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Beginning Your Talent Analytics Journey: Don’t Become a ’Mustang in the Mud’
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Beginning Your Talent Analytics Journey: Don’t Become a ’Mustang in the Mud’

Shawn Flynn
AVP of Global Thought Leadership & Advisory Services, Cornerstone OnDemand

JULY 14, 2021

One of my favorite analogies is ’don’t be a mustang in the mud’. The expression refers to the iconic Ford Mustang – a great car on the street, but definitely not the right vehicle in the mud. More and more I’m seeing organizations work to figure out what problem(s) to attack with predictive talent analytics and I’m reminded of my ’mustang in the mud’ analogy.

Talent Analytics is Hot

The enthusiasm for talent analytics is very strong, and that momentum is driving companies to either engineer or look to partners to help solve multiple talent challenges – new hire turnover, employee development, talent mobility, etc. That’s fantastic, but there seems to be a trend to attack multiple problems at one time.

Deloitte tells us that only 8% of organizations are doing strong predictive analytics. This continues to be a small number and the year-over-year ramp remains low. My hypothesis is that there are a lot of ’mustangs in the mud’ – a lot of horsepower in the wrong environment.

Walk Before You Run

As the niche of predictive talent analytics continues to grow, I get the sense that many companies will immediately begin trying to solve many problems in parallel. My advice to those companies is to start with one – to walk before you run.

Start with one where you know you either have the attention of the business or you feel confident that you can get it. One where the data needed to gain insight into the issue exists, and finally one that is more easily operationalized and/or deployed in the business. Doing so will allow you to:

  1. Assess your technology/partners to determine if within your own network you have access to the predictive analytics solution you will need – both people and technology.
  2. Trial and error for what will become a repeatable process for diagnosing and executing development of the next problem/need/challenge, because we all know there’s always more than one.

At the end of the day, if you’ve never undertaken a formal data and predictive analytics strategy, no matter how great the predictive analytics solution you use, trying to solve for too many things at once will take that Mustang you’re so proud of and put it in the mud where it’s only fractionally as effective.

Scale will come in time, but set yourself up for success early versus attempting to tackle so much that you never get off the ground.

In other words, don’t allow yourself to become a mustang in the mud...

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