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Preparing for the digitisation of the workforce

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Written by:
Preparing for the digitisation of
the workforce
An everis report, written by The Economist Intelligence Unit
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Executive summary
About this research
Foreword
Introduction
1. The background to workforce digitisation
2. Putting strat...
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Executive summary
Executive summary
The world of work is changing, fast and fundamentally. Against a backdrop of difficul...
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Preparing for the digitisation of the workforce

  1. 1. Written by: Preparing for the digitisation of the workforce An everis report, written by The Economist Intelligence Unit
  2. 2. 3 Executive summary About this research Foreword Introduction 1. The background to workforce digitisation 2. Putting strategy into practice 3. Robots on the payroll 4. Machine intelligence at work 5. The on-demand workforce Conclusion 4 6 7 8 9 12 16 21 25 31
  3. 3. 4 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 la- bour. Executives certainly see technology as part of the solution: 82% of those surveyed for this re- port 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 exa- mined 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 nee- ded 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. 4. 5 Executive summary are helping companies extract insight and learn from the growing volume of data they collect. Pro- ponents 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 tech- nology 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 work- force digitisation, few executives surveyed for this report want to see jobs cut from their organi- sation. 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. 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
  6. 6. 7 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 emplo- yees’ children. After he experienced how kids produce their own astonishing movies, videogames, mu- sic, 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 repre- sent 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 expo- nential 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, howe- ver, 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. 7. 8 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 tech- nologies 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 manufactu- ring 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 emer- ging 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 per- forming 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. 8. 9 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, espe- cially 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 stru- ggles 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 de- mand, 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 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. 45%40%35%30%25%20%15%10%5%0% There are no issues High demand for low-skilled physical labour Low employee engagement and/or retention High demand for high-skilled physical labour High demand for high-skilled clerical workers Low employee wellbeing Inability to scale down employment levels in periods of low demand High demand for low-skilled clerical workers Inability to source specialist labour quickly enough to meet demand Limited local availability of specialist labour 7% 14% 14% 15% 21% 29% 31% 32% 37% 42% Source: The Economist Intelligence Unit survey, August 2015
  9. 9. 10 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 mar- ket 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 In- ternet, 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 soft- ware 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 hu- mans 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. 10. 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 everis view Nowadays, everybody is talking about digitisation. Digitisation of companies, the economy, the work- force—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 un- derstand, and one that allows us to use computers to become better players. This metaphor helps us to understand how a new di- gital medium can be used to augment our workforce in ways we are only just beginning to conceptualise. Source: The Economist Intelligence Unit survey, August 2015 3-5 years’ timeRight now 60%50%40%30%20%10%0% Geographic expansion Profit growth Organisational agility Digital innovation Revenue growth Cost reduction Employee wellbeing, engagement and loyalty 28% 54% 42% 24% 40% 31% 38% 36% 34% 36% 27% 40% 35% 53% The background to workforce digitisation 11
  11. 11. 12 Putting strategy into practice 2. Putting strategy into practice The need for companies to apply digital innovations to their employment and staffing issues is wi- dely 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 orga- nisation 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 Source: The Economist Intelligence Unit survey, August 2015 40%35%30%25%20%15%10%0% 5% 7% 20% 16% 35% 23% Not at all Discussed briefly Discussed at length but no action taken A formal strategy has been devised but not yet implemented A formal strategy has been devised and implemented
  12. 12. 13 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 organi- sation has redesigned business processes to allow for greater automation. Third, 40% of respon- dents 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 ma- nages labour using digital technology? % of respondents Source: The Economist Intelligence Unit survey, August 2015 4% 7% 13% 19% 25% 40% 42% 45% 50%45%40%35%30%25%20%15%10%0% 5% Other (please especify) Don´t know/not applicable A lack of desire to innovate Employment law in the countries we operate in A lack of understanding of new techniques and technologies Union protections of our employees Business processes that are too hard to change A lack of budget to adopt new techniques and technologies
  13. 13. 14 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 respon- dents 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 deve- lopment] 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 ques- tions 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. 14. 15 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 conside- rable 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 au- tomated era. “There’s also the issue of how wealth and skills will be distributed in the global eco- nomy 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. 15. 16 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 ex- pand 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 pro- duct-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 sys- tems 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? 50% 11% 23% 15% 3% No use today and no plans to use in future Limited use today Don´t know No use today but we plan to use in future Extensive use today Source: The Economist Intelligence Unit survey, August 2015
  16. 16. 17 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 expec- ted 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 manufactu- ring, 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 manage- ment, 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 respon- dents who are using or planning to use robotics Source: The Economist Intelligence Unit survey, August 2015 6% 8% 15% 18% 20% 36% 48% 60%50%40%30%20%10%0% Other (please specify) Construction Warehouse/stock management Delivery/transportation Infrastructure management Manufacturing Customer service
  17. 17. 18 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 elimi- nate 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 pro- duction 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 opportu- nities 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 crea- ted 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. 18. everis view Traditionally, robotic applications were used in wa- rehouses 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 impor- tant 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 pro- duction problem. However, a new breed of lightweight learning robots, such as Bax- ter 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 themsel- ves, but instead stored in cloud servers, where all the information from sensors and interac- tions is processed—is gaining ground. This enables operators to manage the robots to work together in the most efficient and coor- dinated way. For example, Kiva Robotics (now Amazon Robotics) uses simple robot hardware connected to a powerful server that co-ordina- tes hundreds of robots in huge warehouses. 3. Robots are leaving the confines of indus- trial 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 per- sonal robot) promise to change the way in which we interact with the digital world in a more physical way. “Without automation, we would just be a corner shop, with a couple of people on bicycles doing the deliveries.” Robots on the payroll 19
  19. 19. 20 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-mi- llionth 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. 20. 21 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 Con- versica. “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 Source: The Economist Intelligence Unit survey, August 2015 4% 17% 18% 30% 34% 37% 65% 70%60%50%40%30%20%10%0% Other (please specify) E-commerce Customer service Sales and marketing Internal admin/business processes Data analysis Financial analysis and planning
  21. 21. 22 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 executi- ves, 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 combi- nation 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 per- ceived 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 servi- ces 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 dra- matically increases the efficiency of a small group of people performing highly specialised work.”
  22. 22. everis view At everis, we deeply believe that machine in- telligence 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 ani- mals, humans or natural phenomena in a sustaina- ble 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 produc- tive way. An early but very illustrative example could be Waze, the community-based traffic and naviga- tion 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 organi- sations and will become instrumental in tasks such as customer acquisition. It is, however, also important to consider the implica- tions and consequences of these new capabilities. 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. Machine intelligence at work 23
  23. 23. 24 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 fo- llowing 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 produc- tion with lower-audience sports results—college-level baseball, for example, and lower-division foot- ball 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 pro- vided 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. 24. 25 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 be- come 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 pro- vided by the people that she accesses on Work Market. “These people are self-employed tech- nicians 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 installa- tions 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 per- form 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 out- sourcing, is that it operates in a similar manner to cloud computing: companies can achieve con- siderable 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. 25. 26 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 organisa- tions 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? Source: The Economist Intelligence Unit survey, August 2015 No use today and no plans to use in future Limited use today Don´t know No use today but we plan to use in future Extensive use today 30% 20% 32% 12% 6%
  26. 26. 27 The on-demand workforce CHART 9: Hiring creative talent is the most common application of on-demand, crowdsour- ced 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 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 mo- del. 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-de- mand, 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. Source: The Economist Intelligence Unit survey, August 2015 2% 16% 17% 19% 19% 22% 41% 42% 55% 60%50%40%30%20%10%0% Other (please specify) Office administration Finance and accounting Transportation Software development Legal and compliance work IT support Sales and marketing Creative work, eg, graphic design/copy writing
  27. 27. 28 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 la- bour—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 nota- bly, 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 for- mer 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 mo- ney, 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 be- fore 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.
  28. 28. everis view Digitisation of the workforce goes beyond introdu- cing 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 mana- ge their employees’ relationship with the company. Some guideposts are appearing already. For exam- ple, 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 de- velopment, 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 insi- de 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 therefo- re a new way to access a global, talented and highly specialised workforce. To mention a few examples: incentive-based competitions such as Kaggle, XPRI- ZE, InnoCentive and OpenIDEO have helped compa- nies find innovative solutions to hard questions. The on-demand workforce 29
  29. 29. 30 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 ser- vice, 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 tes- ters meant we got some really good insights from a true outsider’s perspective.”
  30. 30. 31 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 pur- suits—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 strate- gies, 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 explo- ring “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 combina- tions 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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