August 03, 2019
Preparing for Automated Future
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A good receptionist should have certain characteristics: helpful, friendly, organized. But do they need to be human? Perhaps not anymore. Walk into JLL’s Carrington Street office in Sydney and you’ll be greeted by Jill, our new receptionist who can assist in delivery, contact your hosts, recognize employees or visitors, and more. It is just one of a growing number of robotic staff now working in offices around the world.
In the 2020s and beyond, robotic versions of people, such as HUBO – the star of last year’s Davos meeting – will perform tasks previously reserved for humans. But that’s only part of the picture. Yes, automation has begun to displace human workers, as some predicted, but the effect is more than just replacement – it’s advancement. The influx of sophisticated technologies will enable us to think of work in new and innovative ways.
New roles for humans are already emerging as a result of automation. In a recent article for the Financial Times, Gillian Tett recounted how anthropologist Benjamin Shestakofsky spent 19 months inside a California company that uses digital technologies to connect buyers and sellers of domestic services. His thoughts on the topic? “Software automation can substitute for labor but it also creates new human-machine complementaries … (and) new types of jobs.”
The Fourth Industrial Revolution workforce
Contrary to fearsome scenarios about robots replacing humans, cognitive computing, robotics, and workforce automation feature prominently in most projections of the future workplace.
For many organizations, exploiting the emerging technologies of the Fourth Industrial Revolution has become a strategic priority. Many companies are infusing products, services, and operations with digital assets and technologies, disrupting old business models and creating new ones. As described in Nine Elements of Business Transformation, digitization and automation require wholesale changes in how an organization performs, and how humans go about their daily work.
More than 260,000 robots are working in US factories today, with most working in the automotive, semiconductor and electronics industries. This reduces demand for low-skilled labor but increases the need for access to highly skilled talent to manage the robots.
In white-collar workplaces, automation takes the form of cognitive computing assistants like JiLL and robotic process automation, which enables employees to configure software robots to complete repetitive, time-consuming work, such as client profile updates, insurance claims processing, credit card applications or healthcare patient registration. Software robots, or virtual assistants, are assuming formerly human duties such as auto-correspondence, appointment scheduling, and other office functions.
This does not mean the future will be a battle of man-versus-machine. Rather, there is the opportunity for humans to work with machines, suggests Thomas W. Malone, a professor at MIT Sloan School of Management and co-director of MIT’s Inventing the Organizations of the 21st Century initiative. As machine co-workers grow increasingly competent, human-to-machine collaboration technologies will make organizations more intelligent and greatly improve overall human work performance to drive greater business value.
An employee checks robotics arms picking up calissons d'Aix at the French manufacturer factory Roy Rene in Puyricard near Aix en Provence, France, December 15, 2016 which are traditional sweets from Provence, made with almonds and candied melon and created in France in the mid-15th century.
Emerging business models
Even the most thoughtful C-suite executive may find it difficult to anticipate the future, although most appear to recognize that powerful forces are already affecting their industries. Executives at 91% of companies say digital technologies have the potential to fundamentally transform the way their companies work. Exactly how remains to be seen.
Already, we see examples of emerging business models combining the advantages of automation with the creative energy of the human workforce. “Network Orchestrators,” as defined in [email protected], are a new kind of company that delivers value through relationships rather than hard assets or human-provided services. Companies like eBay, Uber or TripAdvisor, for instance, leverage technology to create their networks. These enterprises grow revenues more quickly, generate higher profit margins and use assets more efficiently than companies with other business models.
The ‘liquid workforce’ and the ‘human cloud’
This current premium on speed will continue, even as new organizational challenges arise, such as the destabilization of the way people work, reports McKinsey Quarterly. To achieve fast growth in a human/robot hybrid environment, companies need to pay attention to the stability of their workforce and stay in tune with the needs of the people within the enterprise. It’s only natural that as this trend progresses, companies will need a different scale and mix of workers than today. A different mix of work locations and work environments will also be needed to support these next-generation “digital” talent requirements.
Thus, we are witnessing the emergence of the “liquid workforce” and the “human cloud” as new workforce models. The “liquid workforce” refers to employees who are able to re-train and adapt to their environment in order to stay relevant during the digital revolution. In recent years, Accenture and the business media have popularized the “liquid workforce” term, bringing it into the mainstream business lexicon as Accenture develops innovative and dynamic “liquid” workforce strategies for itself and its clients.
Among companies that create strong processes for managing the “agile workforce”, the “Hollywood model” can become their new competitive advantage in an environment of constant technological disruption, according to Accenture Technology Vision 2016. The Hollywood model brings together autonomous, on-demand workers for project-based work onsite or to perform work remotely. Today, “human cloud” freelance workers comprise 35% of the workforce, and their numbers are expected to reach 75% to 80% of the future enterprise workforce by 2030.
To rapidly assemble the right skills and right capabilities, innovative “crowdsourced” workforce management technology platforms have emerged. Online platforms enable companies to draw from a geographically dispersed talent base for work that does not require in-office presence.
Some companies are also using what former Manpower CEO Jeffrey Joerres has dubbed “micro-market analysis” and “micro-foot printing” to track global shifts in talent availability and costs, rapidly shifting work from one country to another to stay ahead of their competitors. In many industries, a global strategy for finding highly-skilled, cost-effective labor is becoming a necessity.
Preparing for an unknown, increasingly automated, future
Computing advances are accelerating the pace of innovation, enabling companies to launch new products and services in ever-shorter timelines. As this capability grows, new ways of working and collaborating will render some facilities and locations obsolete. Companies will have increased needs for technology-ready facilities, flexibility, and access to new kinds of talent. Those that need to turn on a dime to stay competitive will need to build agility into their real estate strategies and create specialized work environments for jobs that don’t yet exist, in industries that have not yet emerged.
In fact, the growing presence of mobile working and Fourth Industrial Revolution technologies is already affecting how much space companies need, where facilities are located, and how space is configured, utilized and managed. Many companies are rethinking their locations with an eye to the skillsets they need in the future. The drive will be towards operating locations that support business transformation and performance with greater access to target demographics, unique skill sets, and industry innovation.
The next-generation workforce and next-generation work practices will be dramatically transformed and influenced by the next phase of technological evolution. All companies will need to meet these new challenges in strategic corporate real estate portfolio planning and greater workplace innovation to support evolving and disruptive business models – some of which are yet to be created.
In practical terms, neuroeconomics involves the analysis of brain functions that drive decision making. Neuroeconomics is a relatively new branch of science. Professor Jonathan Cohen, a director at the Princeton Neuroscience Institute, describes it as a discipline that tries to bridge economics, psychology, and neuroscience.
Yale Insights he asserts, “I think of economics and psychology as really, in some sense, one discipline. I know that that's a strident statement to make, but they really are siblings separated at birth. Psychology and economics are complementary disciplines, in many cases studying the same phenomena.”
Watching the brain make decisions
In practical terms, neuroeconomics involves analyzing the brain functions behind decision-making. Professor Michael Platt from the Wharton University of Pennsylvania spoke at the World Economic Forum in Davos to explain how the discipline could help us to make better decisions.
He told the audience, “We can measure how much you value something by looking inside your brain. You don’t even have to tell us anything about it. So we can measure your preferences by putting you on an MRI machine and taking snapshots of your brain in action and we can predict your decisions. The brain weighs evidence and value separately to make a decision.’’
Hit the gas, or hit the brakes?
Professor Platt says the values we apply to similar decisions can change over time, or from moment to moment. Whether we are running on time, or we’re late for work can influence how we’ll judge a decision to pass a traffic signal that’s changing from green to red.
He explains there is an economic element to such decisions. “Turns out, the brain has evolved an elegant, and it turns out a mathematically optimal way of solving this problem. All this means is that you've got two buckets in your brain, and each time you get a little bit of evidence, saying the light is red, it goes into the red bucket. If you get a little bit of evidence that the light is yellow, it goes into the yellow bucket. Whichever bucket fills up first wins, that’s the decision that you make.”
Professor Platt told the Davos audience that neuroeconomic techniques are now being applied to areas much less mundane than the decision to drive through a traffic signal.
“My colleagues at Stanford University, for example, have shown that by scanning the brains of a limited number of people in the laboratory they can predict the effectiveness of micro-lending campaigns on the Internet.
“We could also use the same approach to fine-tune our messages to help people make healthy choices. I think another area of potential application is aligning consumers with products, right? This is sort of precision marketing.”
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