Lately it seems that technology is making a lot of people’s lives more difficult, rather than easier. This is partly because the platforms wars have accelerated, making tech companies less friendly and less cooperative with each other, and partly because the development of technology is concentrated in the hands of a few people—all of whom resemble each other closely—and this small group decides who and what technology is for. Increasingly this agenda is decided by the data-obsessed.
As more companies have shifted their attention from the consumer market to the enterprise market, the consumer is only of interest as a value on the market. Products for consumers are being degraded, and the solutions the market offers are often less than ideal. In some cases, such as the discontinuation of Google’s RSS feed, the alternatives are less robust and give the user much less control. Feedly, one of the companies stepping up to fill Google’s footprint, has a terms of service agreement that has the user signing over all rights to their original content, nor has the service been straightforward about how it plans to monetize.
Despite this, the enterprise model hasn’t been able to leave the consumer completely behind—the consumer is still an essential piece of the puzzle, but, like a puzzle, the consumer is broken down into bits that are stored, analyzed, traded and sold. Unfortunately, outdated models, old case studies, and archaic assumptions are employed to these ends, making the results quite less than incisive.
In the meantime, a large segment of the population has been left behind by these models, and neither are these disenfranchised cash poor. On the contrary, companies and marketers from Asia are successfully reaching them.
Since many American tech companies don’t have the understanding or patience (not to mention the desire) to reach these niches, companies and marketers keep hitting the same easy vein. Tapping known markets is quicker and surer than building or organizing new ones, but at this point the competition is stifling. Too much competition over the same ground just destroys the turf and that is what we are seeing now.
A venture capital culture that favors quick profits over longevity produces a predictable crop of companies or “start-ups” designed to produce fast cash but little new infrastructure, technology, or wealth. This model isn’t ideal for the development of novel technologies, which is required if we wish to create new real wealth, spur economic growth, and solve the many big problems facing our world. It’s also no surprise that investors also favors models that bring in data—the more personalized the better.
A stroll through Chicago Tech Week expo floor last week—bitcoins accepted—revealed a redundant multiplicity of casinos, web design boutiques, IT companies, marketing firms, app developers and data-purveyors of every description. We personally were on the hunt for a collaborative and secure document sharing service, but unlucky. What we did find was a lot of companies with floor people who were unable to describe exactly what their company did. Among the many different companies competing over the same concept, there was very little that distinguished any of the brands and made them stand out.
A mania for co-branding and affiliate marketing confused things further. Many people handed me one business card, and then another business card, tried to explain what they did, how the two companies were related, but were never able to succeed. An inconstant wireless signal made it difficult for one staff member to demonstrate his company’s service. There was outsourcing, insourcing, and plenty of storage space for sale.
Without exception the companies that impressed us most had the founders or engaged staffers available on the floor, ready and able to talk about their company. We did talk to exciting companies and people.
There was definitely some fun stuff, but none of it world-changing.
But who said technology has to be world-changing?
The problem is that the technology sector has so often promised exactly that. It promised to save the American economy, and when that didn’t happen, it argued that it should be judged alone for its many merits. Last July, The Economist said passionately: “Why should one treat America’s decaying rust-belt and soaring Silicon Valley in the same regard? Doesn’t aggregating the two commit gross injustice to understanding?”
It would seem so. The so called rust-belt, now past its prime, was once the economic engine responsible for all the advances we still enjoy today, whereas the technological sector has created virtually no new wealth.
And in fact, since that eloquent plea was published last July, we’ve seen a technology sector that offers less choice, less freedom, less connectivity—less of everything.
Enter Big Data, the driver of many of these trends. Everywhere we went we were reminded of its terrible appetite for information. It took the Bing Stage on Thursday with a panel entitled “How Big Data Is Going to Save the Planet”, though more to the point seems to be how Big Data plans to save the industry.
The takeaway message? Big data is going to to save the world, but first it has to figure out how to regulate temperatures in office buildings.
To be fair, despite its lofty title, the focus of the panel was energy, and most of the speakers were specialists in the field of electrical engineering—heating and cooling. They were excited about smart office buildings and smart appliances and all the vast data being sucked in by buildings, embedded with various sensors and such. By collecting and analyzing this data, it’s even possible to reduce energy costs by 20% or so.
Apparently heating or cooling buildings is a lot tricker than you might think, for, as we learned, even if the temperature is perfect, there could still be a problem, because the heating and cooling systems might be operating simultaneously. It was somewhat difficult to hear the details, as none of the panelists or their their supporting staff could make the sound system work. Perhaps this was a ruse. In any case, it is an interesting argument that data-mongers find themselves making:
Machines are better
However, machines are inefficient
Whole scale data collection, storage and analysis is necessary to identify and root out inefficiencies
In the panel’s own words:
Now, information exchange simply between machines is becoming ever more prevalent, creating new opportunities for entrepreneurs to build tools and capitalize on the need to fix the inefficiencies of machine.
It’s easy enough to see how this could help big data shape “economic models that underpin investment strategies.” If you make the problem, you can make the solution. You have a captive market.
Building and maintaining a vast data infrastructure, also known euphemistically as “the cloud” is hardly in its own right an energy efficient endeavor, but if you can use it to pin down a restive market, you can make money.
When people make money without creating new real wealth, the health of the larger economy suffers. Unfortunately, most people involved in the tech sector don’t seem to get it, even as they drop like flies.
We hurried out of the conference onto the floor. Hundreds of different companies were represented there. With all these company’s poised to capture business in the enterprise market the health of the market matters tremendously. Some ventured the observation that the market was pretty shaky. That’s something of an understatement.
On the way out we crowded into an elevator with a group of people. Everyone seemed anxious to get out. As soon as the door began to close a woman spoke to us:
“I’m going to practice my elevator pitch.”
Everyone laughed with evident relief, but she was dead serious. She began to speak, describing some food app that was integrated with Linkedup. Or was it Spacebook? My Face?
Fortunately, the elevator cut her short and her audience took to flight.