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Redefine How Workers Need to Work

We’re all in agreement that human work is changing, thanks, in part, to machines joining the workforce. The new mantra...

5 Minutes Read

We’re all in agreement that human work is changing, thanks, in part, to machines joining the workforce. The new mantra is: wave goodbye to rote work and welcome knowledge work with open arms. But what we don’t seem to be in agreement on is that the way humans work needs to change too.

Take the most famous, well-recognized working structure today: the 9-5. It was designed well over a century ago during the industrial revolution to maximise output of humans doing machine-work. According to the Bureau of labour statistics the average American still works 8.8 hours a day.

In 1930 John Maynard Keynes predicted that technology would have advanced enough that we could work a 15-hour work week. This is pretty achievable today, but instead what’s happened is we’re so hooked on that precious eight-hours-a-day structure that we’re inventing nonsense work to fill up the hours. As we become more efficient in line with technological advancements, we’re punishing ourselves by filling our newly freed up time with unnecessary processes that drive us mad. Daydream, if you will, about the last time you had to fill out an IT support query or get your expenses approved. Turns into a nightmare pretty quickly, no? (Check out David Graeber for more on the theory of bullsh*t work).

Times are-a-changing, and these structures are starting to break down – but progress is slow. The 9-5 is so entrenched, that stigmas attached to arriving late, leaving early and only taking 1 hour for lunch are still forcing workers into unproductive hours of slouching over glaring screens and scrolling through Facebook feeds. Are modern changes in working structures even making us better off? Advances in communication technology might be shattering the 9-5, but they’re replacing it with 24/7 working hours!

My recent research reveals the secret to breaking down outdated, unhealthy working structures and, in the process, increasing worker productivity, engagement and retention. The answer lies in better human understanding: employee needs, their responses to activities they carry out, how they get their best work done. How do we achieve this improved understanding? With the ethical collection of employee data. What we call, Talent Intelligence.

Organisations can achieve deeper levels of human understanding, such as engagement, intention and sentiment by monitoring simple behaviours in the workplace. For example:

  • Activity tracking provides insight into engagement, such as Microsoft MyAnalytics and Do.com, which show how employees split their time across tasks.
  • Behavioral monitoring technology like the Riff Learning videoconferencing platform reveal detailed emotional responses to collaboration, such as levels of concentration, attention and alertness.
  • Organizational Network Analysis (ONA) - powered by technology such as Humanyze, which produces physical badges embedded with infrared, voice and GPS sensors - to monitor employee interaction behaviour.
  • Organisations can understand worker contentment by accessing data that employees publish (e.g. LinkedIn, Glassdoor or Social Media) or in engagement surveys.

With this added insight, organisations can design and deploy hyper-personalised employee experiences that rival the data-driven consumer experiences we enjoy outside of work. For example:

  • Tailored learning and development plans. Organisations will be able to process employee skills data far more efficiently with AI and machine learning so that learning plans can be highly personalised and update in real-time. This is crucial in the new world of work where skills regeneration is vital for avoiding obsolescence.
  • Personalised career plans. Uncover hidden talents and ambitions to design personalised career paths. Salesforce, for example, uses AI to scan annual review documentation and identify people who reference skills or interests they don’t necessarily use in their current role to recommend new internal opportunities.
  • Remove human bias and validate decision making. By backing up decisions made by people with evidence from employee data, prejudice in people management can be substantially reduced – from recruitment, through to promotion.
  • Tackle employee wellbeing with data. For example, insights from employee data can be used to predict employees at risk of excessive stress or burn-out, allowing organisations to take vital preemptive action.

Working structures should be designed a) for the individual: people work best in different ways and one-size-fits-all policies won’t cut it in the future of work. And b) designed with evidence. An evidenced-based understanding of authentic behaviours at work is the only way to break down the stigmas that stifle creativity and dampen employee well-being (i.e., “I can’t be seen leaving my desk other than for lunch,” “I’ve got to answer emails from my boss any time of the day or night,” or “The later I stay, the harder people will think I work”).

For your organisation to take on the challenges of Industry 4.0, break free from the shackles of outdated working structures, and reinvigorate the workforce.

For more insights from our recent research, check out the full paper: Talent Intelligence: Unlocking People Data to Redefine how Workers Need to Work


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