No-collar workforce: Humans and machines in one loop—collaborating in roles and new talent models Tech Trends 2018

With intelligent automation marching steadily toward broader adoption, media coverage of this historic technology disruption is turning increasingly alarmist. “New study: Artificial intelligence is coming for your jobs, millennials,”¹ announced one business news outlet recently. “US workers face higher risk of being replaced by robots,”² declared another.

These dire headlines may deliver impressive click stats, but they don’t consider a much more hopeful—and likely—scenario: In the near future, human workers and machines will work together seamlessly, each complementing the other’s efforts in a single loop of productivity. And, in turn, HR organizations will begin developing new strategies and tools for recruiting, managing, and training a hybrid human-machine workforce.

Notwithstanding sky-is-falling predictions, robotics, cognitive, and artificial intelligence (AI) will probably not displace most human workers. Yes, these tools offer opportunities to automate some repetitive low-level tasks. Perhaps more importantly, intelligent automation solutions may be able to augment human performance by automating certain parts of a task, thus freeing individuals to focus on more “human” aspects that require empathic problem-solving abilities, social skills, and emotional intelligence. For example, if retail banking transactions were automated, bank tellers would be able to spend more time interacting with and advising customers—and selling products.

Consider this: In a survey conducted for Deloitte’s 2017 Deloitte Global Human Capital Trends report, more than 10,000 HR and business leaders across 140 countries were asked about the potential impact of automation on the future of work. Only 20 percent said they would reduce the number of jobs at their companies. Most respondents (77 percent) said they will either retrain people to use new technology or will redesign jobs to better take advantage of human skills.³ Recent Deloitte UK research suggests that despite inroads by digital and smart technologies in the workplace, essential “human” skills will remain important for the foreseeable future.⁴

The future that this research foresees has arrived. During the next 18 to 24 months, expect more companies to embrace the emerging no-collar workforce trend by redesigning jobs and reimagining how work gets done in a hybrid human-and-machine environment.

For HR organizations in particular, this trend raises a number of fundamental questions. For example, how can companies approach performance management when the workforce includes bots and virtual workers? What about onboarding or retiring non-human workers? These are not theoretical questions. One critical dimension of the no-collar workforce trend involves creating an HR equivalent to support mechanical members of the worker cohort.

Given how entrenched traditional work, career, and HR models are, reorganizing and reskilling workers around automation will likely be challenging. It will require new ways of thinking about jobs, enterprise culture, technology, and, most importantly, people. Even with these challenges, the no-collar trend introduces opportunities that may be too promising to ignore. What if by augmenting a human’s performance, you could raise his productivity on the same scale that we have driven productivity in technology?

As they explore intelligent automation’s possibilities, many of those already embracing the no-collar trend no longer ask “what if.” For these pioneering companies, the only question is, “How soon?”

Workers (and bots) of the world, unite!

According to the 2017 Global Human Capital Trends report, 41 percent of executives surveyed said they have fully implemented or have made significant progress in adopting cognitive and AI technologies within their workforce. Another 34 percent of respondents have launched pilot programs.

Yet in the midst of such progress, only 17 percent of respondents said they are ready to manage a workforce in which people, robots, and AI work side by side.⁵

At this early stage of the no-collar workforce trend, there is no shame in being counted among the 83 percent who don’t have all the answers. Given the speed with which AI, cognitive, and robotics are evolving, today’s clear-cut answers will likely have limited shelf lives. Indeed, this trend, unlike some others examined in Tech Trends 2018, is more like a promising journey of discovery than a clearly delineated sprint toward a finish line. Every company has unique needs and goals and thus will approach questions of reorganization, talent, technology, and training differently. There are, however, several broad dimensions that will likely define any workforce transformation journey:

Culture. Chances are, your company culture is grounded in humans working in defined roles, performing specific tasks within established processes. These workers likely have fixed ideas about the nature of employment, their careers, and about technology’s supporting role in the bigger operational picture. But what will happen to this culture if you begin shifting some traditionally human roles and tasks to bots? Likewise, will workplace morale suffer as jobs get redesigned so that technology augments human performance? Finally, is it realistic to think that humans and technology can complement each other as equal partners in a unified seamless workforce? In the absence of hard answers to these and similar questions, workers and management alike often assume the worst, hence the raft of “AI Will Take Your Job” headlines.

The no-collar trend is not simply about deploying AI and bots. Rather, it is about creating new ways of working within a culture of human/machine collaboration. As you begin building this new culture, think of your hybrid talent base as the fulcrum that makes it possible for you to pivot toward the digital organization of the future. Workers accustomed to providing standard responses within the constraints of rigid processes become liberated by mechanical “co-workers” that not only automate entire processes but augment human workers as they perform higher-level tasks. Work culture becomes one of augmentation, not automation. As they acclimate to this new work environment, humans may begin reflexively looking for opportunities to leverage automation for tasks they perform. Moreover, these human workers can be held accountable for improving the productivity of their mechanical co-workers. Finally, in this culture, management can begin recognizing human workers for their creativity and social contributions rather than their throughput (since most throughput tasks will be automated).

Tech fluency. As companies transition from a traditional to an augmented workforce model, some may struggle to categorize and describe work in a way that connects it to AI, robotic process automation (RPA), and cognitive. Right now, we speak of these tools as technologies. But to understand how an augmented workforce can and should operate, we will need to speak of these technologies as components of the work. For example, we could map machine learning to problem solving; RPA might map to operations management.

But to categorize technologies as components of work, we must first understand what these technologies are, how they work, and how they can potentially add value as part of an augmented workforce. This is where tech fluency comes in. Being “fluent” in your company’s technologies means understanding critical systems—their capabilities and adjacencies, their strategic and operational value, and the particular possibilities they enable.⁶ In the context of workforce transformation, workers who possess an in-depth understanding of automation and the specific technologies that enable it will likely be able to view tech-driven transformation in its proper strategic context. They may also be able to adjust more readily to redesigned jobs and augmented processes.

Today, many professionals—and not just those working in IT—are dedicated to remaining tech fluent and staying on top of the latest innovations. However, companies planning to build an augmented workforce cannot assume that workers will be sufficiently fluent to adapt quickly to new technologies and roles. Developing innovative ways of learning and institutionalizing training opportunities can help workers contribute substantively, creatively, and consistently to transformational efforts, no matter their roles. This may be particularly important for HR employees who will be designing jobs for augmented environments.

HR for humans and machines. Once you begin viewing machines as workforce talent,⁷ you will likely need to answer the following questions about sourcing and integrating intelligent machines into your work environments:

• What work do we need to do that is hard to staff and hard to get done? What skills do we need to accomplish the work? How do we evaluate if a prospective hire’s skills match the skills we are looking for?
• How do we onboard new members of the workforce and get them started on the right foot?
• How do we introduce the new “talent” to their colleagues?
• How do we provide new hires with the security access and software they need to do their jobs? How do we handle changes to access and audit requirements?
• How do we evaluate their performance? Likewise, how do we fire them if they are not right for the job?

These questions probably sound familiar. HR organizations around the world already use them to guide their recruiting and talent management processes for human workers.

As workforces evolve to include mechanical talent, HR and IT may have to develop entirely new approaches for managing these workers—and the real risk of automating bad or inaccurate processes. For example, machine learning tools might begin delivering inaccurate outcomes, or AI algorithms could start performing tasks that add no value. In these scenarios, HR will “manage” automated workers by designing governance and control capabilities into them.

Meanwhile, HR will continue its traditional role of recruiting, training, and managing human workers, though its approach may need to be tailored to address potential issues that could arise from augmentation. For example, augmented workers will likely need technology- and role-specific training in order to upskill, cross-train, and meet the evolving demands of augmented roles. Likewise, to accurately gauge their performance, HR—working with IT and various team leaders—may have to create new metrics that factor in the degree to which augmentation reorients an individual’s role and affects her productivity.

Keep in mind that metrics and roles may need to evolve over time. The beauty and challenge of cognitive workers is they are constantly working and developing an ever more nuanced approach to tasks. In terms of productivity, this is tremendous. But in the context of augmentation, what happens to the human role when the augmenting technology evolves and grows? How will metrics accurately gauge human or machine performance when tasks and capabilities are no longer static? Likewise, how will they measure augmented performance (humans and machines working in concert to achieve individual tasks)?

Leading by example

Just as the no-collar trend may disrupt IT, finance, and customer service, so too could it disrupt HR organizations, their talent models, and the way they work. Some HR organizations are already playing leading roles in enterprise digital transformation. Likewise, many are developing new approaches for recruiting digital talent, and are deploying apps and a variety of digital tools to engage, train, and support employees. But in terms of process and tools, the opportunities that AI, cognitive, and robotics offer make HR’s digitization efforts to date seem quaint. In the near future, HR will likely begin redesigning its own processes around virtual agents, bots, and other tools that can answer questions, execute transactions, and provide training, among many other tasks traditionally performed by human workers.

What about using cognitive tools to manage mechanical workers? Another intriguing possibility in the no-collar workforce of the future.

Lessons from the front lines

NASA’s space-age workforce

One of NASA’s newest employees works at the Stennis Space Center. Fully credentialed, he operates out of Building 1111, has an email account, and handles mainly transactional administrative tasks. His name is George Washington, and he’s a bot.

“Rather than viewing bots as a replacement for people, I see them as a way to simplify work,” says Mark Glorioso, executive director of NASA Shared Services Center (NSSC). “We are building bots that will make our people more effective, so as we grow, we are able to do more without adding staff.”

George is one of a small team of bots that NASA has developed to take on rote, repetitive bookkeeping and organizational tasks so human workers may focus on higher-level, strategic activities. Conceived two years ago as part of NSSC’s drive to optimize budgetary resources, the “bots-as-a-service” program started to take shape in May 2017 when George went to work. Soon, Thomas Jefferson and other bots joined him.

Glorioso’s team chose to start small so they could measure the return on investment, as well as help ensure the bots would not inadvertently add to IT’s workload. They identified opportunities to integrate bots by creating journey maps and breaking up processes into analytical pieces—looking for tasks that could be automated. George’s responsibilities include cutting and pasting job candidates’ suitability reports from emails and incorporating the information into applications for the HR team. The other bots’ tasks include distributing funds for the CFO’s office and automating purchase requests for the CIO’s team. Tasks that took hours for a human to complete now take just minutes.

NASA has started to deploy bots throughout the agency. A decentralized approach allows the NSSC’s 10 centers to decide how they want to reposition their staff members, then lets them build their own bots according to the tasks they choose to automate. Each center runs its bots off a single bot community, so the initial investment is shared. Because each task may require robots with different skills, centers can choose software vendors that specialize in specific areas, such as finance. Glorioso’s team ensures that all bots across the 10 centers meet NASA standards, then pushes them into production and manages them. This allows NSSC to scale the bots program as needed. Rather than investing in infrastructure, the center invests in one bot at a time.

The buy-in of the human workforce has been a priority for NSSC from the start. Glorioso’s team demonstrated the bots for the business leads of the center’s major units, then let the leads present the technology to their own teams. They also instituted “Lunch and Learn” sessions to educate employees on the benefits of bots and demonstrate how they work. Staff quickly embraced the bot program as a way to automate repetitive, time-consuming tasks and actively suggested transactions that could be augmented with worker bots.

Although credentialed like human workers, the bots have performance reviews skewed to different metrics. For example, Glorioso’s team is considering turning over password resets to the bots. A bot should be able to handle many more password resets than a human employee, so a higher level of turnaround will be expected of them. However, the quality of the user experience will be the ultimate test. If users find it difficult to communicate with the bots, the experiment won’t be considered a success.

Glorioso says there will always be a need for humans on his team—their expertise is needed to approve budgetary requests, bring in new business, and assist the bots when there are unusual rules exceptions. As the program grows, Glorioso sees potential job creation in the areas of bot-building and bot-performance management: “I’d like to think ultimately we will hire people who can ‘bot-ify’ their own transactions. For now, we build the bots and show everyone how they can help. We are giving them a reason to build their own bot.”⁸

Exelon Utilities powers up the bots

Exelon provides power generation, energy sales, transmission, and delivery in 48 states, Washington, DC, and Canada. The company champions competition as a way to meet economic and environmental policy objectives, so driving efficiencies is key to achieving its overall mission. These efficiencies include optimizing its workforce to fuel innovative thinking. After seeing success with its Strategic Supplier Program—in which Exelon outsourced transactional work to free up IT employees for creative and analytical tasks—company leadership has begun exploring opportunities to augment its human workforce with bots.

“Innovation isn’t a group in an ivory tower—innovation is everyone’s job,” says Mark Browning, Exelon Utilities VP of IT and chief information officer. “It’s an expectation that we all innovate across the organization to reinvent ourselves as a utility. The only way to get there is to let go of transactional work and migrate resources to value-added work that helps the business achieve even greater performance and higher levels of service for our customers.”⁹

Exelon’s CEO has charged leadership throughout the enterprise with exploring the potential of robotic process automation to drive efficiencies and cost savings. The organization recently completed a multi-month assessment to identify areas of opportunity for deploying bots, and the IT organization is facilitating an initiative to build out pilots. A number of departments—IT, finance, supply chain, human resources, legal, risk, and communications—are evaluating their processes to recommend possible use cases that could prove out the capabilities and benefits. With work time-sliced across several different individuals, a key part of the roadmap is not just identifying what tasks are ripe for automation but determining how to adjust job definitions, how employees are organized, and how to navigate through the cultural implications.

“We were able to outsource transactional IT work, reduce costs, and redeploy employees to higher-value work, and we believe we can do that again as we shift to a robotic model,” Browning says. “We want to use RPA to offer employees the opportunity to do more challenging, satisfying work that directly contributes to the organization’s success.”

As Exelon builds a business case showing concrete return on investment, leaders are grappling with how the bots fit into its organizational structure. “It’s not just a technology issue—this affects our people and our mission.”

Browning sees a future in which RPA has matured within the organization, enabling his team to build out capabilities that leverage Exelon’s investments in big data, machine learning, next-generation ERP, the Internet of Things, and other technologies—intersecting to create a closed-loop cycle that could have an impact on business outcomes, he says. “We believe it’s a core competency we want to own and mature. We need to do this right, because RPA is as much about technology challenges and as it is about change management and cultural shifts.”

Risk implications

The Center for Cyber Safety and Education has predicted that there will be 1.8 million unfilled cybersecurity positions by 2022.¹⁰ An augmented workforce—one in which automation can carry out rote tasks to free up human workers for higher-level activities—could help fill that demand. However, corporations should consider how this no-collar workforce could change the dynamic of their existing operations.

Cultural

This new way of working already is affecting how the workforce interacts and engages. It’s not uncommon for employees to communicate with their teammates solely via email, social collaboration applications, or instant message, with unclear impacts on creative collaboration. This can be further complicated when teammates are bots, a development that could stymie knowledge sharing. For example, a cyber professional’s job includes collaborating with peers to build knowledge of attack mechanisms and to develop creative solutions. When automation replaces those functions, there may be less opportunity for interactive collaboration, which could affect the team’s effectiveness. However, with training of people and ongoing training and calibration of the machines, the two working together can help effectively execute a broader cyber strategy.

Additionally, teams augmented with robotic process automation could experience friction derived from the dynamic of mission-based humans versus rules-based bots. When humans perform a cybersecurity-related task, they can apply a sense of mission as well as judgment in executing their task, make exceptions when necessary, and change course quickly to react to immediate threats. But bots often possess limited situational awareness and may be unable to make decisions regarding exceptions. It is critical to automate tasks only after evaluating which functions may require a human’s judgment and capacity for decision-making.

Cyber

Bots can help mitigate cyber risk by automating control activities to facilitate reliability, consistency, and effectiveness. RPA capabilities can enable cyber automation, such as processing vast threat intelligence sources.

But bots themselves could be targets in an attack, exposing sensitive employee and customer data that could damage a company’s reputation. Protecting bot workers, IoT devices, applications, and networks—whether on-premises or in far-flung virtual offices—becomes paramount. Controls should be built in from the start, and then continuously monitored, tested, and adapted to new challenges as they emerge. Because this entails more than equipment decisions, comprising policy and personnel strategies as well, business and IT should work together closely to define cyber workplace guidelines to mitigate risk.

Legal and regulatory

As we automate tasks and augment workers, new regulatory and compliance issues may emerge. Privacy issues, for example, could be a concern, particularly for global organizations subject to the European Union’s General Data Protection Regulation. Workplace bots collecting and processing data through sensors, devices, cameras, and even microphones could inadvertently collect workers’ personal data, which may violate privacy laws in some countries. Additionally, bots performing tasks in highly regulated industries, such as finance, could prove liabilities if a network outage or equipment failure results in a breakdown of automated oversight functions. Finally, labor laws could evolve around as-yet-unanticipated issues as human workers increasingly collaborate with their robot counterparts.

Despite this uncharted territory, the no-collar workforce can help enhance cybersecurity planning and response and could improve overall risk management. Automation of functions such as threat intelligence, security application monitoring, and privilege management may result in greater consistency, reliability, and coverage.

Global impact

Robotic process automation is changing the way we work around the world. Findings from a survey of Deloitte leaders across 10 regions show that automation is affecting most regions, to some degree, across a variety of industries. Cognitive computing and artificial intelligence are not as widespread, but the no-collar workforce is a trend that global organizations likely will need to address if they want to stay competitive.

In Latin America, robotic process automation is of interest to mining and resource companies that require big data for critical decision-making. In Central Europe, robotics and cognitive automation will likely affect the large number of shared service centers and business process outsourcing providers located in the region. Likewise, the talent pool likely will shift from supporting simple processes to delivering solutions that require skills such as critical thinking. This is true for Northern Europe, as well, which expects new roles to emerge as global, around-the-clock, man-and-machine workforces develop; part of this change could involve a more prominent role for IT organizations. Australia’s increasing prioritization of customer and employee experiences, coupled with lower barriers to entry for cloud technologies, is fueling the adoption of augmenting and enabling technologies.

In Africa, the no-collar workforce presents complex challenges within developing markets with high unemployment rates. Highly regulated labor environments could present obstacles, although the region’s technology readiness and availability of cloud platforms could make it possible for organizations to gear up for this much-needed transformation.

Most respondents see RPA being widespread within a year or two, with artificial intelligence and cognitive computing taking a bit longer—from two to five years. All regions expect that some degree of upskilling will be necessary to make the shift.

Where do you start?

Building a no-collar workforce requires deliberate planning. Machines and humans can work well together if you anticipate the challenges, and put in place the resources and governance to make all elements of the hybrid workforce successful. The following initial steps can provide a framework for deconstructing existing roles into underlying jobs, determining which are uniquely human and which can be redesigned for augmentation.

• Assess your needs: Is the no-collar trend a viable option for your company? To answer this question, identify all the areas in your organization where mission-critical activities that do not contain uniquely human work elements occur. Are there opportunities to augment human performance in these areas? If so, are the opportunities compelling? In some companies, augmentation opportunities are potentially transformative; in others, not so much. Remember: Let needs, not technology, drive your strategy.
• Understand how work currently gets done: For each task within a given process, identify who is performing the task, the skills required to complete the task, and the technologies enabling not only this specific task but adjacent or dependent tasks within the larger process. This informational baseline will help you challenge your own assumptions about existing processes, and then explore different talent options and technologies that can be used in concert to improve overall process efficiency. It may also spark fresh ideas about the impact that automation will have on your organizational structure.
• Categorize skills and tasks: Define the difference between skills that only humans have, such as ethical or creative thinking, and nonessential tasks that machines can perform. Understanding that difference can eventually help you redesign jobs, identify opportunities for augmentation, and develop automation strategies.
• Investigate tools and tactics: What cognitive technologies and advanced robotics solutions are currently used in your industry? What new advances appear on the horizon? The speed of technological innovation is bringing disruptive tools online faster than ever. In this environment, IT, HR, and business leaders should stay up to speed on advances in intelligent automation, and try to identify how emerging capabilities and concepts could impact productivity and job design at their companies.
• Easy does it or full steam ahead? Different smart technologies require different approaches. Are you sufficiently ambitious to explore opportunities for “brute force” automation initiatives involving bots? Or does your ambition (and perhaps your budget) align more closely with less disruptive deployments of cognitive technologies or AI? Which approach better supports your organization’s overall mission and strategic priorities?