The Relationship Between People and Machines in the IoT

People have been sharing knowledge for millennia. Only recently are machines and other objects exchanging what they know.

It’s getting easier and faster to collect data from connected devices in the Internet of Things-era, requiring new questions and resisting an impulse to assume causes or connections until effective analysis is done.

Managing how people and machines co-exist is another IoT balancing act.

It’s a topic Martin Baker has been watching closely as senior digital content manger at Hershey Corp. He suggests the book Leading Digital: Turning Technology Into Business Transformation, written by three MIT business experts. Successful companies – guided by so-called Digital Masters — are committed to using data and analytics throughout an organization for sustainable competitive edge.

Want proof? According to the book’s research, Digital Masters are twenty-six percent more profitable than industry peers and generate nice percent higher revenue from their physical assets.

Machines do what they do best, and humans focus on creative, personal tasks where they excel. Together, people and data bring a digital transformation that neither can manage alone, Baker added.

Mining data for knowledge

Are you sifting through tons of data to find a trend? There’s a data warehouse app for that. Then, people need to discuss possible outcomes or responses. They may query the data repeatedly looking for underlying causes or patterns.

“What you know is more important than what you own. But traditional business thinking views money spent on knowledge – people, networks, data, software and processes – as an expense, not an investment. So businesses need new tools to identify, measure and communicate the value of their knowledge,” said Mary Adams.

She founded a consulting group, Smarter Companies, to help executives identify knowledge resources and value them – or the cost of replacement – on a company balance sheet.

For instance, Toyota Corp. executives developed a “5 Why” method of analyzing situations. Asking “Why?” to question a particular circumstance five layers deep led to a deeper understanding of what could be changed – and what couldn’t – in trying to improve daily business operations.

Knowledge sharing and collaboration

“Think of data as the ‘know what’ and knowledge as the ‘know how’ or ‘know why’ – there are lots of things you can do with those raw materials,” said Robert Armacost Jr., a director at iKnow LLC, a New Jersey-based consulting firm. He has led collaboration and knowledge sharing efforts for global enterprises such as KPMG.

Machines share data when programmed, but people need incentives to collaborate and, over time, build trust and knowledge of relationships. Can you get different offices or departments to exchange information or learn from each other? That’s one field where managers aren’t likely to be replaced by an algorithm.

At least not yet.

Image by Saad Faruque on Flickr (CC BY 2.0)