When discussing entrepreneurial focuses, business models are what seem slight of a problem to be viewed upon. This is simply because one which would seem good for making substantial money for an auto manufacturer or a software-as-a-service set up won’t necessarily serve well for any local restaurant.
However, the year 2016 has come up with a way in which almost all business models could be possibly interconnected. It is a conceptual connection known as “dematerialization” brought about by Robert Tercek, an expert and the author of his new book “Vaporized”. This won’t be hard to anticipate if one thinks about how Uber and Lyft have transformed an automobile’s ownership in accordance with the need to travel forthwith. Simply put, the car (material object) has unknowingly been vaporized.
It’s been quite some time since Uber and Lyft have been around. “But what’s less obvious and less discussed is the gradual ‘uberization’ of everything you can possibly think of, from laundry and grocery shopping to education to leasing clothing,” states Tercek.
The lasting continuity for “uberization” of everything is just one for varied innovative or progressive business models coming up over the meaningful year. Let’s have a look at a short three-point conversational list for making money in 2016, of the many experts like Tercek.
1. Extracting collected data to be used as revenue.
For any traditional manufacturer, Tercek emphasizes on asking them or their top team questions like what part of their business consists of information, if it can be delivered separately refraining from the physical product and if yes, how they can learn from it, even cost effectively to make money in 2016.
Now, the solutions to the above could strike you out! Considering you make clothes, all washing instructions could be directed on a simple app, where one could also learn about customer problems through feedback. This way you never know if you could solve your installation problems to capturing solar data whilst simply installing your windows. It is direly the concept to re-think your business options concerning changeable information. It is the fact that you and other firms can actually extract useful customer feedback to enhance greater customer experience, hence making more money.
Tercek explains through the example of how automakers are now valuing Uber’s consumer and regional data collection and traffic patterns for their own interests. This elementary understanding is the route to eliminating those loopy overhauls of their plans. For instance, going back five years when you would’ve bought a car, an automaker was deprived of any of your driving habits.
Long gone are such days and from now on there would be ample software in automobiles and others (that were only thought of as hardware) to catch possible patterns and information concerning customer behavior. Hence, the car is now “uberized” when it comes with software to yield useful information to the world even when they’re not on the road to make money with their car by lending it to other drivers. Tercek adds that such practices are already being exercised when it comes to other power tools like lawn movers etc that are a bit expensive and less often used.
2. Paving association among individuals and machines
Supposing a dishwasher maker (an auto manufacturer or any other maker) turns apt to capturing data regarding its users, and it turns out useful to a project team for innovation of an existing product. The question is how this data can be made useful through social intelligence for humans to make decisions.
This is a question that will eventually be pondered over more and more as increasingly sufficient data becomes available. More business models will be seen in 2016 that will be focusing on how to solve the complexities to patch up human and machine learning, says Northwestern’s Kellogg School of Management Professor, Brian Uzzi. This categorized business model as he says is named as “though partnerships”.
He further adds, “For business leaders, managers, experts, and everyday people, machines will be an extremely important part of augmenting our decision making.” He highlights how on the show ‘Jeopardy’, humans blow their chances by giving wrong responses when they’re lesser confident but machines like IBM’s Watson do not. He comments,“ They do not get stuck or anchored to things in the past.”
Similarly he also points out that individuals have a natural phenomena to let the part of the brain—the visual cortex that processes what we see—affect the decision making. This would very clearly serve useful in a jungle but would be otherwise whilst in a hiring process. A machine would oversee the biasing features like skin color, gender etc thus making it easier to unbiased selections.
Undoubtedly, the first impressions do matter professionally, which is also why Uzzi says that it is important to have a business model that paves a path exactly between human and machine behavior to make decisions. HR departments would employ such a tool even with a high investment and so would many firms which have numerous amounts of team projects. This could help them to determine who would crack under pressure with big teams or vice versa. Over the time this will benefit to know the real leaders or the best collaborators for their projects varying in accordance with factors like team size, nature of project and time of the year they are best at.
For instance, if you could know how your employees use their Dropbox? You could possibly know their behavior if they always initiate some document and leave it or if they are upright before other work over it or even more which one maintains the healthiest record o punctually finished up projects. Hence Uzzi sees this year as the one in which innovative business models shall help many organizations to find better employees and other such data to make better decisions for their firms.
3. “Business model” as a short-term proposition.
With the advent of manufacturers turning themselves as software-as-a-service providers, the dire need for leadership teams to repeatedly evaluate their current models for missed opportunities has risen. This is independent of the business models being profitable or not.
So what is the best way to question the current model? If you really know what your customers feel, it will bring you to surprising concerns. Branding Expert Martin Lindstrom, explains in his upcoming book ‘Small data: The Tiny Clues That Uncover Huge Trends’ how he handed a condom to everyone in the audience, turned off the lights and asked the executives to open them, while speaking at the annual executive retreat at Anshell (a global manufacturer of medical gloves and condoms).
A minute later when the light were back on, not even one of the executives could manage to open the packaging, pointing out what their customers could be experiencing. Lindstrom says that this is what happens at larger organizations when they’re successful. “At large companies, you can look across different divisions. And all of them are fine-tuned machinery for one part of the puzzle, but often there’s no one doing the holistic work of looking at the big picture.”
Hence, one should always be thinking of their customer’s emotional experiences while questioning your business models. One should feel if they are actually in their pants.