Whenever a new product is created many have an idea that it should only ever be to solve a problem that somebody has. Sometimes it is to totally change the way that people perceive something, for instance the iPhone totally changing the mobile phone market. It could also be to take an existing product and simply mane it better, like how Uber created a better way to order taxis.
Regardless of the exact reasons for the product, whether it is brand new, an iteration of a previous version or the same version with added features, the goal is always innovation.
Until recently, this was down to individual brilliance and foresight, such Henry Ford who famously said 'If I had asked people what they wanted, they would have said faster horses.' The invention of the car was only down to his foresight and innovative thinking that flew in the face of public perception at the time. However, in modern times, although this kind of thinking is important, it is taking a secondary role to the use data to inform designs and entirely new products.
The first and most obvious way that data is used to create new products is through web tracking which can suggest what people like, dislike or don't care about. Netflix are a prime example of using this effectively when they created House of Cards, their award winning political drama. Although the concept (the BBC miniseries basic plot with David Fincher and Kevin Spacey attached to the remake) was up for bidding, Netflix could see a correlation between people who watched the original mini-series, films by David Fincher and films with Kevin Spacey. It worked perfectly and became the first internet only show to win a Golden Globe.
However, this is a fairly basic use of data in the creation of a new product, especially as just seeing what a customer might like from previous actions is fairly simple and it is essentially a slightly more complex suggestion engine. There are some companies taking the concept to the physical world though, one of them being Procter & Gamble (P&G).
Their CEO, Robert McDonald is attempting to make the company the most technologically enabled in the world. A key to this is their use of simulation analytics, which uses data to model a product with slight variations in material, design or ingredients. This can then be tested without producing a prototype, saving money, time and ultimately creating a superior product. This process requires powerful modeling capabilities and comparatively powerful computing power, but will ultimately create significant value for both the P&G brands and the customers who use them.
The use of data doesn't even need to be especially complicated and some of the most basic elements of data analysis can simply help to show which of two potentially innovative products is likely to be a popular product. Julep, a Cosmetics startup are a prime example of this.
As a startup, they naturally don't have the same kind of technological or data-driven capabilities as a $219 billion company, but they have still managed to utilize data to decide between two potentially innovative products. This is through simple A/B testing of standard advertising and social media campaigns. It is certainly not as impressive as being able to change the basis of a product on a screen thousands of times, but it allows them to see which of a small number of products is the best received. It is similar to how many startups are using crowdfunding sites. It gives them the opportunity to not only raise capital, but also, by providing multiple options of the products, gives an early indication of which have the most commercial potential.
Data is driving product innovation across the entire business spectrum, from those who are just starting out, to the biggest companies in the world. There is little argument that there is certainly still a place for minds like Jobs, Ford or Zuckerberg, but we are seeing with the use of data that it is no longer a prerequisite to creating truly innovative products.