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What the open source model did for software development, the open talent economy is doing for work. Today’s younger, connected, and mobile workers are managing their careers on their own terms and often outside categories that have defined the workforce for decades. Organizations will need to reassess what they have to offer talent and even what it means to “have” talent in the first place.
The classical employment model—vertically integrated companies hiring full-time employees to work eight- to nine-hour shifts—has given way to a new approach: the open talent economy—a collaborative, transparent, technology-enabled, rapid-cycle way of doing business through networks and ecosystems. The problem for many business, talent, and HR leaders is that they are operating as if the classical “balance sheet” model of talent is still dominant and relevant. It’s not.
Today’s evolving workforce is a portfolio of full-time employees, contract and freelance talent, and, increasingly, talent with no formal ties to a company at all. People move from role to role and across organizational boundaries more freely than ever. Global markets and products are driven by accelerating innovation and growing scale, and they demand talent pools and systems that can be rapidly assembled and reconfigured. Business leaders and customers expect agility, scale, and the right skills on demand. These new business and talent models look less like integrated factories and companies and more like highly orchestrated networks and ecosystems with a multitude of approaches to mobilizing, orchestrating, and engaging talent, skills, leaders, and ideas.
What the open source model did for software development, the open talent economy is doing for work. Today’s younger, connected, globally mobile people are managing their careers on their own terms. Where their parents may have sought job security, they prize engagement and meaning. This means that organizations must reinvent their sense of what they have to offer talent and even what it means to “have” talent in the first place.
In “Reframing the Talent Agenda,” we concluded by saying, “The new [talent] agenda will recognize that corporate boundaries are not the end of the talent management challenge. They are a departure point for influencing, enticing, and integrating talents of freelance, third-party, and open source talent ecosystems from almost anywhere by building new networks and ways of working.”1 This article outlines a new way of thinking about talent that looks at talent strategies across organizational boundaries: in the company, the extended enterprise, and beyond the enterprise.
We recognize that we are in the early years of the open talent economy. Some parts of the landscape are clear; others are still being defined. Like early mapmakers, we recognize that we are creating an early version of a new reality, and we hope to provide a useful and engaging view of the next phase of talent strategy and management.
The open talent economy includes a growing number of categories of talent that are being integrated to produce goods and services:
Some industries, including the entertainment, media, music, and software industries, have well-established models for building teams of freelance talent. Other industries are increasing their use of adjunct talent, which is a growing trend in higher education in some countries. And still other industries are increasingly turning to independent talent of many types to provide deep and specialist skills on a project basis.
In the United States, the number of freelance or independent workers continues to rise. According to MBO Partners, in 2012, there were 16.9 million independent workers in the United States—a number MBO forecasts to rise to 23 million in 20172 and that could reach 65–70 million, or half of the US workforce, by 2020.3 Some sectors of the economy are already witnessing the steady movement of knowledge workers to independent and ad hoc status. The higher education sector (university and college levels) in the United States is a case in point. Over the past 35 years, the percentage of full-time faculty has steadily declined (from 56 percent to 39 percent), with a corresponding increase in part-time and adjunct faculty (from 24 percent to 41 percent) (figure 2).4
The growth in the number of freelancers in the workforce has been accompanied by the rise of online marketplaces, such as Elance.com and oDesk.com, that specialize in connecting contractors and freelancers with employers. Elance.com, for instance, is an online job platform where companies can find and hire freelancers from 170 countries. Launched in 1998 as an e-commerce application to manage contractor services, Elance.com sold its enterprise software division in 2006 to focus on developing a web-based platform for the contingent workforce.5 Freelancers create and manage profiles online and collaborate to find jobs. The work ranges from website development to mobile app development, graphic design, and content writing. As a service fee, Elance.com charges 8.75 percent of the amount an employer agrees to pay the job seeker, who can be paid by the project or by the hour. The number of employers and freelancers using Elance.com has grown markedly in the past three to four years, as have the cumulative earnings of Elance.com’s freelancer community (figures 3–5).
Given the growing ability to digitize many types of work, this category of talent continues to grow rapidly. People in an open source talent community may participate in a literal open source project, such as the development of Linux software, the Fox browser, or Wikipedia. Or they might provide information and advice on a particular topic by participating in blogs and discussion boards (a number of technology companies, in fact, increasingly depend on these sites to answer technical questions that were previously handled by in-house employees—why hire technical and customer support staff when you can encourage blogs and discussion board sites to provide the same support for free?). Some companies are using open source sites and competitions, such as the platform provided by InnoCentive, to post challenges meant to invite insights and inputs to critical business problems.
In recent years, a totally new way of working has become possible. This can be seen in the advent of a range of new business models with a new set of players and a new language. There are three emerging models of open source talent that are central to understanding this evolving landscape:
Crowd work is also emerging as a field of academic study at business and technology colleges and universities.6 Examples of crowdsourcing idea, crowd work, and crowd project marketplaces include:
Year formed: 20017
About the company: InnoCentive is an online platform for open innovation that helps companies reach out to talent around the world by posting problems as challenges. InnoCentive, formed by Eli Lilly in 2001, awards a cash prize to the idea that best meets the challenge criteria. In its first year, it posted 12 challenges and sought 82 submissions from 16 countries.8
Revenue model: InnoCentive charges its clients for posting challenges on the website. Its fees range from $2,000 for a brainstorm challenge to $20,000 for a premium challenge.12
Award amount: Varies from $500 to $1 million13
Year formed: 2005
About the company: Mechanical Turk is an online crowdsourcing platform that helps computer programmers to reach out to a set of people across the world that can help with tasks that are beyond the scope of computers’ current capabilities. These tasks, such as tagging, choosing the best among a group, and performing data duplication, are known as Human Intelligence Tasks (HITs). Estimates suggest that Mechanical Turk reaches around 500,000 workers across 100 countries, with workers concentrated mainly in the United States (50 percent) and India (40 percent).14
Revenue model: Mechanical Turk charges 10 percent of the amount the “requestor” pays to the worker for a task, with a minimum charge of $0.005 per HIT.
Reward amount: The reward amount ranges from $0.005–$10 per HIT.
Growth: The number of workers participating in Mechanical Turk has quadrupled over the past five years.
Year formed: 200118
About the company: TopCoder hosts various online competitions on computer programming among its online community of software developers, algorithmists, and digital designers. The community is accessed via TopCoder’s online platform for open innovation. The projects are organized into small tasks and posted as competitions, with prize money awarded to the winners.19
As documented in the Harvard Business Review case study, among the best-known recent examples of creating a business ecosystem that leverages networks to significantly extend the reach of a critical function and team is P&G’s experience in the last decade with Connect and Develop, sometimes referred to as the evolution of R&D (research and development) to C&D (connect and develop).23 In response to a challenge from A. G. Lafley, the CEO, P&G’s R&D team was asked to develop a strategy for leveraging global scientists, suppliers, and networks for half of their future innovations. The idea was not to replace but rather to extend the reach, productivity, and capability of P&G’s 7,500 product development specialists and researchers by connecting them, using both propriety and open networks, with suppliers (and their 50,000 R&D specialists) and scientists around the world. The result offers a useful case study for talent and HR as well as for business and R&D leaders on how to utilize multiple business models—in this case, in-house (balance sheet) talent combined with external networks to access ideas and insights that can be acquired and commercialized.
P&G’s Connect and Develop network uses multiple talent approaches, including:
Through Connect and Develop, P&G has created an R&D talent and idea ecosystem that integrates a range of R&D talent spanning P&G staff in the company’s own labs, suppliers, retired scientists, and a global network of inventors and researchers. It’s the difference between employing an R&D staff of a few thousand employees within one’s own company and having access to a network of hundreds of thousands, or more, of idea and insight generators around the world.
From an open source talent ecosystem perspective, the experiences of Apple’s app store and Google’s Android store offer another significant example of a business model designed to leverage the efforts of highly talented individuals and professionals who work for themselves or for someone else, but who generate business value, brand value, and profits for a company. Apps were introduced by Apple in July 2008.24 At the Apple app store’s launch, approximately 900 apps, free and for purchase, were available for the iPhone and iPod and were then made available for the iPad. In April 2013, there were more than 775,000 apps for the the Apple operating system, including website tools, publications, and games. In five years, the Apple app ecosystem has grown to a multibillion dollar business with an estimated 300,000 Apple app developers in the United States alone; including developers for the Android and other operating systems, an estimated 500,000 app developers are active in the United States.25
The app industry is largely staffed by developers who do not work for Apple, Google, or any of the curators of the extant app marketplaces. They largely operate as part of the freelance and open source talent economy. Yet the global Apple app store has grown to more than $7.5 billion in the past five years (figure 7). The overall apps market (Apple, Android, and other platforms) is forecasted to potentially surpass $22 billion by 2016.26 Apple takes a 30 percent share of the revenue that flows through its app store.27 That’s a sizable source of revenue, profits, and brand stickiness that comes from people who don’t work for Apple. From a talent perspective, that’s the point: to extend the talent ecosystem beyond a company’s balance sheet and develop new ways to integrate talent and ideas into a business ecosystem.28
Traditionally, HR, talent, and business executives think of talent and employee processes as a supply chain with an on ramp for new employees and an off ramp for retirees. In between, they work for a company in its own offices, campuses, or factories. The process starts with “acquisition” and continues through deployment, learning and development, performance management, rewards, and career planning.
All this is different in the open talent economy, where the life cycle—supply chain—view of talent is giving way to an ecosystem view that requires a fresh perspective on the foundation or scaffolding on which to build and manage talent networks. The starting point is to reimagine both what work needs to be done and who can do it; in essence, the process begins with an expansive view of work design and workforce planning. While the concept of the employee life cycle may continue as the underpinning for balance sheet talent, for other categories of talent, business and HR leaders may need a new set of principles directed more toward navigating and managing talent ecosystems.
Consider the evolution of five core processes from the old “life cycle” to the new “ecosystem” model, and how they are changing in the open talent economy:
A crucial first step for managing talent in the open talent economy is to connect talent leaders with the business executives designing businesses and business models so that they can develop new ways of working that take advantage of the range of current talent models. A second step is to brand and position the business and talent ecosystem in ways that can attract the best talent and engage them to participate, whether that talent resides within or outside the enterprise. While companies will continue to focus on acquisition for the portion of critical talent that remains on their balance sheet, the new approach to talent, as the examples discussed above suggest, moves beyond ways to acquire to ways to attract and access different pools of talent.
The open source economy presents new challenges to workforce planning as well. The historical model was focused on filling capability requirements by hiring people, full- or part-time, to work for the company as employees, with the accompanying expectations of an organizational livelihood and career. In contrast, the future challenge is focused on workforces (yes, plural). The emerging challenge is to plan and design work around, and to access, workforces of all types—on the balance sheet, in joint ventures, borrowed, freelance, and open source.
As an increasing percentage of talent and work moves off the balance sheet, one can see the growing relevance of new learning models. In a world where half of US employees might be independent workers and half of the R&D at leading companies is done outside corporate labs, individuals will have a growing need and incentive to be up to date on leading ideas, approaches, and tools. Lifelong skill development will increasingly be the responsibility of the individual; off-balance-sheet employees will need an off-balance-sheet corporate university. In this connection, an important development is the advent of massive open online courses (MOOCs) from consortia such as EDx and Coursera, as well as new learning models like the instruction offered by the Khan Academy. The value of a certificate of completion from the Stanford MOOC on artificial intelligence or machine learning becomes clearer in an environment where individuals need to both keep their skills up to date and find new ways of communicating their capabilities and credentials.
The second challenge for total rewards is to begin the complex process of creating rewards, meaning, and careers for employees who are not on a company’s balance sheet. One of the areas in which new approaches and innovation are needed is how companies can compensate, reward, and create career options for workers in all segments of their talent portfolio. This might involve creating tiers or categories of freelance employees with different levels of access to projects, work opportunities, and corporate learning and development programs (both online and in person). Additionally, as is already done by network marketing organizations, compensation for off-balance-sheet workers might involve different levels of rewards for different levels and types of participation.
These five core reimagined talent life cycle processes are the start of a new framework for planning and managing talent across the open talent economy. There are other issues as well, including how to measure, anticipate, and manage risks; there have been some highly publicized cases in recent years where employees working for third-party companies to make and assemble products have created reputational risks and related expectations and liabilities. Managing talent risk in the open talent economy will require proactively considering risks associated with all types of talent, including off-balance-sheet talent. In addition, new challenges will arise with respect to systems and reporting, both for managing talent and employee processes and for maintaining collaborative platforms to support crowd work and network-based projects.
Several global megatrends are driving changes that propel the open talent economy around the world in every sector. These global megatrends don’t necessarily arise in the talent sphere, and they affect other business decisions as well, but they are fundamentally changing the structure of talent and work.
Globalization: The coming together of global talent markets across an increasing number of disciplines is changing the way work is distributed and sourced. Communications and connectedness have opened the world to new ways of acquiring, developing, and managing talent and work. The open diffusion of ideas, practices, and technologies—and, above all, people—creates opportunities for different parts of the world to influence and depend upon one another in new ways.
Technology: The growth in computing speed and storage is making virtual and global collaboration possible in more fields every day. When technology makes it easy and economical to work anywhere in the world, all of our workforce and workplace assumptions are open for review. Additionally, the development of smart machines driven by increasingly complicated algorithms (witness Watson from IBM and Siri from Apple) is again shifting work, in some cases from emerging markets back to developed ones. In the future, the open talent economy may well integrate smart machines and people in talent networks.
Mobile: Mobile computing is rapidly expanding access to the network of global workers connected by data as well as voice. Technical and social mobility decouples people and organizations from physical geography and defined markets. Today’s critical workforces are freer to go where they want to work instead of staying where work originates. Easier access to skill development resources is making vertical moves easier, too, for both people and organizations.
Education: In the past 20 years there has been an explosion in the growth of the education sector at all levels around the world, especially in Asian growth and emerging markets. The rapid growth of pools of talented manufacturing, services, and knowledge workers around the world continues to reshape global talent networks. We are witnessing a new wave of innovation driven by massive open online courses (MOOCs) in which leading universities, including Stanford and MIT, are making high-quality courses, taught by many of the world’s leading professors, available to tens of thousands of students around the world.
Social media: The rapid rise of social media has changed the way people connect and collaborate. For the first time, people can quickly, in some cases in real or almost real time, share ideas, information, and requests. These technologies and networks make possible a new level, speed, and intensity of collaboration, and sharing that is critical to the emerging open talent economy.
Analytics: Managing global talent ecosystems requires the ability to manage and mine large pools of employee and business data. Analytics allows companies and employers to access, review, rank, analyze, and maintain millions of records on individual tasks, projects, and workers. A number of freelance and open source talent, product, and idea marketplaces have quickly evolved over the past several years. The scale and reach of these online and open markets require a combination of cloud technologies and analytics to access, sort, and evaluate the hundreds of thousands, and in some cases millions, of people connecting to these networks. The core tools of data collection, mining, and analysis, as well as the ability to handle huge volumes of tasks and workers, make analytics one of the key enablers of open talent networks.
The themes of technology, mobile, social, and analytics are increasingly common ways of framing the forces driving business models in multiple realms. From a talent perspective, these postdigital trends, combined with the larger forces of globalization and the phenomenal growth of the education sector, are reshaping what is possible and relevant for HR and talent executives planning for the future. Understanding these forces and their potential impact, and the opportunities they present for business and talent strategies, requires a broadening of the traditional approach to talent, which has been almost entirely focused on balance sheet employees.
The open talent economy places organizations and talent in new relationships with each other, providing new benefits and new challenges. Employer-worker relationships are more fluid, faster-paced, and more focused on results and impact; at the same time, we are seeing changes in bargaining power, job security, and the social benefits offered by employment. In a business environment that offers a new array of talent markets and models extending well beyond the corporate balance sheet, the open talent economy presents a new starting point for talent strategy and management. Creating talent strategies that integrate different categories of employees and workers across a company’s talent portfolio may be among the fundamental challenges facing business and HR leaders in the next decade. Managing in the open talent economy will require a fresh look at core talent and employee life cycle processes and systems to ensure that they are taking advantage of the range of talent options available and anticipating and managing the emerging risks for talent on and beyond the balance sheet.
As Bill Joy, one of the cofounders of Sun Microsystems, famously remarked: “There are always more smart people outside your organization than inside.” This is one way to summarize the challenge for business, HR, and talent leaders as we chart the next generation of talent strategies and systems in the open talent economy.