That is funny in a sad kinda way, bdzin, but spotlights something that us technically aware types often fail to consider. Namely, the vast majority of people don't know or care about a lot of the warning, safety, and preventative stuff that's built into vehicles. Well, maybe "don't care" is unfair. Not attuned to is a better way of putting it. Also, they don't get why us types are horrified at this. A recent example from my own experience, though only very loosely related, is that I was trying to explain to my teenaged son why it wasn't a good idea that, when he had refilled his flat bicycle tire, he ended up with the tire valve cocked sideways at a 30-degree angle. He didn't understand why I thought that was sub-optimum.
I think the social media streams can be a valuable source of customer intel and feedback and can go a long way in fostering some feel-good, even if not problem resolution, as Alex well notes. To some degree, monitoring these same streams for good ideas that can serve as starting points for design innovations is also a form of crowdsourcing and can help the cause of building better products. On the cautionary side, customers don't always know what they want or what they might want. So the real challenge lies with digging through these streams to find the nuggets of insights that can develop into a real idea.That's a whole lot of legwork.
Focus groups with actual design engineers? Sounds like a great idea. I have been both a participant in early technology focus groups and managed a couple of technology focus groups. The two things I saw missing fairly consistently were first, quality of the participants, aka customers, and their ability to articulate their likes, dislikes, and needs, and second, the presence of marketing people alone, and the absence of engineers.
I was at a BMW dealer trying to explain to a customer who used post-it notes on her dash that the note covered an important warning indicator regarding water temperture. The radio/CD player volume level masked the audible indication of an over-temperture situation. The customer was then out BIG bucks for the ensuing repair. Seems the car manufacturers should also have yet another warning for smart people.
Tim's comment about unfixed issues resonates, and also raises the question about whether the Twitter monitoring that's been adopted by many vendors as a customer service tool, is having any sort of impact. Anecdotally (from my personal experience), it has potential. My Time-Warner Cable went out a few months ago. Wasn't getting any love on the customer-service phone, so I did a tweet. Boy was I shocked when I got a response within 5 minutes from the company's social-media-monitoring person. And he followed up with me twice! It didn't actually expedite the fix, but it made me feel better!
This article reminds me of Tom in Officespace whose main function was to give information from the customers to the engineers. The first step the efficiency consultants did was to remove this position. Direct communication between customers and engineers is very important and can really help with product sales.
I still find it amazing to see message boards full of complaints for a single issue over multiple model years. Obviously, these complaints were made and no one took heed of the problems.
@JimT: The actual interpretation of what users are saying about what they actually want and need in a product is the gold standard, as you well point out, Jim. I think that's the best practice that really differentiates the Cadillac Design Research Team and the smart phone example you cited. It's a great skill to be able to translate those subtle nuances around behavior and what wasn't said into tangible product requirements and innovations that resonate as opposed to being sidetracked by the obvious wish-lists and complaints that customers actively verbalize.
What The Cadillac design team did was excellent Market research, and is exemplary of what every new product development effort should tackle, but seldom does.The “end-users” of the product will intuitively know what works for them, and will always have suggestions like; “It would be great if you had a gizmo that could ….. “.These types of suggestions are considered “need-based” and not necessarily innovation solutions; rather just problem statements.Our job as the design (and market-research) teams is to embrace those needs and then invent the innovation solutions.What mature design engineers and seasoned market research professionals need to look past, are the silly comments made by the focus-group-participants.For example, during one long-past focus study group I managed before the commercial release of Smart-Phones (circa 2002) we provided one real working smartphone prototype, plus 3 other non-working balsa-wood industrial design models offering various form-factor solutions.Without exception, every group participant commented on how much more desirable the light-weight design models were, over the actual working prototype.Well, duh.But the message was clear. The all liked “lighter” over the actual clunky working prototype.If nothing else, it pointed the design efforts of the subsequent years into more exotic and lighter materials.All good inputs.All good things.
It's also worth mentioning that design engineers say they need to be careful in the kind of information they take from consumers. Consumers often don't know what they want and several designers told us they worry about customers "giving answers that they think we want to hear." Cadillac's engineers and designers made a point of sitting in the back seat and quitely watching, rather than asking questions.
Are they robots or androids? We're not exactly sure. Each talking, gesturing Geminoid looks exactly like a real individual, starting with their creator, professor Hiroshi Ishiguro of Osaka University in Japan.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.