Unboxing Workforce: The 2020 Paradigm Shift
Coming to terms with a new workforce reality
Introduction
One of the biggest changes the world of business — and our civilization — has ever seen is happening in the workforce, and we can predict its wave will come crashing down in 2020. It’s a change that will start to take hold in 2020, creating a new norm that we don’t recognize today. And, good or bad, it will be an irreparable change.
Workforce designers today have many more options to fulfill work tasks than ever before and definitions of ‘work’ and ‘workforce’ have become far broader. It raises the challenge of determining how best to engineer a flexible workforce able to cater to the changing needs of an enterprise. The options to get task outcomes completed include:
- Direct workforce (FTEs)
- Indirect contingent workforce
- Independent consultants, freelancers, and contractors
- Gig economy possibilities
- Task-fulfillment and job-board websites
- On-demand workforce portals
- Crowdsourcing portals and knowledge markets
If your retirement is more than a few years off (so you still expect to have need of a career in business), you run a company, or you’re interested in human resource management and the discipline of workforce design — then you REALLY need to understand this change. Because it’s going to be game-changing.
In this article, I explain what we can expect to see happen and why.
2020 is fast approaching
When I was a child it seemed light-years away. I imagined what the world would be like ‘by then.’ Well, now it’s around the corner. I’m speaking of course about how labor markets work in a digital age, where computing and humanity are having to take baby steps together, learning how to work with each other side-by-side.
My brain works differently to other people. I guess that’s true of most of us. In my case, I see influence links between unrelated concepts easier than others; i.e. How might something over there in that box relate to something that’s going on in this box? I guess I must be in touch with my dyslexia gene. But why is this useful in business?
It’s a helpful skill if you need to ‘think outside the box.’ Not a skill you always need. Sometimes useful. It meant that I could ‘anticipate’ concepts like cloud computing and web-based communications before other folks, giving people a two-or-three years head-start in developing solutions. These weren’t guesses. I knew they would happen because of the 1+1=4 logic of trends and innovations. It was only a matter of time. The same goes for the idea that retailers will offer recyclable packaging to help customers get food produce home without using plastic packaging, or that one day we’ll all have the option to employ an AI personal trainer robot to coach us on how to do Yoga correctly. Some innovations are pretty ’inevitable.’
It’s a weird concept in its own right, but my life gravitates around understanding paradigms. A paradigm is a way of looking at something, the lens people look through when they try to understand concepts (like cloud computing) that are mind-blowing difficult to take onboard.
They exist because we humans learn new things by building on the context of known-knowledge, norms of understanding and behavior. That’s why the idea of a micro mobile computing device didn’t take off but a ‘mobile phone’ did (same outcome, different paradigm of understanding), and it’s why, when Edison came up with his incandescent electric light bulb, he made it flicker like gaslight so that his buyers would understand it. When we take on a new idea, we try to understand it based on what we know to be true.
We simply can’t help ourselves.
The 2020 Business Climate
Markets are changing structurally more than ever before as digital innovations encourage consumers and entrepreneurs to re-define what they want and what is possible. The world of 2020 is mind-blowingly different from the consumer-crazed sixties and seventies, and the frugality of the forties and early fifties.
The world continues to grow smaller over time with new travel options Scramjet and hypersonic aircraft expected by the end of the decade flying at up to Mach 5, enabling it to cross the Atlantic Ocean in just two hours and the Pacific in three.
The millennial generation, like no other before it, is hyper-aware of the risks facing the extinction of the planet, and they are more empowered to act to do something about it. They care about the values of companies they buy from, and they want to work for employers that give them the opportunity to have a voice.
People are living longer in a greater state of health, increasing the ‘grey power’ influence on spending. One modeling study carried out by Newcastle University and the London School of Economics and Political Science, reported the fastest growing demographic in the UK is elderly people over 85, whose numbers are projected to more than double by 2035, increasing by 1.5 million.
Consumer markets are moving geographically as the BRICs emerging markets (Brazil, Russia, India, and China) grow in wealth and influence. The middle class in these countries is large and growing. The top 20 percent of the population is over 600 million people, many of whom have purchasing power similar to the average citizen of developed countries.
Technology is having an ever larger influence on lifestyles. We can envisage a time in the next few years when everyone in the world will be connected to the Internet 24x7, while 5G offers 100 times the download and upload speeds of its 4G predecessor.
These factors are driving changing attitudes of consumer behavior, buying habits, and what humans want, faster than ever. Products and services are growing in choice, availability, and affordability. It this climate that businesses have to work within, a market-place where companies need to constantly re-invent themselves to stay relevant and competitive.
Unboxing the Present Day Workforce Paradigm Assumptions
Before we can examine the future of the workforce, unfettered by our present-day preconceptions of how workforces are constructed and how they operate, we need to expose the assumed realities that have largely worked in the same way for decades. To minimize the influence of the distorted ‘lens’ we use to look at how the workforce will work in 2020, we first need to tackle known assumptions head-on and prove them to be unreliable friends if we are to examine the future.
I debunk some of the most obvious assumptions here.
‘Work’ is an activity performed by humans, involving mental or physical effort done in order to achieve a purpose or result.
All of that is pretty accurate. Work describes a job to be done. But work doesn’t have to be done by humans, it can be done by machines — including artificial intelligence based robots. An increasing number of business work activities can be automated. Organizations like McKinsey & Co, Deloitte’s and PWC have performed various studies and the general consensus is that around 30% of known job roles can be at least partially automated by known technologies that exist today, while an Oxford University survey suggested that 47% of the world’s jobs will be taken by robots in the coming decades. Humans aren’t the only ‘worker’ anymore.
Organizations rarely change their business model
Every commercial business in the world finds some way to create value to its customers and then turns this value into returns for its shareholders. The way it does this is called a ‘business model’. At one time, a business that retailed food did that and only that. Today though, we see food retailers selling insurance, telecommunications companies selling content, IT companies selling music, and automotive companies selling finance.
The very construction of markets and how they work is changing faster than ever before. For established businesses, their next competitor is less likely to be an industry peer, more likely to be a software company or broker. Just look at how Uber has transformed the way the taxi industry works, how Skype and WhatsApp have remodeled telecommunications, and how iTunes and Spotify have redefined music consumption. We live in an era where the efficiency of business models matters more than assets for most companies, and where changes to business models are occurring every year, or at least every few years.
When business models change, they redefine what work needs to be done — and who does it. Take Amazon for example. All Amazon customers create their own account, enter their own payment details and personal information. They manage their own address details and shipping arrangements. Compare that to many B2B companies that enter data into Customer Relationship Management (CRM) systems, where sales teams spend much of their time keying in data about their customers. Why? Does it not make sense for the customer to do it themselves? Probably yes, but that pre-supposes the customer is willing to do it because they get value from doing this work themselves.
We know how our organizations work
Even though our present day understanding of ‘business’ has been around since the Corporation Act of 1661, there still isn’t an accurate lexicon of commonly used terms in business. This doesn’t help factual understanding of how organizations work. It makes it harder for people to get their heads around concepts like the hierarchy of tasks. In an organization, there is always a command and control hierarchy. The people running the business have organizational objectives to fulfill. These become ‘their objectives’. To fulfill those objectives, leaders will assign ‘actions’ to their subordinates. Their subordinates will take on these tasks as ‘their objectives’. An ‘activity’ for a leader becomes an ‘objective’ of their subordinate. It makes sense that tasks are not stand-alone elements, they form part of rich activity processing system coupled together by policies, resources, inputs and outputs, accountabilities and responsibilities, measures and risks. The fact is, most organizations don’t know how they work. How tasks get done. There is an entire organizational DNA of meta-data that isn’t normally rationalized or captured into a computer system. It’s missing. That means it’s not possible to use robots to perform certain activities today they could potentially discharge simply because humans haven’t defined and digitized how their organization works.
We know what productivity means
It’s relatively easy to define worker productivity in cases where someone shells peas or makes guitars, but how do you measure the productivity of an office worker that comes up with smarter ways to market to customers or an accountant that manages sales incentives? Do you measure their productivity by the number of ideas they come up with; or the number of spreadsheets they produce? Before you can construct a reasonable measure of knowledge worker productivity, it’s necessary to determine what work needs to be done and what form of ’output’ is valuable. The role of humans in the workforce and their productivity is being put under increased scrutiny thanks to software robots and artificial intelligence. Robots are easier to measure in terms of their productivity. They are able to work 24x7 and their activities are easily monitored through data. Also, good news for employers is the fact they don’t get distracted by Facebook; or deal in office politics to try to secure promotion, or spend half their time outside in the car park vaping and ‘grabbing a coffee.’
Work involves a human resource investing time to produce something
Another curious angle on this subject is whether a work activity needs to be performed at all to achieve the desired outcome. Take, for example, the challenge of a pharmaceuticals company needing to grow its knowledge on stem cell design. It may be a knowledge marketplace answers the questions they have on the subject without requiring work to be done at all.
Thanks to big data and cloud computing, knowledge creation is growing at an unprecedented pace. This is enabled by the role of the Internet to create a global meeting place for a growing population to be curious and to ask new questions. According to Gerald S. Hawkins, progress generally proceeds via mind-steps, dramatic and irreversible changes to paradigms or world views. The more people you have working on problems, the faster pace of knowledge evolution.
There’s a huge blur these days between the challenge of sourcing new (or existing) knowledge and work. Is a knowledge market comprised of ‘seekers’ and ‘solvers’ just a different form of job market? If so, do you need to employ anyone for any future knowledge working function if the outcome can be procured a different way?
Employing large numbers of full-time employees is best
Most organizations employ the majority of their workforce as full-time employees and have done since the origins of enterprise. It’s a long-held belief that ‘it’s the best way to secure the resources you need and control their productivity.’ It’s recognized that talent shortages exist in the labor force today.
A 2019 survey by Gartner shows that talent shortage is viewed as the top emerging risk facing large enterprises. This US centered survey of 137 senior executives in 4Q18 showed that concerns about “talent shortages” now outweigh those around “accelerating privacy regulation” and “cloud computing”, which were the top two risks in 2018.
Given the known talent shortages, surely it makes sense to employ people on full-time contracts in order to secure their commitment to being reliable workers, and only focus on your job, not others? Perhaps, but there are definite downsides to full-time contracts for employers today, including:
- Affordability — While hourly rates for contracted workers can be higher than employing individuals on full-time contracts, the cost of employing a worker is higher with tax, health plans, vehicles, expenses, pensions etc.
- Quality — Contractors have to become expert in their chosen discipline in order to compete in a talent market. The more work they do, typically the more experience they gain and the more adept they become.
- Risk — There are much higher risks in employing individuals than contracting workers through an indirect partner. Employment tribunal cases are currently rising by approximately a third year-on-year in the US and Europe according to research conducted by justice authorities.
- While few would argue, employment risks for FTEs are higher, there are risks to employing contractors too however including increased data security risk, increased risk of privacy data being misused, increased risk of individuals not meeting their job requirements or obligations (perhaps simply opting to take on alternative work for more money).
- Workforce flexibility — Full-time employment creates a static workforce with a static skill-set. That doesn’t offer the level of workforce agility organizations now need to adapt their business models to compete in a rapidly changing world.
Robots can’t do the thoughtful, emotional things that humans can do
We look at robots today as somewhat stupid machines. They might be able to waddle around and say a few words but they’re far less intelligent and dexterous than humans. Maybe so, but they’re catching on fast. The rampant pace of processor innovation characterized by Moore’s Law (i.e. the observation that the number of transistors in a dense integrated circuit doubles about every two years) suggests that robots may not be able to do every work activity a human can perform today, but in just a few years they might. In addition to the improving capabilities of robots, what’s also changing is our willingness as consumers to accept them in performing tasks that humans have previously (exclusively) performed.
According to Forrester Research, 63% of consumers are satisfied getting service from a chatbot, as long as they have the option to move the conversation to a human if needed.
A robust link exists between economic productivity growth and population wealth
One of the golden rules of Marco economics is that a symbiotic relationship exists between increasing productivity and rising wages. This relationship, if it ever did exist, started to fall apart in the 1970s, and for a number of reasons. Fewer jobs are being created — On the 2nd January 2010, the Washington Post reported that the first decade of the twenty-first century resulted in the creation of no new jobs.
Wages are decreasing — As of 2013, a typical production worker earned about 13% less than forty years previous.
Machines are doing more for less — Employers are able to get their outcomes achieved using alternative means including knowledge markets and machines, which means even though productivity may be increasing, the wealth of workers is declining.
Why is this important? It matters because workers are also consumers of products and services. In a consumer economy, the resulting lack of funds to buy goods and services can result in economies to stagnate and fail.
This paradox of automation is best exampled by a story described by Martin Ford in his book ‘The Rise of the Robots.’ told an extraordinary anecdote about automation. The story is about two rivals, the forceful executive, Henry Ford II, and the leader of the automobile workers union, Walter Reuther. The men were both titans in the world of automobile manufacturing and they are taking a tour of a newly built and highly-automated factory. Both were able to see many examples of advanced machinery operating at the plant. The words they exchanged brilliantly encapsulate the paradox of automation:
Henry Ford II: ‘Walter, how are you going to get those robots to pay your union dues?’
Walter Reuther: ‘Henry, how are you going to get them to buy your cars?’
To find talent, businesses need to source through recruitment specialists
We are all accustomed to sourcing talent through recruiters and agencies. In a competitive market for talent, filling vacancies has become increasingly more difficult causing companies to employ people to do it as a job. It’s required a ‘human broker.’ Online platforms offer the potential at some point in the future to cut out the middle-man but, so far at least, the human resourcing industry has failed to find an effective way of automating the brokering of the right talent, at the right price, in the right location and at the right time.
Summary
The assumptions that go to shape how business leaders view their workforce today shape perspectives on what the future to talent markets look like. Until this time in the evolution of business, leaders have presumed that:
- We know what our business model is
- We know how the organization works
- We know what ‘work’ is
- We know what work needs to be done
- We know that humans will do the work
- We know that Full-Time Employment contracts are the best way to secure resources
- We know that employment and productivity leads to the wealth creation needed to fuel the consumer economy
Well, now we can be absolutely certain that we don’t know anymore.
Workforce Design in 2020
Here, I explain the likely design of your workforce in 2020 and I start by building out some classifications of work activities that I trust are helpful in determining the best way of designing the 2020 workforce and how to resource it. When designing a useful classification system, it’s helpful to answer the fundamental question: ‘What factors are most likely to influence judgments on the workforce design approach?’ Some of the key characteristics to think about include:
Capability
Capability is about the ability of ‘someone or something’ (let’s call it a ’production unit’ for want of another term) to get a job done; the power or ability to do something. It raises the question, ‘what type of production unit is best-placed to fulfill the task outcome — a human, machine or something else?
Integrity
Integrity determines to what extent a task can be performed in isolation of policies, processes, people, and systems. We live in an era where everything is connected. Tasks don’t happen in isolation. They almost inevitably occur as part of a thread of activities of some sort.
The majority of business activities must today operate within a highly regulated and data-secure environment. In such cases, it’s difficult to imagine work being farmed out to autonomous people, robots or communities because the level of governance would be too great and the risks too high. Sensibly, a task demanding low integrity could be performed by a worker with high autonomy. Therefore, worker autonomy and the level of need for task integrity are part of the same spectrum.
Integrity has a lot of implications around governance, sociability and solidarity culture, continuity, security, command and control, frequency of use, and approaches etc. A key consideration of integrity is the availability (or paucity) of the resource. Ultimately, if resources don’t exist to get a job done when they need to get done, then it doesn’t matter how ideal a production approach might be, organizations have to look at alternative ways of getting outcomes achieved. Availability of resources, therefore, continues to play a key role in the design of workforces.
Work Classifications
If we break-down tasks into hierarchical classifications, it’s easier to envision how the requirements of each task group can be delivered. I’ve created this simple model to build some context to the various ways workforces are being curated using modern mechanisms.
The Eight Box Matrix
There are two levels to this task hierarchy, what I call the primary level and the secondary.
Primary Level Work Classifications
The foundation thinking behind this structure comes from the book ‘Thinking, Fast and Slow’ by the psychologist Daniel Kahneman. In it, he outlines a psychological behavioral model — a paradigm if you will — for understanding human behavior. In his TWO SYSTEM model, human responses are neatly pigeon-holed into one of two distinct modes of decision making:
Fast Thinking (‘System 1’)
Operates automatically and quickly, with little or no effort and no sense of voluntary control. If I ask you for an answer to the equation what does 2+2 equal, then you don’t need to give it a moment's thought. You know immediately that this is a multiplication problem, and probably even that you could solve it. It’s like driving: Once you’ve learned how to do it, you don’t need to spend any time thinking about it.
Slow Thinking (‘System 2’)
Allocates attention to mental activities that demand effort, including complex equations. It’s all about the need to concentrate.
It stands to reason that computers are generally more effective at tasks that demand ‘System 2’ thinking, while humans are really good at ‘System 1’ related tasks that deal with intuition, native instinct, and non-linear analysis or interpretation (i.e. enveloping knowledge of disparate seemingly unrelated thoughts and introducing an ‘x-factor’). A good example of this is what I call the ‘Newton Day’ factor because of the event that allegedly led Sir Isaac Newton to discover gravity thanks to an Apple. It was the outside influence of the Apple landing on his head that triggered an impulse to think of the same problem in a different way. So far as I know, computers can’t do that!
Secondary Level Work Classification
The secondary level of classifications falls into the two headline groups of tasks that demand System 1 or System 2 competencies to fulfill them.
These, more details classifications, result from work I did at Canon Europe Ltd during my tenure there. In 2017, I was tasked with creating an assessment approach to help companies to determine the best value approach to fulfilling their tasks. Part of my research was to ‘audit’ one operation within a company employing around 500 full-time employees. This research involved a series of 30-minute qualitative interviews with around 20 department leaders.
Unsurprisingly, we filter tasks by the level of Capability and Integrity that each task requires. What we produce is an eight box matrix as illustrated below.
Were we to simply list out our eight task groups, it would read like this.
Some Scenario Examples
Whilst a more forensic analysis of jobs is helpful, we can instantly appreciate how these task groups influence our workforce design by using a few notable examples to test the model and its efficacy.
Non-lineal decision-making
I use the phrase non-lineal decision-making to describe leadership tasks that do not feature as part of an already known process. For many CEOs, the challenge they face with business model design and orchestration comes down to anticipating changes to market conditions and asking new questions about the way their business works to explore new opportunities and threats. This type of decision making requires intuition, a very good radar system and lots of curiosity. You could argue that it is about making decisions about things that haven’t been factored in yet to an analysis model to define a new paradigm. This type of role definitely has a lot to do with System 1 fast-thinking but still benefits from factual business insights derived from System 2 slow-thinking sources. In our model, this type of activity would probably feature in Task Group 2 (i.e. a task that requires Fast Thinking, High Integrity, and High Capability). Lineal decision-making scenarios on the other hand, such as data security event monitoring, will more likely work their way into Task Group 6 (i.e. Slow Thinking, High Integrity, High Capability).
Knowledge sourcing (scientific innovation)
If organizations are looking to source scientific knowledge, then they may not find it necessary to source this information from individuals working within a tightly controlled or regulated environment. It’s quite possible knowledge could be sought from online groups of experts and individuals working discreetly and autonomously, although the nature of the work demands high levels of capability. This scenario might find its way into Task Group 8 (i.e. Slow Thinking, Low Integrity, High Capability).
Website Design
This activity is a helpful illustrative example. For many large organizations, their company website has grown from being a ‘company calling card’ to the user interface for all interactions with customers, including data capture, view, share, and editing activities. Websites play a key role for organizations today as a landing page for new prospects and a billboard for company information. For all of these deeply embedded processes, it’s simply not sensible or practical to outsource such a task (or series of tasks) to an individual working autonomously beyond the firewall and operational governance of the enterprise they serve. This type of task commonly falls into Task Group 5 (i.e. Slow Thinking, High Integrity Low Capacity) or, if lots of creativity is needed, then perhaps Task Group 1 (i.e. Fast Thinking, High Integrity, Low Capability).
Resourcing Models in 2020
Why is this model interesting to Human Resources professionals? I believe it to be useful because it helps responsible leaders to identify characteristics in the types of requirements that exist ‘beyond the job description’ and to explore new ways of meeting these needs. In this section, I go into more detail about the opportunities and risks that innovations in workforce resourcing are creating.
Resourcing Options: 2020 Outlook
There are many ways of ‘getting the job done.’ No longer do organizations have to fulfill their workforce needs by employing humans on full-time employment contracts. So what are the options?
Direct FTE (Full-time Employment) Contracts
It may be a model falling from favor, but direct Full-time Employment (FTE) contracts continue to represent a major contributor to workforce talent pools. Given the state of competition, we can only presume the current trend away from this highly rigid capabilities model will continue as organizations realize the economic necessity to source an on-demand workforce.
According to the findings of Deloitte’s latest workforce survey, only 42 percent of respondents say their organizations are primarily made up of salaried employees. And these employers expect to dramatically increase their dependence on contract, freelance, and gig workers over the next few years.
Indirect Workforce
We live in the era of the freelancer and gig economy. A digitally connected talent market means individuals have many more opportunities to find employment for their skills on their terms. Globally, there are approximately 77 million formally identified freelancers in Europe, India, and the United States. Organizations can access this talent pool through a variety of means; by working through third-party staffing firms, by outsourcing their indirect sourcing approach to a Managed Services Provisioner (MSP), or by advertising their jobs and tasks on digital platforms. Irrespective of the channel, each of these mechanisms ultimately brings access to the same talent pool.
There are challenges in utilizing an indirect workforce, chief among them is the ability to install robust integrity controls to ensure freelancers are able to work as a joined-up part of a team or process and exist with the policy, security, culture etc. of the organization they serve.
According to the report “Freelance statistics: The freelance economy in numbers,” in the United States, more than 40 percent of workers are now employed in “alternative work arrangements,” such as contingent, part-time, or gig work.
According to the 2018 Freelancing in America report published by the Freelancers Union, almost 57 million Americans earn their living on a per-contract basis. This number represents a 3.7 million worker increase since 2014. Last year, the Freelancers Union speculated that 50% of Americans will be full-time freelancers by 2027.
So says Forbes, the six of the freelancer workforce is steadily rising — increasing by 36 percent in just the past five years — and now includes workers of all ages and skill levels (Source: “Shocker: 40% of workers now have ‘contingent’ jobs, says U.S. government,” Forbes, May 25, 2015).
On-demand Digital Workforce Platforms
We are seeing a dramatic increase in the fragmentation of jobs into tasks, ready-made service packages, and Statements-of-Work (SoW) contracts. These alternative ways of procuring workforce resources mean that organizations are able to sugar-cube their resourcing needs and source best-fit, value-for-money solutions from a large addressable market of talent. Examples of on-demand working platforms include Fiverr, UpWork, TopTal, Pay Per Hour, Freelancer.com , and 99designs are part of a growing community of platforms designed to bring organizations easy access to talent on-demand.
Crowdsourcing Communities
Another form of ‘getting the job done’ digital market is characterized by crowdsourcing platforms like InnoCentive and Kaggle that enable organizations to publish competitions for solutions to jobs that need to be done and encourage communities to respond with the best offers.
Facilitated Services Provisioning and Workforce Ecosystems
Perhaps the missing ingredient so far in the workforce options open to businesses today is a hybrid between direct and indirect workforce models that some outsourcing firms have described as the ‘FSP’ model. In this model, a third-party firm or digital platform performs more of the essential integrity enablement and business continuity services surrounding the use of freelance workers to ensure they can perform proportionately more task group activities.
Machines and Robots
With so many innovations happening at the moment in the artificial intelligence and software robotics arena, it’s highly likely that a larger proportion of work tasks today performed by humans will shift across to autonomous and semi-autonomous machine automation. Ultimately, if one were to consider robots as part of the workforce, up to 40% of the present day labor market
Connecting the Dots: Which sourcing options best-fit the various task group classifications?
If we now combine the ‘solution options’ with the ‘requirements’ organizations have to serve the various workforce task groups highlighted earlier in this document we come up with a reasonably useful outlook of 2020 workforce design possibilities. I walk through the various best-fit cases here.
Task Group 1 — Fast Thinking, High Integrity/Low Capability
Fast-thinking tasks favor humans. In cases where capability demands are low, Facilitated Outsourcing programs offer a useful way of combining indirect workforce agility with demands for higher integrity controls.
Task Group 2 — Fast Thinking, High Integrity/High Capability
For tasks that demand higher integrity and levels of capability, direct Full-Time Employment contracts continue to be useful because they reduce the risk of key personnel leaving for other opportunities and the business impact that can create.
Task Group 3 — Fast Thinking, Low Integrity/Low Capability
In cases where tasks don’t need to operate within a tight compliance regime but still require very human creative skills (like logo design), workers can enjoy a high degree of autonomy. In such cases, task-based requisitioning and freelancer job boards offer a good way of fulfilling work demands affordably. The paucity of online indirect talent available from online platforms minimizes the risk of capacity not being available when it’s required.
Task Group 4 — Fast Thinking, Low Integrity/High Capability
When rich human capabilities are demanded ( perhaps very high skill levels for example) crowdsourcing platforms are becoming very popular. Again, Facilitated Outsourcing programs ensure higher levels of continuity and increase the likelihood of project completion, but at a cost.
Task Group 5 — Slow Thinking, High Integrity/Low Capability
Slow-thinking cognitive task groups, with high-integrity demands — perhaps because they need to operate with a ‘fire-walled’ environment — but with low capability demands (as in the case of call center agent and security event monitoring roles). are largely passing to artificial intelligence enabled solutions such as chat-bots and software robots.
Task Group 6 — Slow Thinking, High Integrity/High Capability
Where tasks demand both high integrity and high-capability, these may still fall to a human to perform. As this human capital is extremely precious (such as a Software Systems Architect or CTO in a software company), it would be sensible in most cases to secure these individuals on direct Full-Time Employment contracts. Increasingly, organizations are considering how to ensure business continuity and harness their tacit knowledge for these types of tasks by implementing digital transformations with in-house developed digital platforms designed with the purpose of servicing these business-critical functions.
Task Group 7 — Slow Thinking, Low Integrity/Low Capability
Where low integrity and capability are needed to fulfill slow thinking (cognitive) work tasks, the potential exists to outsource these capabilities to third-party automation platforms. An example might be credit check platforms run by third parties that utilize advanced algorithms and AI to anticipate or predict fraud.
Task Group 8 — Slow Thinking, Low Integrity/High Capability
For slow-thinking tasks that demand high levels of capability but low operational integrity, organizations are well-placed to consider outsourcing options, although the options available to do so remain limited to date.
Making Workforce Integrity Work in a Digital Economy
To create elasticity in a workforce design to mirror the needs of a constantly changing digital economy, organizations have to maximize their use of indirect labor while maintaining high levels of addressable capability and integrity. How? In this section, I walk through the stages of the life-cycle of designing, operating, and transitioning workforce needs to profile opportunities to add richer capability and integrity into the operation of an indirect labor force.
DESIGN
Work Project Definition
Many projects are doomed to fail before they start because project sponsors fail to frame adequately the expectations of a project correctly.
To example this, the volume of content needed to make social media marketing bring value and opportunity to an enterprise is so high that very low investment levels are known to deliver poor results. A minimum investment requirement exists for social media projects to be successful: Better to put marketing spend to other uses rather than invest time and money for no return. Setting out these outcomes is critical to the success of any project, but particularly when indirect labor is used: Contractors are always happy to receive payment for work done, even when projects deliver marginal returns!
SCORE
SCORE is a method of defining procurement expectations and outcomes. It produces a scorecard to measure project performance and deliverables. Another benefit is that it’s also extremely easy and quick to set up, so minimizes project overheads.
SCORE stands for:
(S)cope — Determines the scope of the requirements framed by push-factors (i.e the undesirables that need to be resolved) and pull-factors (i.e whatever prevents the outcome from being achieved now).
©ost — Sets aspirational costs against associated outcomes to determine the best level to set project scope. Potential project results set against their anticipated uplift in costs are categorized into five categories: (1) Minimum Accepted Commercial Value, (2) Meaningful Returns, (3) Ideal Returns, (4) Unexpected Value-Add, and; (5) Significant Unexpected Value-Add.
(O)ptions — Describes the value-adding options that are important to the outcome framed by the anticipated business impact and associated critical success factors.
(R)esults — Sets out the scorecard and operational controls of the project including objectives and measures, RASCI accountability, determined value, and waypoint deadline dates.
(E)xecute — Sets out the project plan GANT including a description of what needs to be done and who needs to do it.
OPERATION
Workforce Sourcing Approach
In this document, I outline a series of potential ways of delivering task outcomes. The workforce sourcing approach needs to get the balance right between task group requirements and solution options. Modern on-demand workforce platforms offer more ways to procure talent. Selecting a best-fit platform that embraces additional controls over workforce integrity and capability — or buying/building your own — will serve to bring more access to indirect talent markets.
Workforce Operations
Modern on-demand workforce platforms come furnished with rich operational governance features out of the box. These may include:
Project Contract Templates
The ability to us pre-created legal contract templates to frame the obligations of parties during different forms of
Project Milestones
The ability to set project milestones.
Project Team Design
Tooling to determine and review project risk across all projects happening on the platform.
Project Team Rewards
Tooling to determine and review project risk across all projects happening on the platform.
Project Collaboration Tools
Socially oriented communications tooling that encourages team-working, knowledge sharing, the retention of project know-how (tacit knowledge) and encourages solidarity and sociability culture, even for dispersed teams.
Project Risk Management
Tooling to determine and review project risk across all projects happening on the platform.
Alert Escalations/Notifications
The ability to pre-define event notifications to alert managers should activities not be performed on time.
Time and Attendance Monitoring
The ability to monitor the attendance of project contributors and escalate matters when attendance reaches unacceptable levels.
Payment Schedules
The ability to align payments with project milestones.
Escrow
The ability to control money flows and not commit funds until work is completed, and to a high standard.
TRANSITION / END-OF-LIFE
Change is something that most people fear. It also represents a high cost to businesses. Implementing supply-chain options and technology solutions that tie organizations to incumbent suppliers can manifest a different kind of restriction on workforce elasticity. For this reason, many vendors now consider their ability to off-board clients and implement mechanisms to ease the burden of leaving to do something new. This might include offering to archive data, export it — or port it. For workforce designers, considering the implications of existing an arrangement is important to ensure business continuity and agility.
Conclusions: What Do We Know, and What Can We Surmise?
Business is about predictability, it always has been. The world of work in 2020 is no different in that aspect to years gone by. The discipline of workforce design must cater for an ever more risk-averse corporate environment, where pressures to improve data privacy, security and governance add to the woes of compliance officers.
Making sense of complex concepts requires context. In the case of workforce design, the industry remains in its infancy in terms of establishing ways to measure the effectiveness of sourcing strategies that span the full spectrum of work fulfillment options. Generally, a direct workforce is afforded richer controls and governance than indirect one. Few organizations operate policies and procedures that embrace these and the digital platform possibilities of task competitions, crowdsourcing campaigns, and other such alternatives. This makes it extremely difficult for a workforce design leader to compare and contrast one form of delivery mechanism against another.
Human Resources leaders face tough decisions in 2020. They must encourage automation and the migration of roles to robotic and AI solutions. To be successful, leaders responsible for the discipline of workforce design in their organization must adopt a holistic 360-degree approach to the resourcing of work tasks that encapsulates direct and indirect talent sourcing options, and extends to knowledge crowdsourcing markets, robotic and AI alternatives. They have to get the balance right in the way they orchestrate their workforce supply chain without getting tied to any particular provider or source.
One of the most critical challenges for HR leaders is to identify how to increase integrity and capability controls over supply-chain options to make indirect labor more accessible to work on projects. The integrity of the workforce can not risk compromise, even when there are compelling reasons to increase the elasticity of the skills base and embrace the economics of the freelancer (and ‘gig’) economy.
Most of all, leaders have to be prepared to embrace digital on-demand workforce ecosystems, and temper curiosity and enthusiasm for the new, with recognition of the need to maintain harmony with internal safeguards around project requirements, project coordination, solidarity and sociability culture, data governance, and risk management if they are to maximize the competitive effectiveness of organizations they serve.
What we know is that organizations that fail to embrace an on-demand workforce paradigm face extinction. What we can surmise is that smaller companies will be faster to embrace change than larger rivals and that in 2020, the divide between the haves and the have-nots will start to show.
About the Author
Ian Tomlin is a seasoned marketer, entrepreneur, and business leader with a 30+ year career at the intersection of strategy, technology, and marketing. As the founder of successful businesses, including Newton Day Ltd, Ian brings a wealth of expertise in guiding companies toward compelling brand stories. Reach out to Ian via LinkedIn to transform your marketing approach and tell your brand story effectively.
