Need to building IoT teams
Building talented Internet of Things (LoT) teams is a challenge as it is a uncharted territory and can make and break the path to success. A team of anthropologists, software architects, and designers at Intel Labs have observed dozens of…

Building talented Internet of Things (LoT) teams is a challenge as it is a uncharted territory and can make and break the path to success.

A team of anthropologists, software architects, and designers at Intel Labs have observed dozens of organizations and interviewed a hundred-plus developers who build IoT solutions for a recent study.

They helped the investigating team identify what worked for them (and what doesn’t) by telling them how they work, how they worked together, the jobs they have to get done, and the challenges they face on the way.

Most IoT project work boils down to the following four types:

“Thing” development: get under the hood of devices to connect them as data sources and actuation points;

Middleware development: weave together data sources to make coherent and actionable wholes;

App development: build the interactions that engage and help users;

Data analytics: create analysis pipelines that turn data into action, insight, and decision making.

The Intel team found that great teams often tap into several of these coding domains. Savvy project leaders actively sought ways to cross-train their teams to ensure broader team-wide coding expertise and tighter team collaboration.

These “hybrid coders” are a valuable type of team whose expertise spanned at least two domains and, as a result, often had a high-level understanding of the IoT initiative as a whole.

The Intel team found that many LoT teams struggled with a common set of coding challenges. Such a situation helped pinpoint which coding disciplines are needed for the project to be successful.

The common IoT coding challenges included gathering and normalizing data to and from large numbers of endpoints, orchestrate system-wide data: integrate diverse data points so they can work together; manage edge data: control and analyze data at the edge to optimize its system-wide flows; deliver just-in-time responsiveness: coordinate system-wide data flows and user interactions to deliver results to the right people at the right time.

The Intel team found that most IoT teams target one or more of these challenges (taking on all four can be unwieldy). To do so, they leaned on specific combinations of developer expertise.

To keep up with the fast pace of industry change, IoT project teams and developers have to constantly learn on the job.

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