Justifying an Advanced Analytics (or Data Science) Team

Building an “advanced” analytics organization has entered the mainstream among companies looking to unlock value from their data. As a talent services firm focused on the analytics space, we talk to at least one executive every week who is looking to hire data scientists or advanced analytics professionals to start a team.

Along with the gold rush into analytics, we have also seen the other side where companies are scaling back their analytics investment as results didn’t meet lofty expectations. Companies hired ahead of the need and failed to prove out the value to internal skeptics, typically in the finance organization.

The gold rush into building analytics teams has seen many failures

We see companies falling into two camps, those that have a clearly articulated idea of what the analytics team will be doing, along with a clear business case and a 2nd group that sees that value of analytics but has not clearly defined what will be done. While the 2nd group has a higher probability of failure, the 1st group also has the potential for failure if the business case is not realized relatively quickly. In both cases, hiring for capacity on Day 1 shortens the timeframe to deliver a return.

To justify an investment in analytics, we have seen some of our clients initially bring in contract resources for 6-8 months before hiring permanent staff. These contractors have all the relevant skills and come with experience having worked at multiple organizations.

Using analytics contractors can justify an investment in building an analytics team

This allows them to validate a business case and show results before committing to permanent staff. The CFO typically likes this approach. Beyond just the justification, using contractors allows companies to:

  • Work out kinks in the data;
  • Set expectations;
  • Better define the role & value of an analytics team;
  • Refine the profile of the right person for the permanent role;
  • Begin to build internal consensus behind an analytics organization.

To ensure success, it’s critical you hire the right contractor. This is an obvious statement, but not as easy as it seems. Our experience says the right person:

  1. Has the right tool-set for your environment – R, Python, Tableau, Hadoop, Hive, etc.
  2. Is comfortable with and likes getting into the data;
  3. Has at least 3 years of hands-on, post-academic experience in advanced analytics;
  4. Has good communication skills;
  5. Is organizationally aware – knows how to interact with different people at a company
  6. Understands the business issues that you are solving

Bringing in a contractor is a low-risk way to justify building out the team. It’s an approach that allows you to fail and iterate your way to success.

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