Jack Philips kicked off this year’s International Institute for Analytics Chief Analytics Officer Summit emphasizing the power and pervasiveness of analytics. Analytics, he says, is a classic disruptive innovation with most companies seeing a slow start and then a sudden inflexion point to rapid adoption and growth. Now the challenge is how to scale analytics, how to drive an analytic operating model forward. In particular an analytic operation needs a leader that is conversant in the technology and methods of data science but also a visionary and communicator, a program builder and manager, and someone comfortable with risk. Dan Magestro, head of research, joined Jack and highlighted the wide range of research and engagement IIA has offered its members. They wrapped up with the key theme of the event:
- Advancing Analytics
- Leadership – how to drive it forward
- Value – how do I focus and show the value
- Culture – how do I change the company to be data driven
With that, Bob Morison came up to open up the event talking about his recent research into “Analytics and Data Leadership: Focusing the roles (subscription required)”. This research was developed from 20 Chief Analytics Officers or Chief Data Officers, 16 of whom were the first to hold the role at their company. Many of them had both roles and they were skewed toward financial services. When it comes to these roles, three things drive their adoption: Enterprise Need for the role, Enterprise Commitment to the role and Candidate Capabilities.
Practically speaking organizations need both roles filled – either by one person or by two working closely together. This is hard because the roles are both new and evolving – role clarity was not the norm creating risk. In particular if both roles exist they must have some distinction such as demand v supply, offense v defense – adding value to data with analytics v managing data quality and consistency. But enterprises need to be ready – in particular when data is being identified as an asset by the CEO and executive team. CDOs tend to be driven by fragmented data environments, regulatory challenges, customer centricity. CAO tends to be driven by a focus on improving decision-making, moving to predictive analytics, focusing existing efforts.
He presented a 2×2 grid: Supply (is you data in shape?) v Demand for analytics:
- Strong demand and supply drives a single person handling a combined role.
- Demand but poor supply tends to drive a need for both roles with a team acting as the analytic data team in between them
- No demand and no supply means you only need a CDO really
Regardless many report to the CIO while others reported to the CEO. One of the challenges of those that report to the CEO is that they become part of the C-Suite and that tends to drive a focus on the business as more of a GM and less of a specific analytic focus. Also a general sense that sometimes one role or the other is easier to “sell” and that starting there is good.
Some disagreement in the research as to the way the roles should work – one person for both (with a strong sidekick for data), two people reporting to the same person or two people reporting separately (CDO reports to the CIO while CAO reports to a business executive). There’s some clarity advantage to a single combined role but a split allows CAO to focus on business while CDO focuses on technology and infrastructure/processes.
Regardless of how the roles get set up, they are evolving:
- Scope is expanding from tactical to strategic, from local to cross-functional and enterprise, standalone to an ecosystem
- Focus is shifting from defense to offense, to more advanced analytics, to decision-making not just data
Success is being measured in terms of capabilities (data governance, big data platform, predictive analytics, model management) and in terms of business outcomes. Challenges are about alignment, building teams, prioritization, business usage, enterprise management of analytics, legacy and culture shift. Pretty usual barriers. What’s next? Lots of very ambitious agendas including product development, marketing, customer experience, digital business and more. Focusing on crossing the inflection point to deliver results.
Connecting with the business is always critical for these roles and all of them spent a lot of time working with business partners as educators and evangelists. They try and triage their customers to focus and generate the successes that will build long term growth in demand and partnering. Some had good working relationships with IT though some found this more challenging.
Organizationally some covered everything, some split their data governance teams out, some divided analytic teams by type of modeling. Data management generally more centralized and more advanced analytics generally more centralized than BI. Lots of CoEs. CAOs in the audience talked about aligning with the business structure especially for more advanced analytics, and about the balance between centralized and distributed teams. Where teams are embedded in the business some clear focus on making sure all the analytics professionals are connected with dotted line associations. Variation, no cookie-cutter answer and ongoing adaption as things change.