When wearables were first introduced to the workplace, they became the star technology in corporate wellness programs. However, the use of wearables in the workplace now extends far beyond just tracking the health and fitness of employees. Take this example from Bank of America.
A few years ago, the banking corporation used data gathered from sociometric badges (wearable devices equipped with sensors) to discover something interesting about their call center employees: those with the fastest “average call handling time” were also the most social.
The company then decided to introduce team-wide coffee breaks in place of individually scheduled ones. The result was a $15 million increase in annual productivity.
As this story shows, wearables such as smartwatches, fitness trackers and sociometric badges, can yield some definitively actionable–and revenue-generating–insights for employers. HR must be prepared to use wearables as another data source to be contextualized in order to solve workforce challenges such as employee engagement, retention, innovation and more.
To unlock the power of wearables data, you need to first define what questions you will ask, and what business outcome you need to address. Otherwise, you will end up asking the wrong questions, getting the wrong information, and generally missing the mark. Follow these steps to get the most out of your wearables data:
Step 1: Separate fact from fiction
Let’s say the Marketing department at your company is having an issue with campaign execution. They’re failing to meet timelines and delivering sub-par work. Everyone has several hypotheses about the cause of the problem, from poor engagement to a disorganized manager, but where do you start your investigation?
Before even mining wearables for insights, start by jotting down all your concrete observations about the issue and ask yourself related questions: “Are people doing overtime? When did they start slipping on the work?” This will help you move towards an investigation based on pure, unbiased perception.
Step 2: Look at the business impact
Go back to your notes from Step 1 and highlight anything to do with the overall business goals (consider areas such as revenue, customer satisfaction, or growth). This can take a bit of time, but it is worth the effort: With the right questions, you can avoid analysis paralysis. Some analytics platforms even have HR best practice questions baked into the information architecture to help guide you through this step.
For the campaign scenario described above, a good question that addresses the business impact is: “How does the allocation of individuals to multiple teams impact key corporate marketing campaigns?”
Step 3: Set your scope of work
Focus your analysis on the group most impacted by your key questions. You also need to determine what is the appropriate time period to investigate. For example, if the campaigns have been slipping over the six months, look at a timeframe that goes back at least a year and a half.
Once you understand the who and when, then you can dig into the why of situations. For our scenario, good questions are: “How often are people on multiple teams? Which roles are spread across multiple teams? How many different teams do people have to focus on?” This will help you select the right metrics to investigate. Project contribution history, meeting patterns, and employee churn details will all help you decipher why campaigns are being missed.
Step 4: Pick the right data sources
Select the data sources that will give you the information you need for this particular issue. For example, if information about communication patterns is important, a wearable such as a sociometric badge can be a valuable data source.
Be warned, however, that analysis solely from one source will not provide a clear picture of how workforce trends are impacting business outcomes. To really glean actionable insight from wearables data, you need to combine it with other information, such as employee absence rates and engagement data from your HR management and performance management systems, business outcome data from your ERP, and team communication patterns from a sociometric badge. From here, you can bring all that information into a single system that supports broad, ad-hoc analysis.
Step 5: Ask more questions of the data
If you see any red flags, drill deeper into the data to determine what is causing the problem: “Do people feel they have a connection to the business? Are our experts receiving adequate learning opportunities and recognition?”
True analysis requires the ability to combine different metrics, different statistical processes, and different ways to share and display the data so that “analytic stories” – ones that answer critical business questions – can be told.
Step 6: Introduce your solution
Now it’s time to take action, whether it’s improving compensation, or changing the structure of teams.
When dealing with people, you are working with an eco-system of choice, which can be a messy situation: the reality is if you do something, the results will only happen for a segment of your population. Therefore, it is crucial to ensure whatever solution you develop is related to the appropriate “who” uncovered in step three.
When wearables are combined with solid data investigation premise and multi-dimensional analysis, HR can gain powerful and actionable insights that help move the needle on workforce and business outcomes.
