While I’m relatively new to the predictive generation (five months at the time of writing!), it doesn’t require extensive experience to foresee that every institution globally—whether start-up, multinational, government or NGO—will in some way be affected by predictive analytics. But more important, there is a real need to be ready for the impending data transformation tsunami. 

In 2008, I took on a role within a global communications agency to help make sense of the then-nascent social media domain and how it might have an impact on a brand’s reputation. I had no real experience with social, but I did have experience working with tech companies of all sizes and knowledge of the tech scene zeitgeist. I recall one core challenge was talent. We were looking for people who not only understood the social landscape, but could also figure out how to apply it within a communications context—people who were not bound by traditional swim lanes, but were agile enough to operate across marketing functions and who may not have known what the future looked like but were curious enough to figure it out.

Watching the duels between social media advocates and social media skeptics play out against a canvas of uncertainty was both fascinating and frustrating. Everyone could sense a tectonic shift was happening, but no one really knew when or how great an impact it was going to have. We were essentially all in the same boat, learning again, being challenged to innovate and counsel clients in an ever-changing environment.

 As I take on the role of leading the Edelman Predictive Intelligence Centre (EPIC), I once again find myself in a similar thrilling, yet petrifying situation. This post isn’t about explaining what the Predictive Intelligence Centre is. You can read that in the launch press release. Instead, I’d like to focus on the similarities of my experiences in 2008 and 2018.

As I said, I’m thrilled to be a part of the predictive generation. The potential power that predictive intelligence will put in our hands as communicators is enormous. The Internet of Things enabled consumer electronics, smart city initiatives, blockchain-enhanced business processes and AI augmented apps to rocket us toward a wired and connected society, resulting in better quality data being generated in bigger volumes. Similar to when social networks, tweeting and blogging first became mainstream, we suddenly have access to information that was previously very difficult and costly to acquire.

Although data is already being coined as the next major currency, the value, for me, isn’t just the data. The value is the wisdom we can gain from the data through predictive analytics. There are many definitions of predictive analytics, all of which are pretty similar, but I like IBM’s version for its succinctness.

Predictive approaches, irrespective of the data science and computing foundations, have been around for hundreds of years. Even so, most brands still suffer from data haze; they are not gaining any wisdom from the data they already have or the data that could be available to them. This is the petrifying element.

As I build a team comprising behavioral scientists, big data analysts, digital marketers and psychometrics analysts, among others, I’m transported back to 2008. We are not hiring conventional talent. The magic happens when we find the right mix of technical knowledge combined with curiosity, agility and ability to apply skills within the context of communications.  We all know there’s a tectonic shift coming, but no one really knows the magnitude of the effect it will have on brand reputation. 

So far it seems that, more often than not, data analytics programs deliver pockets of value but have yet to be considered holistically as providing sustained benefit to organizations, just like when companies first started experimenting with social media. Many experts, much more experienced than me, expect predictive intelligence to change this.

As predictive intelligence becomes more sophisticated, institutions will be able to make more informed decisions with more impactful results in a more effective way.

Our vision is to change the way organizations build relationships and trust with stakeholders based on a scientific analysis of people, what matters to them and what drives their behavior.  Have we got all the answers for how to do this? No. But we recognize the potential and are investing heavily in talent, systems and processes to find the right answers. 

Yeelim Lee is general manager, Edelman Predictive Intelligence Centre.