12 months,” Schmarzo writes.
Prioritize the use cases: “It is important that all key business stakeholders have a voice in determining the relative value and implementation feasibility of each use case,” says Schmarzo. “This ensures that all parties are in agreement about where and how to start prior to the organization investing significant money and time building out an analytics capability that the business stakeholders may not use or trust.”
Estimate financial value of use cases: “Employ a simple polling technique to get an estimate on the financial value of each use case from each business stakeholder,” says Schmarzo.
Identify potential data sources: “Conduct business stakeholder interviews and facilitated brainstorming sessions to identify those data sources that might be useful in support of the target business initiative,” Schmarzo advises.
Estimate financial value of the data: “Map the data sources to the use cases, and determine the relative importance of each data source to each individual use case,” says Schmarzo.
Estimate financial value of data: Schmarzo says it’s best to keep this as simple as possible.