“AI is changing the cost and availability of expertise, and that will fundamentally alter how businesses organize and compete,” said “Strategy in an Era of Abundant Expertise,” a Harvard Business Rreview (HBR) article by Harvard Business School professor Karim R. Lakhani and Microsoft corporate strategists Bobby Yerramilli-Rao, John Corwin, and Yang Li. At its most basic level, a business can be thought of as a bundle of expertise organized to accomplish specific tasks for competitive advantage. The evolution of this expertise defines the evolution of the business.
The article defines expertise as “a combination of deep theoretical knowledge and practical know-how in a specific domain.” Expertise can take many forms, such as deep subject matter knowledge in a specific field, — like manufacturing, software engineering, or a medical specialty, — and the skills needed to successfully run a business, — e.g., marketing, sales, operations, finance. “Companies create value by applying their expertise efficiently at scale to solve problems for their customers. Typically they possess it in a variety of areas, but most differentiate themselves through their unique proficiency in just a handful of activities that are fundamental to how they create competitive advantage.”
While critical to a company’s success, keeping up with technological advances can be quite challenging for two key reasons. First, expertise is constantly expanding, making it difficult to stay abreast of advances and insights in a competitive global marketplace. And second, the cost of accessing that expertise is constantly falling, lowering the barrier for new, fast moving competitors. The interplay between these two forces, — “the increasing amount of expertise required to create value and the decreasing cost of accessing that expertise — shapes companies and affects the scope of their operations.”
The intrinsic structure of companies has long been a subject of study, most famously by Ronald Coase, the eminent British economist and recipient of the 1991 Nobel Prize in economics. In 1937, Coase published a seminal paper, “The Nature of the Firm,” in which he argued that, in principle, a firm should be able to find the cheapest, most productive goods and services by contracting them out in an efficient, open marketplace.
However, markets are not perfectly fluid. Transaction costs are incurred in obtaining goods and services in an open marketplace — including tasks such as searching for the right people, negotiating a contract, coordinating the work, managing intellectual property and so on. A firm’s size and scope is determined by the relationship between internal and external costs.
Firms will keep expanding and adding people as long as doing so is less expensive than securing the additional goods and services in the marketplace. But, there are limits to what can be produced efficiently within the firm, as well as to how big a firm can get and still remain competitive against faster moving companies. All that growth generally leads to ever larger, multi-layered hierarchical organizations. The additional layers of management and staff can cause the organization to become bureaucratic, significantly impacting its ability to quickly embrace new ideas and technologies when market conditions change.
As explained by Harvard Business School professor Clayton Christensen in his theory of disruptive innovation, history shows that fast moving entrepreneurs and startups will then enter at the bottom of a market, and eventually displace the established market-leading firms with innovative products, services, and business models. A well managed company strives to achieve an optimal balance between what work gets done within and outside its boundaries.
“For most of industrial history Coase’s theory predicted the evolution of businesses as the cost of access to expertise fell,” noted the HBR article. “To keep pace with competition, they invested heavily in growing their internal expertise across product manufacturing, finance, sales, and other functions, developing complex structures to manage sprawling operations. In recent years, however, the trend toward ever-expanding operational scope has reversed as the breadth and level of expertise needed to remain competitive has continued to grow.”
“Since the 1980s several technological innovations have led companies to rely more and more on markets to access expertise far broader and deeper than what could practically exist within a single entity.” The explosive growth of the Internet has made it much easier for companies to transact with each other around the world. The connectivity and universal reach of the Internet has enabled companies to integrate and better coordinate all their various processes, as well as to go beyond the boundaries of the firm and develop highly sophisticated global supply chains.
Vertically integrated firms have evolved into virtual enterprises, increasingly relying on supply chain partners for many of the manufacturing and services functions once done in-house. In addition, the past few decades have seen the emergence of open source and other forms of collaborative innovation where companies and individuals successfully collaborate on an increasing variety of projects alongside more traditional proprietary business models.
How will AI impact the future of work It’s hard to tell because we’re in the experimental stages of the rapidly evolving AI era, where companies are introducing a variety of tools to help improve productivity and efficiency of everyday business tasks.
In a 2015 paper, “The History and Future of Workplace Automation,” MIT economist David Autor raised an important question: why hasn’t automation already wiped out the majority of jobs. The answer, he wrote, isn’t very complicated, although frequently overlooked. Most jobs involve a number of tasks or processes. Some of these tasks are more routine in nature, while others require judgement, social skills and other human capabilities. The more routine the task, the more amenable it is to automation.
But just because some of the tasks have been automated, does not imply that the whole job has disappeared. To the contrary, automating the more routine parts of a job will often increase the productivity and quality of workers by complementing their skills with machines and computers, thus enabling them to focus on those aspect of the job that most need their attention, judgement, and expertise.
“Companies that take advantage of AI will benefit from what we call the triple product: more-efficient operations, more-productive workforces, and growth with a sharper vision and focus,” wrote the authors in their HBR article. Let me discuss each of these potential benefits.
Cost and time savings. “Companies can transform many of their business processes and achieve new levels of efficiency by empowering employees to leverage AI for discrete tasks.”
“Historically companies have looked to offshoring and outsourcing to reduce costs. However, they found it cost-effective only if they outsourced an entire process. Now, with AI assistants, people can access expertise for individual tasks or steps within it, which allows them to make improvements without having to move the entire process. The ease and low cost of handoffs to AI mean that many processes can now be run far more efficiently.”
Greater workforce productivity. “As companies adopt AI assistants, those assistants will effectively put at least a base amount of expertise into the hands of every employee who uses them, enabling that person to perform better.”
AI assistants can augment the knowledge and expertise of just about every employee, whether low, average or high performers. “It may reduce the time and cost to onboard new hires, broaden the pool of those who can perform specific processes, and provide more flexibility in how employees are deployed to achieve outcomes.”
More investment in activities that matter. “As AI agents and bots transform business processes and empower workforces, companies will be able to fundamentally rethink how they deploy their resources.”
“Smart ones will identify the handful of processes in which they can provide world-class expertise and capabilities and reallocate resources to deepen the moats around those processes. At the same time, they will reduce employees’ focus on noncore processes by leveraging AI-enabled platforms provided by third parties.”
Finally, the article adds, to take advantage of the benefits of AI-based expertise leaders should be asking themselves three key questions:
- Which aspects of the problem we now solve for customers will customers use AI to solve themselves?
- Which types of expertise that we currently possess will need to evolve most if we are to remain ahead of AI’s capabilities?
- Which assets can we build or augment to enhance our ability to stay competitive as AI advances?
“Without question, companies will continue to use bundles of differentiated expertise and other hard-to-replicate assets to create and capture value,” wrote the authors in conclusion. “But the expertise and assets that proved valuable in the past will need to be reexamined as AI improves. Over time the organizations that fully exploit AI to rapidly adapt their operations and strategy are the ones that will thrive.”
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