I have recently been spending a good deal of time reading and learning about human-centered design thinking. Particularly books about creative confidence and design thinking authored by David Kelley and Tom Kelley, brothers and founder (David) of one of the leading design firms in the world, IDEO. Yes, this is a departure from spending an exorbitant amount of time developing the left-side of my brain.
In one of their books, the term Hybrid Insights is used to describe the more recent practice of "combining qualitative human-centered research and big data to embed stories in the data, to bring the data to life. It brings the ‘why’ and the ‘what’ of consumer emotions and behavior together." The authors contend that "coupling insights based on consumer empathy with analytic confidence within relevant target markets may be a way to take the best of both insight generation approaches."
I found this to be a fascinating way to think of how creativity and innovation can be inspired by research and analytics, as well as how business leaders can more easily consume and act upon analytic insights that have been enriched through a creative-minded data synthesis and storytelling process. This would imply that creative and analytic outputs can both be elevated by combining these multi-disciplinary skills.
In order to further propel and encourage full collaboration between analytic and creative professionals, I believe the analytics community needs to continue to advance the ability to discover human emotions and empathy in big data. Professionals that rely on consumer insight to create and innovate have long used consumer demographics and behavioral insights provided by analytic practitioners to help inform their work. These data sources have provided tremendous value, but it's time to take insight generation to a new level. Providing human-centered insights at scale has the potential to supercharge the inspiration and ideation practices that are used across all facets of business.
We still have a lot of work to do to make this a reality. The ability to use analytics to draw emotions and attitudes from big data has certainly come a long way in the last 5 years, but it is still a work in progress. Tools and platforms are now available that can ingest unstructured data and use natural language processing (NLP) and text analytic techniques to detect consumer sentiment, emotions and attitudes. However, the results are still sometimes susceptible to linguistic and contextual misinterpretations which contributes to a 'wait-and-see' full adoption by some companies or business units.
Human emotions from unstructured data come in many forms and can collectively provide incredibly valuable insights if they can be identified in a timely, accurate and efficient manner. This includes social media posts, blogs, forums, reviews, survey verbatims, news articles, web chat sessions, customer support voice interactions, YouTube videos and more. The ability to store and process unstructured data cost-effectively has led to the enormous amount of data that can now be mined for consumer insight. Some data experts estimate that businesses collect close to 2.5 quintillion bytes of data per day. That is 2,500,000,000,000,000,000 bytes of data per day. This very exciting, but let us not forget that this data collection and usage needs to do done with the highest level of consumer transparency, incorporating the utmost ethical usage practices (see my recent blog post on consumer data privacy).
Authors David and Tom Kelley, state the importance of deeply understanding human needs. To paraphrase, “they believe you need to get at people’s motivations and core beliefs. You need to aim to understand why people do what they currently do, with a goal of understanding what they might do in the future.” Although they apply these human-centric practices primarily in product and service design, the benefits of human-centered insight generation can be applied across many areas of business, such as marketing communication, customer support and human resources.
I believe we are on the verge of significant breakthrough in our ability to generate human-centered insights. I also believe it will require the combined expertise of analytical and creative minds to turn the raw data into contextualized human emotions and empathy that tells the data-driven, inspirational story of how we should engage with consumers on their terms.
I welcome your thoughts and comments.