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title: Mistakes & Learnings
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"In one of our live experiences I made a couple mistakes. It was a mistake that stood out for someone that left a lasting impression."

| Invite a friend  /  View in Browser A few months back in one of our live experiences I made a couple mistakes. I could blame it on the functionality of a certain video conferencing tool but at the end of the day, it was a user error on my part that had messed up a breakout room experience for the participants.   Fast forward to the end of that program and feedback from the 50 or so participants - overall very positive, but for one of them that breakout room mistake I made was a big deal and it was reflected in their satisfaction of the over all experience.   It was a mistake that stood out for someone that left a lasting impression.   Fast forward to this week, I received the survey data back from another program I co-deliver. We received an NPS of 62, which is pretty good on all accounts. I have my beefs with NPS as a measuring tool but it's can be a helpful guide to understand different aspects of the participant experience. It's a starting point for investigation and lately I have become become fascinated by exploring the distribution of its results - the tails and the anomalies in experience that shape the superfan experience at one end and the dissatisfied at the other.   I am curious: Curious about what needs where met, or not met. What was satisfying and what was missed. And what they all wanted more or less of.  We can learn from both, and the in-between. And sometimes one mistake can be the difference maker. But how do we actually learn from this spectrum of inputs and expectations that shape satisfaction of the customer?   I have taken it upon myself to investigate all aspects of the distribution and trying hard to not get hung up on any one anecdote or piece of date - positive or negative. What are we doing well? What can we improve? What expectations are we not meeting? What expectations can we meet?   It's a continuous balance of tinkering and an attempt to ensure we iterate and improve at each step, while staying objective and true to what we believe in.    We have something that works well, but of course can be improved. But how much can we change it to satisfy someone who maybe the experience isn't for and risk compromising why it is we are here and exist for?   Of course at the meta level it’s very easy to say “if it’s not for someone it’s for no one” but in practice to figure out what to adapt it can be messy, grey and conflicting. Like a good story, if there’s no tension or challenge overcome things could become a bit bland! We continue with Dano Marr’s 3-part series on artificial intelligence. In this piece he specifically explores some of the challenges posed by the technology. "Stuff goes wrong all the time. You make mistakes. Fate can be brutal. And to have a place you can go to where no matter what happens they love you, it's like a warm blanket."     John Harris on Resilience & Imagination  Make change happen.   hyperisland.com    Invite a friend  /  View in Browser   Feel like this newsletter isn't your cup of tea? Unsubscribe here. Hyper Island, Virkesvägen 2, 120 30, Stockholm Unsubscribe Manage preferences View in browser |
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