The Autonomous Economy

I walk into an airport, feed a credit card into the kiosk, which spits out a boarding pass. At the same time, my seat is blocked, my meal, beer, and pillow are released, TSA knows I am coming, the gate knows I am coming, the flight crew knows I am coming, the incoming gate at my hub knows I am coming, and I am boarded on my next flight.

I didn’t realize that until one time I was transferring in Philadelphia and the video board was down.

A human attendant looked at his clipboard, and told me to go to the wrong gate all the way across the airport. I got there and found out my exit gate was actually just two away from my entry gate.

When I got back to my gate, the airline was holding the plane. They knew I was in the airport somewhere.

Now before all this computerization, a small part of that data was communicated by harried humans with clipboards. They are mostly gone now. That’s why when the plane system burps, there is no hope of getting a fix by standing in line.

Switching a business from the carbon-based units with clipboards to the silicon-based units with screens takes time. Humans are better at improvising, and can communicate with other humans.

Computers are vastly cheaper, and when the system is complete, can communicate better with computers.

From an operating cost model, reducing your business to computer driven data makes sense no matter how difficult it is. The first in an industry to successfully implement an automated system gets an enormous advantage. The problem is when your system inadvertently maximizes customer prevention.

Banks and airlines know that a mal-system interlude can tank your customer sat. If the Internet never forgets, how long do angry customers hold a grudge?

When I read about the disappearing middle class, I remember all the people with clipboards outwitting their business systems to get me home. By the same token, anyone who hides a known system burp has to be taken out of the loop, as that burp often represents hundreds or thousands of instances that went unreported.

Open Source Leadership teaches us that more eyeballs get the problem fixed easier and faster. It used to be that we were trying to get a little more time before reporting to try to come up with a solution. Today that is exactly the wrong way to play.

Where do you see the autonomous economy changing your life, for better or worse?

Don't File It – Use That Data

Big Data is a means to extract useful information from great volumes of data collected from various inputs. If the data is available and accurate, the distilled information can be useful if the project is well conceived.

Last week we attended a Big Data session put on by NCA-GTUG to highlight some successful in-use projects with Splunk boiling down huge quantities of continuous real-time data into useful information about monitored activities – almost real-time. Fascinating.

Next day I participated in a GovLoop Webinar on Optimizing Service With Big Data, which outlined the expanding use of the Big Data approach in the Government sector – and an example of effective use of police data to reduce crime.

The city of Santa Cruz applied Big Data tools to 10 years of collected police crime data. They cut the data by type of crime; they sliced it by location; they diced it by time, day of week, day of month, and month of year, to get a detailed picture of the characteristics of crime occurring in Santa Cruz.

Then the process was reversed to create when, where, and what predictors of crime probabilities as a data based tool to apprehend or prevent area crime.

By manipulation of large volumes of existing data, the police department created a knowledgebase analogous to the instincts of long-service patrolmen with a 'feeling' about crime activity and targets. This predictive tool is intended to help the SCPD be more effective in the reduction of crime. Of course, personal experience is what sets the Doers apart from others – this data approach is a supplement, not a replacement for experience.

The results bear out this supposition: property-based crime is down by 12% and burglaries down by 25% since implementing the project. Good results, which supplement the other tools available to the police in doing their jobs – like when the two-way radios replaced the call boxes on the street.

This example demonstrates a valuable subsequent use of gathered data to glean information about patterns, trends, or other relationships among the measured items. Two important element to a successful project with massive volume of data is the relevancy of the project to get usable information and the completeness and accuracy of the input to get sound information.

What are some Big Data applications that could create valuable information for your operations or future planning?