Want Big Data Innovation? Rethink Your 'Need' for a Chief Data Officer. What you should do instead is bridge the divide between your IT and business needs. Say hello to the 'chief growth officer.'

The ability to quickly gather the right data from the right sources, to make the best business decision possible, is crucial. Yet, the common perception that you need a chief data officer (CDO) to make that decision a reality is not always true.

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While the role of CDO only recently emerged, it is steadily growing, with Gartner predicting that 25 percent of organizations will have a CDO by 2017. However, while a big data strategy is vital, a CDO may not be.

Organizations need to ditch the mindset that big-data innovation is an IT task reserved for the technically minded. To be data driven, and to be successful at it, all business users should be able to access the right data so they can creatively solve real problems.

Executing that is possible with the help of a new kind of data leader that takes a design approach to big data -- say hello to the "chief growth officer."

Bridging the divide between your IT and business needs

The industry has long claimed that to leverage your data assets, you should hire a CDO. But that is not a necessary investment on the path to becoming a data-driven business; in fact it may even be detrimental.

When it comes to big-data strategies, there exists a damaging divide between IT departments and business needs. CDOs tend to focus on building out complicated architectures with complex technologies, and the end result isn't always relevant to the business problems that need to be solved.

A CDO's role forces this individual to focus on collecting data sources and building a data lake. Yet simply bringing data together doesn't accomplish much. Instead of using data analytics just for the sake of it, organizations need their data strategy to be laser-focused on solving real problems backed by transformational use cases (a list of actions or event steps).

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With CDOs at the big-data helm, organizations risk losing sight of the business problems they need to solve. If businesses are trying to traverse a short distance from point A to point B, a CDO's solution is all too often to spend excess resources to construct a high-speed boat not really suited for the job.

In reality these business users simply needed a pedal bike that could solve their initial problem, and solve it fast.

Solution: Hire a chief growth officer and adopt a 'design-thinking' approach.

In contrast to a CDO, a chief growth officer uses data to creatively grow the business. These staffers focus first on why the company needs data to solve the problem, and then build out the technology behind it. Their agenda is based on use cases that will build the company. And that approach bridges the gap between IT initiatives and business needs.

Rather than focus on the latest and greatest in big-data technologies, chief growth officers take a design approach that focuses on real business problems and works backwards. Far too often, we see companies churning their wheels to build Apache Spark or Kafka tools, to boast real-time and extreme-processing capabilities.

Yet once companies implement these technologies, they apply only to a minority of use cases (a list of actions or event steps). In reality, these business users first needed tools that could help them analyze things, like personally identifiable information (PII).

To develop a design approach to data analytics, start with the use case and scale from there. Consider what questions you want to ask your data and prioritize the ones that will deliver the biggest ROI. Once you have the top use cases identified, you can consider what specific big-data technology tool will solve your problems.

The design approach to big data leaves room for creative thinking to solve, whereas the old, traditional approach by CDOs doesn't allow for inventiveness.

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By arming themselves with a chief growth officer and a design approach to big data, companies can harness the power of creativity, great user experiences and computational power, to solve business problems in the best way possible.