Herbert Simon coined the phrase “bounded rationality” to describe why organizations and individuals often make decisions that are irrational or incomplete. Without going into too much detail, the concept of “bounded rationality” was born out of Simon’s understanding that people are limited in their ability to collect, process, interpret, and assess the importance of information. Thus, if we cannot properly analyze information, we cannot make complete rational decisions. If we are forced to simplify concepts and expected outcomes, we are forced to settle for our understanding of reality and make a decision based off that perspective. Our rationality is thereby limited, or bounded, to our scope of understanding the information.
So how does this abstract concept fold into today’s discussion on technology? Firms are accumulating data at an unprecedented rate and eager to tap into insights via advanced analytics. Something to the extent of 667 exabytes of data, or 1.7 million Libraries of Congress, are currently traveling over the globe’s telecommunications networks. Value like individualized transaction information, geographic preferences, purchasing patterns, and medical histories open a large window of opportunity for firms. Some estimates put the “big data” market capitalization at around $150 billion. And that number doesn’t even include the value created by insights born from analysis.
Algorithms and predictive models have replaced some human subjectivity from the traditional model of decision making, but this replacement has been skewed toward mundane and robotic tasks like airport ticket kiosks or switchboard operators. In fact, the vast amount of data that is now available at our fingertips is only forcing us to make more decisions. In a way, technology has enabled the human employee to focus on higher value-added work. And these roles carry more weight than employees have previously been entrusted with.
Sure, a call center can automate simple decisions like giving better leads to more successful agents or an online insurance company can create quotes in seconds. But what about the back-end? Ultimately, it is human behavior which will dictate where those decisions are automated and, more importantly, how that automation will be formulated. At the front end? Instead of having attendants at the ticket counter, airlines may find opportunities in using those employees to create travel plans and itineraries for prospective customers transforming their role from clerical to sales oriented.
But this presents a new challenge for organizations in the coming decades. If we shift human actors from the mundane and repetitive, to more complex roles that rely upon human judgment and interaction, then how can we measure and analyze commensurate behavior? Instead of relying upon correlations and patterns of naturally occurring data like we do now, how can we look at substantive metrics of individual level decision making?
IBM and McKinsey have published a lot of great articles on this subject in a blooming field known as “Social Business”. Business leaders have begun to acknowledge the augmented role of individuals and their ability to collaborate, empathize, and realize business opportunities outside of their rigid job descriptions. The workforce of the future will be far more cybernetic and synergistic creating value from multiple points of expertise and perspective. Companies who do not acknowledge these forces will be left behind, and therefore it is vital for enterprises to begin partnerships with industry leaders to build an institutional awareness and comfortability with this new level of analysis.
The analysis of human behavior using our current mathematical models has been a difficult task. Ask any social scientist who has attempted to use empirical methodology in their research and they will likely agree with the notion that human behavior is not explicitly rational and therefore isn’t necessarily a linear process. The question then becomes – “what methodology of data analysis for human outcomes makes sense?” – and the answer won’t be regression.