When a new job title is created and introduced to an organization, the immediate response is typically a combination of apprehension, confusion and sometimes rejection. It's not unusual for people to scrutinize the role, question the business need and worry about how it will affect them.
Riding on the coat tails of the Big Data phenomenon, the roles of data scientist and Chief Data Officer (CDO) are two job titles that have started to crop up in businesses, both large and small. This may not come as a surprise, but let's take a step back and explore exactly why these roles are being created, what they do and how they are affecting the way organizations run their businesses.
Firstly, there's a lack of choice - to remain competitive, organizations have to find innovative ways (or people) to exploit their data and gain valuable commercial insights from it. If you aren't, you can bet that your competitors are. Secondly, with a growing emphasis on data-driven decision making, organizations have understandably established and defined roles for the ownership, management and analysis of data within their businesses.
Traditionally, the responsibility for data has fallen within the remit of IT teams to manage and control. Today, with data being used in the wider business sense - rightfully so, organizations are increasingly looking beyond IT to get value from their data.
A CDO presides over an organization's overarching data strategy; ensuring information is utilized and managed effectively across a business. They hold responsibilities such as the delivery of collective platforms, defining data policies and ensuring best-in=class data governance. This role is of particular importance in industries that are heavily regulated, such as financial services or pharmaceuticals.
The CDO is also accountable for educating the rest of the organization about how data can be used strategically to drive revenues for the business. Given the far-reaching scope of this role, CDOs must regularly engage and collaborate with other C-Suite executives.
In comparison, a data scientist is responsible for data exploration, analysis and modelling. Their objective is to discover hidden insight, which can be used to solve business challenges and provide companies with competitive advantage. It is also vitally important that a data scientist is an exceptional storyteller, who is able to articulate their counsel alongside applied business empathy. Humanizing the story is particularly pertinent.
As we see a sharp increase in the number of businesses using data analytics, the more we hear claims that businesses are suffering from a lack of specialist skills in this area. There is increasing concern, therefore, about the lack of people with these titles - CDOs and data scientists - who apparently hold the keys to unlocking the true business potential of data.
However, a fundamental mistake is being made here. Data is not only for data scientists to explore and for CDOs to manage. Capable business users can be proactive with data too if they have the right tools - tools that are intuitive and accessible, and which encourage exploration through Natural Analytics.
Business users also have one great advantage over CDOs and data scientists: they understand business context and the implications of patterns, exceptions and associations that they explore. With easy to use, exploratory technology, there's no reason why organizations cannot or should not empower savvy employees to spot opportunities, anomalies and areas for business growth. Enabling data enthusiasts at the business level is something that a good CDO should be encouraging; this will only compliment and strengthen the theoretical discipline that data scientists apply to their analysis.
There is little doubt that in today's business climate, organizations must establish data roles and responsibilities - who owns the data and who is accountable for realizing its value? While new "data" titles are rightly being introduced to help manage and analyze the abundance of the data which organizations are faced with, it is just as important to facilitate a conversation around the data with the wider business. By empowering all employees and nurturing data enthusiasts with intuitive, effective platforms and applications, businesses may gain more than they could ever realize by looking beyond one sole data employee to make a good decision.