Behind the buzzwords: What good people analytics looks like
Gilbert Dietrich is current Executive Director and Head of People at Aperto, a leading digital agency and IBM company, former head of People Operations at SoundCloud, and former Team Lead at Google covering Germany and Emerging Markets. We spoke to him about his insights on why People Analytics matters to companies, and how to plan for success and make the most of a company’s people data.
Why does People Analytics matter to you?
Better decision making is possible
People Analytics is simply about understanding the people at your company with the help of data, and using that information to benefit both employees and the company. It involves looking at the information you already have and using it to help you make good decisions. The information can be simple yet insightful, like the average characteristics of the employees you hire, or the length of time that people stay with your company before they leave. You can learn from that information, identify patterns and make better decisions. One example is understanding the difference between people who stay at your company, and people who leave. You do not need to have massive amounts of information points for this, or be a large company. Instead, it is OK to have just a few data points, spread out over time. You can then look at this information over time, and learn from it in order to make better decisions.
What is the tangible value of investing in People Analytics?
Reaping a high return on investment
People Analytics has a high return on investment (ROI). You can make better decisions about allocating resources and understanding, retaining, and getting the most out of your talent. For example, recruiting great people in today’s world is taking a lot of time and costing a lot of money. By looking at information about your current employees, you can understand the kind of people you want to recruit in the future. You could identify talent or skill gaps in your company and prepare for them. This can save a lot of time and money.
Imagine the executives at a company have a retention target. You could use People Analytics to demonstrate to your CEO why people are leaving, and suggest ways to improve it. Analytics allows you to put data behind goals and measure if you are on track to achieve them.
What is an example of a relevant People Analytics goal?
Asking important questions & getting answers
The most important thing is to start with a good question. For example, “are people staying long enough to pay off the investment we are making in them?” or “What is the group of people that I should focus on when I’m recruiting?” Imagine that people spend three years on average at your company. Then, look at this data from different angles, seeing if factors like gender or education affect it. By connecting data points you are already answering questions, starting to identify patterns, and creating an analysis. This applies to almost everything. You can analyze learning and development data, feedback data, survey data on employee satisfaction.
Is there any particular area you think People Analytics is ripe with potential for?
Using data to tell stories that matter
People Analytics allows you to tell stories that matter. It lets you bring what is happening at a company into a clear, cohesive picture. One example is the attrition or leaving rate. Another is diversity. Let’s say you are building products for users. You want the product team to represent the market you are delivering to. To do that, you can run a report on the makeup of team. The report can show if you are equipped with the right diversity of people in each team or department. Around diversity, there is a huge opportunity and potential to collect data and put that to use.
The words “Human Resources” & “Data” are often not thought of in the same sentence. How do they fit together for you?
Creating useful solutions with humans at the centre
Human resources is about people. Doing People Analytics lets you understand the people in your company, and then communicate to them what you have learned. The information you have stored can be very useful to employees and executives. You can can use this information to create tools like dashboards, help centers, and forums. For example, you could create a dashboard where executives and employees see live up-to-date information on People Operations in the company, right down to the newest hire. Even better, you can build these tools together with people at your company. This makes them user-friendly and relevant. Don’t think only about what you as HR think is useful. Instead, ask employees and executives what would be most useful to them, whether questions to answer or tools to build. Get feedback early in this process, and test your first iterations. Effective People Analytics means using data to build for humans, and with humans.
Practically speaking, what would you recommend for companies to get started with People Analytics?
Match the right people, system, question & users — and provide context
First, find people who can analyze data. Internal company employees are often too busy to do this for HR. Therefore, you can hire or train this talent within your own HR team. Build a team with a mix of people, including people who can work with data, statistics, and software. If you do not have this in your budget, you can also contract an outside data analysis service.
Secondly, it is critical to have good tools for storing and displaying data. Spreadsheets are not enough. Use easy, open HR tools. Make sure the tools store data securely. Make sure it also has its own data visualization, or works with outside visual tools (for example, Tableau). Ensure you have processes to consistently update your tools, and your accompanying, company-facing visual dashboard.
Next, as I mentioned before, you need to have a good question. Then, work with your users through interviews, user tests, and iterations to answer that question in a useful way. Lastly, don’t just report back the statistics you find, but benchmark your results against a meaningful backdrop. A finding like “60% of our job-leavers are women” needs the context of industry averages, information on how the rate has changed over time at the company, and the gender makeup of the company’s workforce.
Collectively, the right people, system, question, and user involvement, and benchmarks will come together to create an effective approach to People Analytics.