3 Tips for Using Data-Driven Technology to Augment
Labor Management, Technology , Big DataThe adoption of wearable technology in the supply chain space has accelerated during the past six months, as the COVID-19 pandemic ushered in a new wave of workplace safety concerns. Now, in addition to reducing worker injuries, IoT technology is increasingly used to protect workers from the virus with newly added social distancing and contact-tracing capabilities.Companies utilizing this connected tech now have more data at their fingertips than ever before. When it comes to optimizing this information to keep workers safe from illness and injury, here are three tips to keep in mind:1. Collect meaningful data. When you deploy smart technology in the workplace, be certain the data you are collecting is relevant and actionable. It should help you identify who is at risk, what behaviors are most unsafe, and when high-risk behaviors are occurring. For example: If you are looking to more precisely and reliably monitor worker contacts to reduce the likelihood of spreading COVID-19 in your facility, your tech solution should be collecting data on every single employee interaction, including when they occur and for how long. Or, if you are aiming to identify unsafe postures to reduce ergonomic-related injuries, your data should include details on every high-risk posture performed by each individual worker.Robust data best allows you to uncover the root causes of injuries and potential risks at your facility, while also helping you make proactive decisions to improve worker safety and well being.2. Look for actionable insights. You’ll want to understand and put to use all the data you’ve collected, so an IoT tech solution that offers a powerful and easy-to-use analytics platform is key. By utilizing custom configuration and sorting capabilities, you’ll be able to compare and contrast your data to find actionable insights.Monitoring and checking your team’s data a couple times a week will help you pinpoint risks faster, such as who is performing the most high-risk postures, or what time of day the most frequent close contacts are occurring. Try filtering your data by worker, time/date range, job type, etc., to find the answers to questions such as: During which hours/days/weeks are the most high-risk postures performed? Which employees have the longest contact durations each day? Are any jobs a significant percentage of the risk?3. Follow through with changes and improvements. Once you’re regularly analyzing your data, you’ll begin to spot trends and gain insights into high-risk behaviors, timeframes, and segments of your workforce. Use these insights to make process changes and workplace improvements, or to identify coaching opportunities. Here’s an example of how that might look in action: You compare employees' high-risk posture data by job type and discover that sorters are performing excessive awkward reaching postures. Next, you dig deeper to determine why, and it’s clear these workers are being forced to reach over a sorting belt side rail, causing the unsafe movements. With this actionable insight, you remove the railing and significantly reduce high-risk postures among this group of employees.This was a real-life scenario for a leading home improvement retailer who, with this one improvement, brought their sorters’ high risk postures down from 300-400 per day to only 10-15.A Smarter, Safer WorkplaceBy following these three tips—collect meaningful data, look for actionable insights, and follow through with changes and improvements—you’ll get the most return on investment from wearable tech and the rich data it provides. As you increase your worker safety, injury rates will go down and workers’ compensation claims costs will follow. Furthermore, employee retention and productivity will go up, as workers stay healthy and gain confidence by working smarter and safer.
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