09
Employee safety and wellness are critical areas of any HR team’s work. Intelligent, data-driven HR is about using data and analytics to better manage employee safety, improve working conditions for staff, and boost employee wellbeing and wellness. Technology, particularly sensors, has helped to make the work environment safer for a long time now – including smoke alarms, gas sensors, security and entry systems etc – but the emergence of big data, and especially the Internet of Things (IoT), has taken this to a completely new level. A big part of intelligent employee safety and wellbeing is about humans and machines working together. It is incredibly powerful when workplace systems are aware of the people in the workplace – what they are doing, how they are performing and how they are feeling – and this is perhaps one of the main driving forces in making our workplaces safer and our employees happier. We will see examples of humans and technology working together throughout this chapter. In particular, this chapter will explore how employee safety is improving all the time thanks to data and analytics technology, as well as ways in which companies can better look after their employees’ physical and mental wellness. I will also take a look at some of the main pitfalls concerning data-driven employee safety and wellness, particularly the need to protect employees’ health data.
Improving employee safety with data and analytics
I believe that making sure people are safe at work is a critically important role of big data. Obviously, there is a sliding scale of data-related technology, from completely automated robotics-driven factories at one end of the scale to the more realistic (for most businesses, at least) end of the scale where sensors and other technology are deployed as part of a safety programme. This chapter assumes that your business sits at the latter end of the scale.
Embracing technology, not abdicating responsibility to technology
I am not talking about companies relinquishing all responsibility for employee safety over to machines. There was an interesting story in 2016 about how participants in a Georgia Tech study were found to trust safety robots over their own common sense, even when it was obvious the robot was leading them into a dangerous situation.1 In the experiment, people were guided to a room by a clearly faulty robot; it either took them via an obviously inefficient route to the room in question or broke down in the process – all of which was set up by the researcher. Once the participants were settled in the room, the smoke alarm was triggered and the unreliable robot then guided them through corridors filled with artificial smoke. Here is the scary part: even though the robot was clearly leading people the wrong way, away from emergency exit signs, most people in the study still chose to follow the robot. A few even followed the robot into a dark room blocked by furniture – again all set up by the researcher. People trusted the robot, despite the fact that it had proven itself to be faulty or unreliable at the start of the experiment. This crazy outcome shows how we need to marry technology with human experience and common sense, rather than just turning over all responsibility for our safety to machines.
In today’s data-driven world, almost everything can be measured, and it is now possible for companies to measure a great deal about what their employees are doing and how they are feeling. One of my favourite examples of just how much we can measure comes from the world of healthcare. Cloud-based health monitoring, which is at the cutting edge of modern medicine, enables healthcare professionals to monitor people’s health from afar and provide help or advice when needed. One wearable device developed by Philips Healthcare Informatics, for example, helps elderly people continue to live in their own homes, rather than moving into a care home.2 The device – a small plastic fob that is worn around the neck – contains a tiny mobile phone, motion-sensing software and an accelerometer. Not only can the wearer call for help by pressing a button on the fob, the device itself can alert people if the wearer has fallen over. In systems like this, data are transmitted from the wearable device to the cloud, where analytics programs pore through the data looking for signs of concern and alerting medical professionals when needed. Wearable devices can even detect subtle changes, like a deterioration in the wearer’s gait, which may be a cause for concern and require therapy. They can also seamlessly track blood pressure, heart rate, blood sugar levels, blood oxygen levels and much more. As we will see in this chapter, this kind of wearable technology can play a huge role in employee safety and wellbeing, and the technology is advancing all the time.
How the IoT is making workplaces safer
Of course, most employers want their workplaces to be safe environments where no one gets hurt. Yet, workplace accidents and work-related health issues remain a problem. The Health and Safety Executive estimates that, annually in the United Kingdom, an average of more than 600,000 workers are injured in workplace accidents and a further 500,000 suffer ill health believed to be related to their work. It also estimates the total cost of workplace injury and illness to be over £14 billion.3 Much of this cost is borne by the individuals affected, but almost £3 billion is borne directly by employers. The impact of work-related accidents and health problems is huge, not only for the individuals and their families, but also for the employer in question and their reputation. Clearly, something needs to change.
Changing employee behaviour
Today, the IoT is transforming the way we think about and deliver employee safety. One of the challenges in workplace safety is getting employees to change their behaviour in line with existing company safety rules or to adopt new safety initiatives. And this can be particularly helpful in industries or companies that rely on contract or temporary employees, like the construction industry. The IoT helps to encourage employee adoption of safety initiatives by providing much clearer monitoring and insights into safety-related behaviour. IoT devices, particularly wearables but also sensors, now can generate a mountain of real-time data on workplace safety and employee activities. Not only can these data show whether safety rules and initiatives are being properly adopted, they also can lead to insights that help to improve safety programmes in the future. And the more these data improve safety programmes, the greater the employee buy-in and the more likely employees are to adopt new or improved safety initiatives in the future. Crucially, because IoT devices can be used to transmit real-time data for on-the-fly analysis, managers then can be alerted when unsafe practices are taking place and take appropriate action. A couple of examples of this were given in Chapter 4, including the use of video data to detect that an employee was not wearing the appropriate safety gear, prompting a notification to be sent to the employee’s supervisor. Analytics like this can help to significantly reduce workplace accidents and injuries in the future. Indeed, our ability to predict workplace accidents is improving all the time. A few years ago, researchers at Carnegie Mellon University used real-world data to create predictive safety models that had accuracy rates of between 80 and 97 per cent.4 The model, which is now in use at a number of companies, takes workplace safety inspection data and uses these to predict not just the number, but also the location of safety incidents over the next month.
The role of wearables
Throughout this chapter we will see plenty of examples of IoT devices, such as sensors, tracking bands and smart helmets, being used across a variety of industries. Clearly, wearable technology will have a huge impact on the field of employee safety, and the vision of a ‘connected worker’ is starting to become reality in many different industries. The beauty of IoT devices is that they make employees (and their supervisors) more aware of what they are doing and the environment around them, whether that means alerting someone when they are close to over-exerting themselves and need to take a break, or raising the alarm when the proper safety equipment is not being used. This awareness in itself can dramatically improve safety, because more aware workers are likely to behave in a much more safety-conscious manner.
One example of IoT technology in action comes from steel producer North Star BlueScope Steel. The company has been working with IBM to design a safety programme that incorporates IBM Watson’s cognitive computing power and sensors in wrist bands and helmets.5 The programme, called IBM Employee Wellness and Safety Solution, delivers alerts in real time to workers and supervisors in the event that proper safety protocols are not being followed, or when an employee’s physical safety is in question. For example, if the technology detects a worker is not moving and they have an increased heart rate and high temperature, it could mean they may be suffering from exertion or even extreme heat stress, in which case a supervisor could be alerted, or the employee advised to take a break. What is really exciting is the ability not only to monitor individuals in real time, but also to personalize advice and actions to individuals based on what the data are reporting.
Similarly, the Honeywell ‘Connected Worker’ solution, developed in partnership with Intel, uses sensors to gather data on workers’ heart rates, movements and gestures to deliver personalized advice that can help to prevent accidents or injury6 – more on this later in the chapter. The same sort of sensor technology also can be used to monitor the environment in which someone is working. Data can be gathered on temperature, noise levels, humidity, light levels, toxic gases and radiation. Robots can effectively ‘smell’ now, and can use sensors to detect chemical signatures like blood or alcohol in the air. Blanca Lorena Villarreal, a researcher from the Tecnológico de Monterrey in Mexico, has developed an ‘electronic nose’ that can be built into robotic devices.7 And this is not the first time this type of technology has been used. Örebro University in Sweden has developed a ‘Gasbot mobile robot’ that has been used to detect methane leaks in landfill sites. In fact, robots can detect such leaks much faster and more accurately than humans.8 I will look at more examples from different industries later in the chapter but, for now, it is clear that the IoT is the future of employee safety.
Making driving safer
Driving remains one of the most dangerous things humans do, whether it is simply driving to and from work, taking to the road to visit clients or driving machinery as part of their job. One US company has now turned its iris-scanning technology towards making driving safer. Delta ID’s collaboration with Gentex Corporation, known for its rear-view-mirror technology, has resulted in a rear-view mirror that scans the iris of a driver and authenticates that the driver is authorized to drive the vehicle. While this technology is primarily aimed at security for now, it is feasible that this sort of driver-scanning technology incorporated into rear-review mirrors could be used in future to identify when a driver is feeling tired or is even under the influence of alcohol or drugs.9
Driver fatigue is a huge issue and may contribute to up to 20 per cent of road accidents. What is more, road accidents caused by driver fatigue are roughly 50 per cent more likely to result in death or serious injury.10 If your employees are driving vehicles as part of their job, it pays to make sure they are not struggling due to fatigue. And this does not just apply to transportation companies or individual employees taking to the roads in cars (like sales people, for instance). Driver fatigue can be an issue when driving any kind of vehicle. A report by Caterpillar has estimated that operator fatigue is one of the main causes of accidents involving earth-moving equipment, like diggers and bulldozers.11 For those companies in the mining and construction industries, for example, driver fatigue is therefore a key aspect of employee safety.
One Australian company, Seeing Machines, has developed technology designed to tackle driver fatigue by tracking the driver’s eyes.12 The tracking system, designed specifically for vehicles used in the mining industry, incorporates a camera, global positioning system (GPS) and accelerometer. It tracks eye and eyelid movement, such as how often a driver blinks, how long those blinks last and how slowly the eyelids are moving, and it can do all this even if the driver is wearing sunglasses. It can even analyse the position of the driver’s head and whether it has started to drop. When a driver closes their eyes for longer than 1.6 seconds, an alarm is triggered inside the truck – both a noise and a vibration within the seat. Then, if the alarm is triggered for a second time, a dispatcher or supervisor will be contacted, so that they can make contact with the driver via radio. If a third alarm is triggered, the driver would generally be taken off their shift. Speaking to Wired magazine, Seeing Machines CEO Ken Kroeger said the system could reduce ‘fatigue events’ by 70–90 per cent.13 Caterpillar has been so impressed, it is now introducing the technology into some of its mining trucks. Interestingly, the system also can be used to detect when a driver is distracted and taking their eyes off where they should be, again triggering an alarm in the cab.
Seeing Machines is not the only company offering this technology; there are many other devices available for monitoring fatigue and attention, including the Maven Co-Pilot, a headset-style device that measures fatigue and distraction in drivers.14 It is easy to see how this technology has applications far beyond vehicles used in mining and, potentially, it could be integrated into any kind of delivery vehicle, company car, heavy goods vehicle (HGV) or even aeroplane.
Making industrial and manufacturing settings safer
This vision of a connected worker may soon become reality in many industrial and manufacturing settings. Earlier in the chapter I mentioned the Honeywell and Intel ‘Connected Worker’ solution, and I believe this is the sort of wearable technology that will revolutionize employee safety. The technology comprises a number of wearable sensors that gather data on heart rate, breathing, motion, posture and even the presence of toxic gases. All this information is pulled together into a dashboard display that gives supervisors and safety professionals an accurate picture of what employees are experiencing in real time and enables them to respond to dangerous situations and flag potentially unsafe conditions to prevent injury or illness. Of course, most industrial and manufacturing settings involve humans working with machinery. The IoT, particularly sensors, plays a vital role in increasing machine safety and efficiency. Sensors can be used to assess machinery compliance, safety anomalies, machine stoppages (and their causes) and much more – all of which helps companies to better understand what is going on in real time on the floor, better understand the safety risks, accurately pinpoint machinery misuse and reduce safety-related stoppages. This blend of machinery and IT systems is often referred to as the ‘connected enterprise’.15
Despite the fact that technology plays a critical role in most industrial and manufacturing settings, safety management traditionally has relied on rather dated methods and information, often based on what has happened in the past or at other locations. The ability to gather real-time insights therefore makes a huge difference. One way in which data are proving particularly valuable is in identifying discrepancies between the way machinery and safety systems are designed to be used, and the way in which they are actually used in practice. For example, data may highlight that emergency stop buttons on machines are not in fact being used in emergencies, but to clear routine jams. This misuse could reduce the efficiency of the safety system and cause it to fail when it is really needed, thus putting people at risk. Insights like this highlight when additional safety training is needed for employees. Without understanding what is really going on and why, those in charge of ensuring worker safety are effectively working in the dark. Data and analytics provide the guiding light. Plus, with the predictive capabilities of analytics, machine safety systems can predict risk through a detailed risk calculator.
Making construction sites safer
Construction sites present many safety hazards for employees, and construction workers can experience a number of work-related health problems, such as exposure to hazardous substances, vibrations and noise. One start-up company, SmartSite, has developed a hardware and software solution to help. The system, which is currently being trialled with construction companies, uses sensors to measure noise levels, ultraviolet light levels and air quality to tell bosses when workers may be at risk. The aim is to accurately measure actual conditions on the ground at construction sites instead of identifying risks based on previous jobs.
Thanks to IoT technology, even hard hats are now being made ‘smart’. SmartCap have produced hard hats fitted with sensors that detect (with almost 95 per cent accuracy) fatigue in those operating machinery. Originally developed for truck drivers, the hats are already being used by construction company BAM Nuttall on rail projects in Wales, with roll-outs expected in Scotland soon.16
Another construction company, VINCI Construction UK, has been using ViSafe sensor technology to gather real-time data on how construction workers move as they do their jobs. These data have proved that one particular mortar board (those boards with a handle underneath used by bricklayers) actually reduced the risk of bricklayers suffering lower back injury. The EcoSpot mortar board system reduced the amount of time workers spent with their backs bent more than 20 degrees by as much as 85 per cent. Not only that, but the company found the EcoSpot system led to a 17 per cent increase in productivity, ie the number of bricks laid per minute.17
Keeping people safe in the heat
In recent years, the United Kingdom has experienced a number of heatwaves with temperatures above 30°C. That may not seem high to those who work in places like the Middle East or the Australian outback, but for the United Kingdom it is extreme! Even sitting at my desk writing can feel like an exertion in this level of heat. But particularly for those who work outdoors or do very physical jobs, extreme heat can present serious risks.
Engineering company Laing O’Rourke, which operates in the Australian outback, uses IoT technology to keep its employees safe in such extreme conditions.18 The company uses a smart hard hat fitted with a sweatband sensor that measures the heart rate and temperature of wearers, as well as the external temperature around them. The data are uploaded from the hard hats to the cloud, where they are analysed to look for patterns that suggest a worker might be at risk of heatstroke. If an employee is in danger, the hard hat itself receives a sound and vibration alarm that alerts the worker to take a break in the shade. This technology is clearly applicable beyond outback conditions, and heat sensors could be used in a number of different settings, ranging from fruit farms or vineyards to construction sites.
Researchers at the University of California-Berkeley have now gone a step further to develop a device that can be easily incorporated into wristbands and headbands to monitor sweat chemicals, which could be a far more accurate way to predict when someone may be at risk of dehydration, heat exhaustion etc. The sensors detect sweat but, critically, adjust the reading according to changes in skin temperature. These signals are then uploaded to an accompanying app that can give real-time information on dehydration levels.19
Looking at the link between connectivity, employee safety and productivity
While it is clear that increased connectivity of both workers and machines can help to dramatically increase safety, it can also significantly boost productivity. Think about the factory machinery example outlined earlier in the chapter: if machinery or safety systems are not being used in the way intended, this can lead to earlier failure or extended shutdown for unscheduled maintenance, which obviously impacts on productivity. Detailed insights on safety-related issues can improve troubleshooting and resolve downtime issues much faster, and even prevent them from happening in the first place through improved staff training. The same is true of connected individual workers. We have already seen in this chapter how connectivity helped to improve bricklayers’ productivity by 17 per cent. Other studies have shown that connected workers are typically 8–9 per cent more productive, and that having connected workers actually reduces costs by around 8 per cent.20 With benefits like these, it is no surprise a study of around 500 manufacturing bosses found that 85 per cent believed connected workers will be commonplace in their operations by 2020.21
Improving employee wellbeing and wellness
As well as ensuring working environments are safe, sensors are also commonly used to ensure workplaces are pleasant environments to be in – think temperature sensors, windows that open automatically to control ventilation etc. This sort of technology is commonplace in many organizations, so, in this section, I am going to look at some of the newer or more up-and-coming ways in which companies are looking after their employees. Much of this focuses on employee health or wellness, and how many organizations, such as BP, are providing data-driven employee wellness programmes.
Why is wellness important?
It makes sense that the healthier employees are, the happier they are and, therefore, the better they perform for the company. Some of the most common work-related illnesses include mental health issues (like stress and anxiety) and musculoskeletal problems (such as back pain), and these health issues are costing companies increasingly more through employee absence and lost productivity. One report shows workplace absence currently costs the UK economy £18 billion a year, and this is predicted to rise to £21 billion by 2020.22 In this landscape, wellness programmes are becoming increasingly more popular among employers, in an effort to encourage employees to be healthier and, therefore, happier. But such programmes are not just about reducing absence, wellness programmes also have been shown to boost employee engagement and retention.23
Data and analytics are beginning to play a key role in improving the effectiveness of wellness programmes and encouraging employees to engage with such programmes. Wearable fitness tracking bands such as the Fitbit brand are increasingly being offered to employees either for free or at a subsidized rate in order to help them monitor their activity levels and encourage them to be more active. There is more on this later in the chapter.
At the organizational level, analytics allow employers to analyse data on their wellness programmes – such as data from wearable devices or responses to pulse surveys to help them better design and manage aspects of employee wellness. For example, if pulse surveys highlight that one aspect of a wellness programme has a take-up that is lower than expected, the company can either modify and improve that part of the programme or replace it with something new.
Looking after your employees’ mental health
As we have seen throughout this book, artificial intelligence (AI) is also playing an increasing role, particularly when it comes to employees’ mental health. In Chapter 8 we looked in detail at the use of pulse surveys and sentiment analysis to identify how employees are feeling. This sort of technology, particularly sentiment analysis, can even pinpoint signs of stress, depression or anxiety in employees. With more than 400,000 people suffering from stress-related illnesses that stem directly from work every year, stress should be an especially big concern for employers.24 According to the Health and Safety Executive, in 2015–16, stress was responsible for 37 per cent of all work-related illness cases and 45 per cent of all working days lost due to illness.25 Digital health company BioBeats recently conducted a trial with BNP Paribas on the use of data to help employees better manage their health and wellbeing through personalized, AI-based recommendations. As part of the trial, 560 BNP Paribas employees wore a Microsoft Band 2 that continuously gathered biometric data and transmitted those data for analysis by BioBeat’s AI engine. According to the findings, the programme was able to identify perceived and actual stress, and links between stress and ruminators.26
Improving physical health with the IoT
As well as identifying when employees are in physical danger, or suffering from stress or anxiety, technology is now able to help employees lead healthier, more active lives. The IoT has played a huge role in this – for example, how many people do you know who wear a fitness tracking band or use an app on their phone to track their activity or number of steps a day? The answer is a lot, I bet.
Reducing the risk of back problems
I was shocked to learn that 12.5 per cent of all sick days in the United Kingdom are down to back pain.27 Increasingly, this can be attributed to how many of us sit down at a desk all day. We are simply not designed to sit down for seven hours a day, even if we do sit correctly with perfect posture the whole time. Most of us struggle to maintain great posture all day; come to think of it, most of us are not even aware of our posture a lot of the time. Yet poor posture can have serious long-term health effects and should not be overlooked.
While workstation risk assessments and ergonomic products like back supports and foot rests go some way towards protecting employees against back problems, it is clear that more could be done. Part of the solution may lie in the IoT. We have already seen many examples of how products and people are becoming increasingly connected, now even your office chair has undergone an IoT makeover. Even with a super fancy ergonomic chair, it is still possible to sit badly because we are generally not aware of our posture while we are busy working. With this in mind, the Axia Smart Chair, produced by BMA Ergonomics, has been designed to monitor your posture as you sit at your desk and provide feedback where appropriate on how to improve your posture to avoid back problems.28 Sensors in the seat register the user’s posture and make them aware when they are sitting incorrectly; vibrations let the user know when they have been sitting down too long in a bad position. A ‘smart label’ also enables users to actually see their current posture or how they have been sitting for the last hour, and accompanying software provides practical advice to help workers improve their posture. The idea is that, by increasing awareness of posture throughout the day, employees can modify their posture as needed and avoid back problems in the future.
The role of fitness tracking bands
The IoT is also impacting on employee health and wellness in more obvious ways: wearable fitness tracking bands. These are increasingly becoming part of corporate wellness programmes around the world, and Fitbit, one of the largest fitness tracking providers in the world, counts BP and Bank of America among its corporate clients. Target has given over 300,000 Fitbit bands to its employees, IBM gave out 40,000 Fitbits to staff over a period of two years and Barclays has given 75,000 employees subsidized Fitbit trackers.29 Fitbit’s corporate wellness offering now includes a suite of tools and resources for employers, including dashboards to monitor how employees are doing. And the trackers themselves do far more than encouraging staff to get up and walk more; Fitbit claims they also increase engagement in wellness programmes and improve health outcomes. And, particularly in the United States, these trackers are also being used to reduce health insurance costs, by allowing employers to leverage employee health and activity data to negotiate with insurers. As part of BP’s ‘Million Step Challenge’, the company gives employees a Fitbit and challenges them to walk a million steps in one year to earn a discount off their insurance premiums for the following year. Reportedly, the programme has an impressive participation rate of 75 per cent. Furthermore, 81 per cent of employees in 2015 reached the 1 million step target.30 This is not to say that you must rush out and buy thousands of fitness trackers for your staff, but it does point to how employees are willing to engage with IoT-enabled wellness programmes. As increasingly more people are investing in their own fitness tracking bands, and as mobile apps are increasingly offering similar capabilities to track activity and other health metrics, it is possible wellness programmes could leverage these developments to their advantage.
Predicting health issues in the future
The next logical step in IoT-enabled employee wellness is using predictive analytics to pre-empt health conditions. Intel’s COVALENCE Health Analytics Platform combines wearable technology with predictive analytics to help companies identify early warning signs of illness and take action.31 The platform uses data gathered from fitness trackers (such as heart rate, activity levels, sleep patterns etc), as well as historical health data and self-reported health data. By analysing these data, the system can pinpoint trends and flag up warning signs of potential health issues or lack of progress towards an employee’s health goals.32 Employees who are identified as being at risk then can be helped with tailored support and coaching in order to help to delay or eliminate altogether the onset of health issues.
Looking at the potential downsides of data-driven employee safety and wellness
It is clear that we can monitor an increasing number of data about employees’ activities and health. The question is, perhaps, how much monitoring is too much? Particularly when it comes to employees’ health data, these are obviously highly sensitive and personal data and employers need to tread carefully and act in an open and transparent way (see Chapter 6).
Health data are valuable data
Shockingly, health data are reportedly 10 times more valuable on the black market than credit card data.33 In 2014, one of the largest healthcare providers in the United States, Community Health Systems Inc, was targeted by hackers who stole personal information on 4.5 million patients;34 and this is in line with a wider trend of cyber criminals targeting health data. Large batches of personal health data are incredibly valuable because they can be used for medical fraud. And because medical fraud is typically slower to detect than, say, banking fraud, that makes health data far more tempting prospects for criminals. Plus, health data are frequently not as well protected as credit card data or other obvious sources of fraud, which makes them an easier target. While this is more of an issue for healthcare providers who are often operating on old legacy computer systems in desperate need of an update – as the 2017 WannaCry malware attack on the UK National Health Service shows35 – it still needs to be considered by employers who are working with employee health data. It is imperative you guard these valuable employee data with the same level of protection as you would your customer data.
How much should employers know about their employees?
We know that tracking employee data can have a whiff of Big Brother about it, and sometimes employee scepticism is well warranted. One 2016 article showed how employers are already using data to identify when employees might be pregnant or considering becoming pregnant before those employees were ready to divulge the news to their employer.36 Not only is this an invasion of privacy, it also opens up the potential for employers to slyly discriminate against pregnant or soon-to-be pregnant women (such as overlooking them for promotion) before they have been officially informed of the pregnancy. The article describes how healthcare analytics company Castlight Health, which works with employers like Walmart, has the ability to mine workers’ health data and identify particular segments of the employee population according to the data. ‘We can tell who’s at risk for being diagnosed with diabetes, who’s considering pregnancy, who may need back surgery’, Castlight senior product manager Alka Tandon told Fortune.37 And while Castlight makes it clear it does not disclose the names of individual employees in the data it shares with clients (it only shares top-line numbers), it is easy to see how employers potentially could still work out who the data are referring to. Or, if the data highlighted that, say, 20 per cent of female employees were considering starting a family, the employer might begin to discriminate against women in its hiring practices.
There is also the issue that employees may simply be uncomfortable with their bosses knowing how fit (or not) they are, or their employer having the ability to identify when they might be at risk of health issues. Back in 2012, Ohio healthcare provider The Cleveland Clinical announced that employees who were overweight or at risk in other ways (such as being a smoker) and who did not join the company wellness programme would have to pay more for their health insurance – over 20 per cent more, in fact. And those who did join the programme but did not meet health targets set by programme administrators for them also saw their premiums rise by almost 10 per cent. Pennsylvania State University faced a similar controversy when it tried to get employees to undergo mandatory health check-ups and fill out a health risk questionnaire that asked them whether they had recently been divorced or were planning to become pregnant. Under the plan, anyone who refused to fill in the questionnaire would be fined a whopping US $100 per month. The school was forced to abandon the plan after significant staff protest.
Navigating these challenges
The challenge for HR teams is therefore to encourage participation in wellness programmes and use data to help employees live healthier lives (which, in turn, financially benefits the company) without making employees uncomfortable. BP’s 1 million steps challenge gave bosses access only to aggregated data, not the ability to drill down into individual activities, and that is a smart way of doing it. Crucially, BP’s programme is also voluntary. When participation in wellness programmes becomes mandatory, or when employers feel their health data may be used to punish them in some way, buy-in for wellness programmes is reduced. In addition, as we saw in Chapter 6, when you offer employees an incentive in return for their data, they are far more likely to get on board, and that is exactly what BP did when it offered lower insurance premiums to those who hit a million steps in a year. There are of course many non-data ways in which to facilitate employee wellbeing, such as providing on-site exercise facilities or discounted (or free) gym membership and serving up healthy food in the canteen. Data in no way replace good practice like this. But, used well, data and analytics can give HR teams precious insights into how to manage and improve employee wellbeing and safety.
Key takeaways
I think employee safety and wellbeing comprise one of the most exciting and fast-developing areas in relation to data and analytics, and I hope this chapter has inspired you to use data to improve your own safety measures and wellness programmes. Key points from this chapter are:
· Over half a million UK workers are injured in workplace accidents each year, and a further half a million suffer ill health believed to be related to their work.
· Data-related technology, especially wearable technology and sensors, is making workplaces safer and more comfortable places to be, ranging from construction sites and factories to regular offices.
· Because IoT devices can transmit real-time data for on-the-fly analysis, managers can be alerted when unsafe practices are taking place and take appropriate action.
· While increased connectivity of both workers and machines can help to dramatically increase safety, it can also significantly boost productivity.
· Wellness programmes are becoming increasingly more popular among employers, in an effort to encourage employees to be healthier and, therefore, happier.
· Wearable fitness tracking bands such as Fitbits are increasingly being offered to employees either for free or at a subsidized rate.
· It is important to take proper precautions to protect employee health and wellness data. Also, remember that employees may be uncomfortable with their bosses knowing how fit (or not) they are.
· The challenge for HR teams is to encourage participation in wellness programmes and use data to help employees live healthier lives without making those employees feel uncomfortable.
In the next chapter I move from making sure employees are safe and healthy to giving them the opportunities to grow, learn and develop in their careers, with a little help from data and analytics, of course.
Endnotes
1 Alphr [accessed 23 October 2017] People Trust Safety Robots over Common Sense, Even When It Puts Them in Danger [Online] http://www.alphr.com/robotics/1002840/people-trust-safety-robots-over-common-sense-even-when-it-puts-them-in-danger
2 New Scientist (2015) [accessed 31 January 2018] How Cloud-connected Sensors will Provide 24/7 Healthcare [Online] https://www.newscientist.com/article/dn28342-the-internet-of-caring-things/
3 Health and Safety Executive [accessed 23 October 2017] Costs to Great Britain of Workplace Injuries and New Cases of Work-related Ill Health – 2015/16 [Online] http://www.hse.gov.uk/statistics/cost.htm
4 Schultz, G (2013) [accessed 23 October 2017] The Era of Big Data Analytics in Safety [Online] http://www.naylornetwork.com/ngc-safetyMatters/articles/index.asp?aid=241739&issueID=38258
5 O’Connor, C (2016) [accessed 23 October 2017] Improving Worker Safety with Wearables [Online] https://www.ibm.com/blogs/internet-of-things/worker-safety-and-wearables
6 Honeywell (2015) [accessed 23 October 2017] Honeywell & Intel Demonstrate Wearable IoT Connected Safety Solutions for Industrial Workers & First Responders [Online] https://www.honeywell.com/newsroom/news/2015/11/honeywell-intel-demonstrate-wearable-iot-connected-safety-solutions-for-industrial-workers-first-responders
7 Science Daily (2014) [accessed 23 October 2017] Electronic Nose Could Aid in Rescue Missions [Online] http://www.sciencedaily.com/releases/2014/07/140723110403.htm
8 Gasbot [accessed 31 January 2018] The Gasbot Project [Online] http://www.aass.oru.se/Research/mro/gasbot/index.html
9 Cision PR Newswire (2017) [accessed 31 January 2018] Delta ID Introduces Iris Scanning Technology for In-car Biometrics and Secure Autonomous Driving at CES 2017 [Online] https://www.prnewswire.com/news-releases/delta-id-introduces-iris-scanning-technology-for-in-car-biometrics-and-secure-autonomous-driving-at-ces-2017–300386174.html
10 RoSPA [accessed 23 October 2017] Driver Fatigue and Road Accidents [Online] https://www.rospa.com/road-safety/advice/drivers/fatigue/road-accidents
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