The Insightful Leader

Why marketers and journalists benefit from an understanding of how effective lists are designed and deployed.

Tips for creating an audio brand and managing your company's voice on social media.

This month’s Insight In Person podcast is an encore broadcast from January 2015 that investigates how to get off to a strong start in the new year. Blake McShane, an associate professor of marketing at the Kellogg School, explains that when faced with paying off multiple debts, those who tackle the smallest debt first are more likely to succeed in paying off everything. Eli Finkel, a professor of management and organizations at the Kellogg School, cautions that relying on others to reach our goals can undermine our own efforts. Miguel Brendl, an associate professor of marketing at the Kellogg School, underlines the importance of setting intermediate goals to avoid that motivational lull in the middle of longer tasks. Finally, Sunil Chopra, a professor of managerial economics and decision sciences at the Kellogg School, explains why the best possible outcome for many retailers come January is to have nothing to do.

Kellogg Insight takes a look at how humans can learn to work with machines in decision-making, and how machines can learn to understand us. We talk to three researchers who approach these relationships in exciting ways. Kellogg professor Brian Uzzi studies how machine learning can improve human decision making. David Ferrucci, formerly the principal investigator of IBM’s Watson project and now a senior technologist at Bridgewater Associates and founder and CEO of Elemental Cognition, discusses machines as collaborative thought partners. Sandra Waxman, a professor of psychology at Northwestern University, discusses how humans learn to understand the world, and what that means for machine learning.

We often have complicated relationships with machines, whether we are anthropomorphizing our navigation system, expressing our "love" for our phone, or getting creeped out when technology gets "too human." 

But do we trust these machines... and do they trust us?

Kellogg Insight takes a multifaceted look at human-machine trust with four researchers who approach these relationships in different ways. Kellogg professors Adam Waytz and Rima Touré-Tillery look at how designers can build human trust in nonhumans by integrating human characteristics—while avoiding the "uncanny valley" of over-humanization. Brenna Argall and Todd Murphey, from Northwestern's McCormick School of Engineering and Applied Science, design robots that can learn to trust humans.

From tweets to scientific discoveries, human behavior is surprisingly predictable.

Why do some ideas go viral while others go nowhere? Is it all about reaching that mythical tipping point, or is something else at work?

Kellogg Insight talked with two researchers who are starting to find answers by analyzing huge amounts of data. Microsoft’s Duncan Watts explains why we should stop worrying about a tipping point, and Kellogg Professor Dashun Wang discusses how human behavior is more predictable than you might think.

Advertisers pay good money to reach potential customers as they read the news on their phones, or shop on their tablets, or skim their Facebook feeds at work. But determining whether those digital ads actually lead to new purchases? That can be surprisingly tricky.

But determining whether those digital ads actually lead to new purchases? That can be surprisingly tricky.

In this Insight in Person podcast, we chat with Kellogg faculty members, as well as researchers from Facebook, to find out why many of the techniques that advertisers use to measure effectiveness are so inaccurate. We also learn what advertisers should be doing whenever possible.