The Human Algorithm: Redefining the Value of Data

The onslaught of real-time social, local, mobile (SoLoMo) technology is nothing short of overwhelming. Besides the gadgets, apps, social networks and appliances that continue to emerge, the pace of innovation is only outdone by the volumes of data that each produce. Everything we share, everywhere we go, everything we say and everyone we follow or connect with, generates valuable information that can be used to improve consumer experiences and ultimately improve products and services.
While the amount of personal and ambient information churned out by SoLoMo is often inundating or even perplexing, it is this “big” data that will help businesses evolve and adapt in a new era of connected consumerism. More importantly, the study and understanding of relevant big data will shift organizations from simply reacting to trends to predicting the next disruption and adapting ahead of competition—thus, marking the shift from rigid to adaptive business models
From business to education to government and everything in between, without studying how the undercurrent of behavior is evolving, organizations cannot effectively adapt to new trends and opportunities. Change though, cannot be undertaken simply because of pervasive data.
Without interpretation, insight and the ability to put knowledge to work, any investment in technology and resources is premature. But, by investing in human capital to make sense of would be ominous data, organizations can modernize the role of business intelligence to introduce a human touch. SoLoMo analysis becomes the sustenance that feeds the insights for more informed and inspired innovation. The result is nothing less than relevance and a significant competitive advantage.

From Information Paralysis to Analysis

You’ve heard that old saying, over analysis leads to paralysis. In the face of big data, it’s easy to see the tidal wave that can result from the influx of inputs and sources. Equally, the lack of governance, support and transparency can lead to stalls and or the abandonment of new efforts altogether.
The reality is though that how organizations connected with customers yesterday is not how customers will be served tomorrow. Meaning, the entire infrastructure in how we market, sell, help, and create now requires companies to not only study data and behavior but also change how it thinks about customers. This is a bona fide renaissance and to lead a new era of customer engagement requires knowledge acumen. I refer to the confluence of data and interpretation as the human algorithm—the ability to humanize technology and data to put a face, personality, and voice to the need and chance for change. Data tells a story, it just needs help finding its rhythm and rhyme.
On the surface, social, mobile and other disruptive technologies are valued for the communities of people they bring together. Open a window to look inside and you realize that the undercurrent of transformation is information. To adapt and ultimately lead change requires an official role to not only listen, but study.
Today many businesses use any one of the myriad of social media management systems to monitor conversations, track sentiment and measure share of voice. That’s not intelligence however. Much of what we see today is important, but it’s measuring activity not translating behavior into creativity or strategy. Part of the problem is that social media lives in a silo unto itself. Indeed, organizations employ business intelligence and research teams today. The reality is though that BI too sits in a silo. Either way, information or the lack thereof is either held prisoner within one part of organization or it’s under valued and not in demand among the very teams that can benefit from it.

The Human Side of Information

The human algorithm is part understanding and part communication. The ability to communicate and apply insights internally and externally is the key to unlocking opportunities to earn relevance. Beyond research, beyond intelligence, the human algorithm is a function of extracting insights with intention, humanizing trends ad possibilities and working with strategists to improve and innovate everything from processes to products to overall experiences.
The idea of the human algorithm is to serve as the human counterpart to the abundance of new social intelligence and listening platforms hitting the market every day. Someone has to be on the other side of data to interpret it beyond routine. Someone has to redefine the typical buckets where data is poured. And someone has to redefine the value of data to save important findings from a slow and eventual death by three-ring binders rich with direction and meaning.
One place where the human algorithm can have an immediate impact is in social media listening. In addition to tracking simple data signals such as conversations, sentiment, share of voice and service inquiries, data can present insights into preferences, trends, areas for innovation or refinement, R&D, co-creation, et al. Even though sophisticated tools can help track data points that can lead to these insights, it still takes a human touch to surface them and in turn advocate findings within the organization. It’s the difference between insights, actionable insights, and executed insights.
The truth is that a community or social media manager is not tasked with this type of responsibility therefore, insights largely remain undiscovered. It takes a new role that unites the disciplines of business intelligence and social media with the perseverance of a change agent. Without it, all of the insights capable of leading organizations to the next big thing will meet its long time arch nemeses fear and skepticism.
Big data is just that…it’s big. While the profusion of information today can lead to analysis paralysis, by listening with intent, organizations can tune-in the signals that will direct opportunities to adapt to and lead this new era connected consumerism. This is about innovation—inside and out. Those who don’t plug in and invest in technology’s human counterparts are in turn making an investment toward potential irrelevance. But remember, data is just the beginning. Data must always tell a story and that takes a human touch to extract data, surface trends, and translate them into actionable insights across the entire organization.