Following the second day of the Front End Innovation Conference in Boston, nestled in the Boston Fish Pier, Signals held a stimulating panel event that discussed actionable ways to use data analytics to improve innovation. Moderated by Co-Founder and editor of Innovation Excellence Julie Anixer, along with Thomas Thurston of Growth Science, innovator and entrepreneur Frank Moss, and our Signals CEO Gil Sadeh, the discussion centered on the challenges faced by innovation teams at leading corporates, the potential (and hurdle) of big data, and fresh ideas on how to bridge that gap and tapping big data for innovation work. Here are some of the highlights from that conversation.
Product Launchers Need Something to Hold Onto
New product development is a space plagued by so many unknowns that when presenting a new concept, decision-makers are always looking for something to hold onto — in other words — evidence that validates pursuing a particular idea over other alternatives. Tools that offer descriptive analytics and can describe the consumer demand or current market solutions as-is are a powerful aid in this situation. It is a valuable asset to helping you push forward the best ideas, and quickly eliminate over-crowded spaces.
Connecting the Dots for the Right Context
One Director of Innovation from a medical device company remarked, often we arent looking for answers, but really struggling to find the right questions to ask. Finding the right questions starts with making the right connections. We know that A) Data reveals patterns, and B) Cross-connections across data sources often reveals non-obvious findings and occurrences that can provide direction and lead to smarter questions.
One healthcare company used this process to identify lower-leg robotics as a huge and as yet untapped opportunity. By making connections between the volume of patient voices on social media and online communities and cross-checking this with competitors development pipelines, they were then able to create the groundwork for asking smarter questions – and determine how strong the opportunity truly was .
Seeing is Believing: The Power of Visualization
Data visualization is the most critical way to quickly convey the power of data to non-quants. But not all visualization techniques are created equal. Best practices can be taught to non-quants to help them get the most value out of data solutions, such as: Always filter out largest sample sizes from the analysis to reveal more interesting, subtle insights. Becoming agile and adept at visualizing and interpreting data queries will continue to be critical for non-quants in the analytics era.
Caution: More Data Does Not Equal Smarter Data
More data isnt necessarily smarter data- especially if your questions havent changed. Too often companies take a narrow approach, focusing on capturing more data to answer questions they were already asking- instead of answering new strategic questions they havent before been able to answer. Smart data is more valuable than big data.
A company can use data from analyzing patents and publications to help identify trending technologies in microbiology. Or, they can take it a step further and cross-analyze those trends with data on company M&A activity, hiring activity and more to ask questions that reveal which of these trending technologies in microbiology are most competitive. The competitive advantage will go to those who think about new strategic questions data can now allow them to answer.
Stick to Your Strategy: Its a Discipline
While it can be enticing to mess around with big numbers — interpretation of Big Data should never be random, and rather should be connected to core strategic objectives, solutions, and tasks.
Dont Worry About Your Experience Level: Stay in the Game
You havent lost the competitive advantage yet. Most big data solutions have been created to serve the healthcare and financial services industries. If you arent using a big data solution it doesnt mean you have lost out — it means that by acting today you have an opportunity to build a real competitive advantage in a space with a lot of buzz but misunderstanding.
