How To Deal With Customer Risk Aversion As An EdTech Innovator

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How To Deal With Customer Risk Aversion As An EdTech Innovator | Cómo Enfrentar la Aversión al Como Innovador EdTech
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It’s never easy to break new ground. It’s even harder when the field has been occupied by the same players as always, who don’t necessarily see why they should change business as usual given their years (or even decades) of dominance. But when there is an overarching ethical dimension involved preventing them from taking risks, what hope is left for the innovators?

We tend to expect data and results to speak for themselves. After all, they are objective and unequivocal accounts of quality and performance. But even after making a solid case in favor of experimentation and learning as a way to increase value in the long term, the customer or stakeholder simply may not buy in, which can certainly feel disconcerting.

As Blackboard’s Mike Sharkey argues, the answer to this conundrum could start with visualizing an extra step between skepticism and the incontrovertible evidence that still fails to convince. The key, which may or may not surprise you, is empathy. Specifically, the kind of empathy that helps us see deeper into the customer’s worldview and find the reasons that keep them from taking bolder action.

No matter which side we’re on, we are all biased. And no matter how hard we work to overcome them, there is always a chance our biases permeate into our products. With more advanced technologies, such as analytics and machine learning, these biases are only growing more menacing. This is exactly why full disclosure about the bias on each side is vital from the get-go. Sharkey believes “openness, collaboration, and sharing is the way to go.”

And in order to accomplish this, there is only one way forward: having lots of conversations, at least some of them face-to-face. Communication allows us to start looking into the reasons behind a customer’s “low tolerance for experimentation.” Once you get a good idea of the customer’s way of thinking, you can use Sharkey’s model to frame the existing situation, where the “tolerance for experimentation” axis is crossed with the “mission criticality” axis on a plane.

This model works by outlining possible paths towards a higher experimentation tolerance with the goal of finding one the customer finds less “critical” or irreversible. The path, of course, must be feasible. Sharkey makes one final point: Our ability as an industry to take paths of lower criticality are almost always possible because of previous technological breakthroughs.

At the end of the day, it’s not perfection or promise that breaks new ground, but human connection.

Read more about “Analytics and Ethics…a Perceived Shift?” at blog.blackboard.com.


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