What does it take to sustain innovation in your organization? Ideally, you could devote time, money, and resources to a think tank that had nothing to do but produce a steady stream of promising innovations all day every day. But that isn't realistic for the majority of organizations that do not have the name Google on a sign out front. Everyone else needs some assistance to achieve and maintain a state of regular and consistent innovation. Many forward-thinking businesses are finding that big data holds many of the answers to driving innovation. Here's why.
If you can find a little waste to shave off here and a few minutes to cut there, you can make huge strides in operations without a big whammy of an innovation. It just takes small bits of insight and innovation, and big data can deliver that.
Much of innovation management isn't just coming up with the Big Bang of ideas. A lot of innovation is made up of smaller improvements that combine to make a big impact. For example, say you can reduce 10 percent of your operation's waste here and make a 15 percent improvement in production time there. Eliminate a bottleneck, streamline a couple of processes, and together you've significantly improved your operations without producing a single new revolutionary idea. That's the power of using big data in your internal operations. Small innovations add up to huge improvements.
Similarly, big data can not only answer some of your questions about the market, your customers, the industry, and your competitors, but it can also bring up a host of other questions that set your innovation team off on the path of developing new concepts. Big data is known for generating as many or more questions than it actually answers. While this can be frustrating for teams who are tasked with solving a particular problem, it can be a goldmine for those assigned to innovation management. Big data can deliver some stunning revelations that can be used in all kinds of ways.
For instance, did you know that commuters who get to work and home each day via train are happier than those who drive their own cars, ride the bus, or ride a bicycle? People in Tokyo get less sleep than people in other cities around the world, and men in Texas are more likely to call each other 'bro' than 'dude'. Innovators can delve into data and find all sorts of strange, intriguing, and outright surprising facts each of which usually leads right back to more questions. This is the sustenance of a healthy innovation program.
Sometimes the data proves something very different from what you originally assumed was true. For example, when the market for tablets and smartphones took off like gangbusters, while the market for desktop PCs remained stagnant, many assumed that this meant the end of the desktop computer.
In fact, Microsoft bet quite a bit on that fact when they developed Windows 8, which ended up being a bad marketing and business mistake. The reality was, that tablets and smartphones were new, and a number of demographic groups bought and bought until the market was saturated. Many users abandoned their desktop computers for smaller, more portable devices, but many jobs and activities simply can't be done on a small touchscreen. Big data can be used to prevent many of these wrong assumptions because it can tell you what's going on behind the scenes. Data analytics can determine patterns and correlations that are impossible for humans to perceive.
As we just touched on, big data can find those hidden correlations, identify patterns, and detect trends even before they are obvious to the 'naked eye'. Sometimes innovation is all about combining this product with that, or this concept with another. Big data can find those patterns and lead your innovation team down new and uncharted waters.
For instance, data analytics can examine hundreds of thousands of scenarios relative to growing corn to identify the ideal blend of watering, sunlight, fertilizer, and other conditions in order to produce more and better corn crops. Similarly, healthcare providers can use big data to analyze various patients, their medical conditions, and treatments, thereby determining what treatment is ideal for a particular patient based on factors like their age, sex, ethnicity, and how far the disease has progressed. These insights lead to spectacular innovations that can save lives, feed more hungry people, and change the world (or maybe just your business) for the better.
What will your business or your industry look like in the future? Is it time to scale back operations or invest wholly in growth and expansion? Big data can point the way through predictive analytics.
What will your customers want next? Innovation is largely a matter of predicting what the next big thing is going to be. Many data analysts have harnessed the power of big data to develop predictive analytics tools that can look ahead, predicting the future both within and outside of your business. Will the market for your current products hold steady, or should you back off on production next year? Is there a feature that your next product ought to have, based on feedback from customers or general consumer sentiment? Predictive analytics can tip off your innovation team, as well as keep your production, R&D, and other departments informed.
While the majority of innovation done by big data is for the betterment of all, there are downsides to using data analytics. For example, what happens when big data is so good at predicting who will develop diabetes or have a stroke that insurance companies refuse to provide health insurance to those people? Always consider any potential downsides to using big data for your innovation purposes. It's the ethical responsibility of leveraging such a powerful tool.
Big data can be used for all kinds of innovations. The only true limit is what you can imagine doing with data analytics. Your innovation team will never be the same. When it comes to better innovation, nobody has your back like HYPE Innovation.