Meeting Employers’ Needs in the Data Economy

• Companies that capitalize on data-driven management benefit from the network effect, a positive feedback loop in which each interaction improves services and attracts new users.
• These companies can use data to outperform rivals by offering the right merchandise and improving the customer experience.
• While software and service companies want to partner with universities to offer data certifications, business schools also should create programs designed to turn out tech-savvy graduates.

 
In 2022, supply chain disruptions, pandemic uncertainties, and inflation caused many retailers to struggle to control inventory levels. Kohl’s and Nike saw their inventories balloon by over 40 percent, leading to rampant discounting as outdated merchandise remained on the shelves. But Macy’s largely avoided these issues, raising its inventory levels by a modest 7 percent.

How did Macy’s do it? The company’s data-savvy leadership team combined information from co-branded credit cards with economic indicators such as inflation and wage growth to predict what consumers would be demanding in future months. The result was a prescient shift in orders that led Macy’s to have the right products on the shelves at the right time. This put the retailer in stark contrast to competitors who faced a glut of some items and a scarcity of others as consumer preferences changed.

Macy’s is just one example of the way that information is the engine of growth in the new data economy. In fact, a 2017 story in The Economist describes data as the oil of the 21st century. Over the past five years, data has spurred growth for online retailers, Silicon Valley tech firms, and traditional brick-and-mortar companies like Macy’s.

Data technology is so important for the economy that it can even determine the competitiveness of nations. For instance, in the 2018 book AI Superpowers, author Kai-Fu Lee notes that the U.S. excels in the discovery of technology, but trails China in producing the talent needed to apply the technology. He expects that China will be the next superpower in the race for technological innovation.

Business schools have a tremendous opportunity to turn out graduates who have the business and technical skills to keep organizations and countries competitive. But first, these future business leaders need to understand the factors that are shaping the new economy and reshaping competition.

The Network Effect

The data economy is driven by the network effect, a positive feedback loop involving customers, data, and services. Each Amazon shopper, each Kroger loyalty card holder, and each Caterpillar equipment operator leaves a trail of data. Insights gleaned from this information enable the company to provide better service, ranging from product recommendations to targeted promotions to preventive maintenance. This improved service attracts more customers who generate more data, which is then used by firms to create even better service.

The network effect provides companies with the potential for growth in revenue with modest increases in capital investment and operating costs. For example, after implementing its data-driven customer loyalty program in 2003, Kroger achieved 52 consecutive quarters of growth in same store-sales. Its current same-store sales are double the 2003 level.

The network effect makes technological capability essential to competitive advantage. Companies with technological capability constantly improve their products’ ease of use, glean insights from data, and develop and implement new technology. This culture of ongoing technological improvement is known as development and operations, or DevOps. The book The Phoenix Project describes how managers can use the tools and culture of lean manufacturing, the theory of constraints, and Six Sigma to create shorter flow times, quicker feedback loops, and faster rates of continuous improvement.

The data economy is driven by the network effect, which makes technological capability essential to competitive advantage.

The technological capability of a company relative to its competitors determines its rate of growth (or decline). Amazon was not the first online retailer, Google was not the first search engine, and Spotify was not the first online music streaming service. Each company used superior technology to become a success story within the data economy.

The New Rules of Competition

Businesses that understand how to use data can compete by a whole new set of rules. For example, in the past, newspapers traditionally earned most of their revenues through advertising; subscriptions did not even cover printing and delivery costs. However, as publications moved online, both subscriptions and ad revenues sharply declined for most publications, and many newspapers struggled or closed.

But The New York Times was able to use data science to restructure its business model. Through machine learning, the paper determined how to help editors do their jobs better and how to engage readers with an enhanced user experience. The paper also created a funnel of subscribers by offering some free content and deeply discounting first-year subscriptions. As a result, the paper has seen its subscriptions rise from 1.5 million in 2012 to 10 million today—and subscribers, not advertisers, have become the paper’s primary source of revenue.

Players in other industries also have relied on superiority in data-driven management to triumph over rivals. For example, in 1998, Circuit City was the largest electronics retailer in the U.S., with success driven by brand recognition and operational efficiency. But the company didn’t respond quickly enough when Amazon began selling electronics online in 1998 and Best Buy followed suit in 1999. Amazon and Best Buy also offered some low-price, low-margin products that motivated potential online customers to create accounts and shop frequently, which facilitated the collection of customer data and primed the network effect.

In 1999, Circuit City went online, but its platform was more onerous to use than those of the other two retailers. It also failed to capture enough data through online sales to develop a better understanding of its customers and products. It made bad decisions in both virtual and in-store businesses, and in November 2008, it filed for bankruptcy.

What Has Changed?

The network effect has become a powerful economic force due to four phenomena:

Big data. The three V’s—the growth in the volume of data, the velocity at which information is collected, and the variety of data available—have reshaped the economy.

Artificial intelligence (AI). By constantly “learning” as it ingests more data, AI not only can improve business decision-making, but also can outperform humans in high-skill endeavors such as medical image interpretation and financial auditing. In addition to performing clerical tasks, AI can guide robots in assembly line work, warehouse picking, and other manual jobs. AI chatbots can engage in humanlike conversations and perform tasks such as writing essays or computer code.

Enhanced computing power. Due to constantly improving technology and economies of scale, the cost of computing has shrunk, and so has the cost of collecting, storing, and moving data. Cloud computing allows hardware and software to be provisioned instantly with no capital investment.

As data technology tools have become more user-friendly, they have become more accessible to nontechnical users.

Democratization of technology. As data technology tools have become more user-friendly, they have become more accessible to nontechnical users who bring critical thinking skills, communication skills, and a broader knowledge base to work projects.

The Managerial Talent Gap

Despite the critical importance of data management, there is a shortage of talent for both managerial and technical positions. To fill some of those gaps, tech-oriented companies—such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, Oracle, and Salesforce—are offering certifications. A 2017 study by Business Insider magazine found that AWS certification results in a 26 percent increase in salary on average.

Many of these certifications are suitable even for entry-level nontechnical workers, some of whom advance to earning specialized credentials in areas such as cloud platforms for AI. Even for future managers who never do hands-on work with these platforms, the certifications provide valuable understanding of concepts such as security, scalability, reliability, performance efficiency, and cost.

While software and service companies offer their own industry certifications, many of these companies are willing to share content, practice exams, and computer time with universities as a way to develop more tech-savvy talent. Business schools, too, can offer their own data management and analytics programs to supply workers who will keep industries and nations competitive.

The Critical Skills

Because companies need workers with a wide range of tech-oriented skills, business schools should offer courses in a number of functional disciplines. Most obviously, schools should create business analytics programs that turn out graduates who know how to ask relevant business questions, find answers, and communicate in a language managers can understand.

In such courses, students should gain experience solving applied problems. For instance, they could use market basket analysis, a data mining technique, to find ways to grow businesses. They also should learn simple exercises that show how AI can make predictions and identify outliers, associations, and clusters. These future managers should understand that AI can help quantify, but does not eliminate, the uncertainty that is the essence of most business decisions, and it may require a large amount of training data before it can be effective.

Business analytics skills are so crucial that the Institute for Operations Research and the Management Sciences (INFORMS) gives out the UPS Smith Prize to schools that excel in providing students with these skills. The award has gone to business analytics programs at the University of Tennessee Haslam College of Business (2018), the University of Cincinnati Lindner College of Business (2019), and the University of Iowa Tippie College of Business (2021).

According to INFORMS, programs that receive the prize do not just help students acquire strong technical skills. They also offer students opportunities to work in teams, practice leadership, make oral presentations, write reports, take personality assessments, receive coaching, and interact with industry practitioners through capstone projects and on-campus forums.

A Varied Curriculum

But companies need tech-savvy workers in every department, which means business schools should consider creating data-oriented courses in other parts of the curriculum as well:

Business strategy. In these courses, students should gain an awareness of the new competitive landscape, including the drivers of the data economy and the keys to successful competition. They should study examples of industries in which data technology has changed the rules of competition and defined new winners and losers.

Companies need tech-savvy workers in every department, which means business schools should create data-oriented courses in many disciplines.

Entrepreneurship. In these classes, students should learn how to use data to disrupt many traditional business operations. Such skills would make them valuable to companies such as Innovu, which uses data to determine how companies across Tennessee can reduce employee turnover, cut healthcare costs, and improve safety.

Operations. These courses should focus on the DevOps culture of achieving short flow times, short quality feedback loops, and continuous technological improvement.

Other functional business disciplines. Because companies need graduates with technical expertise in areas such as marketing, finance, and supply chain management, business schools should create minors and certification programs for business students in these fields.

The liberal arts. Employers are looking for workers who bring in fresh perspectives, as venture capitalist Scott Hartley notes in his book The Fuzzy and the Techie and numerous interviews. Therefore, business schools should consider creating minors and certifications aimed at students majoring in arts and sciences disciplines.

Executive education. These lifelong learning offerings should include short-term, long-term, and certificate options that allow alumni to keep up with the data economy.

Trained for the Future

No matter what kind of courses they’re teaching, professors can use business simulations to enable students to compete in a simulated data-driven economy. Through business games, students can observe the network effect in action as they experience the challenge of pricing products and services that both produce valuable data and serve as funnels for new customers.

As students gain confidence in how to collect and manage data, schools can be certain that they are training the next generation of managers who will know how to streamline operations, drive sales, and outperform the competition.