Improving strategic execution with machine learning – Michael Schrage

MIT Sloan Management Review Executive Editor David Kiron

David Kiron, Executive Editor, MIT Sloan Management Review

Research Fellow, MIT Center for Digital Business

From MIT Sloan Management Review

Machine learning (ML) is changing how leaders use metrics to drive business performance, customer experience, and growth. A small but growing group of companies is investing in ML to augment strategic decision-making with key performance indicators (KPIs). Our research,1 based on a global survey and more than a dozen interviews with executives and academics, suggests that ML is literally, and figuratively, redefining how businesses create and measure value.

KPIs traditionally have had a retrospective, reporting bias, but by surfacing hidden variables that anticipate “key performance,” machine learning is making KPIs more predictive and prescriptive. With more forward-looking KPIs, progressive leaders can treat strategic measures as high-octane data fuel for training machine-learning algorithms to optimize business processes. Our survey and interviews suggest that this flip ― transforming KPIs from analytic outputs to data inputs ― is at an early, albeit promising, stage.

Those companies that are already taking action on machine learning ― investing in ML and actively using it to engage customers ― differ radically from companies that are not yet investing in ML. They are far more likely to:

  • Develop a single, integrated view of their target customer.
  • Have the ability to drill down to see underlying KPI data.
  • Check their KPI reports frequently.

These differences all depend on treating data as a valuable corporate asset. We see a strong correlation between companies that embrace ML and data-driven decision-making.

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The trouble with cybersecurity management – Mohammad S. Jalali

Mohammad Jalali, MIT Sloan Research Scientist

From MIT Sloan Management Review. 

Cybersecurity is becoming top of mind for customers and organizations, as highly publicized data breaches and cyberattacks at large corporations have revealed just how much damage a hacker can do by accessing or manipulating an organization’s systems. In addition to the immediate financial and operational consequences, a breached business often faces class-action lawsuits, regulatory fines, damage to its reputation, and a string of other ramifications.

Consider Yahoo. In April 2018, the company agreed to pay a $35 million fine for failing to report a 2014 data breach in which hackers stole personal information from hundreds of millions of user accounts. A month prior, a judge had ruled that the victims of the data breach had the right to sue Yahoo for negligence and breach of contract for not disclosing its systems’ security weaknesses.

Yahoo is not alone; a startling number of companies have faced public relations disasters surrounding security breaches in the past few years. On the one hand, the trend makes sense; cyberattacks are becoming more common than ever as hackers become more adept at penetrating systems. On the other hand, it doesn’t make sense, because while those carrying out cyberattacks are gaining more tools, so are the specialists who defend against them. Cybersecurity practices can — and need to — be better.

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Seeing past the hype around cognitive computing – Jeanne Ross

Jeanne Ross, Director & Principal Research Scientist at the MIT Sloan School's CISR

Jeanne Ross, Director & Principal Research Scientist at the MIT Sloan School’s CISR

From Information Management

Given the hype around artificial intelligence, you might be worried that you’re missing the boat if you haven’t yet invested in cognitive computing applications in your business. Don’t panic! Consumer products, vehicles, and equipment with embedded intelligence are generating lots of excitement. However, business applications of AI are still in the early stages.

Research at MIT Sloan’s Center for Information Systems Research (CISR) suggests that small experiments in cognitive computing may help you tap the significant opportunities AI offers. But it’s easy to invest huge amounts of cash and time in failed experiments so you will want to carefully target your investments.

The biggest impact from cognitive computing applications is expected to come from automation of many existing jobs. We expect computers to do—faster and cheaper—many tasks now performed by humans. Progress thus far, however, suggests that we have significant obstacles to overcome in our efforts to replace human intelligence with computer intelligence. Despite some notable exceptions, we expect the displacement of human labor to proceed incrementally.

The business challenge is to determine which applications your company is ready to cash in on while resisting the lure of tackling processes that you can’t cost-effectively teach machines to do well. We have studied the opportunities and risks of business applications of cognitive computing and identified several lessons. These lessons offer suggestions for positioning your firm to capitalize on the potential benefits of cognitive computing and avoid the pitfalls.

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Tech innovators open the digital economy to job seekers, financially underserved – Irving Wladawsky-Berger

MIT Sloan Visiting Lecturer Irving Wladawsky-Berger

MIT Sloan Visiting Lecturer Irving Wladawsky-Berger

From The Wall Street Journal

The future of work is a prime interest of the MIT Initiative on the Digital Economy, started in 2013 by researchers Erik Brynjolfsson and Andy McAfee. To help come up with answers to questions about the impact of automation on jobs and the effects of digital innovation, the group launched the MIT Inclusive Innovation Challenge last year, inviting organizations around the world to compete in the realm of improving the economic opportunities of middle- and base-level workers.

 More than $1 million in prizes went to winners of the 2017 competition in Boston last month in four categories: Job creation and income growth, skills development and matching, technology access, and financial inclusion. Awards were funded with support from Google.org, The Joyce Foundation, software firm ISN, and ISN President and CEO Joseph Eastin.

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“The Future of American Innovation”– a podcast with David Schmittlein

MIT Sloan Dean David Schmittlein

MIT Sloan Dean David Schmittlein

MIT Sloan’s David Schmittlein appeared on CEO Global Foresight to discuss how the United States is leading world innovation in life sciences, information technology, and energy.

The segment was recently made available as an 8-minute podcast on the Innovation Gamechangers podcast, available on iTunes.

Dean Schmittlein also discusses innovation clusters and how the MIT community encourages a culture of collaboration and action learning. The program also includes interviews DARPA director Arati Prabhakar and Carl Dietrich, an MIT alumnus and CEO of flying car company Terrafugia.

Listen to Innovation Gamechangers podcast, available on iTunes.

David Schmittlein is the John C Head III Dean and Professor of Marketing at the MIT Sloan School of Management.