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MIT CDB Assistant Professor, Renee Gosline, Describes Digital Marketing's Newest Influencers

MIT CDB Video: Sinan Aral on Social Commerce

At the recent MIT CDB conference on Big Data, professor and social networking expert, Sinan Aral, discusses peer influence and how it can impact product marketing strategies and the online economy.

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Digital automation, and its impact on labor, society and the economy, has been studied from multiple perspectives and through many lenses.  In his new research and analysis, Daron Acemoglu, the Elizabeth and James Killian Professor of Economics at MIT, acknowledges inequalities created when automation displaces certain human skills. However, he also says it is possible for new technology to create more complex versions of existing tasks where labor has a comparative advantage, tipping the scales back toward a future with plentiful jobs.

Acemoglu completed his graduate work in mathematical economics and econometrics at the London School of Economics, where he also received his Ph.D. in economics. His recent research focuses on the political, economic and social causes of differences in economic development across societies; the factors affecting the institutional and political evolution of nations; and how technology impacts growth and distribution of resources. Acemoglu has published four books: Economic Origins of Dictatorship and Democracy (joint with James A. Robinson), Introduction to Modern Economic Growth, Why Nations Fail: The Origins of Power, Prosperity, and Poverty (joint with James A. Robinson), and Principles of Economics (joint with David Laibson and John List).

He recently spoke at an MIT IDE seminar on the topic of, "The Race between Machine and Man: Implications of Technology for Growth, Factor Shares and Employment.” IDE Community manager Paula Klein followed up with four questions. Below are his responses.



Q.  The current rivalry between digital automation and humans seems focused on economics and labor issues— concerns that labor will be progressively marginalized and made redundant by new technologies. Is this focus premature or overstated?

A: It is certainly not premature. We have seen many different types of tasks produced and performed by labor, even fairly skilled labor, become automated over the last 30 years. We also know of new technologies that will automate some very major occupations (regulations permitting), including driving, airplane piloting, some aspects of surgery, certain types of diagnoses and even parts of the practice of law.

Yet there is an aspect of it that is overstated. These are still only some of the occupations that humans perform today. The more important overstatement comes as one turns from automation to the prospects for future employment creation. This rapid process of automation does not mean that the future economy will not create jobs. If you look at the last several decades, qualitative evidence suggests rapid automation has been going on for more than a century, and a lot of the new employment comes in new tasks and occupations. So, as machines take jobs previously performed by humans, the economy appears to create yet other tasks and jobs to employ the displaced workers.


Q: How does your task-based framework help explain the current economic situation and provide context? Can you briefly summarize the model and your research?

A: Our framework helps us understand the aforementioned patterns and why the fact that new employment will come from new tasks and activities. But more importantly, because it endogenizes the speeds at which existing tasks are automated and new tasks are created, it also highlights why a period of unusually rapid automation generally brings a subsequent period of rapid creation of new tasks. Put simply, rapid automation depresses the price of labor which has fewer tasks to work. This then makes it more profitable for new tasks, which employ new labor, to be created.


Q: How might these new tasks spur economic growth and innovation?

A: The growth implications of creating new tasks are essentially a corollary of what I have just described. Growth comes about both because of automation -- we can do things we have been doing more cheaply-- and because of the creation of new tasks; we have new goods and services using better technology. Anything that spurs innovation triggers faster economic growth. So, rapid automation is a double whammy: it benefits us directly and it spurs additional creation of further growth-enhancing new tasks.


Q: What guidance can you offer to employers, workers, students and policymakers to prepare and adjust for the Second Machine Age?

A: All of these scenarios are no consolation if you do not have the skills that new tasks and jobs will demand. Some economists are now questioning whether college is a good investment. There are certainly reasons for rethinking some of our long-cherished assumptions: college is expensive and college graduates have not done very well in the labor force over the last 15 years or so. Nevertheless, improving the skills of our workforce and improving our own skills still remain the only ways of ensuring that we adapt to the future of technology.

Most discussions and examples of business innovation focus squarely on the production side; how new products are created, built and marketed to improve efficiency and move the technology dial forward.


What gets lost in this classic view, however, is the human capital impact resulting from disruptive innovation, according to Michael Schrage, research fellow at MIT Sloan School’s Center for Digital Business. And, he asserts, that misrepresents innovation’s real role.


“Innovation is not just about faster, better, cheaper products and services, but an investment in the human capital and capabilities of customers and clients,” he told faculty at a recent lunch seminar on the topic of “Misunderstanding Human Capital,” at the CDB. “The transformative effect on human capital” is largely misunderstood or absent when innovation’s value is considered, Schrage argues. “Successful innovations transform users and customers” not just production processes, he asserts.


At the lively, interactive lunch session, Schrage noted that when Ford first mass produced automobiles he also facilitated “the mass production of drivers” – a form of human capital that hadn’t really existed before.


Similarly, Google created searchers, not just search engines, disrupting the way consumers interacted and adding value to Google’s algorithms. Walmart trained consumers to look for low prices, while Tesco focused on customer loyalty. Schrage wants to call attention to what he terms the “misunderstanding of mass production’s significance on human capital,” and to study the consequences – positive and negative -- of these actions on consumers.


This thinking borrows from two-sided market theory and platform economics where creation of one new market can lead to the creation of a new, complementary network such as iPhone apps, Schrage says.


Schrage’s latest research seeks to demonstrate that “consumptionary capital” is an important aspect of innovation that has been widely overlooked. In fact, technological innovation often creates and enhances human capabilities and increases competencies that can generate new business opportunities. Eyeglasses were technical innovations that made it possible and affordable for more people to read and see; hearing aids and cochlear implants were technical innovations that made it possible for more people to hear. They expanded the abilities and capabilities of their users to do and consume more, he says.


Schrage introduced his viewpoint in a Harvard Business Press e-book last year, Who Do You Want Your Customers to Become?  His premise is summarized by HBP as follows:

Asking customers to do something different doesn't go far enough. Serious marketers and innovators must ask customers to become something different instead. Even more, you must invest in their capabilities and competencies to help them become better customers.

A primary insight of the book is that innovation is an investment in your clients, not just a transaction with them, and that transforming customers will transform the business.

By addressing questions such as: How will skills change as a result of Google cars? How do innovations such as recognition engines and crowdsourcing impact consumer habits, behavior and income? How are new consumer norms created? –the research may help businesses better understand their customers. From that, they can adopt more meaningful marketing and product development plans that will yield more -- and more valuable -- customers.


Successful business innovators like Henry Ford, Steve Jobs and a Jeff Bezos, he argues, have clear visions of who they want their customers to become.

That the amount of business data is skyrocketing is hardly news. All we have to do is consider the huge volumes of data and archives at any major financial institution, retail business or healthcare organization. Then multiply those amounts by a several times and you’ll have an idea of the staggering amount of information amassed at web-based businesses such as Google and Amazon.


More important than the quantity of information generated, however, is an understanding of how it is used and how it can create value for organizations, their customers and the overall economy. At the MIT Center for Digital Business, a recent statistical study on the implications of big data offers significant proof that proper use of analytics and business intelligence tools can help businesses use their digital information to grow efficiently and show bottom-line results.


Specifically, my paper with Heekyung Kim, Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance?, finds that “companies that use data-driven analytics instead of intuition have 5%-6% higher productivity and profits than competitors.” Research was based on the business practices and information technology investments of 179 large publicly traded firms. Huge improvements in metrics are allowing a granular analysis of data—whether it resides on mobile devices, in email or elsewhere in data centers-- to find out more about customer behavior. What’s more, the relationship between data-driven decisionmaking and performance also appears in other measures such as asset utilization, return on equity and market value. Our results provide some of the first large-scale data on the direct connection between data-driven decision making and firm performance.


As we wrote in the recent Atlantic magazine article:

“Today, businesses can measure their activities and customer relationships with unprecedented precision. As a result, they are awash with data. This is particularly evident in the digital economy, where clickstream data give precisely targeted and real-time insights into consumer behavior.”


And while web-based digital companies – notably, Amazon and Google--are in the forefront of data analysis, now we are seeing offline companies in logistics, manufacturing, retail, casinos and finance making use of these techniques as well. Gallo Wines, UPS, Caesar’s Entertainment and are a few examples cited in the Atlantic article. Marketing and sales organization are leading the way and are far ahead of some other departmental users, but increasingly, we see business units such as HR using email to help internal staff productivity benefits. Similarly, manufacturing lines are gaining access to real-time data from CRM and ERP systems to help them track trends and demand.


To delve into this topic in-depth, we are offering a new two-day executive education course on March 28 at MIT Sloan in Cambridge, Mass. [see related blog for details here.]