Boost your corporate analytics: The rise of the citizen data scientist

Are you one of those businesses struggling to hire the talented data scientists needed to manipulate corporate data for insights? Well, I have good news for you! It no longer should!

A couple of weeks ago I read an article on CIO Online how the lack of big data talent hampers corporate analytics and how this causes nightmares for CIO’s. There is indeed an exponential growing need for deep analytical skills but there are alternatives that could enable your company boosting corporate analytics while in the meantime you can continue to track down highly skilled analytical talent!

The rise of visual data discovery and approachable analytics (read more here) are making room for a new hybrid role within organizations; the so called “citizen data scientist”. This citizen data scientist is able to create or generate models that leverage predictive or prescriptive analytics using these more visual tools and approachable analytics. But their primary job is not in the field of statistics or analytics.

There’s more to this then just a new hybrid role that will be proven extremely valuable to your organization. These citizen data scientists can leverage their business knowledge and embed it in whatever it is they are testing, prototyping or building. More so, in collaboration with different stakeholders, they will help drive initiatives from all different business units within the enterprise. Their data and analytics undertakings will give a quick start to new and innovative projects.

A good strategy will determine early where there are already good pockets of expertise, where more talent is needed, and where talent could be better used. It will also make clear which initiatives should be further developed, which should be maintained and which should be cancelled. Key here is to work in smaller iterations and fail fast when necessary.

It is clear that harnessing a group of citizen data scientists to complement your deep analytical skills will prove to be a strategic decision as your organization can continue to enable and expand analytics supporting operational processes and decision-making while the deep analytical skills can further develop initiatives launched by the citizen data scientists.
Leading organizations that are really fostering such a culture and cultivating their analytical teams have a higher probability to acquire deep analytical talent. Keep this in mind when you start developing your analytical teams and the way they work.

Given enough time to grow, these junior hires can be taught the skills necessary for their company’s business and industry. In return they are provided a progressive career path forward.
Some firms rotate talent through different business silos, enabling employees to combine their analytical knowledge with domain knowledge to gain a stronger understanding of the impact of actionable insights on corporate decision making.

From a technology perspective you will need to equip your newly assigned citizen data scientists with the right tools so that they can combine their business expertise in the best way possible. This is a decision that should not be taken lightly. This fits into a wider perspective where you need to think thoroughly about a firm foundation for your enterprise insight platform that will support your data strategy of the coming years.

Click here if you want to read more about future proofing your Data Strategy!

To summarize:

  1. The shallow pool of deep analytical skills should not hamper your corporate analytics.
  2. The rise of visual data discovery and approachable analytics have forged the hybrid role of citizen data scientist.
  3. Executing a good strategy regarding this new hybrid role and the collaboration with different stakeholders within your organization will boost your corporate analytics and help you capitalize on it.
  4. An enterprise insight platform (the technology) should be built to enable different types of users to capitalise on data insights.

What are your experiences in boosting your corporate analytics? Where do you see opportunities and what are your challenges?