Big Innovation Needs Big Data
In today’s highly competitive business landscape, companies thrive by doing things differently — and getting the most out of your innovation program is key to supporting atypical strategies.
Then comes the million dollar question companies are asking: What powers innovation? While out-of-the-box thinking is a basic and obvious prerequisite, this alone won’t work unless it’s backed by insight and analytical knowledge of your target customer. That’s where Big Data comes in.
Big Data and the Innovation Pipeline
In the past, innovators had to extrapolate data from focus groups, periodic surveys, and behavior observation in order to ascertain what customers wanted and what they would buy. This data has its limitations — it’s often a game of hit-or-miss when scaling the info to gauge market interest or acceptability. These days, however, big data offers greater levels of information than ever before, and when used properly, it takes the guesswork out of the equation.
When used correctly, big data yields insights into segmenting customers more precisely than was possible in the past. It helps businesses tailor products and services to meet the precise requirements of their customers, and supports the development of business models that further these ends. However, the task is easier said than done. The challenge of harnessing big data to drive innovation rests in devising a data management strategy that integrates big data into the innovation pipeline.
Innovators need to first accumulate data from all sources related to their target customers, like demographics, psychographics, and behaviors, as well as transactional data generated from web sources, customer service interactions, and social media engagements. The latest source comes from data generated by the Internet of Things: sensors embedded in objects like toys, toothbrushes, automobiles, and industrial goods, which transmit valuable data on how customers behave with a product, the extent to which they are satisfied with it, and many other crucial insights.
The next and the most challenging task is to extract what customers require or what needs to be done differently to satisfy customer wants from this data. This is by no means an easy task. It requires overcoming several barriers, such as demolishing data silos, overhauling legacy systems and procedures, and overcoming incompatible standards. These steps are necessary in order to build the right computing architecture required to extract and analyze the data. The resistance is often significant, ranging from cultural to organizational, and from technological to budgetary. However, the opportunities revealed make the task of resolving the challenges very much worth it. Truly innovative companies do not limit this to a one-off exercise, but rather, they integrate it into the product development lifecycle, so that innovation is ingrained into the company operations and reflects on the product or service offering.
Breaking Down Barriers
That said, the world’s most innovative companies do not limit their quest to big data alone. Most successful innovators opt for collaboration technologies and use crowdsourcing to allow customers to directly influence product and service features. Very often, crowdsourcing and conventional methods (such as market surveys) can be most effectively used in tandem, which will reinforce the results surfaced from the analysis of big data.
Forrester Research estimates that organizations utilize less than 5% of their available data. If you are looking to increase this number substantially in your organization, talk to Mindjet to see why innovation matters and how you can go about implementing a sustainable innovation program in your business.