2 Comments

Summary:

Technology buyers in some sectors drool over the promise of things like cloud computing and big data, but those words don’t mean a whole lot in places like warehouses or manufacturing plants, where how something works is far less important than that it works.

forklift
photo: Crown Equipment

Until recently, Jon Sobel and Sight Machine had a perception problem. “Someone once said we were too Michigan for Silicon Valley and too Silicon Valley for Michigan,” Sobel joked during a recent phone call.

He can laugh about it now that companies like GE have made “Industrial Internet” a household term, but it’s still a little true. You see, Sight Machine, which is co-headquartered in San Francisco and Ann Arbor, Mich., is trying to sell big manufacturing plants — from the ones building cars in nearby Detroit to those producing packaged foods — on the idea that they need to upgrade their computerized vision systems for quality control to Sight Machine’s cloud-based platform. It might end up being a transformative experience, but try telling that to prospective customers.

Whether they’re selling computer vision platforms or highly instrumented forklifts, companies trying to push the current generation’s hot technologies on users who don’t read the tech business press can end up playing a distorted version of the $100,000 Pyramid: The two contestants both want to get to the same place, but the contestant doing the selling can’t just throw a bunch of words out and hope they mean something to the buyer.

The trick to winning is establishing a strong sense of trust. That means knowing the technology they’re selling cold, but knowing the customers even better.

Translating tech speak into factory speak

“If you say I’m from Silicon Valley [and] I’m here to help,” Sobel said, “they’ll throw you out.”

It’s not because the manufacturing sector is afraid of technology (it spends hundreds of billions on it every year) or biased against Silicon Valley geeks who have never gotten their fingers dirty actually building something. It’s because the manufacturing sector can’t afford to replace its tried-and-true systems — however flawed — with promises of the next big thing.

These are production systems that move fast. Sometimes, they’re building very expensive machinery or components for very expensive machinery. You can’t come to them with a beta system and expect to just apologize if something goes wrong, or worse yet, come in pitching a half-baked idea that’s great in theory but has never really been tested in the field.

Vendors also can’t come in bandying buzzwords about. That might work in the C suite or in Silicon Valley, where some terms get people so excited they border on pornographic, but not so much on a factory floor in middle America.

“People on the plant floor don’t really think about buying software, they’re used to buying equipment,” Sobel explained. “… We don’t use words like cloud or big data, it doesn’t mean anything to them. … They say, ‘Does it work?'”

Sssh ... this is the result of cloud computing and big data technologies.

Sssh … this is the result of cloud computing and big data technologies.

Although he’s not coming from the Bay Area, Jim Gaskell, of New Bremen, Ohio-based forklift manufacturer Crown Equipment, can vouch. His business has evolved from one that sells big forklifts — or lift trucks, as they’re known in the industry — to companies running large warehouses and distribution centers into one that sells big forklifts and a cloud platform to manage data from all the sensors Crown is installing on them.

“They don’t buy it because it’s a neat gadget that makes them feel better,” Gaskell said. “They buy it because they’re trying to accomplish a goal.”

But it is high technology …

In the case of Sight Machine, the technology Sobel is trying to sell is a fusion just those buzzwords he warned against lobbing at customers — cloud computing, big data, computer vision. Speaking to me, a tech journalist, Sobel went so far as to describe Sight Machine’s platform as “Ruby on Rails for vision.” It’s a software framework for real-time computer vision, but it’s a lot more than just vision.

After the system identifies whether units moving across the assembly pass or fail inspection, it stores and the images in the cloud and generates data based on the units’ dimensions, time stamps and other points. Users can then access that data from their desktops, analyzing everything from time-series data on the whole line to how many standard deviations an individual unit’s dimensions were from the ideal. It doesn’t matter what algorithms are programmed into the camera’s processor — or even if the camera has an embedded processor — because all the work is done elsewhere.

sm2

It’s the kind of easy and detailed data analysis that somebody covering cloud computing and big data for a living might expect. Sobel said his company is even engaged in discussions with companies like Microsoft and Google about the cutting edge in image-recognition algorithms. He co-founded Sight Machine along with Slashdot Co-founder Nathan Oostendorp, who, it turns out, is also a skilled industrial engineer.

But it’s likely none of this matters much to the guys writing the checks that pay Sight Machine’s bills. To some of them, the idea of using a cloud platform might be an utterly new concept. They’re just trying to escape from the Stone Age — some customers were previously keeping quality control data in three-ring binders — without fear that upgrading to 21st-century technology will render their operations, however antiquated, ineffective.

And “that’s the norm, not the exception,” Sobel noted, because many computer vision systems in place today are really just designed to identify abnormalities and make pass-fail calls on the fly. Once that call is made, the data is often erased by the camera’s embedded processor. That’s why some factories turn to those binders or other jerry-rigged systems that allow them to keep some records, even if accessing or analyzing them is nigh impossible.

“There’s nothing revolutionary about [what we're doing] except that it just hasn’t been done in manufacturing,” Sobel acknowledged.

Teaching moments in the world of forklifts

Crown Equipment has experienced the same sort of situation, although its customers are often coming from a place of even less emphasis on data analysis. Five years ago, Gaskell said, people used to ask Crown Equipment about advice on managing their fleets of forklifts and they wouldn’t even know how many they had. They’d ask, for example, if $1 million was a reasonable cost to manage their forklifts for a year without any real context around that number.

So Crown’s first move into the data space was just to help customers get a handle on their fleets: Figure out how many they have (“A lot of customers end up having too many trucks,” Gaskell said) and the degree to which they’re using them (“They think they’re using the truck 24-7 … they find out they’re using them 4 to 5 hours a day,” Gaskell said), and then figure out a plan for making that more efficient.

Now, the company is managing sensor data from its lift trucks so companies can figure how they’re being operated and ensure they last, in part by changing drivers’ behavior. The sensors are measuring things like speed, whether the machine is sitting idle, force of impact and even whether the wheels stopped moving (this, it turns out, can be a sign of whether someone ran over a bump in the floor or crashed into something). “Once the operator realizes he can’t fool you … that’s gonna start changing operator behavior,” Gaskell said.

Analyzing the force of impact in InfoLink.

Analyzing the force of impact in InfoLink.

But in order to let customers actually benefit from all this data, Crown has had to help them evolve their cultures into ones that value data over words. He estimates 9 of 10 customers would probably not take full advantage of Crown’s cloud platform, called InfoLink, if left to their own devices. So the company educates them not only on how to use it, but also on the fact that the data is telling the truth even if, for example, a driver said he just ran over a twig.

“It started off about selling hardware,” Gaskell said, looking back on Crown’s business. “What it’s turned into is providing a service.” And as a service provider, he added, “There’s a different quality level … that I have to provide for my customer now.”

A question of trust

Back in San Francisco, Sight Machine’s Sobel is trying to develop with its computer vision customers the type of relationships an established company Crown has with its forklift customers. And he thinks he might have it figured out. “Everybody thought … that it would be impossible to sell to manufacturing clients,” he said. “I have found … that it’s incredibly straightforward.”

It all boils down to establishing trust, which means being up front about what the technology can do for customers today, as well as what it can’t do. There are no exaggerations or promises of amazing capabilities coming down the pike. “That,” Sobel said, “is the one thing that’s fatal with these guys.”

  1. Nicholas Paredes Friday, October 25, 2013

    I’m unsure what systems are used in our warehouses as opposed to say Amazon, but the robotic pickers are amazing. Designing for mobile in this space is different in that the solution has to be verified against costs.

    No company will implement a new system for the sake of the technology. But, I have seen blue collar guys implement complex inventory management and purchasing systems.

    Share
  2. Will Worthington Sunday, October 27, 2013

    cool story, bro! really glad to see Big Data making its way into the middle America and being useful to a sector that sorely needs it.

    Share

Comments have been disabled for this post