Innovation Management and Big Data are a dynamic duo for companies to embrace.
Data Is Everywhere
We're all overwhelmed by data — this is news to no one. Thanks to digital technology, just about every purchase, every social update, every tap of an app, every Google search is there for the harnessing, and the growth of the Internet of Things will only expand this data. Data is a constant — and that's good news.
A McKinsey Global Institute (MGI) study on big data notes several ways it can provide value in a number of industries and verticals:
That's only to name a few. But perhaps the most important insight MGI offers is this:
Policies related to privacy, security, intellectual property and even liability will need to be addressed in a big data world. Organizations need not only to put the right talent and technology in place but also structure workflows and incentives to optimize the use of big data.
Idea management software is how you structure the workflow for your big data.
The Big 'Why' Behind Managing Ideas
"You're only as good as your last haircut," according to Fran Lebowitz, but the sentiment applies to your last big idea as well. If you don't top yourself, one of your competitors surely will.
So innovation must also be a constant, but it's not as daunting a prospect as you may think.
Innovation isn't just about lighting-in-a-bottle inventions that change the world — though, of course, it can be that. Everyone hopes to achieve the kind of industry-disrupting innovation that puts their company indelibly on the map of progress. But more often than not, innovation is about simple, but game-changing, improvements to your operations, such as how you approach customer service, or product assembly, etc.
Innovation takes practice, just like anything else in life.
More than that, innovation at its best is an organization-wide endeavor, based on the needs and desires of your target audience — whether that's consumers or your own workforce. That's where the data comes in, and why you need a solution for keeping track of it all.
Automation is non-negotiable. Gone are the days of segregated R&D teams, existing in a bubble of trial and error.
R&D teams now must serve as part of a broader innovation initiative, acting as innovation team leaders pursuing innovation across business units, carrying the best projects forward based on actual data, not hunches.
Experimentation Is the Name of the Game
It's not that failing is not an option — but you want your failures to happen in the development phase — not out in the market where you stand to lose the most. When innovation is part of your culture and daily routine, failing becomes just another benchmark.
Fail often and early, as John C. Maxwell says. And let your innovation management tools keep track of the big data as you continue on — failing forward until you succeed.