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 are honored to hear from Jon who has performed over 100 People Analytics Deployments! So without further ado, take it away Jon!

Over the past few years, I've had the opportunity to work with hundreds of organizations along their people analytics journey. In that time, I've seen a lot of success stories, but I've also seen a lot of failures. I often tell my clients that there is no guaranteed path to success. They may be disappointed to hear this, but it is the truth. The good news is, I'd be sharing a few key patterns for success that I've noticed.

Here are the top four lessons I've learned from these experiences:

Lesson 1: Start with a clear business objective

The first step in any successful people analytics initiative is to start with a clear business objective. What do you hope to achieve by using people analytics? Are you trying to improve employee engagement, reduce turnover, or increase productivity?

Once you know what you want to achieve, you can start to identify the data that you need to collect. It's important to collect data that is relevant to your business objective and that is accurate and reliable.

Lesson 2: Get an engaged and active sponsor

People analytics is a new and complex field, and it's important to get support from leadership before you start. An executive needs to understand the value of people analytics and they need to be willing to invest in it. They have to set the vision and hold leaders accountable.

In my experience, key user groups often want to become more data-driven. However, this is a more strategic goal that can be 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 sets goals and expectations for how people use the people analytics solution. They also review how people are using the solution, provide verbal or monetary recognition to change-makers, and hold their leadership team accountable for usage that is not in line with their goals.
• Scenario 2: Having the head of people analytics fully own the deployment of the people analytics solution. Moreover, they must also manage up with key stakeholders to demonstrate the value of the solution, and they must work with HRBPs who do not report to them. They must also compete with other key HR initiatives for resources.

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.

Once you have a supportive leadership, you can start to build a team of people who are passionate about people analytics. This team should include people from HR, IT, and other departments.

Lesson 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 use this data?
• 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?
• 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.

Lesson 4: Go beyond HR with your people analytics

In the most successful people analytics deployments, I've seen that going beyond HR is a key pattern. This builds on the three lessons I noted above and requires data that supports a business need, a key executive sponsor from the business, and a phase after HR.

Some clients 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 is to deploy to HR and the business, then deploy 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. Be sure to get them aligned on your efforts.

Thank you again 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.