Ideas Made to Matter
Strategy
4 forces upending business from MIT Sloan Management Review
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Business executives turn to MIT Sloan Management Review to better understand management practices, especially those driven by technological advancements. Here are four key developments that leaders should master to position their organizations for success in the age of disruption.
Leading into the future
What will it take to be a great leader five years from now, or even 10?
That’s the fundamental question underlying the work of MIT Sloan senior lecturer Douglas Ready, who argues that companies undergoing digital transformation need leaders who “fully embrace and understand how to compete and lead in the new economy.”
In a series of blog posts introducing MIT Sloan Management Review’s yearlong "Big Ideas Initiative: The Future of Leadership in the Digital Economy," Ready argues that the nature of work is being fundamentally changed by technology, demographics, geopolitical developments, and shifting cultural norms.
Of those four, trust in particular is crucial to leading effectively, Ready writes, because trust-based environments allow employees to feel safer taking risks, innovating, and speaking their minds — all critical to companies seeking to excel in the digital economy.
The problem with big data
Big data gives leaders insights that help them drive performance, cut costs, increase profitability, and analyze their customer base.
There’s just one drawback: The analytics tide is not lifting all boats equally.
MIT Sloan assistant professor of finance Maryam Farboodi posits that large companies, which produce more data relative to smaller organizations, are better able to attract investors, which view them as a less risky bet.
“Big companies get more than their fair share of financing at better terms, and are therefore better able to prosper,” Farboodi writes. “Smaller, younger companies, by contrast, receive less financing, which hampers their ability to grow.”
Working with colleagues at Stanford and Columbia, Farboodi developed three recommendations for preventing big data inequality. They include making small companies aware of the data imbalance, warning investors of their bias toward data-rich companies, and considering policy change as a solution.
Every leader’s guide to the ethics of AI
It’s never too early to worry about the ethics issues surrounding artificial intelligence.
Thomas Davenport, a fellow at the MIT Initiative on the Digital Economy, cites data showing some 30 percent of large companies in the United States have undertaken multiple artificial intelligence projects, with some 2,000 startups worldwide concentrating on AI.
At present, there’s a gap between how AI can be used and how it should be used, writes Davenport and his co-author who co-authored Vivek Katyal of Deloitte. Until regulations catch up, company leaders are “on the hook for making ethical decisions about their use of AI applications and products,” they write.
Davenport offers a series of recommendations for establishing a foundational approach to AI integrity within an organization. They include making artificial intelligence ethics a board-level issue, helping to alleviate employee anxiety, and recognizing that AI often works best with humans.
Tomorrow’s KPI dashboards will be your boss
As a business leader, of course you closely monitor your organization’s key performance indicators. But are you monitoring them in real time on your smartwatch? Your mobile phone? The digital assistant on your kitchen counter?
If not, you will soon — or so predicts Michael Schrage, a research fellow at MIT Sloan’s Initiative on the Digital Economy.
Schrage argues that the “KPI everywhere” climate will and should transform leadership behavior. KPI dashboards — smart, personalized, and powered by artificial intelligence — will be your new boss, he writes.
Schrage also writes that carefully curated data points can help cure the “KPI overload” that plagues the health care and travel industries, leading to better applications of machine learning and less reliance on intuitive decision-making.
