Jeff Jonas, better known as The Wizard of Big Data, is the Current Founder, CEO and Chief Scientist at Senzing. He was formerly Chief Scientist of Context Computing at IBM and an IBM Fellow. Most recently he joined ClickFox as a Strategic Advisor.
I recently sat down with Jeff to discuss the parallel of “Context Computing” to Journey Analytics, both built upon having connected, contextualized data and the limitless possibilities of the types of problems that can solved when data finds data.
He defines context as, better understand something by taking into account the things around it. By way of example, “If I were to hand you a puzzle piece with just flames on it, how would you know if this “fire” is good news or bad news? Without any surrounding puzzle pieces to know whether that is fire in a fireplace near a glass of wine – GOOD – versus down the hall near the kids’ bedroom – BAD, there is no way to know. This whole notion about better understanding something by taking into account the things around it, is equivalent to every time a customer interacts with your organization through its various touch points. Every single one of those interactions is a puzzle piece with features on it. Just like the edges of a puzzle, these are the features in each data point and it takes combining all of those to get an understanding of the whole picture.”
Tim: What was it was about ClickFox & Journey Analytics that interested you in becoming a strategic advisor, being someone who doesn’t do this often?
Jeff: I get invited to a good number of boards & advisory positions. I was selective in choosing Clickfox. Journey Analytics – specifically, the notion of being able to combine all the different ways that humans get something done – is exciting. Combining dispersed events to reveal pathways and journeys reveals places where the business is creating friction or joy. This is just damn interesting to me as this opens the door to improving business outcomes. Having followed the space and Marco (ClickFox CEO) for many years, ClickFox basically owns the mountaintop and I’m happy to help push the vision forward.
Tim: Looking at journeys holistically across any touch point and any entity, not just customers, is what gets us really excited. The way people look at data is really shifting across different problems & industries and not just the “purchasing journey” and that is something we have a common with you.
Jeff: Think of journeys like typography. Looking at a map and thinking about the way people navigate a website, then into the call center, then try their mobile app. Those are all pathway attempts to get somewhere and I often think about that spatially – like how would that look if you drew it on a map with peaks and valleys.
Tim: In your Strata+Hadoop World talk on Context Computing, you talked about how complex problems are solved when data finds data. What are some of the more complex journeys that you’ve seen improved as a result of connecting data to reveal context and how do you apply context computing in parallel to a journey science approach where everything has a journey, generating data along the way?
Jeff: One of the hardest parts about data finding data is you have to figure out if it’s two different people with two different events, or one person that had both events – also known as “Entity Resolution.” If you can't figure out who's who, then it’s nearly impossible to understand what their goals were or what outcomes occurred on their journey. Did their journey represent opportunity or risk? A lot of the ClickFox work is around finding opportunities in customer experience, but it only takes a small pivot to take a platform like ClickFox and use the rich set of puzzle pieces, data finding data, to find risk as well.
To the question on complex journeys, what’s really captured my imagination is geospatial data – where things are and how they move physically. If you could wish for any kind of transactional data (puzzle piece), this is it. Understanding where people were when they’re making decisions adds so much predictive quality on why they made the decision they did – drawing on this insight even better experiences can be created. That data will bring more fidelity to our understanding of people’s journeys, such as when they're taking the journey, what kind of journey, and at what times a day.
I have applied that kind of geospatial awareness to projects like helping Singaporeans better protect the Malacca straight by taking a billion vessel geospatial event records – where they are in the world, how they move, and who they were hanging out with. Another fun project was the asteroid collision project, taking six hundred thousand known asteroids and predicting when they're going to be near enough in their journey to potentially pound into each other over the next twenty-five years. These predictions have helped astronomers know where to look and when in the night sky.
Tim: It’s encouraging that approaches taken in one problem space or industry are relevant in almost any application, provided the data is available to support it … like the approach you mentioned earlier using your space time box method. What are the big problems you focused on today?
Jeff: Right now, I’m working on my third start up, Senzing. A lot of organizations are trying to figure out who is who and who is related to who. Today, you either have to buy expensive software or hire a lot of people to build it. I know some companies employing one hundred people to do just this. What we're doing is taking a complicated problem, entity resolution, and making it easy for everyone. It’s not the exotics of asteroid hunting, but it’s about tackling who is who, affordably, and without a Jedi Knight or mathematician to solve it for you.
To make the best decisions possible, really in any scenario, you must understand the context surrounding a situation. There is so much data available today, but without context, it’s just a mess of puzzle pieces waiting to be put together. This is what excites me about the scientific approach to journeys that ClickFox takes. All of the individual events that are collected are the puzzle pieces and when they’re placed into context, journeys emerge. Understanding these journeys informs better decision making because you can see where the customer has been and where they’re trying to go.
Read Part 2 of Our Interview with Jeff Jonas: