Future of Work — Technology, Trends & Impact on Jobs

Future of Work — Restaurant in Yiwa, China

This second blog about the future of work (FOW) will go a little deeper (and longer) into some of the trends that pertain to the FOW. As we see the output of studies done by McKinsey, BCG, Deloitte and others, we can begin to assess what actions we might start taking as individuals, leaders, members of society to ensure we are prepared for change and disruption.

As I covered in the first blog, technologies, business models, demographics, and even workplace attitudes are changing — and are doing so at the same time! Therefore, the transformation going on across those multiple areas, is creating an exponential disruption. With that disruption, will come some reckoning we’ll have to do re: how we work, collaborate, live, survive and thrive.

A major catalyst of this revolution is technology — it has a significant impact on labor and industry is redefining what is a career, a job, and who the workforce is. Therefore, the emphasis of the blogs going forward will be on technology and on people, with some side jaunts around policy/social acceptance.

TODAY’S blog includes: 1) a review of just a couple examples of changes occurring in technology/access to information 2) a few data points that will give an idea of the trends happening across multiple areas relating to people and technology, and 3) a brief discussion on what may render certain roles or activities susceptible to disruption via automation.


Automation — the ability to use technology to improve business performance by reducing errors, improving quality, safety, throughput and achieve customer satisfying outcomes that can go beyond what we can do as humans.

The data is showing that automation has historically improved productivity amongst the G19 countries, but since 2008 recession, the business productivity is at its lowest since the 70’s. As I mentioned in the last blog, the aging of the workforce (and therefore less available skilled folks) will require automation to boost productivity even higher. Although automation alone is not the silver bullet we are seeing a lot emphasis on that from companies. Efficiency, cost-out, Cash, Inventory reduction, variable cost productivity, etc. are being propelled by automation.

We all know about CRM, ERP, PLM, GL, MES, etc. systems that help drive automation, thereby increasing business performance. But there is also the adoption of other technologies such as robotics/RPA- robotic process automation — often done to reliably deliver outcomes where tasks are truly repetitive, and may not require subjective human judgement or deliberation. That enables companies to use software to automate well defined data transactions currently performed by people.

BTW, robots used to cost 400k. They now cost easily $22k. (ie Baxter the robot from Rethink Robotics). So, technology is cheaper, faster and more accessible. Moores law.

Artificial intelligence — giving systems/software/tools the ability to learn and make decisions in new situations as humans might do. That is usually done via algorithms (formulas) and with enough data points/examples so that the technology can use their ‘intelligence’ in increasingly new situations. For example, if an algorithm can earn to recognize someone’s face, then they can use that intelligence to spot them in Facebook photos, or from digital facial images captured in a crowded airport. When an autonomous car ‘learns’ how to drive via a series of test drives, it takes that knowledge and can learn to apply it in other terrains that it may have not driven before.

Digital Twin — enables companies to look at a digital representation of the physical product in order to enable simulation of how a product may respond, perform, or even go out of service due to environmental factors. (BTW, you can look at certain social media apps as our digital twin — it’s a digital representation of sorts of who we are — and those apps use algorithms to help determine what we might buy, where we might go on vacation, etc.) When there’s a digital representation of a machine, and that machine is connected to the manufacturing company’s network, the need to have mainly corrective maintenance (think field engineers that must be onsite at a hospital or power plant) will be largely replaced with preventive maintenance — driven by the machine itself sending signals to remote engineers that are sitting in a online center with the machine telling them it’s having issues that can be fixed , electronically/onsite BEFORE it goes down. Prevention vs Correction.

Big Data/Analytics — that is where the huge amounts of storing, processing and sending/receiving of all types of data have happened in the last 15 or so years. Today my iphone 7 has more processing power than NASA did in 1969. Now, the ability to analyze all that data — whether it is structured (like in columns/rows in a spread sheet), or unstructured data from video, health records, images or emails — is enabling companies to make decisions in how they design, sell, make and service their products. There will be nearly $1T of value unlocked in just a few years because of this.

What’s the big deal as it relates to FOW?

· every company will now need to use analytics and data in how they work, how they make decisions, or run the risk of competition beating them to it. Productivity, customer fulfillment, and much will be at risk if companies don’t adopt that. That points to a systems & process change to ensure there is a means to see wing to wing across the vertical functions to get customer’s needs met faster than ever.

· people will need to learn how to use analytics in doing their job. What used to take 10 people to gather data, spot trends, normalize the data because of differences in currency, or units of measure, etc will be done in 10 minutes using big data. That points to a skill shift of those executing in their roles. We need to recruit for these new skills.

These are just a few of technological advances –but they all have implications in what new skills will be required in the digital economy. We will need a workforce with more digital savvy, CX/UX focus, software/open source/API skills, 3D/model-based thinking, creative competence , solutions selling, agility , analytics and product management.

Accessing Ideas & Information — As the cost of technology goes down because of advances in cloud tech, or improved storage, the access of technology is going up (there are about 7.6B people in the world, and they will be using 11.5B devices in a few years). We will be able to access people at anytime, from anywhere — strangers and colleagues alike. And these people are smart!! They are inventing, innovating, curating and incubating wherever they are.

Information, is available everywhere, all the time, about everything. That information / data is multiplying exponentially, is ubiquitous, and is wanted by every person and every company to solve their problems. BUT, there isn’t one company, or one person that knows everything. So, we must tap into what information or skills we need, when we need them, wherever that information may exist.

The days when a company may want to hold on to every employee ‘just in case’ they need their expertise to work on something super important is coming to an end. Instead, they can go online and find those smart people who would have the most up to data and experience of a topic and use them for a gig to do product design, or compute a more effective insurance actuarial algorithm, use them to create a digital marketing campaign, or whatever, and then that person goes on to another ‘gig’.

In the FOW, The presence of people that can come in and out to do a ‘gig’ will change what ‘employment’ is, will redefine who owns the newly developed IP (the company or the gig workers?), changes how we think about employer sponsored health insurance (if the gig person isn’t really an employee of the company) and will require companies to embrace social or cloud-based networks as a way to engage these workers that may work for us in bursts, and not continuously. There will now be more blurry boundaries between employees and the gig/freelance/rented talent.


· 66% of job losses in the next 5 years will be white collar office functions

· 38% of employers reported difficulties in filling jobs in 2015 due to lack of available talent (think boomers, or others that don’t possess skill sets I mentioned above for this digital economy)

· Nearly 40% of US workers are now contingent — platforms like Uber, TaskRabbit, etc have made contingent/freelance work easier than ever.

· 44% of millennials expect to leave their current employer within 2 years

· Automation and robotics could displace 5MM jobs across 15 major economies by 2020.

· Industry trends: average professional worker’s age is younger, average tenure in years is lower, willingness to relocate is lower, cross functional moves are increasing.

· 92% of CHRO’s and CEOs are looking at ways to flatten the hierarchy, make jobs more dynamic and leverage more contingent labor.

· By 2027 relearning will be constant and non-routine — 2 out of 3 jobs will require more thinking than doing. Robots will be doing the doing –humans will be doing more of thinking. (think RPA or cobots on the factory floor)

· Automation may raise productivity growth to 1.4% annually. (is that enough?)

· 60% of all jobs have at least 30% activities that could be automated. But another finding is that only about 9% of jobs have activities that are 100% automatable. More jobs we do will be augmented or enhanced through automation than being automated away.


Given the types of things going on because of the accelerated availability of automation, digital technology, AI/Analytics, etc. there’s been a lot of study done on what types of jobs will likely be impacted. And to what extent will jobs be eliminated vs augmented.

There’s nearly $16 Trillion in ‘wages’ being paid in the global economy. McKinsey has found that between 40 & 50% of those roles can be automated in some manner. Some roles more than others. That’s still about $7 Trillion in wages that may be affected in some manner.

If a role is more predictable, is physical, involves collecting/processing/analyzing data, that will have a higher likelihood of being impacted by automation. Roles like manufacturing-welding, packaging, loading- food service, retail and even mid management roles can be more automated. As I stated above, about 60% of all roles are comprised of activities that can be automated by at least 30%.

The McKinsey study was done on over 800 occupations from retail to education, food service, healthcare, sales, web developers, etc. McKinsey found that the roles that are less predictable, construction, crane operations, medical care first responders, trash collecting are automatable at a much lower rate.

The lowest potential for automation will be those that require key capabilities like creativity, social intelligence and high perception/manipulation — ie — greeters, fashion designer, biologists, product management/explaining product details, responding to complaints/giving advice, etc.

Someone said that the increased role of digital technology, will make us humans, more, uh, human. Creativity, intuition, context, empathy and prioritization will be capabilities humans will need to apply in future roles that robots won’t possess to as significant degree for some time, if ever.

What’s happening with the Middle Class? David Autor, an MIT economist says that since the 80’s, computers have increasingly taken over tasks like clerical work, bookkeeping, repetitive jobs in manufacturing — all middle class workers. Increasingly, the higher skilled roles requiring creativity and problem solving with use of computers have proliferated. And the lower skilled roles, such as janitors, home health aide and others that are hard to automate have also grown. So as the high and lower skilled roles grew, the middle-class roles have shrunk. We see that in all the political discussions, right? The disappearing middle class — and the growing gap between the wealthy and the poor.

Bottom line is that productivity has continued to rise somewhat, and employment has waned, resulting in falling median incomes. People are falling behind because technology is advancing so fast, and our skills and organizations cannot keep up.

Summary: Yes, I know this could sound like a gloomy forecast of massive job loss…. But even though there will likely be reductions in certain fields, there will also be the creation of brand new roles. These new roles may be left unfilled if we don’t focus on ensuring our workforce is continuously learning/unlearning/relearning, is curious & agile and that we open ourselves to the gig economy to find & recruit the ‘best’ talent ho matter where they are or who they currently work for.

To me, the Future of Work is not the death of jobs, but it’s about creating an environment in our workforce, where we create the Work of the Future, and allow workers to work in ways that work for them, while they deliver solutions for our important customers, and business growth for our company.

What do you think? If you didn’t get my first article on this topic, let me know.

Want to read more? Data Sources:

· World Economic Forum: The Future of Jobs Jan 2016

· Oxford University Study ~2014

· McKinsey Oct 2016

· Deloitte Jan 2016

· Future of Employment: How susceptible are jobs to computerization — Carl Benedikt Frey/Michael Osborne

· Boston Consulting Group- New Way of Working

· Deloitte — Rewriting Rules for Digital Age

· Follow Heather McGowan — she has GREAT perspectives on the human angle

· My Friend at GE — Richard Arthur — great perspectives on social impacts


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