Success with data is dependent upon diversity
The task of building a data analytics team is no easy one. Its quite important from the outset to be mindful of not holding a one dimensional focus when seeking to build a balanced team of analytics professionals. One important consideration that should not be overlooked is ‘diversity’.
There are many visible examples of successful analytics teams that have been established within the framework of a robust diversity hiring policy, most noticeably at major brand name companies such as Google, Barclays and Spotify. But with smaller companies, how critical is diversity within the analytics business unit for success?
One approach that small to medium sized companies can take is to define and write a hiring policy that sets out to include not only people with analytical skills, but also those with business and relationship skills who can help frame the question from the outset and then communicate the results effectively at the end of the analysis.
As an example, the multinational conglomerate Bouygues values a diversity of capabilities for its analytics teams, with a diversity-centric policy that holds data and analytics as most effective when world-class technology skills are paired with strong functional domain knowledge.
Diversity within analytics can be achieved by establishing teams from a multitude of business backgrounds; a blend of both IT and functional skills.
Robust comprehension of data science is essential to any analytics team, and there should be statisticians, mathematicians, and machine learning experts within the analytics business unit who understand algorithms and how they can be applied on data.
With a focus on data engineers who can build the pipelines to get the data in place for completing all the analysis, along with domain and business experts who understand the complexities of the problems that the business is trying to solve.
Technically, a data scientist is supposed to be a “unicorn” that can do all of this simultaneously, but unicorns don’t exist. Successful data science teams are diverse, where individuals bring in these competencies that need to come together.