Information technology is often seen as something that large corporations buy into, having a systems administrators that monitor all forms of the organisations internet and network infrastructure.
This isn’t actually the case. Well, at least not for the last couple of years at any rate.
According to Gartner’s Peter Sondergaard, the consumer technology market is actually much bigger than the enterprise technology market.
As broadband becomes widely available and cheaper device are flooding the markets, consumers have access to more services. With that, their demands have increased that companies adapt to their behaviour, instead of companies expecting consumers to adapt to theirs.
As an example of this, Sondergaard mentioned taxi-hailing company Uber. He explained that Uber took a step back from traditional taxi companies, and looked at what people really needed.
“You have to watch what the customer does, and don’t ask them what they want,” he said, explaining that Uber didn’t start with a traditional dispatch service, but saw that consumers had mobile phones and the need to call for a taxi.
Since both the customer and the driver have mobile phones, it almost seems natural now to bring the two together – and every company should adapt this philosophy.
“That is what companies are faced with now. They need an approach that mimics the approach of Uber,” he said.
The buzzword from Gartner at this year’s annual Symposium is algorithms, and how they will be playing a huge role for consumers and businesses alike.
Algorithms at their core are definitely not a new thing, as they’ve been around for ages, but Sondergaard said that we are in an age of algorithms now without even knowing it.
“The difference now is that companies haven’t managed their software code this way before. If you don’t manage it as an assets, then you are painting yourself into a corner,” he said. “The world has been too focused on big data over the last three years, but you need to hone in on what is really important.”
The analysis of algorithms is turning out to be much more than just gathering data, detecting patterns and giving people what they want. Staying with Uber as an example, the company’s lifeblood is pretty much built on an algorithm that brings drivers and passengers together.
But what on earth can a company like Uber possibly do with all the data that have been generated through hailing a taxi over the years?
Well, Uber can go through its data sets to pinpoint data that helps it run more efficiently. It can also give the data to city planners, so that roads and city infrastructure are better conceived and constructed.
Sondergaard surmised that Uber can help city planners to rid cities of bottlenecks, “but they won’t necessarily sell the data – they should rather just give it away.”
For now, it seems like a feasible plan, but as more companies start to explore and experiment with different kinds of algorithms, it might cause a bit of a problem in the future. Algorithms can be coded to perform various and different functions without any human intervention or knowledge, so in the future there will probably be a need for them to be regulated.
But that, according to Sondergaard, isn’t going to happen anytime soon.
“Algorithms will need to be regulated, but we don’t have the systems in place or a regulator to do that now. The regulators don’t have the knowledge to do so, and it will take a long time until they do. But the necessity of managing it in a responsible way will become important.”
In a case where an algorithm has caused a bit of havoc in the industry and a serious headache for regulators, Bitcoin is a prime example.
The crypto-currency threw financial regulators and institutions for a loop, as the online-only monetary value seemingly defied all boundaries when it came to value and transacting online.
Algorithms are found in almost all online retail environments. They form the core of Google, and it’s almost impossible to not find them in their crudest form in all websites.
As with everything technology related, it is only a matter of time until we find out which companies will be using algorithms for the greater good, and those that will use them for selfish or even nefarious purposes.