Problems, as it turns out, are the fastest way to bring visibility to your day’s mechanics. Everything is smooth sailing until it isn’t, and then whatever failed is suddenly the center of attention.

This makes the new class of automated tech really hard to get right.

For the muggle world, not all invisibility is magic.

You have to earn invisibility

Automated products hit a wall if you make them run silently in the background before teaching people how they work. Invisibility is earned, a lesson we learned the hard way.

The quick and dirty background about our app: Robin is a room booking tool for offices that runs on mobile, web, and tablets. You can book from the apps directly, but there’s also a twist for mobile users — we can run in the background and use iBeacons to detect when you’re in a room, booking calendars automatically. This means your team stays updated with a live feed of who and what’s available.

The fact you don’t need to open the app to use it is where our problems start.

The original app showed where you were, and did everything else in the background.

Our early approach (as you can see in the screenshot above) was “Keep your phone in your pocket, we’ll handle the rest”. The thinking was that if people just had the app installed, we could do the rest automatically based entirely on presence data. It was a noble idea (aren’t they all?), but after our beta launched we quickly realized being so far out of the way created a new mess of problems.

The challenge with “hiding the work” too early is people never learn how to do it manually — just ask anyone who’s walked into a closed door. In usability, these cues are called affordances, and are how (most) people manage to use everyday objects like chairs without instruction manuals. New tech already starts with a knowledge gap. Early on you’re better off automating 95% and requiring a button for the final 5% than skipping the education step.

Then there’s the issue of credibility. If you can’t see how a decision is made, it’s harder to trust the results. Amazon reminds you recommendations are “based on your purchase of X” for a reason.

Missing feedback moments

In our case, getting feedback from the beta was very difficult. We would talk to customers several weeks in and we’d hear “Oh, I actually haven’t opened the app recently.” Things were mostly working, but we had a visibility problem and our usage metrics alone weren’t telling stories we could act on — we were flying blind.

“Oh weird, you’re not showing up yet.”

Worse still, when the app did have bugs it failed silently in the background. Our early users would notice Robin wasn’t working when they had room collisions or the web dashboard stopped showing a coworker.

The only time people remembered we were there was when the app had issues, which is a terrible way of reintroducing yourself.

Getting to this point was slow because when you’re working with a system with no screens it’s hard to give people feedback of “It’s working” without interrupting them constantly. On the other hand, by the time it’s not working you may not have the option to tell anyone — like only noticing a broken air conditioner after you start to sweat.