Using Data to Drive Culture

Let me start with a story.  A large, global organization is trying to change their culture and change it quickly.  They have three goals for what success looks like regarding this initiative, which targets a notably higher attrition rate than their industry:

• Improve Engagement Scores by 50% in 2 years. Each subset of engagement (manager experience, communication, etc.) has a leader assigned to execute specific actions to drive up that score.  Those leaders form the Engagement Committee who meet monthly to stay connected, ensure alignment between initiatives, etc.
• Increase # of Diverse Hires by 35% in 3 years. Retention data, as well as feedback from engagement surveys, exit interviews, and demographic analysis drove this specific goal.  The company wants to decrease their attrition rate from 35% (above industry average) to 20% (just below industry average) but in doing so, want to bring in more diverse hires to help the organization as it moves into the future.  This is one of the initiatives to drive that forward.
• Alignment with Global Issues by 2022.  Implementations completed by 2024.  The organization would like to be more aligned to what’s going on with the world, such as their carbon footprint and environmental practices, employee health and safety, etc.  Each work stream will provide a formalized action plan by Q1 2022, which will be reviewed and approved by the Executive Committee.  Knowing some changes will take time, the expectation is that all projects will be completed by 2024.

Now, let’s look at how measurement can be leveraged here.  Keep in mind these ideas are not exhaustive – just meant to stimulate how you think about similar types of work.

• Improve Engagement Scores by 50% in 2 years. Each of the subgroups should ask themselves – what will it take to improve our scores by 50%?  How can we align predictive metrics to those areas that will provide indicators for whether we’ll hit the goal in 2023? How will we collect or retrieve that data, analyze it, and report back on it?  Setting this up at the outset makes measurement significantly easier and through management/monitoring, will allow you to pivot much more efficiently and effectively, when needed.
• Increase # of Diverse Hires by 35% in 3 years.  The obvious outcome here is % of Diverse Hires; however, what is going to be done to bring in those diverse hires?  Depending on the strategy, there will likely be several talent acquisition measures included, as well as demographic data (department, role, experience, etc.).  Organizations typically do very poorly at measuring their talent acquisition process, so there will likely be significant change management for this area of focus, as well.
• Alignment with Global Issues by 2022.  Implementations completed by 2024.  Here, each subgroup not only needs to consider their internal data, but also the external data.  How do you ensure that you’re well aligned with the global issues to be able to monitor results and provide context for your internal data?  For example, if you’re focused on helping employees maintain good mental health, you’d want to know the current research and resources.  Again, you will go through the same process as before in terms of predictive metrics and the process to manage them.

You’re probably saying, “if it were this easy, wouldn’t everyone do it?”  Well, it’s a fair point because change is often not easy.  I find that the “bigness” of work like this often inhibits people because they just don’t know how to manage it.  So, how do we help people get better at thinking in this way?  How do we upskill our workforce to be more data-centric?  There are many answers to this hypothetical question, so based on the resources, capabilities, and leadership investment for your organization – come up with options that are practical and make sense.  Start small, build capability and experience, and results will follow!