*The strategic side of the CDO role: how to help your Data Officer succeed*

Part 5 :: Real-world applications

Over 60% of executives now report their firm having a Chief Data Officer (CDO) – up from just 12% back in 2012 – and the numbers are expected keep growing. Data (of all kinds) is already essential to business decision making, and will only grow more significant from here.

As that happens, CDOs will prove crucial to helping companies succeed with strategies driven by data science and business intelligence (BI). Yet despite their importance to enterprises’ future success, many CDOs enter their roles amid a mountain of ambiguity.

At a Tech & Data Summit in New York, Bloomberg interviewed panelist Jon Neitzell, former CDO of Goldman Sachs’ Fundamental Equities unit, about some of the attributes that can help CDOs better strategize and succeed in their role. Neitzell mentioned that many companies are launching the role with misconceptions in mind and outsized expectations from the outset.

“I’m seeing a lot of businesses bring in the CDO function thinking, ‘Data is the new oil, data’s supposed to drive my business, so we should put someone in charge of figuring out what that means,’” says Neitzell.

“Then they’re just kind of unleashing these hires in their organizations without necessarily mapping resources to them,” he says. “So you start to get a lot of challenges, because there are multiple versions of what success looks like, and everyone has a different view of what it should be.”

Start with a strategic foundation

Creating a clear version of success requires an organizational framework for understanding the CDO role, and equipping hires to execute.

CDOs who can quickly understand organizational workflows and management structures are more primed to make an impact. As both a veteran Goldman portfolio manager and board advisor of recently acquired AI company Kensho Technologies, Neitzell brought a mix of internal knowledge and technology expertise to his role – and has applied that background to understand how his division’s models and strategies should evolve.

Collaboration also helps ensure cultural alignment.

​​​​​​​At Goldman, for example, there are individual data and market intelligence professionals by division all communicating up to a BI group run by the firm’s CDO, Jeff Wecker. Clear reporting lines and internal knowledge-sharing are helping each division “map a consistent path” for CDOs to realize meaningful objectives.

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​​​​​​Prioritize accuracy, utility, and scale

No two CDOs at Goldman – or anywhere else – will have identical objectives however.

To design an impact-driven roadmap and “business model” for their success in the role, CDOs must conduct unique SWOT analyses to learn where gaps and revenue opportunities exist – and ask whether the existing technology and data-science infrastructure can scale to the challenge.

A scalable infrastructure for BI and data is rarely ready-made, according to Neitzell, so CDOs tend to start working with tech teams right away.

Yet jumping straight to infrastructure investment is risky since it takes more than technology to address the full spectrum of data practices:

1. The data or ‘heavy lifting’ of ETL – extracting, transforming, and loading/preparing data for analysis
2. The data science (and mathematical or statistical integrity) behind the company’s processes, methods, and conclusions
3. The business model framework for incorporating data signals into decisions (mindful of changing market or competitive forces)

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​​​​​​Without all three pillars addressed, companies can’t design, inform, and create accurate feedback loops or usable hypotheses. Companies should expect CDOs to build models and make technology suggestions as they go, respecting that ROI has more to do with the utility of data for decision-making than the volume of data sets or reports.

Maintain agility to be ready for action

Building out data-driven strategies helps companies understand their customers and competitors better and faster, which is crucial to avoiding obsolescence as competitive landscapes evolve.

But these strategies also change the way firms do things – which can create resistance or competition internally.

CDOs may need to extract resources from various areas across the business or partner with younger, less proven companies to execute their strategy. Goldman, for example, invested in data-structure and storage startup Crux Informatics last year to fortify their data supply chain.

For CDOs to achieve those efforts successfully, there needs to be strong buy-in among leadership for the value of a data-driven strategy – and the resources it takes to create a winning one.

“This role is new and challenging in that you’re trying to cut across lines and unify specific areas of excellence into a cohesive strategy that can really move the needle now,” says Neitzell. “It’s incumbent on everyone involved to actually execute that opportunity.”