Automation is here to stay.
As an integral part of any digital transformation project, automating the repetitive, the manual, and the unnecessarily time-consuming is no longer a potential future strategy, but an immediate imperative. The productivity gains now being achieved by these projects mean that organisations who do not yet have an automation strategy risk being left behind by the competition.
Deloitte’s most recent Global RPA Survey found organisations reporting payback within 12 months, with over 90% benefiting from increased accuracy and compliance, and 86% seeing gains in productivity.1
Inevitably, with seismic technology shifts come equally radical alterations in the labour market, both in terms of the numbers of people and the types of skills required. New processes demand new ways of working and managing, and transformation projects of every size need people who can take advantage of the continually expanding possibilities of emerging technologies. Without the right knowledge and skills in place, automation projects are doomed either to fail, or to require many years’ investment before the requisite returns are achieved.
Finding and recruiting the right people is always a top-of-mind challenge for the C-suite, but this issue is more urgent and less tractable than before, and playing out against a backdrop of scaremongering headlines about robots ‘stealing our jobs’. In the US, the number of workers available per job opening fell to 0.88 at the end of 2020, its lowest level in 20 years . So how can enterprises close the skills gap quickly and effectively, while maintaining a fair and just working environment for all their people? We think the answer lies inside the organisation: re-skilling and up-skilling the people you already employ, rather than searching for increasingly scarce external talent.
The perception of workers being replaced by robots does not reflect the reality of automation. Automating repetitive tasks speeds up productivity and reduces the burden on employees. This creates opportunities for enterprises to leverage economies of speed, rather than economies of scale, freeing up employee time for them to concentrate on the complex tasks that can only be done by humans. Nor is it an either/or equation for many roles: people working hand-in-hand with intelligent automation can do the job better, quicker, and with less effort.
But does this higher productivity mean that fewer people are required overall? This fails to take into account all the new roles being created to build, manage and scale automations for organisations. McKinsey’s 2020 report on the future of jobs in Europe found that:
“….the effect of automation on the balance of jobs in Europe may not be as significant as is often believed….While automation adoption will grow over the next decade, a shrinking labor force on the continent means that, by 2030, finding sufficient workers with the required skills to fill the jobs that exist and are being created in Europe may be challenging.”
“Even if there is a net decline in jobs, filling available positions would nonetheless be challenging for European employers….Even with a decline of 9.4 million jobs…from the pre-pandemic levels, employment rates would stay stable.”
The most important benefit of automation is not reducing costs by reducing headcount: it’s doing more, better, and more quickly. The real problem for the enterprise is how to ensure the right skills are in place to carry out the new technology-related jobs. The most sought-after skill in IT right now is automation, and the demand for tech talent generally is so high that relying on people to expand their skills and move around the job market naturally will inevitably lead to scarcity of talent and runaway wage inflation.
At this year’s World Economic Forum summit, the Future of Work was a core theme on a challenging agenda that also sought to tackle issues such as climate change and inequality. (The irony of discussing the future of work at a summit being conducted virtually for the first time due to the world of work having undergone rapid and fundamental change was not lost on the participants.) The Future of Work is not a new topic: the WEF and many other organisations have been warning of fundamental changes coming to the labour market for many years. In its report modelling eight future scenarios in which the key variables were education, workforce mobility, and technological change, the WEF drew the conclusion that to avoid the more dystopian outcomes brought about by fast technological change, educating the workforce in new skills will be of vital importance.
“ The quality of and access to reskilling, upskilling and re-training support will determine how three billion people already in the world’s workforce will fare in the transition underway and engage with new opportunities in the labour market.”
If we take a sector-based approach, the Financial Services Skills Taskforce6 in the UK has indicated that over the next ten years although the overall size of the sector will remain relatively stable, the structure of job roles, specialisms and professions willl ook radically different because of trends in Automation and AI. The introduction and adoption of new technology to improve customer experience, managing risk, meeting regulatory requirements, and providing new products requires a varied blend of skillsets, knowledge, and behaviours.
The 2020 Future of Jobs Survey published by the WEF shows that the Financial Services sector is not the only one that is experiencing these shifts–there are similarities across all industries in strategic and redundant job roles reflecting the acceleration of automation and other emerging technologies. Growing in demand are roles such as Data Analysts and Scientists, AI and Machine Learning Specialists, Robotics Engineers and Process Automation Specialists all of which will require a well-defined career path and learning journey to support employees with their long-term development.
Tackling these trends means not leaving anyone behind. Workers carrying out low-skilled tasks must be given the opportunity to re-train into new roles, but building new skills into the workforce requires effort from a number of different sources. Governments have a responsibility to predict changes coming over the horizon and ensure that the workforce is fit to respond, through the education sector as well as through industry schemes, policy and funding.
In Singapore, the SkillsFuture7 initiative was created to provide Singaporeans with the opportunities to develop their fullest potential throughout life, regardless of their starting points. It provides information and training for employees at every level to increase their skills, as well as working with organisations such as the Institute of Banking and Finance to map the skills that particular industries will require in the future. As the Singapore Minister for Manpower Josephine Teo pointed out at Davos:
“It won’t be possible to save every job, the transformations will continue…but we must all try our level best to save every worker.”8
Singapore Minister for Manpower, Josephine Teo
The scheme also encourages individuals to become responsible for driving forward their own learning. Technology acceleration means that skills become obsolete in very short timeframes, so it is important to view training as a lifelong work in progress.
The third part of the jigsaw is the employer. There are significant incentives for employers to take an active part in re-skilling and up-skilling their workforce rather than relying on the market to provide. The investment required to train your own people in new roles more than repays itself in terms of securing hard-to-find skills. As Gartner advises in its look at how finance teams can use RPA:
“Consider using new RPA responsibilities as stretch opportunities for high-potential employees whose responsibilities will become obsolete with greater RPA adoption. This supports meaningful finance transformation instead of just cutting costs or head count.”9
Adopting a successful skills strategy requires identifying the right capabilities, competencies, and curricula for the workforce. This is often a time-consuming effort on the part of HR and L & D departments since there is no industry standard, but employers do need to approach this futuristically and clearly articulate future roles in their business, skills required and tasks that will be performed. Employers also need to conduct a skill gap analysis to help their people with a pathway for refreshing their skills and offering continuous learning opportunities. This means thinking laterally and broadly about the kinds of roles people can train for:
“Skills adjacency is defined as the proximity between the skills required for two different jobs. Among students at Udacity, a for-profit educational organization offering online technology courses….a significant 33 percent found a new job with only medium or low skills adjacency, indicating that reskilling someone from a non-tech role to a tech role can succeed.”10
This success is made even more likely by the fact that all the automation partners we work with embrace the low-code approach, committing themselves to producing robots that can be created, managed and scaled by administrators with minimal coding skills.
The cost benefits of training your own people are clear:
“Reskilling is cheaper than hiring. While reskilling an internal employee may cost $20,000 or less, the cost of hiring often costs $30,000 for recruitment alone, in addition to onboarding training. And new hires are two to three times more likely to then leave.”11
As well as the savings made by not having to onboard new people, retaining your existing workforce also means holding onto the cultural understanding that existing employees hold about an organisation, which value should not be underestimated. Investing in training your people into more interesting and fulfilling roles reaps benefits in terms of loyalty and has the potential to create lasting strong relationships between employer and employee.
This is why at Roboyo, we take a Human+ approach to building the workforce of the future. Our consultancy services are designed to embed skills and expertise in our clients’ organisations, establishing Centres of Excellence and robust governance to build employee capabilities. Our change management programmes support the culture to shift towards automation, and our training Academy provides skills training and certifications delivered by experienced industry professionals. Its time to get people learning.
Never miss an insight
Over the last 12 months but process automation (RPA) and its more ingenious cousin, intelligent automation (IA), have quietly moved from interesting pilot experiments to the top of almost every CEO’s to-do list.
In an era of radically transformative change which is disrupting and redefining traditional business models, a clear understanding of the following topics can make the competitive difference between winning and losing.
Over the last 12 months,
robotic process automation (RPA) and its more ingenious cousin, intelligent automation (IA), have quietly moved from interesting pilot experiments to the top of almost every CEO’s to-do list. As Forrester’s 2021 Predictions piece puts it:
Now, automation has moved to heated board-level discussions that often end with statements such as “If we don’t automate everything we can, we may not survive.”1
1. Organisations who started RPA projects 4-5 years ago are now demonstrating clear and significant value
A year is a long time in technology, and 4 years is a lifetime. Over that period, both the technology and the organisations implementing it have evolved dramatically, with excellent results. Deloitte’s most recent Global RPA Survey found organisations reporting payback within 12 months, with over 90% benefiting from increased accuracy and compliance, and 86% seeing gains in productivity.2 Putting in place the right skills and the right governance means that these early adopters are now past the initial investment stage and in a position of maturity, with stable operating costs bringing even faster paybacks, and meaning RPA can be scaled up into the wider business.
2. The first 10 automations are hard, but the next 50 are much easier
The learning curve for organisations starting their automation journey is often steep, especially when projects are not seen as strategic priorities. Gartner’s 2020 CFO survey showed 66% of respondents intending to focus on RPA over the coming year, but 56% anticipating challenges in implementation.3 Getting those first few automations up and running can be difficult – but once an organisation has them under its belt, what we see is the technology taking off at an exponential rate. With the right structures, knowledge and skills coming together, it becomes quick and cost-effective to implement automations in multiple areas of the business simultaneously, with demonstrable results.
3. RPA is a big step, but from there it’s just a hop to IA
In the same report, Forrester predicts that:
“… by the end of 2021, one out of every four remote workers will be supported by new forms of automation, either directly or indirectly…robotic process automation (RPA) bots combined with conversational intelligence and other intelligent automation will handle business tasks often invisible to the home worker.”4
Intelligent Automation combines robotic, intelligent (AI and machine learning) and autonomous systems to provide even greater gains in productivity. The foundations laid to bring RPA to an organisation mean that bringing in Intelligent Automation is a much easier task. The skills, knowledge and governance are in place but even more importantly, the culture shift for the organisation is well under way. Our experience at Roboyo working with organisations in sectors such as banking, insurance, automotive and manufacturing, and many others means we have supported this culture shift first hand.
Return on investment calculations are vital to automation projects, and many organisations want to see impacts achieved after one or two months, possibly three. But the shift in mindset for the whole organisation, from experimenting with automation to building it into the very fabric of the business, can sometimes take a little longer. Those that started this journey a few years ago are now able to take advantage of both exponential developments in the technology, and a workforce embracing the savings in time and effort that it brings.
So, if you haven’t started implementing IA in your organisation yet, is it too late? Thankfully, no. Those early adopters are undoubtedly starting to reap the benefits of their forward thinking in terms of higher productivity and efficiency, which could make them more competitive. However, newer, more sophisticated tools such as our platform Roboyo Converge can now dramatically speed up the automation journey of organisations only just starting out. Developed based on the expertise and experience we’ve built up over the last five years, it gives automation teams an end-to-end automation ecosystem to overcome the challenges of scoping, managing and scaling automations.
Clear-sighted organisations that bring automation to the top of the priority list, invest in the most up-to-date tools and skills, and address the structural, cultural and institutional factors that make automation a success, will see their productivity expand in leaps and bounds.
As the old saying goes, the best time to start your automation journey was five years ago. The second best time is now.
Never miss an insight. Sign up now.
As an integral part of any digital transformation project, automating the repetitive, the manual, and the unnecessarily time-consuming is no longer a potential future strategy, but an immediate imperative.
1. How will Intelligent Automation disrupt your industry in the next 2-10 years?
2. What should you expect of your future employees in an intelligent automation environment?
3. What is the future context of customers, competitors, and employees to future proof today’s investments in intelligent automation?
Intelligent automation can be applied in many areas of your business; however, organizations must take a holistic approach to maximize value and understand the forces of change influencing the future.
While some organizations may believe they have time before understanding and preparing for Intelligent Automation, this technology already is an integral part of our daily routines. Alexa, a bot (short for “robot”), reads stories to children and plays music with voice cues for seniors; the onset of the pandemic drove interactive sales of bots engaging in dialog with prospective customers via email, as well as qualifying sales opportunities; traffic reporting coupled with commuting advice…the list is endless. As in our private sphere, Intelligent Automation also has entered the business sector. A recent MIT study clarifies this.
During the last five years, perhaps the most apparent manifestation of change in the workforce is the ubiquity of intelligent automation technologies. Automation solutions create and update case management files for insurance companies, execute journal entries for banks and manage invoices to support procurement teams. Executives, managers, and office staff around the globe increasingly face demands to interact or even collaborate with digital workers – computer-generated “bots” that range from desktop macros all the way to multi-application solutions with interactive voice capabilities. As workers and companies around the globe shape the new norms of post-Covid dynamics, business leaders are in a race to build the strategies and operating models necessary to integrate a distributed workforce with software-driven solutions that change how people work. Bank of America analysts refer to these worker-robot collaborations as “robo sapiens,” and others refer to them as collaborative robots, or “cobots.”
Robotic Process Automation (RPA) is a critical part of Intelligent Automation. It is an innovative technology which automates structured business processes. RPA works just like one of your employees, interacting with the user interfaces of your existing applications and carrying out structured processes automatically. Automated solutions which use RPA can provide a company with many benefits including increased productivity, reduced costs, and accelerated ROI.
In 2016, RPA began appearing as the buzzword du jour in presentations and sales pitches around the globe. By 2019, the global RPA software market achieved a valuation of $1.41 billion dollars, and predictions for double-digit growth persist through at least 2024. Today, RPA is prevalent throughout many business sectors, including insurance, energy and utilities, manufacturing, healthcare, banking, and financial services. According to a 2019 study commissioned by UiPath, a leading RPA technology vendor and our software partner, and conducted by Forrester Consulting, 86% of respondents indicated increased efficiency, 57% reported enhanced customer service and 57% reported increased employee engagement.
Software sales growth is only one indicator in a complex network of trends resulting from the rapid and pervasive adoption of RPA, content intelligence applications, machine learning and natural language processing. According to Pitchbook, since 2010 RPA is considered an emerging trend. With the 185 RPA companies they are analyzing, there has been 244 deals and $8.76B capital invested.
The integration of RPA with AI takes software bot capabilities to a whole new level beyond rule-based processing.
These trends span strategy, operations and the technology mix underpinning all aspects of business in the 21st century. Coupled with the Macro Forces of Change that influence our collective futures (described below), the ascendency of automation is shifting the lives of every member of the workforce, personally and professionally.
Senior executives find themselves grappling with changing customer demands, new contests for competitive primacy and an ever-evolving technology landscape. Coupled with the social and economic headwinds engendered by the Covid-19 pandemic, leaders are embracing intelligent automation as a force multiplier when managing cost, efficiency, and business continuity challenges. 67% of executives agree they plan to accelerate the pace of implementation, and 90% anticipate increasing the investment in automation to increase workforce capacity over the next three years.
Successfully transitioning from investment and application implementation to workforce enablement requires a profound shift in methods and communication. Helping managers and employees to understand the motives for adopting automation requires a clear and well-communicated vision aligned with the company’s purpose and values. Automation may be the vehicle, but durable, visceral transformation occurs first and foremost at the human level. The shortest path to success with tools like RPA and chatbots is defined by customers or employees willing to adopt the new tools. Progressing from the c-suite agenda to integrate operations requires leadership to distill the vision into a comprehensible strategy and operating model and engage at every level iteratively and continually.
The composition and distribution of the workforce is shifting not only at a headlong pace but in ways that startle even the analysts. Across many organizations and industries, the demand for higher cognitive, socio-emotional, and technological skills are often at loggerheads with the immediacy of ever-faster productivity demands. The McKinsey Workforce Institute’s 2018 study cited the drastic shift in the competencies deemed critical for the evolving workforce. By 2030, the study predicts that employees will spend 41% to 50% more time using technological skills.
Leading enterprises are now beginning to ask how they can organize a blended workforce of humans and automation to leverage the complementary strengths each offers. How can they use automation to enable humans to make the most of their abilities, rather than replace them? Does the workforce trust the bots and learn to partner with them?
Without a clear plan, consistent communication and deep engagement, workers throughout the hierarchy can be circumspect. In fact, just 15% of workers believe their organization can manage the change successfully. That stark statistic is indicative of the need for commitment to a people-focused automation strategy. The hybrid organizational chart will inevitably include bots, but not considering and planning for potential displacement, either real or perceived, can have catastrophic implications.
There’s more to this than bold, all-hands notifications trumpeting the need to embrace the future. Effective leaders will begin by first evaluating the continuum of work the company does, assessing where intelligent automation augments the impact of human effort or can provide the capacity to shift people to higher-impact opportunities. Where automation can provide the highest impact with minimal or no human intervention, training and enablement are essential to bridge the gap between uncertainty and adoption.
Before adopting intelligent solutions into an organization, it is essential to develop a roadmap to ensure success – one where employees and managers also have bought into the company’s vision. Many of these technologies can offer immediate and measurable impacts to productivity, quality and even revenue acceleration. However, they are neither a panacea nor the commercial philosopher’s stone, transforming leaden activities into golden profits. Despite all the talk of chatbots, machine learning and robotic processing, intelligent automation needs to be focused on the human experience. Customer and employee experiences are at the core of every successful automation strategy, and as the pace of adoption increases, successful leaders will need to deepen their commitment to understanding and managing the forces driving change in the workforce and how technology can enhance employee’s ability to succeed in an increasingly dynamic present.
When planning to adopt Intelligent Technologies, it is critical for organizations to look beyond the technology disruptions and construct a holistic perspective on these forces which pushes to examine policy, environment, biology, psychology, and societal elements within the ecosystem. When evaluating the forces of change driving the future of automation in the workforce, several Macro Forces of Change should be evaluated in the context of your business:
Shifts in the balance of power across political, economic, and human entities transcend traditional boundaries and frameworks will disrupt how governments and businesses operate. In the last two years, there’s been a 78% increase in job posts on LinkedIn that mention work flexibility demonstrating the power of the workforce and causing new HR policies and resource competition.
2. Societal coalitions and collisions
Global connectivity creates new relationships while shifting beliefs and expectations create clashes with traditional shared assumptions and social norms. These new tribes influence beliefs around skills and development. The half-life of a skill is currently five years and likely will continue to decrease.
3. Bio-digital convergence
Pervasive and invasive technology further integrates humans and machines impacting human performance, policies, data privacy, and ethics. Research has found that up to 50% of time spent on job activities across all sectors could be automated with current technology.
4. Infrastructure adaptation
The convergence of physical, cyber, and human infrastructure creates a smart, boundaryless, global “interstructure,” which improves efficiency but increases friction between those who do or do not embrace this integration. Supporting a more virtual and global workforce, 95% of the world’s population will have access to the internet in 2030, up from 60% today.
5. Security everywhere
Disruptive technology, an increasingly connected society, and novel techniques, create an increasingly complex landscape. This feeling of ubiquitous threats ripples into the personal lives of employees and the data security of the extended organization network into employees’ homes. We are developing a security-everywhere mindset which bridges macro threats with micro security.
6. Trust elasticity
Connected humanity creates new relationships among people and institutions with differing behaviors and customs, which strains the trust of others; AI/ML enables an arms race between creation and detection of misinformation, which strains trust of content. Individuals who experience epidemics between ages 18 to 25 are 5.1% less likely to have confidence in the national government, and 6.2% less likely to approve the performance of the political leaders.
7. Resource scarcity
Growing demand for limited resources like energy, water, rare earth minerals, and food, due to global population growth and climate migration, creates conflicts over control of limited resources. Automation and real-time tracking across supply chains increased during the pandemic to mitigate risks.
8. Disaggregation of location and activity
Pandemic physical distancing accelerates the virtualization of life; disconnecting location from activities alters work, learning, commerce, and social norms, and geographic movement. Organizations are struggling to determine the best way to bring employees back to the office while keeping in mind the requirements for future like talent acquisition and learning.
Equally important is the need to understand the key factors that might influence your specific industry, and how to recognize and mitigate risk. While initial investments in intelligent solutions can be focused on point solutions, as intelligent automation grows, this approach will lead to suboptimization and rework. We recommend starting with the end in mind and in the future with an outside-in approach and approach building your automation roadmap at an enterprise level to ensure a comprehensive perspective. As with most disruptive technology, the impact is felt by the humans, employees, or customers, interacting with the new technology. As organizations prepare for implementing RPA, they must take a human-centric approach to planning the change.
Toffler Associates and Roboyo tackled these concepts and more in our interactive webinar, The Future of Work is Now: Strategies for Intelligent Automation and Talent Transformation. Listen now and learn more about developing your automation roadmap and the value proposition and risks of RPA for your organization.
As an integral part of any digital transformation project, automating the repetitive, the manual, and the unnecessarily time-consuming is no longer a potential future strategy, but an immediate imperative.
Over the last 12 months robot process automation (RPA) and its more ingenious cousin, intelligent automation (IA), have quietly moved from interesting pilot experiments to the top of almost every CEO’s to-do list.