Solving the Expertise Crisis in Your Big Data Project

Joe Wynne is a versatile Project Manager experienced in delivering medium-scope projects in large organizations that improve workforce performance and business processes. He has a proven track record of delivering effective, technology-savvy solutions in a variety of industries and a unique combination of strengths in both process management and workforce management.

  Business Intelligence   Strategy  

Today, in big data projects it is a critical success factor for you to anticipate expertise constraints. Data analytic specialists are so sexy now that it may be extremely difficult to fill that role. And education is not keeping up with demand, so you won’t be seeing improvements in recruiting for this role anytime soon.

To maintain your position as a high-performance project manager, you must be ready with a smart tactic to respond to this specific resource constraint.

First, a bit of context. There are a number of activities required to ensure you respond appropriately to any potential expertise shortage. For example:

1. Analysis to determine the nature of any expertise gap
2. Determination of best steps to fill gap, which may include identification of pool of resources to recruit or train
3. Recruiting to go after needed resources from the identified pool
4. Selection of the candidate

Your smart tactic for dealing with a potential data scientist expertise constraint is to concentrate on the analysis very early in the project. 

Facilitating the Analysis
Immediately find out if you will need data analytic specialists in your project. There may be adequate resources available in house to work at the times you need them to be, but don't assume this will be so.

Your sponsor may already know the answer to this question based…

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