The Top Four Lessons Learned From 100 People Analytics Deployments

Written by Jon Burton - GUEST BLOGGER

June 8, 2021

The Top Four Lessons Learned From 100 People Analytics Deployments

Our blog post this week comes from Jon Burton, the Senior People Analytics Consultant from Visier. We appreciate the opportunity to hear from Jon who has performed over 100 People Analytics Deployments! So without further ado, take it away Jon!

“I’ve had the good fortune of being able to partner with many large multinational organizations along their people analytics journey.  A common mantra I’ve shared with my clients is there is no recipe book for guaranteed success that exists today.  However, having been able to witness and partner with more than 100 companies along their people analytics journeys, with clients ranging from a single person dedicating part of their time to leading an analytics deployment, to a large and mature team with dedicated change management resources to assist the team, I’ve noticed a few key patterns for success:

  1. People analytics needs to connect to a business problem (or at least a key HR problem).  When asked what business problem your people analytics solution will solve, I’ve seen far too many companies respond with a variation of the following “it will make us more data driven, allow us to bring together disparate data sources, or provide us with predictive capabilities”.  Pushing data out absent a connection to a measurable business problem (or at least a key and measurable HR problem) will make it harder to achieve success.
  2. Engaging an active and engaged executive sponsor who can set the vision and hold leaders accountable.  I’ve seen many organizations invest in a people analytics team, solution and have an executive that wants to be more analytical, but does little to nothing to support the deployment.  In my experience, key user groups will have a desire to become more analytical, but this is a more strategic goal that is often overtaken by the more tactical needs that pop up day-to-day.  Which of the following scenarios do you think will result in a higher impact to the organization:
    • Scenario 1: Having a strong and engaged sponsor who can set goals and expectations for usage, review usage, provide verbal or monetary recognition to those who are making changes, and hold their leadership team accountable for usage not in line with their goals OR
    • Scenario 2: Having the head of people analytics fully own the deployment of the people analytics solution – trying to manage up with key stakeholders to demonstrate value and HRBPs who do not report into them, but competing with other key HR initiatives.I think we all know the answer to which scenario is more likely to be successful, but I suspect many of us also more commonly see the other scenario.
  3. Phase your deployment – don’t do a big bang to all users.  A successful people analytics deployment will require more energy and resources from a people analytics team.  Questions will move from – how do I, why does this data say X when I have seen or think Y, to more advanced questions such as am I better off hiring externally or finding internal talent to develop for a key role, or how can I meet my diversity goals for key leadership positions.  These higher value questions will require more effort and partnership (and thus resources) from a people analytics team to support.
  4. A key pattern I’ve seen in the most successful people analytics deployments is to go beyond HR with your deployment.  This builds on the three patterns noted above and will require data that supports a need of the business, a key executive sponsor from the business, and is a key phase needed after HR.  More clients that I want are hesitant to deploy outside of HR for a variety of reasons, but this has been a consistent pattern of success with many of my clients.  A best practice I’ve seen with many of my clients (and consistent with my “phase your deployment” pattern) is deploying to HR and the business, then deploying to finance.  This group is a key owner of numbers within an organization and is likely to have differences in numbers and perhaps assumptions as to what makes up headcount, so be sure to get them aligned on your efforts.”

Thank you again from the Team to Jon Burton from Visier for being on the HR Data Labs podcast and for writing this guest blog post! We appreciate you sharing your knowledge and experience with us and our audience! To connect with Jon visit his LinkedIn and visit Visier’s website to learn more about how to get people answers on demand with Visier.

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about the author
Jon Burton is the Senior People Analytics Consultant at Visier Inc. With 20 years of experience under his belt partnering with senior leadership to convert their needs into actionable plans, he helps organizations plan and execute their people analytics deployment, develop meaningful visualizations, and brainstorm on ideas to maximize the value of their people analytics platform.

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