4 ways to entice the best data scientists
It’s the sexiest job of the 21st century, according to Harvard Business Review. Hyperbole aside, data science has emerged as the hot profession of our time. In our digitised world, with a proliferation of big data available, data scientists offer the golden ticket – a skill set that can access and analyse masses of data, using the resultant insights to solve business problems and uncover opportunity.
Like most things sexy and new, there is a supply vs demand issue. Global consulting firm McKinsey estimates that by 2018, the US alone will experience a whopping 60% skills shortage in the field of data science. This shortage will affect large and small companies alike. The competition for data scientists will be fierce, growing in direct proportion to the recognised importance of data science as a discipline.
Keeping pace has never been more important. Here are four simple ways you can ensure you are business-ready to attract the best data scientists:
1. Lead the way
To successfully integrate analytics within your business, leadership support is a must.
Leaders need to endorse the science and they need to trust the data. Good analytics will uncover previously unconsidered insights, and there will be times when those findings challenge personal convictions around what does and doesn’t work within the business. Strong leadership will ensure the move from instinct to analysis is both supported and understood by the greater business. The endorsement of senior leaders will also allow data scientists the creative freedom to uncover those valuable insights previously locked up inside the data.
The endorsement of senior leaders will also allow data scientists the creative freedom to uncover those valuable insights previously locked up inside the data.
2. Access is key
To succeed in answering business problems, data scientists require unfettered access to all enterprise data available and equally, the right tools to dig into that data. Tools of the trade, in particular the software and hardware data scientists use, should be made readily available. Removing any barriers to access will enable your analytics team to spend the greatest portion of their time on what the data is saying, as opposed to getting to that data in the first place.
Removing any barriers to access will enable your analytics team to spend the greatest portion of their time on what the data is saying, as opposed to getting to that data in the first place.
3. Communicate the story
Once you have mined the insights, you need a strong communication strategy to ensure these insights are shared across the business. To avoid any instance of Eureka! moments occurring in a vacuum, pair analytics teams with communications teams to deliver the message. Have the teams co-locate if you can and encourage partnership between the two functions. Really clever people doing really clever things should be talked about, and loudly, by the team best positioned to tell the story.
Really clever people doing really clever things should be talked about, and loudly, by the team best positioned to tell the story.
4. Value is the point
In addition to communicating insights to the greater business, it is important to point to the specific commercial value analytics creates. Measure success by keeping a scoreboard of the revenue attributable to a particular uncovered opportunity and include any downstream work that occurred as a result of the analysis.
As your investment in data science starts to generate positive revenue outcomes for your business, you need to continuously communicate the value this investment has generated.
Data science might be the sexiest profession of the century; it is also fast becoming integral to business success. With leadership support, access to the right tools and data, a strong relationship between analytics and communications, and a clear way of showing value, you can lay the foundation for data scientists to embed themselves in your business and unlock the growth opportunities big data contains.