Talent is every organization’s lifeblood. Jim DeLoach discusses how, coupled with demographic and social trends, the technologies of the digital age are transforming the workplace. Executives and directors need to pay attention as electronic workers (machines and algorithms) become more prominent in their companies.
In last month’s article, I discussed how shifts in workplace dynamics are forcing companies to transition the traditional labor model to a talent ecosystem in which much of the organization’s work by human beings will be completed by nonemployees. This change is disrupting the traditional human resources model and could very well make it obsolete over the next several years.
Impact of Digital Labor on the Shamrock Organization
The context of that discussion is Charles Handy’s concept of the “shamrock organization,” introduced nearly 30 years ago. Just as shamrocks generally have three leaves, this organization consists of three components: a core of essential executives and workers, supported by outside contractors and part-time help. In this article, I use Handy’s model to discuss the implications of digital labor and how they affect the way companies manage the workforce. Specifically, last month’s article emphasizes two of the three dimensions of the evolving labor model – skills and scale – whereas this article discusses the third: digital labor (machines and algorithms).
This discussion is important to executives and directors for two reasons:
- It is common knowledge that technology is expected to affect work, jobs, job roles, wages and society at large significantly and continuously over the foreseeable future.
- In the digital age, management must understand and harness technology’s role in supporting and shaping each workforce category of Handy’s shamrock model: (a) the “professional core” of well-qualified, hard-to-replace and highly compensated employees; (b) the “contractual fringe” of self-employed individuals and specialized organizations who complete assigned tasks and projects to achieve specified results on-demand; and (c) the “contingent workforce” of flexible, part-time workers.
The point is that as management hires, develops and manages each of these labor pools, the tools of the digital age are expected to reshape each pool by adding a “digital component” that offers a higher level of performance in certain areas. For example:
The work of the professional core is impacted by digital labor performed by next-generation robotic process automation (RPA) and, at even more advanced levels, artificial intelligence (AI) and machine learning. With these capabilities, what’s left in the core are those people needed to perform work on higher-value activities that play to such skills as analytical thinking, innovation, active learning, creativity, originality, initiative, critical thinking, complex problem-solving and other unique attributes of being human.
With respect to the contractual fringe, traditional outsourcing models extended organizations beyond their own walls decades ago. Today, newer, cutting-edge developments are jolting traditional business models and labor pools. Cloud computing platforms and applications, RPA, AI, the human cloud and related advancements are equipping executives with far greater agility to scale up or down to exploit opportunities and respond to unexpected threats. As it becomes easier to automate large amounts of shared service center-type work, the benefits of offshoring (e.g., lower costs) are reduced; this, in turn, is creating an incentive to onshore, a trend which will impact certain markets and companies across the globe.
As the age of physical locations, people and infrastructure continues to transition to the digital era, technology-enabled digital labor offers powerful hyperscalability enhancements to the scalability and muscle offered by the human contingent workforce, along with additional capabilities and a higher level of performance that is faster, more reliable and less costly than that which is typically expected of human beings in performing certain tasks.
Bottom line: New and emerging technology is greatly influencing – often by enabling and sometimes by making more complex – how companies design and manage their labor models. As the future world of work evolves, organizations need to advance toward optimizing their mix of human and electronic workers – internal, interim and outsourced. This task entails freeing work from the entity’s current jobs structure and organizing and monitoring it in a framework of discrete, deconstructed units executed through a range of approaches, relationships and technologies. These sources include outsourcing and offshoring, consulting partnerships, interim staffing, traditional automation, business process as a service (BPaaS) relationships, managed services, RPA, AI and a variety of human cloud arrangements.
The Role of Technology in an Evolving Workforce
While this message may present mixed signals, depending on one’s perspective, it is nonetheless a reality that no management team or board can ignore. Simply stated, technology has a role in supporting and shaping each component of the workforce by offering additional capabilities that will increase quality, compress elapsed time, reduce costs and enhance scalability if applied intelligently. It is a powerful “northbound train” that everyone must board, or they risk getting left behind at the station on the wrong side of the competitive balance.
In last month’s article, I asserted that the shamrock in its contemporary form forces important fundamental questions when organizing work:
- Is it core?
- If not core, can we outsource it?
- Are there cost-effective labor model options that offer us more flexibility?
- Alternatively, can we give it to a contractor or freelance worker who can do it better than we can?
- If modifications to the labor model are needed, what’s the business case that compels us to change it?
To the above, I add two more questions to address the opportunities presented by digital labor:
- Whether the work is core or not, can we automate it?
- If it is a task that can scale up rapidly due to demand, can technology be used to introduce hyperscalability in the face of increased demand?
As leadership focuses on the realities of a transforming workplace and the implications of digital labor to that transformation, they should consider the following questions (in addition to the ones recommended last month regarding the labor model):
Questions for Executives and Directors
- What are we doing to stay abreast of the technological trends affecting work and the workplace? The effect of machine learning, deep learning, advanced analytics and automation on the workplace, particularly within the industry, should be assessed continuously over time and the executive team and board briefed periodically.
- Given the evolving technological trends, how are we evaluating their impact on our workforce? What’s the goal of automating work (g., what are we seeking to accomplish and why? What are the benefits and costs to the organization? What are the likely implications of automation on the industry, given the nature of the work and workplace and our competitive position? What are possible actions by competitors if we don’t act? Which technologies should we embrace now versus later?)? This evaluation should fuel planning for an automated component of the workplace and should be a business discussion, not an IT discussion.
- Are we automating the right processes? Processes that are heavily dependent on people and involve routine, methodical manual tasks are more susceptible to human error and require a lot of time to execute. Furthermore, machines are much better than people at analyzing large volumes of data, creating opportunities for combining advanced analytics and machine learning. These manual and data-intensive processes are ideal candidates for automation.
- Are we avoiding automation of poorly designed processes? Sometimes, it is necessary to alter a process or change a step in the process with an eye toward improving its design and its relevance to the customer before automation becomes a possibility. Without such changes, it may be difficult to automate. For example, redundant and unnecessary process activities should be eliminated and the remaining activities refocused by aligning them with actual customer wants before considering automation options. It may even be preferable to redesign the process altogether to enhance quality and productivity, and that effort may result in a different automation solution. If there are process deficiencies, variations and exceptions, it makes sense to analyze their root cause and address the issues at the source before considering automation. The point is clear: Organizations should not automate a broken process.
- Is the organization effective at managing automation? Of necessity, innovation in automating work must be considered a key success factor on a strategic level. In other words, high levels of automation must be an expectation reflected in the organization’s culture, or it won’t happen. For example, assume that management’s operating philosophy emphasizes a lack of tolerance for costly, manual repetitive processes in general. Thus, management seeks to achieve efficiencies by reducing dependence on people in executing such processes using proven solutions such as RPA and machine learning. Given this expectation, management must establish appropriate incentives for business and functional units to undertake automation initiatives and fund automation requests that meet established criteria. In setting this tone, it is vital that the organization’s employees buy in to management’s automation agenda. Even with low tolerance for manual-intensive processes, automation does not happen if employees do not believe the organization is agile enough to act on opportunities. In addition, the change management process must address employee fears that automation is a threat. (See next question.) Once these barriers are penetrated, the incentives put in place to automate can gain traction.
Management should identify and quantify the opportunities for applying automation starting with rule-based, standardized activities where a nonintrusive approach to automation is possible. Where appropriate, management should progress to machine learning, deep learning, speech recognition, natural language recognition and other AI components to automate intelligence; however, while these higher levels of automation extend the scope of process automation beyond basic manual tasks, they require more time and greater care to implement. For example:
- Policies and guidelines for governance of AI applications regarding the appropriate learning rate and other essential management control questions should be established and consistently followed.
- As the digital workforce expands, processes must be in place to oversee and manage the robots, the electronic “workers” that weave their way into the shamrock. For example, what data is used to monitor performance, how are improvements identified, what protocols are in place for updating programs and/or algorithms and how are human employees informed of these updates? Whether workers are human or electronic, the principles of continuous improvement to achieve operational excellence apply.
Investments in AI research and new technologies must be managed with the objective of maximizing the value delivered consistent with established business goals. As the pace of implementation varies by industry and is expected to pick up, management had best stay abreast of developments.
- Is the organization effective at managing change from automation? In the digital age, change is discontinuous as well as constant. Managing shifts in workplace dynamics requires a clear view as to what the organization might look like several years down the road and taking steps management is comfortable pursuing now – at least directionally – to get there. As technology automates work activities and intelligence, management needs to focus on integrating the new capabilities in a manner that is seamless to the customer experience; this includes effective integration with all relevant customer-facing and regulatory compliance touchpoints and systems. For example, what are the feeds to the automated activities and, in turn, what processes do they feed? How is the integrity of these feeds preserved? At what points are human interactions and decisions needed in an otherwise automated process?
Members of the workforce whose jobs have been eliminated through automation need to be retrained, reskilled and redeployed so they can perform higher-value, mission-critical tasks. Through it all, people’s perceptions of change must be managed, particularly (as noted earlier) when they perceive a threat to their continued employment. Management must be forthright in explaining the “why” behind the change, its benefits, the strategic imperative of making it happen and the potential opportunities for employees – and, in doing so, recognize the multigenerational composition of the workforce. Needless to say, the change enablement challenges of this task are daunting in the digital age.
- How does the organization maximize its chances of success? For an organization to be successful in the digital age, management must encourage a collaborative, diverse and inclusive workplace. The board and executive leadership team must understand technology and digital business models and embrace the opportunities and possibilities presented by technology. The organization’s highly talented, diverse and inclusive “professional core” must embrace digital capabilities as a core competence, assess them regularly and access sandbox environments and test data frequently to experiment with new technologies. Management should position the entity as a learning organization, investing in training, education and development. Digital tools should facilitate social collaboration and work, empowering teams and employees with better interaction and communication, raising staff motivation and increasing engagement. In this way, they drive efficiency and agility, increase productivity and generate faster work results.
In considering the above questions as well as the ones posed in my September article, it makes sense to look beyond the organization’s growth and profitability objectives to the social impact. New work and new job roles that are created as a result of new business models, industry consolidation and new automation may not fit easily into traditional jobs, and they may not always be optimally sourced through traditional employment channels. Simply stated, automation affects people and talent strategies alike. Companies owe their people the assistance needed to enhance their skills and employability. They owe their shareholders a digitally savvy focus on the workplace.
As executives transition the workforce to the digital age, they need to be aware of and embrace enabling technologies that will help the enterprise better serve its customers and create value. The board has an important role in assessing management’s thinking as the company’s talent and labor model strategy evolves.
 The Age of Unreason, Charles B. Handy, 1989, Harvard Business School Press, pp. 90–101.