Preparing for the digitisation of
the workforce
An everis report, written by The Economist Intelligence Unit
Written by:
Executive summary
4
About this research
6
Foreword
7
Introduction
8
1. The background to workforce digitisation
9
2. Putting strategy into practice
12
3. Robots on the payroll
16
4. Machine intelligence at work
21
5. The on-demand workforce
25
Conclusion
31
3
Executive summary
Executive summary
The world of work is changing, fast and fundamentally. Against a backdrop of difficult-to-solve
staffing and employment issues, companies are increasingly turning to technology to help them
get work done.
For many, automation provides an answer. Advances in robotics and artificial intelligence mean that
machines are increasingly capable of taking over work that was previously performed by human
employees. In many cases, they are proving a great deal faster, more efficient and more accurate,
thereby making it possible to perform certain tasks that were previously impossible to carry out.
At the same time, senior executives are looking beyond their own workforces for the skills and
labour they need, searching Internet-based jobs marketplaces that connect them with a seemingly
limitless pool of on-demand workers.
In this report we explore how these trends—collectively termed “workforce digitisation”—are
changing the nature of work and how organisations are preparing for this revolution. Written
by the Economist Intelligence Unit (EIU) and sponsored by everis, it is based on a survey of
over 220 C-level and other senior executives, desk research and interviews with companies and
thought-leaders who have considered the likely implications of new ways of working.
The key findings are:
Workforce digitisation is taking place against a backdrop of high demand for talent. The
most common labour and employment challenge among respondents to the EIU survey is limited
local supply of skilled labour. Technology offers a number of solutions to this issue: three examples
examined in this report are robotics, artificial intelligence (AI), and on-demand, crowdsourced labour. Executives certainly see technology as part of the solution: 82% of those surveyed for this report agree that their organisation needs to transform the way it sources and manages labour using
digital technology, and 80% believe that an organisation’s ability to use digital sources of labour will
be a key factor in its future success.
More than half of companies have devised a strategy to address workforce digitisation,
but fewer than one-quarter have deployed it. The impact of the digitisation of work is certainly
on the corporate agenda. Only 7% of respondents say their organisation has not discussed it at
all. But while a total of 58% of respondents have devised a strategy that covers the digitisation of
labour, only 23% have implemented that strategy. Common barriers to taking action on workforce
digitisation include an absence of technical knowledge, business processes that are too hard to
change, and a lack of desire to innovate. This does not mean workforce digitisation technologies
are not being used—quite the opposite—but they are not being deployed strategically. This may
prove problematic, as the technologies raise a number of strategic questions.
Robotics technology is being used to free highly skilled physical workers to focus their
talents on where they are needed. Robotics is the least adopted of the three technologies examined in this report. It is commonly adopted among companies which report high-demand for
high-skilled labour, and the most popular application is in manufacturing, although adoption in
warehouse or stock management may grow faster in future, the survey suggests. Concerns have
been raised about the impact of robots on human employment. Companies interviewed for this
study which use robots claim they allow skilled employees to focus their talent where they are needed most, and permit new capabilities and company growth that would otherwise not be possible.
AI has the potential to displace mid-ranking clerical workers. AI is already fairly widespread in
business, the EIU survey reveals: 43% of respondents say their organisation is making some use of
the technology. By far the most common application today is in data analysis—recent innovations
4
Executive summary
are helping companies extract insight and learn from the growing volume of data they collect. Proponents see AI as a tool to help expert knowledge workers to become more productive. However,
they concede that clerical staff whose job is to process, compile and integrate information sources
could well be displaced.
On-demand, crowdsourced labour offers scalability but raises strategic issues. Digital technology is allowing businesses to recruit on-demand workers on a larger scale and at greater
speed than ever before. Survey respondents acknowledge that using temporary workers has its
drawbacks: 74% believe that using contract or short-term labour prevents organisations from
building knowledge, and the same proportion say that offering employees job security is
important to attract top talent. Nevertheless, 44% use the on-demand, crowdsource labour
model to some extent, most often to access creative talent such as graphic designers or
copywriters. The ongoing public debate about Uber, the taxi-booking app, may dissuade
companies from making strategic commitments to this kind of service, but integrating them into
the overall employment strategy will require executive oversight, sooner or later.
Business leaders who wish to benefit from workforce digitisation can expect to face tough
questions from employees. Each of the three technologies discussed in this report can be seen,
not without reason, as a threat to current employees. While they are eager to benefit from the workforce digitisation, few executives surveyed for this report want to see jobs cut from their organisation. Many of the experts interviewed for this report argue that automation can help to make
people’s working lives safer and allow them to focus on higher-value work. And survey respondents
value the engagement, loyalty and accumulated knowledge of employees. As they begin to apply
workforce digitisation more strategically, executives must ensure that these values are protected
—for the benefit of the organisations, of their employees, and perhaps even society.
5
About this research
About this research
Preparing for the digitisation of the workforce is a report by The Economist Intelligence Unit,
sponsored by everis. The report investigates the groundwork that companies are laying as they
consider the role that robotics, artificial intelligence and the ready availability of on-demand,
crowdsourced labour will play in their employment and workforce strategies.
The research draws on a survey of 228 senior-level and C-level executives from companies in the
US, Europe, Latin America and Asia-Pacific.
It incorporates interviews with the following executives:
Alex Allen, vice president of marketing, Spring Venture Group
Robbie Allen, founder and CEO, Automated Insights
Hal Blenkhorn, director of engineering, Tegra Medical
Rodney Brooks, founder, chairman and chief technology officer, Rethink Robotics
Paul Clarke, chief technology officer, Ocado
Ian Davies, head of engineering and technical director, Easyjet
Lou Ferrara, vice president and managing editor, Associated Press
Jennifer Griffin, vice president of content integrity and insights, Bazaarvoice
David Hale, CEO, Gigwalk
Daniel Nadler, CEO, Kensho Technologies
Tanya Perry, vice president of US sales and operations, Shopguard
David Plouffe, senior vice president of policy and strategy, Uber
Brad Schneider, director of applications development, The Container Store
Mark Skilton, professor of practice, Warwick Business School
The report was written by Jessica Twentyman and edited by Pete Swabey.
6
Foreword
Foreword.
By Marc Alba, Chief Innovation Officer. Head of NextGen Consulting.
everis. An NTT DATA company.
Recently the chairman of a major corporation, told me he was fed up with all the “digital blah-blah”
(as he called it), convinced this was just another hype fostered by analysts, consultants and vendors.
Asked about my opinion, I first thought about highlighting the amazing new possibilities of digital and
how they are transforming one sector after another. Instead, I invited him to one of the sessions we
regularly hold at everis to unleash, through the power of digital, the innate creativity of our employees’ children. After he experienced how kids produce their own astonishing movies, videogames, music, robots, apps or fashion designs within a couple of hours, just by being exposed to coding tools,
makers toolkits or 3D printing, he started to understand what digital transformation really means.
Digital natives such as these children will be—and often already are—our future clients and employees.
The corporate chairman, and the rest of us, would rather be prepared for the digital natives, as they represent something close to a new civilisation. Hype? For sure, as with any other next “big thing”, workforce
digitisation is subject to occasional exaggeration. However, well beyond “blah-blah”, a digital tsunami full
of stories of disruptions is already putting many industries under siege. Moreover, it is transforming the
nature and definition of the workforce.
This leads us to where the story of this report begins. In 2014, we in everis, after joining the NTT DATA
family and becoming part of the NTT Group, defined our new collective goal/dream: becoming the
number one business and IT services company in the world. Those who do not know us enough usually
laugh when we share this dream. But, those who know how we created this company from scratch to
become a business with nearly 15,000 employees and sustained double-digit organic growth, know this
is possible, and smile when they think how much fun this new journey will bring (again!). In the thorough
transformation of our business that we are undertaking to achieve this global leadership, digital is not
a nice-to-have: it is our new oxygen, a key ingredient for survival, the cornerstone to become an exponential organization. As part of our transformation journey, we decided to sponsor this report, written
independently by The Economist Intelligence Unit.
Firms throughout the world have been aiming to excel in the first waves of digital, focusing on digitising
processes and channels. But two new disruptive waves are now emerging: digitised workforces and
digital habitats. Digital habitats heavily rely on the Internet of Everything and Ambient Intelligence. The
digitisation of workforces—the focus of this report—consists of many components. This report, however, focuses on three key disruptive technologies: crowdsourcing, artificial intelligence (AI) and robotics.
This report aims to provide real-world learnings and insights on the digital workforce in general, and on
these three technology trends in particular. When commissioning this report, we decided not to focus
on assessing digital workforce technologies from the viewpoint of the “supply-side”, as other reports do.
We have seen and experienced enough of crowdsourcing, AI and robotics, to conclude that they are real
game-changers. Rather, we decided to focus the research on the “demand-side”, understanding how big
corporations and key decision makers assess the impact of the digitisation of the workforce.
Workforce digitisation involves complex hard and soft issues. One of the main general concerns is jobs
losses, which applies to both jobs virtualisation through crowdsourcing and jobs computerisation through
AI (software bots) and robotics (hardware robots). For us at everis, this is the key challenge post by
workforce digitisation; job creation and talent development have always been our motto with 15,000 jobs
in everis, 80,000 in NTT DATA and close to 250,000 in NTT. For us, the tricky new equation to solve is
how to continue creating jobs and developing talent while leveraging a hybrid workforce that combines
human and machine “talent”. This led us to create a new concept we call the Augmented Workforce, to
harmoniously and sustainably combine human and machine intelligence. Here again, this report provides
valuable insights on both the bright and dark side of the digital workforce.
The real game-changers across industries are striving to lead this emerging digital workforce revolution.
Similarly, in order to become the global number one consulting company, last year we created a new
strategic initiative called NextGen Consulting. Our goal is to disrupt and reinvent consulting through the
creation of one-of-a-kind assets that enable us to truly go digital, open and exponential, leveraging the
huge potential of crowdsourcing, AI and robotics. The results have been amazing so far, so I really hope
this report helps you to embrace workforce digitisation, as we have.
7
Introduction
Introduction
Faster, more efficient robots. Intelligent computers capable of learning new tasks. A vast pool of
freelance human talent, accessible to employers on demand, over the Internet. The future of work
is already here. Are company leaders ready to embrace it?
Many are, according to a new worldwide survey of 228 C-level and senior executives, conducted
by The Economist Intelligence Unit (EIU) and sponsored by everis. Eight out of ten (80%) agree
that the future success of their organisation will depend on their ability to harness new digital technologies and techniques to solve their skills and labour challenges.
Achieving that success, however, will depend on their ability to understand and exploit the new
technologies. The biggest barrier to embracing the digitisation for 45% of respondents is a lack of
understanding.
This report focuses on three technology-driven trends that are changing the dynamics of work in
the 21st century. The first is robotics, which has spread beyond its early use on car manufacturing production lines to other sectors such as healthcare and farming. According to the industry
trade body, the International Federation of Robotics (IFR), robot sales reached 178,132 units in
2013—by far the highest level ever recorded in one year. In 2014 they rose by a further 27% to an
estimated 225,000.
The second is artificial intelligence (AI). This is a field that has progressed significantly in recent
years thanks to the increased and more widespread availability of computing power and new
programming techniques that approximate “intelligence” in software, enabling computers to tackle
tasks that were previously thought to be solvable only by the human brain. Thanks to such emerging techniques, computers can now handle some of these tasks faster and more accurately than
human beings.
Finally, there is on-demand, crowdsourced labour. A number of Internet-based marketplaces have
emerged in recent years that connect companies or individuals who have a task they need performing or a problem to be solved with independent, on-demand workers who have the time and
skills to do that work. The veteran in this market is Elance, which was launched back in 1999 and
is now part of Upwork, but more recent entrants include Work Market, Gigwalk and TaskRabbit.
Employers like this style of sourcing skills and labour, because it offers the chance to offload work
that is repetitive or short-term or seasonal onto a seemingly limitless pool of outside providers,
without overburdening the company payroll or benefits programme. It also allows employers to
keep fixed costs lower, paying only for labour as needed. Many workers like it too, because life as
an independent contractor allows them to balance work with the other demands on their time (the
care of children, for example) and to retain control over the type of tasks they take on, the nature
of the teams with which they work, as well as their working hours and locations. In many cases,
on-demand workers can work from home, while at the same time interacting with other team
members across the world to solve complex problems.
This report examines these trends in depth, but first it explores the business trends that are creating
demand for new approaches to labour and investigates the extent to which these trends are on the
corporate agenda.
8
The background to workforce digitisation
1. The background to workforce digitisation
It is a cruel contradiction of the modern age that while many people are unable to find work, especially among the under 25s, companies also struggle to find the talent they need to fill positions.
According to the Hays Global Skills Index 2015, a measure of labour supply and demand across
the globe, “global labour markets are approaching crisis point as the supply of skilled workers struggles to keep pace with demand.”
This gap between supply and demand is evident among respondents to the EIU survey. Over
four in ten (42%) say their organisation suffers from the limited local availability of specialist labour.
Meanwhile, 37% suffer from an inability to source specialist labour quickly enough to meet demand, suggesting their current labour sourcing prevents them from handling fluctuations in their
workload. Only 7% of companies say they suffer no staffing or employment issues.
CHART 1: Limited local availability of specialist labour is the most common staffing and
employment issue
From which, if any, of the following staffing and employment issues does your organisation suffer? % of
respondents
Limited local availability of specialist labour
42%
Inability to source specialist labour
quickly enough to meet demand
37%
High demand for high-skilled clerical workers
32%
Inability to scale down employment
levels in periods of low demand
31%
29%
Low employee engagement and/or retention
21%
High demand for low-skilled clerical workers
High demand for high-skilled physical labour
15%
Low employee wellbeing
14%
High demand for low-skilled physical labour
14%
7%
There are no issues
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
Source: The Economist Intelligence Unit survey, August 2015
These issues apply across both large and small companies. For example, limited local availability of
specialist labour is an issue for 45% of respondents from large organisations (with annual revenue
in excess of US$500m) and for 39% of those from smaller organisations. Similarly, sourcing labour
quickly enough to meet demand is an issue for 40% of large-organisation respondents and 33% of
those from smaller organisations.
9
The background to workforce digitisation
High-skilled clerical workers are the most sought-after, the survey reveals, with 32% of respondents
identifying high demand for such staff as an issue. Around one-fifth (21%) report high demand for
low-skilled clerical workers.
For physical labour, the shortage is less acute: 15% report high demand for high-skilled physical
labour and 14% for low-skilled physical labour. But the issue is more pronounced for respondents
in Latin-America, where 26% report high demand for high-skilled physical labour and 24% for
low-skilled physical labour.
Against this backdrop, it is little wonder that entrepreneurs have sought to ease companies’ labour
issues through the application of digital technology.
One such company is Gigwalk, a San Francisco-based start-up that offers instant access to a market of independent workers (“gigwalkers” in the company parlance) who are available to perform
an often simple, observational task in a specific location. A mouthwash manufacturer, for example,
might hire gigwalkers to check whether their products are being properly stocked and presented
in a local supermarket.
Gigwalk CEO David Hale believes that companies are waking up to the possibilities of using the
Internet and related technologies to extend their workforce.
“I think what we’re in right now is a second phase of outsourcing,” he says. “My background is
in subcontract manufacturing, and if you look back over four decades, companies have become
accustomed to outsourcing labour. They’re just looking to do it in different ways now, using the Internet, and on a more individualised basis. Companies have tasks they need performing, but often
those tasks are aligned with particular strategies or projects, so what companies like ours offer is
real-time labour arbitrage.”
Other companies seek to ease the skills gap by automating work that is best suited to human
beings and freeing up employees—and the budget that pays for them—to focus on more
differentiated tasks. In some cases, this enables them to deploy employees on new projects
that weren’t previously possible due to time constraints.
“Company leaders are starting to think: how many staff hours do I have at my disposal and how
could my employees’ time be better spent?” says Robbie Allen, CEO of artificial intelligence software vendor Automated Insights. “So tasks that are data-driven and repetitive and could be better
performed by computers, those will be the candidates for automation. Others, the ones that humans are good at—well, there’ll be more time for employees to concentrate on them.”
“I believe that the future is going to be much more about humans and software working together
and humans and computers splitting tasks according to their strengths,” he adds.
Getting work done is not the only issue that companies face, however. Around three in every ten
respondents (29%) say their organisation suffers from low employee engagement or retention.
Furthermore, respondents believe that employee engagement will become more of a concern in
future. Revenue and profit growth are the most common priorities today, with 54% and 53% of
respondents identifying them as such as top priorities, but in 3-5 years’ time they expect their focus
to shift towards geographical expansion (42%) and employee engagement (40%).
Clearly, one of the challenges associated with adopting new, technology-driven models of labour
sourcing will be to maintain that engagement throughout the upheaval. This is just one example
of how the digitisation of labour will present strategic issues that will require strong leadership to
overcome. But are these issues on the boardroom agenda?
10
The background to workforce digitisation
CHART 2: Respondents expect their organisation to shift their current focus on revenue and
profit growth to geographical expansion and employee engagement in the next 3-5 years
Which of the following objectives are your organisation’s top priorities right now? And what will they be in
3-5 years’ time? % of respondents
3-5 years’ time
Right now
Revenue growth
54%
28%
Profit growth
53%
35%
Cost reduction
27%
40%
36%
34%
36%
38%
31%
40%
Organisational agility
Digital innovation
Employee wellbeing,
engagement and loyalty
24%
Geographic expansion
0%
10%
20%
30%
42%
40%
50%
60%
Source: The Economist Intelligence Unit survey, August 2015
everis view
Nowadays, everybody is talking about digitisation.
Digitisation of companies, the economy, the workforce—even digitisation of relationships. But what
does it really mean, and what does it imply to turn
something digital?
A classic example may be digitising chess. We
may think in a naive way that turning chess digital
is putting the board and the pieces inside a screen.
Others, going a bit further, may understand that the
game is now being played in a different medium, one
that allows the players to be in different locations. But
what is really going on under the hood? Through the
process of digitisation, what we are doing is turning
chess playing into a domain that computers can understand, and one that allows us to use computers
to become better players.
This metaphor helps us to understand how a new digital medium can be used to augment our workforce
in ways we are only just beginning to conceptualise.
11
Putting strategy into practice
2. Putting strategy into practice
The need for companies to apply digital innovations to their employment and staffing issues is widely accepted. A resounding 82% of respondents to the survey agree that their organisation needs
to transform the way it sources and manages labour using digital technology. Almost as many
(80%) believe that their organisation’s ability to use digital sources of labour will be a key factor in
its future success.
This helps to explain why more than half of the executives surveyed by The EIU say their organisation has devised a formal strategy to address the potential impact of digital technology on
its workforce. However, only a minority have put their strategic thinking into action: just under
one-quarter (23%) have both devised and implemented their strategy, while 35% have drawn up
a strategy without putting it into practice.
This does not mean organisations are not already applying digital solutions to their labour issues.
More than one-third of respondents (38%) say their organisations have adopted robotics, 43% are
using AI, and 44% employ on-demand crowdsourced labour, the survey reveals.
However, results suggest that this activity is not being implemented strategically. Only around
one-quarter of organisations have formally assessed opportunities to use crowdsourced labour
(26%) or AI (25%), and 11% have done so for robotics. Just 15% have addressed digital labour
sourcing technologies in either their HR or digital strategy.
CHART 3: Fewer than one-quarter of respondents say their organisation has devised and
implemented a formal strategy
To what extent has the potential impact of digital technology on your workforce and employment strategy
been discussed or addressed at the most senior level or your organisation? % of respondents
A formal strategy has been devised and implemented
23%
A formal strategy has been devised but not yet implemented
35%
16%
Discussed at length but no action taken
20%
Discussed briefly
Not at all
7%
0%
Source: The Economist Intelligence Unit survey, August 2015
12
5%
10%
15%
20%
25%
30%
35%
40%
Putting strategy into practice
While the technologies that underpin workforce digitisation are not new, they have only recently
emerged on the executive agenda thanks to breakthrough innovations and falling costs. Executive
boards can be forgiven for not having fully realised their strategies just yet. However, many of the
challenges that companies face in making effective use of these technologies will require strategic
directives to overcome.
When asked to identify the main challenges to transforming the way their organisation sources and
manages labour using digital technology, 45% cite a lack of understanding of new technologies
and techniques, more than any other response. This is despite the fact that 76% of respondents
believe their organisation understands the risks and benefits of digitising labour.
This finding underscores the fact that while digitisation may relieve demand for certain forms of
labour, it will intensify the need for technical expertise. For example, demand for robotics engineers
in the US is expected to grow by 13% between 2014 and 2018, according to the country’s Bureau
of Labour Statistics.
The second most common challenge is that business processes are too hard to change, as cited
by 42% of respondents. This, at least, is being addressed: 41% of respondents say their organisation has redesigned business processes to allow for greater automation. Third, 40% of respondents cite a lack of desire to innovate.
CHART 4: A lack of technical understanding is the most common challenge to workforce
digitisation
Which of the following are the main challenges to transforming the way your organisation sources and manages labour using digital technology? % of respondents
A lack of understanding of new
techniques and technologies
45%
42%
Business processes that are too hard to change
40%
A lack of desire to innovate
A lack of budget to adopt new
techniques and technologies
25%
Employment law in the countries we operate in
19%
13%
Union protections of our employees
Don´t know/not applicable
7%
Other (please especify)
4%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
Source: The Economist Intelligence Unit survey, August 2015
13
Putting strategy into practice
Budgetary concerns are a relatively uncommon challenge, although they are more pronounced
among smaller companies. At organisations with annual revenue under US$500m, 36% of respondents say their organisation lacks money to adopt new techniques and technologies, compared
with just 26% in organisations with revenue over US$500m.
This shows that companies are willing to invest in technology that has the potential to transform
their organisation. European airline easyJet, which is investigating the use of drones to support
aircraft maintenance (see section 3), has adopted an “intrapreneurial” model to identify and nurture
technology investments.
“We’re granted seed money by the board to experiment with a particular technology or approach,”
explains easyJet’s head of engineering and technical director, Ian Davies. “If that’s successful, we’ll
outline a viable business case to an internal board that’s chaired by CEO Carolyn McCall and has
other board members in a session in which we’re invited to pitch our ideas.”
“Based on that, we’ll get the money we need, but we’ll also be expected to track our efforts closely
and report back regularly on how they’re going, whether we’re delivering on target and getting the
results we predicted,” he says. “We probably have between 15 and 20 R&D [research and development] projects like that running at any particular time. Things that cost a lot of money require
boardroom involvement—that’s a given.”
According to Rodney Brooks, founder, chairman and chief technology officer of Rethink Robotics, a
US-based maker of smart, collaborative robots, when customers deploy the company’s products,
their executives are focused on productivity, efficiency and operations. “Most of our customers are
very concentrated on the day-to-day running of manufacturing,” he says. “The C-level executives
are focused on operations and look for automation tools that are flexible, increase productivity and
fill in the labour gaps that all their enterprises suffer from.”
However, as will be shown throughout this report, the use of labour digitisation raises difficult questions that leaders who wish to exploit the benefits will need to contend with.
The first of these is how the introduction of automation and crowdsourced labour will impact their
existing workforce.
In 2013 a well-regarded and often-quoted study, The Future of Employment: How susceptible are
jobs to computerisation? by Carl Benedikt Frey and Michael Osborne of Oxford University’s Martin
Programme on the Impacts of Future Technology examined over 700 occupation types, noting the
types of tasks that workers perform and the skills required. The report concluded that almost half
(47%) of job roles currently available in the US could be susceptible to computerisation over the
next two decades.
Few executives surveyed for this report want to see jobs cut from their organisation: only 25% of
respondents believe that their organisation needs to reduce the number of full-time staff it employs
in order to be competitive. Seven out of ten, meanwhile, believe that “businesses have a moral
obligation to create and maintain human employment”.
Nevertheless, workers will have heard the public debate and may have justifiable fears about the
impact of automation and on-demand labour on their livelihoods. If they are to maintain a loyal
and engaged human workforce, executives will need to acknowledge these concerns and have a
strong response to them.
Meanwhile, they must also consider how the digitisation of labour will impact their competitive
position within their markets.
14
Putting strategy into practice
Mark Skilton, professor of practice in information systems and management at Warwick Business
School in the UK, says that most pioneering work in robotics and AI is being led by companies such
as Google and Amazon, and growing adoption will further tip the balance in their already considerable favour. “There’s a risk of ‘brain drain’ from companies and countries not able to compete with
these huge R&D-centric cloud companies,” he warns.
Beyond that, there are macroeconomic questions about how society will function in a more automated era. “There’s also the issue of how wealth and skills will be distributed in the global economy and how governments that rely on taxation from employment will protect their economies,”
Professor Skilton says.
“It’s not all doom and gloom,” he adds. “I think there are several generations of development yet
before the physical world of humans is replaced with fast and cost-effective [digital] alternatives,
but it is right to consider the ethical and economic repercussions of this technological scaling of
computing.”
These are questions that executives should consider sooner rather than later.
15
Robots on the payroll
3. Robots on the payroll
In May 2015 Ocado filed a patent application with the United States Patent and Trademark Office
that provides some interesting insight into how the UK-based online grocery retailer plans to expand its already extensive use of robots to further increase efficiency in its vast customer fulfilment
centres.
What Ocado proposes is to reduce the width of the aisles between shelves and instead have product-picking robots operating on a frame positioned above shelves. The reclaimed space will, in
turn, be used to store more inventory.
This is just one facet of a multi-pronged R&D effort into robotics at Ocado, according to chief
technology officer Paul Clarke. “We have multiple applications for robotics across our end-to-end
solution, and we have had R&D programmes working on these for several years now,” he says.
“Potential applications include inbound product processing, food processing, autonomous systems including driverless vehicles, and automated picking of goods into customer orders.”
Ocado is ahead of the game. Of the three areas under investigation in this report, robotics is the
least-adopted: 38% of respondents say their organisation is using robotics today. Of these, 15%
say they use it extensively, while 23% say that its use in their company is limited. Only 11% say that
they do not use robots today but plan to do so in future.
CHART 5: Only 38% of respondents say their organisation makes some use of robotics today
To your knowledge, to what extent does your organisation currently use robotics?
3%
15%
No use today and no plans to use in future
No use today but we plan to use in future
50%
Limited use today
23%
Extensive use today
Don´t know
11%
Source: The Economist Intelligence Unit survey, August 2015
16
Robots on the payroll
Here, there is a clear distinction between large and small companies: at companies with over
US$500m in annual revenue, over half of respondents say their organisations are making extensive
or limited use of robotics. By contrast, at companies with revenue of less than US$500m, only 27%
are using robotics.
This may be due to the investment required. A September 2015 report from strategy house Boston
Consulting Group (BCG), How Robots Will Redefine Competitiveness, finds that the total cost of
purchasing and deploying a robotics system for spot welding in the US automotive industry was
US$133,000 in 2014 and that the costs of peripheral equipment—such as sensors, displays and
expensive safety structures that protect workers—are often greater than the cost of the robots
themselves.
But prices are dropping quickly, the report’s authors note. By 2025, that average price tag is expected to fall by 22% to around US$103,000. At the same time, the emergence of lower-cost robots
such as Rethink Robotics’ Baxter and Sawyer models, which cost under US$40,000, is opening
up the field to small and medium-sized enterprises.
Unsurprisingly, the most common application of robotics among survey respondents is manufacturing, as identified by nearly half (48%) of respondents who are using the technology. Manufacturing
is the heartland of robotics, and companies in the sector have been using robots since the 1930s.
The second most common application is a more recent innovation: warehouse or stock management, as cited by 36% of robot-using respondents. Notably, this application is more common than
manufacturing among respondents who are not using robotics today but plan to do so in future.
This suggests that use of the technology will grow faster in the warehouse than on the factory floor
in the near future.
CHART 6: Manufacturing is the most common application of robotics
In which of the following functions do you use or plan to use robotics over the next 3-5 years? % of respondents who are using or planning to use robotics
48%
Manufacturing
36%
Warehouse/stock management
20%
Customer service
Delivery/transportation
18%
15%
Infrastructure management
Construction
8%
Other (please specify)
6%
0%
10%
20%
30%
40%
50%
60%
Source: The Economist Intelligence Unit survey, August 2015
17
Robots on the payroll
More applications will become viable as the cost of robotics falls. Already, some companies
are proving remarkably inventive in how they deploy the technology: low-cost airline easyJet, for
example, is investigating the use of automation in maintaining the company’s fleet of aircraft.
Earlier this year engineering chief Ian Davies and his team successfully completed the first trials with
an automated “quadcopter” drone, equipped with a video camera, to check aircraft for signs of
lightning damage. He believes that unmanned aerial vehicles (UAVs) could help reduce inspection
times from several hours to just half an hour, meaning that aircraft in good working order could be
back in service in a fraction of the time, avoiding costly delays.
They are also safer, he adds. “Typically, we’d have engineers up on cherry-pickers, wearing
harnesses, trying to get close to areas of suspected damage. They’re spending 90% of their time
trying to position themselves safely and only 10% of their time actually doing the inspection.”
The primary driver of robotics adoption is a short supply of highly skilled physical labour, the EIU
survey reveals. Of those respondents who identify “high demand for high-skilled physical labour”
among their key staffing issues, 67% are making some use of robotics.
At EasyJet, the driving force behind automation is to relieve demand for highly skilled labour by
eliminating many of the unskilled tasks that engineers currently need to do. In that way, says Mr
Davies, their time is better spent on higher-value work and on driving new innovations for the
company.
“We [should be] using skilled engineers to do skilled engineering work, rather than using them to
drive cherry-pickers and operate lifts, which is a huge waste,” he explains. “We’re looking to eliminate that waste by using automation, so that engineers can spend more time using their skills on
value-added, analytical work.”
He admits that the prospect of increasing automation was not universally welcomed at first. “With
the workforce in general and unions and so on, there can be some scepticism to begin with,” he
recalls. “But once they see what we’re trying to achieve—the health-and-safety aspects, the speed
aspects—they’re more accommodating.”
The impact of robots on workers has been much discussed in recent times, and any company
introducing them will have to contend with concern or even outright opposition from their workers.
Mr Brooks of Rethink Robotics argues that robots and humans are not in competition: they are
complementary. “While robots can handle monotonous, potentially dangerous tasks on the production line, humans are being allowed to move to tasks that require greater dexterity, cognition
and a higher level of intelligence,” he says. “These robots are not a replacement for humans, but a
tool that is helping to make their job more efficient and interesting.”
The question on everybody’s lips, though, is whether the use of robotics will reduce job opportunities for physical workers, skilled or unskilled. This is a line of reasoning that Ocado’s Mr Clarke
finds frustrating.
“Ocado started out as a business determined to use automation for the fulfilment and delivery of
groceries, [at a time] when all the incumbents were convinced that doing it manually, in physical
shops, was the only sensible way,” he says. “As we have developed as a business, we have created almost 10,000 jobs.”
“It’s missing the point to suggest that, if we didn’t have automation, we would employ more people,
because that argument fails to recognise that we also wouldn’t have a business of any significant
scale, so we wouldn’t have a need for a large number of employees in the first place”.
18
Robots on the payroll
“Without automation, we would just be a corner shop, with a couple of people on bicycles doing
the deliveries.”
everis view
Traditionally, robotic applications were used in warehouses and factories to automate repetitive and
precision tasks within large mass-production chains.
With the appearance of new technology and the
reduction of costs in hardware, we see three important robotic trends that may lead smart companies to
rethink its use:
1. Industrial robots have always been a difficult
and costly technical solution to a specific production problem. However, a new breed of
lightweight learning robots, such as Baxter from Rethink Robotics or NEXTAGE from
Kawada, offer the possibility of reusing robots
for different tasks as needed. This new type of
robot can be configured for fully customised
production series—a far cry from the 1980s
mass production paradigm for use of robots.
The new type of robot can even be taken out
of factories and used in other settings, such as
in hotels or restaurants.
2. Cloud robotics—in which the knowledge,
skills, and the team-interaction of robots are
no longer hard-coded into the robots themselves, but instead stored in cloud servers, where
all the information from sensors and interactions is processed—is gaining ground. This
enables operators to manage the robots to
work together in the most efficient and coordinated way. For example, Kiva Robotics (now
Amazon Robotics) uses simple robot hardware
connected to a powerful server that co-ordinates hundreds of robots in huge warehouses.
3. Robots are leaving the confines of industrial environments and—in new and different
shapes—are starting to permeate society.
Projects such as the self-driving car (a robot
disguised as a car), drones and exoskeletons
are clear examples. There is also a new wave
of consumer products beyond the cleaning
robots. Projects such as Jibo (a family personal robot) promise to change the way in
which we interact with the digital world in a
more physical way.
19
Robots on the payroll
Tegra Medical reduces rejects with new robot arms
Faced with rising manufacturing costs and a customer base that increasingly expects generous
discounts, executives at Tegra Medical, a Boston, Massachusetts-based contract manufacturer of
medical devices, recently invested in three robot arms from Universal Robots (UR).
Today, these robots tend machining cells that produce artery closure and meniscal repair devices
implanted into cardiac patients. Two are responsible for picking up blanks, moving them between
a lathe, a grinder and a conveyer in a cycle that now takes only ten seconds, compared with 22
seconds using manual labour. The third feeds three different part numbers simultaneously into the
same machining cycle, in a mixed-model manufacturing cell.
“Being in the medical industry, we can’t change our process without notifying our customers and
going through validation activity,” says Hal Blenkhorn, Tegra Medical’s director of engineering. “But
by simply replacing the operator with the robot, we just changed the handling of components in
between the processes. That was a huge win for us.”
Using the robots has freed up the time of 11 full-time workers, who are now handling more complex
tasks and ensure improved product quality, he adds. “With the UR robots, we only get a few rejects
per day. Before, that number was significantly higher.”
In under a year, one machining cell equipped with a UR robotic arm recently produced its one-millionth part, according to Mr Blenkhorn.
“Accuracy and repeatability over time was a big concern for us,” he says. “We were questioning
whether we could put the robot through this kind of duty cycle in a high-volume cell and get
year-after-year repeatability—but it is as good today as a year ago, when we turned the cell on.”
20
Machine intelligence at work
4. Machine intelligence at work
At Spring Venture Group, a Missouri-based company that sells health insurance policies to US
seniors, employees like to joke: “One of these days, Mary’s going to take over all of our jobs.”
“Mary” is a virtual persona, based on software from sales conversion management specialist Conversica. “She” follows up leads from which sales executives have failed to get a response and
engages with them via email. Once “she” gets confirmation from prospects of their intent to buy,
Mary alerts a human colleague to follow up by telephone and close the deal.
“I was sceptical at first about the results we’d get, but I had one of those moments where I didn’t
want to be the guy who said no to a technology that could transform the way we work,” explains
Alex Allen, vice president of marketing at Spring Venture Group.
“We had Conversica run a test on 10,000 leads that we’d considered ‘dead’ and stopped calling,
and the results we got were shocking,” Mr Allen recalls. “The cost per acquisition was about 25%
lower than using our sales executives to keep calling clients until they got a response.”
Today, Mary works through between 15,000 and 20,000 leads per quarter, Mr Allen says, enabling
sales agents to spend their time more productively, following up leads that have a better chance of
a sale at the end of the process.
Spring Venture Group is far from alone in its use of artificial intelligence or machine learning. In the
EIU survey, 43% of respondents say their organisation makes use of AI today. Only 13% say they
use it extensively, however; the remaining 30% use it only in a limited capacity. Meanwhile, more
than one-quarter of respondents (26%) plan to use AI in future.
Driving this adoption is a surfeit of clerical work that would otherwise require human intervention,
the survey suggests: 62% of respondents who identify high demand for low-skilled clerical workers
as one of their key staffing challenges have adopted AI, a greater proportion than any other group.
By far the most common application of the technology is data analysis. Of those respondents who
make use of AI, almost two-thirds (65%) do so in order to support data analytics.
CHART 7: Data analysis is the most common application of artificial intelligence
In which of the following functions do you use or plan to use artificial intelligence/machine learning over the
next 3-5 years? % of respondents who are using or plan to use AI/machine learning
65%
Data analysis
37%
Customer service
34%
Financial analysis and planning
Sales and marketing
30%
18%
Internal admin/business processes
E-commerce
17%
Other (please specify)
4%
0%
10%
20%
Source: The Economist Intelligence Unit survey, August 2015
30%
40%
50%
60%
70%
21
Machine intelligence at work
As digital technology has hugely expanded the volume of data that companies can collect, it stands
to reason that they have recruited machine intelligence to help make sense of it. One of the areas in
which AI has made particular progress in recent years is pattern recognition, which has a number
of applications in business. For example, online media companies such as Amazon, Spotify and
Netflix apply AI techniques to their customer data to understand variations in personal taste and
use that understanding to make recommendations for books, music or movies.
The other most common drivers, albeit significantly less popular, are customer service (37%),
financial analysis and planning (34%) and sales and marketing (30%). The fact that companies
would choose to interact with customers and prospects via automated means is a reflection of how
data-intensive many client relationships have become.
Australia-based bank ANZ, for example, has used IBM’s “cognitive computing” platform Watson,
which employs a number of AI techniques to help financial advisers provide wealth-management
strategies. The tool rapidly analyses information about the client’s own account as well as market
trends and assists the advisers as they compile a personalised report. According to IBM executives, the aim is to reduce the time it takes to create these reports from weeks to a single session.
Robbie Allen, CEO of AI-driven analytics company Automated Insights, believes that this combination of automated number-crunching and human analysis characterises the work of the future.
“I see a real future for computers being used to extract insight from data, but with humans then
analysing those insights, using the strengths of interpretation that they can bring to the equation in
order to create strategy,” he says.
Nevertheless, just as robotics can be seen as a threat to physical workers, so too can AI be perceived as competition for clerical staff. Again, executives who wish to introduce software-based
automation may face opposition from workers.
Daniel Nadler is CEO of Kensho Technologies, a company specialising in AI for the financial services industry with the goal of training computers to perform analytical tasks for which many banks
currently employ expensive white-collar workers or, as he puts it, “automating human-intensive
knowledge work”.
Kensho’s technology uses AI to take natural-language queries posed by bank employees and
respond to them in the form of quantitative, numerical answers. Today, this work that is mostly
performed by human employees, which Mr Nadler considers suboptimal.
“The banking system has possibly the worst ratio of all industries of highly paid people performing
tasks that do little to add value,” he says. “For many of them, their jobs revolve around moving
columns of data between spreadsheets in preparation for analysis by other employees higher up
the chain.”
AI certainly jeopardises these jobs, Mr Nadler believes. “If you’re one of these tens of thousands
of mid-level people, then yes, you should be worried about your job,” he says. “There’s no point in
being overly delicate about that issue: you’re performing work that can be done faster and more
accurately today by AI, and that can be a major boost to efficiency in many financial services
companies.”
“But for higher, cognitive analytic functions you still need humans—you need really smart humans,
in fact. And if as a bank you’ve got those rote, mechanical tasks covered by automation, then you
can have more smart humans doing more smart things. I see AI as a ‘force multiplier’ that dramatically increases the efficiency of a small group of people performing highly specialised work.”
22
Machine intelligence at work
As well as increasing their efficiency, he adds, it also allows these “smart people” to turn their minds
to innovation: identifying new markets to target, new assets to explore, and new products and
services to launch.
everis view
At everis, we deeply believe that machine intelligence represents the dawn of a new type of
industrial revolution. In the first industrial revolution,
the introduction of the steam engine expanded the
range of work beyond what could be done by animals, humans or natural phenomena in a sustainable way. This allowed humans to do things they had
never been able to do before, such as flying, We
think the current advances in machine intelligence
(neural network models and the computing power
to process them) will similarly enable humans to
perform unprecedented cognitive tasks.
This expanded ability will have a tremendous impact
on organisations, well beyond the simple automation
of many current tasks. It will augment peoples’ ability
to accomplish more complex tasks in a more productive way. An early but very illustrative example could
be Waze, the community-based traffic and navigation app acquired by Google, which helps individuals
make decisions based on a dynamic set of variables.
We expect that machine intelligence will move soon
from back-end operations to the front-end of organisations and will become instrumental in tasks such
as customer acquisition.
It is, however, also important to consider the implications and consequences of these new capabilities.
23
Machine intelligence at work
Associated Press puts AI on the earnings beat
“I could see that automation was going to have a place in journalism somehow, and I wanted
Associated Press to be ahead of that curve, not behind it—or a victim of it.”
This is how Lou Ferrara, vice president and managing editor at Associated Press (AP), the global
news service, describes his decision to use AI software from Automated Insights to digitise the
process of reporting on the financial results of US-listed companies.
Earnings reports had become the bane of many AP journalists’ lives, he says. The stories had a
relatively low value to readers compared with the more in-depth analysis and reportage that its
staffers were able to offer. Worse, some earnings releases were going unreported owing to the
constraints on their time.
In mid-2014 AP began automating earnings reports using Automated Insights’ software, but
with an editor comparing the stories produced in that way with the press releases issued by the
companies involved.
“We did that for a whole financial quarter, not publishing them until we’d checked them. The following quarter we took automated reporting live. Now the story goes straight to the wire without
any human intervention.”
In 2015 the process has been live throughout. Now Mr Ferrara is testing automated story production with lower-audience sports results—college-level baseball, for example, and lower-division football and basketball. “I have demand for these stories, but not the staff to produce them,” he says.
It is in more data-driven stories that Mr Ferrara sees the most value for automated reporting.
“There will always be story-creation and news-gathering and analysis tasks that need to be provided by an experienced reporter—our audience expects that from us,” he explains. “But stories
that are based on pure data—earnings or game scores—that’s not the place where you need to
deploy that reporter.”
According to Mr Ferrara, the driving force behind AP’s use of automated reporting is not to reduce
headcount. “My stated goal has never been about jobs,” he insists. “It’s about how we spend our
time. Whether I have 100 staff or 20 staff, it’s about how much time I have to produce the content
we need to provide with the staff I have. Automation is part of the solution to that.”
In other words, he is not looking to put journalists out of work. He is looking to extend the range of
coverage that the company can provide to its readers. In the case of corporate financial results, for
example, the use of AI has increased the number of companies covered by AP by a factor of over
ten—from around 300 to 4,000.
24
The on-demand workforce
5. The on-demand workforce
When Shopguard, a Hungary-based supplier of shop fittings for displaying and securing consumer
electronic devices, expanded into the US a few years ago, it needed a way to install and maintain
its products at retail outlets across the country.
At first, the company’s vice president of US sales and operations, Tanya Perry, tried working with
third-party providers of technicians, or “site representation firms”, but quickly found that response
times were too slow and that pockets of the country remained uncovered. She then turned to Work
Market, an on-demand, crowdsourced labour platform, in order to identify and manage qualified
freelance technicians to cover the work required instead.
“At first I was really, really nervous,” she recalls. “My main concern was there’d be a lack of human
contact between ourselves and the technicians representing us in the field. We’d used third-party
rep firms in the past, because they offer the promise of a single point of contact and someone else
to manage technicians on your behalf. But that simply hadn’t worked out for us. In fact, it had become the biggest thorn in my side.
“I knew I was taking a risk by using Work Market, but I also knew I had to try another way.”
Ms Perry says she has been “incredibly impressed” by the work ethic and quality of service provided by the people that she accesses on Work Market. “These people are self-employed technicians who have a very clear understanding that, in order to be successful, they have to perform
well. They have to turn up on time, do the job well, trouble-shoot where needed. They make their
living on being able to figure stuff out, on being resourceful, good communicators, and they’re far
more experienced and dedicated as a result.”
This, she adds, has allowed Shopguard US to see a dramatic uptick in the percentage of installations that are completed successfully on the first visit, allowing it to reduce the cost of service visits
by 10%. And that, in turn, has led to better customer satisfaction—and the time saved by working
in this way has meant that Ms Perry and her internal team have more time to focus on business
development work to grow the company’s customer base.
Work Market is one example of a new breed of labour-sourcing service, in which businesses or
individuals use the reach of the Internet to find freelance workers, often at very late notice, to perform certain tasks. Other freelancing and staff augmentation platforms include Elance, TaskRabbit
and Gigwalk.
The range of skills accessible to employers in this way is seemingly limitless. Amazon’s Mechanical
Turk marketplace, for example, posts jobs that range from transcription work to filling out an online
survey. Workers (or “Turkers”) can then browse for available jobs and perform them for money.
Another approach is to set a competition: Kaggle, for example, is an online service through which
organisations can offer prizes for solving data analytics problems.
One of the defining characteristics of the crowdsourced model, as distinct from conventional outsourcing, is that it operates in a similar manner to cloud computing: companies can achieve considerable scale but on a temporary basis, only paying for that scale when it is need. Indeed, it has
been referred to as “the cloud of jobs”.
It’s a model that has worked well for US-based domestic appliance manufacturer Whirlpool. In
2014, when the company launched its Express Clothing Care System, a steamer/iron hybrid, it
wanted to ensure that it was getting the best from its merchandising and promotional spend. It
used the Gigwalk service to recruit people to visit retailers and check whether the products were
25
The on-demand workforce
positioned prominently and demonstrated correctly. Users of Gigwalk’s app were able to quickly
spot a fee-paying opportunity at a store in their vicinity, record their observations and send their
feedback to the company. This demonstrates how the model allows companies to rapidly scale
labour up and down according to demand.
The model has already been widely adopted, with some 44% of respondents saying their organisations use on-demand, crowdsourced labour today. Just 12% say they use it extensively, however,
while 32% say their use is limited. A further 20% plan to use the model in future.
The approach is most common in the US: 58% of US survey respondents say their organisation
makes some use of on-demand, crowdsourced labour. By comparison, 44% of respondents in
Latin America make some use of such services, 39% in Asia-Pacific and 35% in Europe.
CHART 8: 44% of respondents say their organisation makes some use of on-demand,
crowdsourced labour today
To your knowledge, to what extent does your organisation currently use on-demand, crowdsourced labour?
6%
12%
30%
No use today and no plans to use in future
No use today but we plan to use in future
Limited use today
Extensive use today
32%
20%
Source: The Economist Intelligence Unit survey, August 2015
26
Don´t know
The on-demand workforce
CHART 9: Hiring creative talent is the most common application of on-demand, crowdsourced labour
In which, of the following functions do you use or plan to use on-demand, crowdsourced labour through
sites such as eLance etc? % of respondents who are using or plan to use on-demand, crowdsourced labour
Creative work, eg, graphic
design/copy writing
55%
42%
Software development
41%
IT support
22%
Finance and accounting
Sales and marketing
19%
Transportation
19%
17%
Legal and compliance work
Office administration
16%
Other (please specify)
2%
0%
10%
20%
30%
40%
50%
60%
Source: The Economist Intelligence Unit survey, August 2015
The use of on-demand labour presents its own challenges, and executives acknowledge these. For
example, 74% of respondents to the EIU survey believe that using contract or short-term labour
prevents organisations from building knowledge. The same proportion say that offering employees
job security is important to attract top talent.
Clearly, though, few organisations are about to switch their entire workforce to the on-demand model. Today, companies are most likely to use the model to hire workers whose talents are not core
to the proposition of the business, the survey suggests.
The most common application of the on-demand model is to recruit for creative work, such as
graphic design or copywriting, cited by 55% of respondents who are using or plan to use on-demand, crowdsourced labour. This is followed by software development (42%), IT support (41%)
and finance and accounting (22%).
Nevertheless, executives may feel uneasy about relying on a remote and transient workforce to
conduct their business. One way to combat this unease is to achieve data-driven visibility in the
freelance workforce.
Bazaarvoice is a US-based marketing services company that moderates online customer reviews
for clients including Intercontinental Hotels Group, automotive maker Lexus and retailers such as
Debenhams, Argos and Crate & Barrel. To do so, it relies on a worldwide team of some 330 remote
freelance workers.
The cost is not inconsiderable: the freelance workforce costs the company some US$3m per year,
around 2% of annual revenue. According to Jennifer Griffin, vice president of content integrity and
insights at Bazaarvoice, this expense is justified by analysing the performance of the freelance
workforce in detail.
27
The on-demand workforce
“We’re lucky in that we’re drowning in data,” she explains. “We can look at how fast a freelancer
works, how many reviews they get through per hour, what their accuracy and quality is like. That’s
key for any management team contemplating using a remote workforce—the more quantitative
[you can be], the better.”
But some questions cannot be answered by data analysis. Thanks to Uber, the legal status of
temporary workers sourced through digital means is currently the subject of high-profile debate in
many countries.
The “ride-sharing” company’s business model is entirely reliant on on-demand, crowdsourced labour—independent drivers looking to make some money by using their own vehicles to transport
customers who book a ride on the service.
It has been dogged by controversy at every stage in its evolution. In several jurisdictions, Uber is
waging battles with authorities over whether or not its drivers are full employees (and therefore
entitled to certain rights and benefits) or simple contractors (as the company argues). Most notably, the California Labour Commission ruled in June 2015 that they fell into the former category, a
decision against which Uber has appealed.
According to David Plouffe, senior vice president of policy and strategy at the company (and former campaign manager for Barack Obama’s 2008 successful presidential bid), Uber now provides
work for some 20,000 drivers in London, 45,000 in Los Angeles and 25,000 in Chicago, among
others.
“They’re teachers, retirees, students, parents—they may drive for a few months, make some money, then stop,” he explains. “They may choose to vary their hours from week to week, working
five hours one week and 15 the next, according to their other commitments. For many people, it’s
a good economic opportunity.”
As governments the world over ponder the legal status of Uber drivers and whether to make some
kind of regulatory intervention, executives could be forgiven for taking a wait-and-see attitude before making a strategic commitment to the on-demand, crowdsourced labour model.
However, given that the model is already widespread, they should make sure that they are aware
of how their organisation is using it, how it fits within their overall staffing strategy, and consider the
impact on the engagement and well-being of their existing workforce.
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The on-demand workforce
everis view
Digitisation of the workforce goes beyond introducing new technology; it affects relationships among
colleagues and between employers and employees.
So when a workplace is digitised, employers have to
rethink how they source talent and how they manage their employees’ relationship with the company.
Some guideposts are appearing already. For example, we know from recent studies (such as the 2015
“Internet Trends” report of venture capital firm Kleiner
Perkins Caufield & Byers) that more global talent is
looking for jobs that are flexible in terms of career development, corporate structure, projects, schedules,
culture etc.
With this in mind we should consider the on-demand
workforce not just as a group to take on tasks that
do not add value to our core business, but also as
a source of talent and skills that we don’t have inside our corporations, are hard to find, or would take
months or years to develop in-house. This is not a
simple matter, since it implies that companies may
increasingly count on external talent for core value
operations, and not only for support tasks.
As Bill Joy, co-founder of Sun Microsystems, says:
“No matter who you are, most of the smartest people
work for someone else.” These platforms are therefore a new way to access a global, talented and highly
specialised workforce. To mention a few examples:
incentive-based competitions such as Kaggle, XPRIZE, InnoCentive and OpenIDEO have helped companies find innovative solutions to hard questions.
29
The on-demand workforce
The Container Store hires the crowd to test its apps
Like most retailers today, The Container Store is locked in a fierce battle to give customers a great
online experience on their mobile phones and tablets. One of the biggest challenges is making
sure that their customer experience is the same, whether the customer uses an Apple, Android,
Microsoft or other device, says Brad Schneider, the retailer’s director of applications development.
The breadth of devices available is already staggering, and we see no end to the fragmentation,” he
says. “This is not a space that’s consolidating, so the problem of multiple devices running multiple
browsers that are all evolving rapidly is one that we know is here to stay.”
For the past five years The Container Store has used Applause, a crowdsourced app-testing service, to relieve some of the strain on its nine-strong in-house quality assurance (QA) and testing
team. The work is passed to Applause’s large community of independent software developers.
This additional resource recently came in handy when the retailer launched new “Click and Pick-up”
services on mobile, which allow customers to make a purchase online and then pick it up in-store
or from the kerbside in front of the store. In the run-up to collection, customers can use the mobile
app to alert store employees that they are on their way, while the store can keep them updated on
where to collect their item and which member of staff will hand it over.
“We had Applause testers doing physical tests: placing orders on mobile, going to the store and
reporting back on how it all worked. It wasn’t something we could do ourselves, because we’re
biased—we know how our systems work and what expectations there are. So using outside testers meant we got some really good insights from a true outsider’s perspective.”
30
Conclusion
Conclusion
In the face of growing competition for talent, company executives are enthusiastic about the
possibilities of workforce digitisation. They acknowledge the need to digitise their labour practices
and believe that their ability to do so effectively will contribute to their future success.
As this study reveals, robotics, AI and on-demand, crowdsourced labour are by no means rare pursuits—around one in four companies makes some use of each of them. Furthermore, they are on
the corporate agenda, with over 50% of companies surveyed having drawn up a strategy related
to their use.
Only a minority of companies have put that strategy into practice. This is understandable, given
that many of these techniques have only recently become possible or affordable. When they are
involved in their deployment, executives are most likely focused on practical considerations: what
will this technology cost, and how much will it boost productivity?
Going forward, that is unlikely to be sufficient. Workforce digitisation has the potential to transform
the working lives of millions of people, not necessarily for the better. Executives owe it to their
employees, their shareholders and society at large to be aware of the broader impact of their
workforce digitisation strategies.
Above all, they must think creatively: what might workforce digitisation enable their business to
achieve that seems difficult or even impossible today? In order to reap the real benefits of these
trends, they need to consider how they might contribute to company-wide innovation, new strategies, new directions.
At any large organisation, this is a trend that is already under way. Business leaders would be
advised to investigate how automation and crowdsourced labour are being used within their
organisation, what impact they are having on the workforce, and how they are affecting their
company’s competitive positioning. Only then will be they be able to answer the tough questions
that a workforce digitisation strategy may well raise.
NEXT STEPS:
Start investigating
As we have seen in this report, many companies are already reaping the benefits of workplace
digitisation. To avoid being left behind, executives should be investing time and effort in exploring “the art of the possible”. As cognitive technologies and advanced robotics become more
accessible and less costly and freelance work pools grow, significant barriers to productivity and
innovation are falling.
Consider the future workforce
The types of work that businesses are able to offer human employees look likely to undergo a
radical reinvention in the years ahead. Executives need to consider what their workforces will
look like five, ten or even 20 years from now. What human skills will they need—and how might
they set about recruiting, developing and retaining them?. Above all, how might human strengths
and talents be best aligned with future strategies for growth and expansion?
Test the waters
Consider small-scale pilots, where possible, of the types of technologies discussed in this report.
Evaluate their impact on productivity and employee engagement. Analyse which different combinations of workplace digitisation and existing workforce strengths produce the best results, with input
from a wide group of internal departments, including (but not limited to) R&D and human resources.
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Argentina
Belgium
Brazil
Colombia
Chile
Italy
Mexico
Peru
Portugal
Spain
UK
USA
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