The mad science of deployment: Augmenting human abilities

In 2010, Apple made the iPad. Organizations quickly adopted the device and sought to deploy it in scale. But how? At the time, there wasn’t a reliable, repeatable method to configure large amounts of devices. SHI took matters into their own hands and figured out a way to deploy tens of thousands of iOS and macOS devices before DEP was added to Apple’s deployment strategy. In today’s session SHI shared learnings from this experience and provided an exclusive preview of what they’re doing next to advance the future of human intelligence.

After taking a brief look back in time to where they started in 1990, presenters Dave Siederer and Hector Ibarraran, fast forwarded to 2012 and reviewed common questions IT admins had as a result of the limited tools that were available at the time. They included:

• “I have been tasked to deploy 1,000 iPads to my organization in the next three months. How should I proceed?”
• “What is MDM, and how can I utilize it in my mobile deployment?”
• “What happens if the CTO of our organization loses his iDevice containing company-sensitive data?”

At the time, SHI didn’t have all the answers, but they had some. With what they created, users could benefit from a custom app load and MDM enrollment, a custom background and icon arrangements.

“Our services have evolved with the times, as the first DEP-authorized reseller, along with using many other tools and partners to make our services the best they can be,” Siederer said.

Then they introduced expert. “Expert is what’s coming next. This is our big vision,” Ibarraran said. The goal is to give IT admins more time to do the things they’re good at and enjoy instead of asking “Have you turned it off and then back on,” over and over again. He further explained that while Expert has some AI components, it won’t answer a question if it isn’t 100 percent certain of the answer.

They then took a look at the question life cycle, using the question, “How many monitors can the Mac Pro support?” as an example. Siederer explained how it works in a few points:

1. The life cycle of the question generates a minimum of four messages, if all the contexts are satisfied with each message. If a vendor need to be involved, the cycle extends further.
2. Throughout the life of the question, no intelligence is captured. If the same request occurs throughout the day, the same process is repeated, because dialog between parties isn’t captured.
3. Expert gives the ability to model dialogs for later use with the Dialog Builder. This reduces the amount of messages going back and forth and ultimately shortens the question life cycle.

Ibarraran concluded the session saying, “The whole idea is that we want everyone in the audience to get back to the things you do best.”