Skip to Content
Uncategorized

Taking Hold of Supply Chains

A “tangible interface” turns simulations into collaborations.
July 1, 2002

Neville at the warehouse calls Sophie at the factory to tell her that surging demand has almost depleted the company’s stock of microchips. Alarmed, Sophie orders piles of raw materials to build more chips. Three months later the warehouse is restocked, but now Neville says demand has fallen off. Sophie immediately stops ordering materials-only to see demand rebound, resulting in a new chip shortage.

Unintentional feedback loops like this are rife in business, and they’re hard for managers to tame without knowing which loops cause the most damage and therefore should be tackled first. They’re also costly; word of supply chain glitches typically degrades a firm’s stock price by 20 percent, according to researchers at the Georgia Institute of Technology. While computer simulations of supply chain fluctuations help, they’re hard to interpret or operate collaboratively. Now, with the aid of a tabletop computer interface invented at the MIT Media Laboratory and funding from Intel, researchers at MIT’s Sloan School of Management are giving managers a hands-on feeling-literally-for the factors that can mend or upend their supply chains.

The system is one of a number of “tangible interfaces” being developed at places like MIT, Mitsubishi and the Oregon Graduate Institute to do everything from simulating business processes to augmenting communication in military command centers. Sloan professor Thomas Malone says the MIT system is designed to “get everyone playing together,” exploring “what-if” scenarios such as the effects of building more warehouses or changing shipping routes.

A supply chain simulation starts with graphics projected from overhead onto a Media Lab creation called the Sensetable. Users can place wireless “pucks” on specific areas of the surface-for example, a graph of inventory versus time-then turn a dial atop the puck to strengthen or weaken the parameters affecting the graph, with repercussions immediately displayed on related tables and graphs. A group of managers studying Sophie and Neville’s problem, for example, might try varying the time delay between inventory reports and raw-materials purchases, perhaps finding that inventories stabilize when Sophie waits a week before acting on Neville’s information.

“Supply chains are these things that everybody talks about, but nobody can see,” says Intel director of information technology-industry business research Mary Murphy-Hoye, who initiated Intel’s investment in the project. “Introducing a degree of tangibility could change the nature of the conversation.”

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

How scientists traced a mysterious covid case back to six toilets

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.