Where Industry Meets Innovation

  • Contact Us
  • sign in Sign In
  • Sign in with certificate
mit campus


Search News

  • View All
  • ILP News
  • MIT Research News
  • MIT Sloan Management Review
  • Technology Review
  • Startup Exchange

ILP Institute Insider

February 7, 2018

Communicating with Data and The Art of Persuasion

Miro Kazakoff is a lecturer, entrepreneur and consultant focused on how individuals use data to persuade others. He created the curriculum for the communications component of MIT’s Business Analytics Major and certificate. He is also the co-founder of Testive, an education technology company that combines technology, analytics and human coaching to help students prepare for high stakes exams.
Daniel de Wolff

Daniel de Wolff

In certain circles of industry and academia there remains a belief that “If the data is robust enough, it speaks for itself, but data never speaks for itself,” says Kazakoff. “It requires a person to give it a voice, to explain it, and to provide narrative and a sense of connection.” Kazakoff created “Communicating with Data,” a requirement for the new Business Analytics certificate offered by MIT Sloan. He wants to ensure that in addition to understanding the basics of conducting business analytics, students leave with the skills to ensure leaders use that data to make the right decisions. “This class, and much of my current work outside the classroom, is really about turning information into action: How do you take the knowledge and the right answer that you’ve generated and use that to change the minds of people who will never be as close to the analysis as you are. They may barely understand what you do.”

Miro Kazakoff
MIT Sloan School of Management

The Boston Globe recently interviewed Kazakoff after he and MIT Sloan Professor Kara Blackburn conducted a survey into the communications habits of the incoming Sloan MBA class. The survey painted a picture of millennial’s communications habits and what communication habits in the workforce may look like in the future, and the future does not look bright for long form writing. While 84% of students surveyed cited creating presentations as a substantial part of their work before coming to Sloan, only 40% said that long form writing was a substantial part of their jobs. “We need to put a lot more energy and training into teaching people how to structure and organize their thoughts. That’s something that writing forced people to do inherently,” says Kazakoff. “Now we’re going to have to teach it separately. All those slide decks let people cheat rigorous thought.”

The survey also highlighted the importance of visual literacy: “Visual literacy is essential when working with data. It’s as important a skill as writing and speaking when it comes to making complex data understandable,” says Kazakoff. “We have a whole generation of managers who have been given the tools of design without the training. It’s like handing your managers a pen without the confidence that they ever took a writing class in all of their education.”

His career as a lecturer and entrepreneur balances a belief in the importance of data and technology combined with an understanding that human beings are an essential part of the communication process. People not only interpret the meaning of the data but also drive how it will be used. Before coming to lecture at MIT Sloan, Kazakoff co-founded Testive, an education technology company that combines an online learning platform with a human coach to help students prepare for high stakes standardized tests. The algorithms that power the adaptive online learning platform were developed by Kazakoff and co-founder Tom Rose when both were students at MIT, as was the realization that people tend to be motivated by other people. In other words, Kazakoff and his team found that while good tech and a product that scales is essential for startup success, it’s not enough for educational success. “Machines can do amazing things, but they aren’t good at connecting with people emotionally and motivating them to do the hard work of actually learning,” says Kazakoff.

Video link coming soon...

“As I’ve returned to academia to focus on data communications,” says Kazakoff, “it’s been fun for me to continue exploring the line between what the machine can do and what humans still need to do when it comes to behavior change.” He relays an anecdote about an orthopedic surgeon at Boston Children’s Hospital who approached him to improve her communication skills to better serve her patients. As an expert surgeon, she found that her inclination was to begin patient conversations explaining diagnosis, procedure and risk, and only briefly touch on what the patient’s likely outcome and recovery time would be for a few moments at the end of the conversation.

Through discussions with Kazakoff, the surgeon decided to try out a different approach, beginning her patient conversations with the outcome (e.g., “You will be able to play hockey this season,” or “I’m sorry but you’ll most likely be sitting on the sidelines for the next few months.”). The seemingly simple shift altered the quality of her interactions by showing her patients that she was focused on the things they valued. “That’s one of the most interesting and exhilarating parts of data communications—helping people. Making the complicated simple requires a lot of energy and thinking, but it doesn’t require us to dumb-down or give up what’s important.”

For Kazakoff, one of the most exciting aspects of data communications at the present moment is the explosion of information, increased processing power and where humans fit into the equation. “We are collecting more information than ever before. We also have the processing power to handle that information in ways we never could before—and we are bringing machine learning to bear on it,” he says. But he notes that as information and technology have evolved, our brains have remained mostly unchanged for the last 10,000 years. This presents an interesting problem: “As machines take over more of what we call ‘thinking,’ how do we as human beings explain the decisions that our algorithms are telling us to make so that that we can use what the machines tell us and explain it to others?” As you might expect, MIT will be at the forefront of this exploration and Kazakoff will be in the thick of it, helping to shape the narrative so we can all understand.