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Workplace analytics: surveillance or saviour?

Could ever-more sophisticated systems transform how businesses measure and improve their productivity through close analysis of their employees’ work patterns?

So many business models are now dependent on processing value from data that it has become a commercial imperative to refine the productivity of knowledge workers. Typically, however, organisations have struggled to increase the productivity of employees whose jobs consist primarily of knowledge interactions with colleagues, customers and business partners, and of complex decision-making based on understanding and judgement.

These employees constitute, as management consultancy McKinsey & Co has pointed out, a large and growing part of the workforce in developed nations. Raising their productivity offers a big economic opportunity.

Interest in methods for boosting knowledge-worker productivity date back (at least) to management guru Peter Drucker’s 1999 assertion that this is “the biggest of the 21st-century management challenges... In no other way can developed countries hope to maintain themselves, let alone maintain their leadership and standards of living”.

This becomes a predicament when studies suggest many knowledge workers seem to be working longer hours than they used to, with few discernible performance gains. A 2016 report by the Smith Institute that looked at employees’ perspectives on productivity found 27 per cent of those polled thought their productivity had stalled or declined over the previous two years, despite having worked longer hours.

Expenditure on ‘productivity-boosting’ IT over the same period has been maintained, which presents something of a productivity paradox. A number of studies have tried to explain it; at a macro scale, it is characterised by corporate ‘power users’ who clamour for the latest computer kit, only to have their productivity dip irrecoverably until they get familiar with new systems.

However, the problem with knowledge work is that it’s difficult to capture, measure and quantify suitable metrics that might indicate how the quality of this kind of work could be improved. The arrival of workplace performance analytics software might now, however, be the way to address such blind spots.

Put simply, workplace analytics systems integrate with wireless communications available in most workplaces – and increasingly with enterprise applications that knowledge workers use on a regular basis – to obtain data about their actions, interactions and other work habits.

The software collates this data to show patterns of behaviour. These patterns can then reveal inefficiencies or other work process misalignments that may be fixed. The objective is to aggregate efficiency gains from individuals or groups to achieve overall improvements in the organisation’s performance.

The potential scope of workplace analytics is broad. It can also take in policies and procedures, workspace planning and ergonomics, and self-quantification. The workplace analytics ethos espouses inclusiveness and openness to its findings. After all, one of its motivations is to provide individual employees with validated metrics they can use to raise their professional game, and thus provide evidence in support of career advancement.

However, individual workers’ reactions to the methods and objectives of workplace analytics can be mixed. To mature employees it may feel like previous time-and-motion studies intended to root out shortcomings in skills or get hard workers to work even harder.

There is certainly a debate to be had about the ethics of what’s been called a “new frontier of staff surveillance”, but this has not deterred a range of software vendors such as Kronos, Sage People, Tao Leadership, Engagement Multiplier, WPA and, more recently, Microsoft.

Yet it’s an occupational reality that analytics-based employee assessment already operates inside most organisations. Furthermore, employers are obliged to monitor their workers’ behaviour during working hours, make analytics-based monitoring part of their duty of governance (with GDPR looming), and use all lawful means at their disposal to ensure they have the right people working to deliver the organisation’s mission.

“Many organisations have found it helpful to put a ‘workplace standards definitions’ document in place that clearly identifies roles, responsibilities and expectations, and also defines metadata inputs that measure team members against standards,” says Todd Marthaler, analytics consultant at Calabrio. Workplace analytics builds on this to provide managers “with an enterprise-level dashboard of time and activity that offers a high-level view into each team member’s workflow. This includes everything from multi-channel interactions to desktop activities to offline work – all of which can provide insights critical to the business.”

At its core, workplace analytics systems monitor and analyse employees’ activities in relation to their job roles, the IT tools they require, and how they use them to get their jobs done. The general field is sometimes referred to as ‘workforce analytics’, where emphasis focuses more on personnel attributes and team dynamics.

Analytical disciplines are also extended to the issue of workspace analytics. This is where people in work environments such as offices are monitored and analysed by sensors and smart tags to find out if alternative interior layouts could lead to more efficient use of floor space, or result in work conditions that better promote individual and team productivity.

Workplace analytics are not strictly defined disciplines, and proprietary solutions use branded terminology to describe products and procedures. Industry standard-setter Microsoft has just entered the sector with an add-on to Office 365, and this could be a sign that some standardisation is coming.

In an increasingly digitised world, workforce analytics “provides decision-making and insight tools to take advantage of the many processes that affect employees”, says Neil Pickering, customer and industry insight manager at Kronos. With the means available to extract data from employee actions and behaviours, in ways comparable to scrutinising ‘big data’ sets for commercial opportunities, it seems inevitable that many employers will want to use data in an employee-oriented way. Pickering adds: “From hiring to employee scheduling to work activities and time tracking – these data sets provide insights into the activities and challenges an employee faces, and also inform their supervisors’ decisions.”

Despite relentless deployment of IT, performance management is under intense scrutiny because growth in productivity remains an ongoing challenge, agrees Paul Burrin, CMO at Sage People. “For functionally-specific roles, like sales executives or call-centre operatives, key metrics can be determined by benchmarking individual performance to a defined set of quantifiable business outcomes – such as profit, leads generated and customers retained.” But for other job functions this can be more challenging, Burrin acknowledges.

Attitudes toward workplace analytics are also influenced by the popularity of personal self-quantification technologies, such as fitness trackers, as a segment of the workforce see professional performance improvements as a personal quest. Ryan Fuller, CEO and co-founder of workplace analytics firm VoloMetrix, predicted shortly before his company was bought by Microsoft that “the self-quantification trend will evolve beyond physical health to encompass all aspects of people’s daily lives – including time spent at work.” ABI Research reckons that around 17 per cent of the 202 million wearable devices shipped in 2016 were given to enterprise employees.

Fuller sloganises his message as ‘Improving the way work works’; but to do that, employers will have to acquire an understanding of what is happening ‘on the factory floor’, and appreciate that individual performance may be governed by factors that rest beyond an employee’s personal control. Workplace analytics aims to both identify and address methods that are inefficient, and identify work practices that could enable people to get more done to a higher agreed standard, and in some cases, analyse work environments for factors that may have a bearing on performance. In order to get at determinants that impact performance, it is key to quantify the physical workplace itself.

Workplace analytics raises questions that many employer organisations have not thought about, let alone acted upon, even as part of staff appraisal programmes. They ask what inhibits knowledge workers from working optimally, assuming that it is not some self-imposed reluctance borne of grievance.

To the critical mind, some underlying factors for performance deficits are readily evident. At a basic level, there’s the question of keyboard skills and ‘computer literacy’. Most recruiters assume job applicants have basic keyboard skills, and are ‘familiar with’ standard desktop applications. Yet how many recruiters check an applicant’s actual IT proficiency before or after they are hired?

The use of employer communications tools is another area where analytics should reveal efficiency snarl-ups. Many workers now have unified communications platforms that provide email, video conferencing, instant messaging and other real-time collaboration tools. Yet many users default to email even when it is the least efficient medium for a particular task.

By a similar token, how often would a voice call be more efficient than an email exchange? If people make fewer workday voice calls, is this because they have concerns about affecting others’ workloads, slowed by responding to emails about matters that could have been sorted in a 15-second phone call? These kinds of undiagnosed technology tangles are also what workplace analytics looks to uncover.

“Technological solutions are excellent at recording people in places, but not whether the person in the space was happy, frustrated, uncomfortable or successfully completed the task,” explains Graham Bird, workspace director at workplace consultancy Where We Work. “We know from experience that people generally divide their day into half-hour sessions. We know this because we have run continuous 30-minute observational studies alongside under-desk sensor systems, and the utilisation results were within 2 per cent of each other. The observational study, however, recorded what was happening at the desk, the breakout point, the meeting room, etc, from which we could ascertain the success of the given spaces.”

One further important development for workplace analytics is the availability of in-building wireless communications that help capture and relay data from individual sources, such as people and workspaces. Most modernised workspaces already bristle with wireless connectivity that can be used by workplace analytics’ applications.

Newer iterations of the 802.11 Wi-Fi standard promise better performance and make it more feasible for network operators to add subnets dedicated to specific applications. “It will become the norm to have space/people monitoring devices in smart buildings,” says Bird. “Useful utilisation data is readily available through existing security access systems, desk and room booking systems, intelligent infrastructure systems and suchlike. Along with these, more specific utilisation monitoring tools such as sensors, thermal-imaging cameras and RFID tags are becoming commonplace.”

One company is using wearable social sensing technology to analyse how people communicate in real time. Haider Imam, co-founder of Tao Leadership, says: “Not only can we determine the characteristics that make up teams and companies, we can also describe those characteristics mathematically.”

Tao Leadership’s ‘sociometric badges’ are based on technology developed by MIT Media Lab spin-off Humanyze. “The GEM badge is designed to measure face-to-face interactions between employees with an infrared transceiver, Bluetooth, two microphones, and two accelerometers,” explains Imam. “GEM badges are used to learn about social interactions from sensory data, and then model structure and dynamics of employee social networks in workplaces. No audio is recorded, all data is anonymised and confidential. What we are interested in is the macro picture – trends in team, divisional, and organisational behaviour. The secret AI sauce is in proprietary software algorithms the recorded badge data is fed through.”

Some of these technologies may raise hackles among employees suspicious of being tracked as they go about their day, but workplace analytics moves into a different gear when it uses data generated by workers doing their designated tasks using standard business applications.

A sign, perhaps, of the shape of things to come as signalled by Microsoft’s just-launched workplace analytics add-on to its flagship Office 365 enterprise solution.

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