The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

All Posts

The EQ Behind The IQ: The Growing Disconnect Between The Data-Driven Business And It's Customers

February 27, 2019 at 7:18 AM

Alan Turing once said:

"A sonnet written by a machine is better appreciated by another machine."

Why am I talking about machine and EQ? At Principa we are very interested in the relationship between machine and people and especially the translation of data. 

But what qualifies me to talk about the EQ behind the IQ, is that I - like all of you - am a customer. A customer at the mercy of brands that either do or do not use data wisely, or display EQ. 

Despite all advances in technology, some brands aren't much help. The more technology and data we use, the further we seem to be pulling our people from our customers. I think a quote by E. O. Wilson is apt here. 

"We are drowning in information, but starving for wisdom." 

So, what is my point? I see an opportunity here. An opportunity to bridge the gap between machine and the people who interact with them every day. 

It's called behavioural science: the next step in data science. 

We know that data-driven decisions are good ones, the remove bias. But any time people are involved, results will never be 100% accurate, for e.g. when it comes to a number of statistical paradoxes we've written about before, like the Gambler's paradox. 

But actually, human behaviour is pretty predictable. If we gather enough information and find significant correlations, we can begin to predict how people will interact. 

How?

  1. Understand your current data universe
  2. Think about human behaviour at key touchpoints
  3. Capture as much information as possible
  4. Look for patterns and correlations
  5. Experiment (deploy, test, refine)

But remember: in the age of machine, don't underestimate the power and value of humans. 

Jaco Rossouw
Jaco Rossouw
Jaco, CEO of Principa, has over 26 years of experience in the financial services industry specialising in Insurance, Retail and Banking. He is an analytical technologist at heart with a track record of delivering innovative business solutions over a wide geographical region from South Africa to the Middle East and Europe. He serves as leader, motivator and imagineer to one of the finest collections of data, business and computer scientists in South Africa. He holds a Bachelor of Science degree with majors in mathematics and computer science.

Latest Posts

My learnings on the effective use of automated self-service bots.

Organisations and individuals, need to adapt and change to the new ways of working to ensure that we survive this pandemic, and protect our sustainability for the future.

The time is NOW for model validation and adjustment.

One of the major premises used in credit scoring is that “the future is like the past”. It’s usually a rational assumption and gives us a reasonable platform on which to build scorecards whether they be application scorecards, behavioural scores, collection scores or financial models.  That is reasonable until something unprecedented comes along.  You can read about this black swan event in our previous two blogs here and here

10 ways the COVID-19 crisis will affect your credit models (PART 2)

This is the second of a 2-part blog. You can read the first blog here.