About me.
I am first and foremost an analytically-oriented person who has been luck enough to combine nature--ability, talents, interests, etc.,opportunity, and experience into my professional life.
Professionally I am an analytics practitioner and I work with people and organizations across the full range of analytics. I implement, manage, mentor, direct, and advise clients.
Growing up
I was born a very young child. Like all human children I was curious, and was encouraged in my curiosity. We were reasonably poor, a working class family of six children, but we had books. Lots and lots of books. We were and are a family of voracious readers. I can barely remember being unable to read, and have always been fascinated by the things that books make available and knowable.
As a young boy I read a story about another boy whose scientist Dad had a computer installed in their house. A big, room-filling computer that required its own custom-built addition. In those days computers really were room-filling behemoths. The boy figured out that he could get the computer to help him with his homework if it had the information in his school books. So he brought them home and got their contents entered into the computer—the book was vague about how that happened. After that, when he wanted to get the answer to a question he’d type it out on the teletype terminal and the computer would print out its response on the attached line printer. (this was the 1960s)
This was a shatteringly novel and appealing concept. The idea that computers could help us learn and know things, and use that knowledge effectively, fascinated me then. It still does, and I’m happy to have been able to have a career helping other people use computers to help them learn things.
Some time later I read another story in which one of the main characters, a young girl, was given access to essentially unlimited computing resources, including massive amounts of historical data, with no goal other than trying to find out something interesting. She discovered that there was a strict correlation between the popularity of male facial hair and economic cycles. Real science fiction stuff for then. The details of the story are a bit hazy; I can’t even be sure who the author was although I’m inclined towards it being Heinlein, and I think I read it between forty and fifty years ago.
Education and Early Experiences
My first direct experience with computer-aided data analysis was in analyzing bird banding data using COBOL and punch cards at the University of Guelph in 1974-75. My professor was a member of the North American Bird Banding Society, and the analyses my class conducted had real meaning. This connection between data and information it can provide for people is the foundation upon which analytics for humans rests.
During the latter half of the 1970s I worked in seismic exploration in Canada’s western oil fields. Our work resulted in massive sets of records that were sent to the company’s headquarters where sophisticated analysis revealed geologic features likely to contain valuable gas and oil deposits. This was truly fascinating.
In those days the paths to being able to work with computers in the way I wanted were few and required specific qualifications, so I went back to university and obtained my Bachelor of Business Adminstration, majoring in Computer Information Systems, from Georgia State University in 1985. I graduated summa cum laude; previously an indifferent student, I was motivated by the opportunity to finally pursue my deep interest as my profession.
Analytics as my Profession
Upon graduation I went to work for JCPenney using a new, innovative product: PC/FOCUS. At that time FOCUS was the leading fourth generation language (4GL), invented to create reports using an English-based reporting language. This enabled report writers to create reports much, much more quickly than when writing COBOL programs. Even better, the advent of 4GLs made it possible for nontechnical people to create their own reports without needing to wait for a programmer to be available. Given the customary backlogs in data processing departments, this was a fundamental change, enabling people to get information when they needed it, not weeks or months later.
After about a year I went to work for FOCUS' vendor—Information Builders, Inc. (IBI)—as a consultant helping clients use FOCUS for reporting and data management, concentrating on supporting business users’ information needs. As consultants our work was largely devoted to two main foci.
One focus was preparing reports for our clients. In form this was analogous to the existing technological/programming approach to reporting with FOCUS replacing COBOL as the reporting language. In practice our clients benefited because we could produce reports much, much faster than they could get them from their data processing departments' COBOL programmers.
The other focus was in helping our business clients adopt FOCUS for their own use, developing their FOCUS skills so that they could create their own reports without waiting for technical support, from us or their data processing shops. Many clients were eager to learn enough FOCUS to be able to satisfy their common needs while relying on support for more complex requirements. Many other clients were willing and able to dig deeper and learn how to use FOCUS for increasingly sophisticated reporting.
Prior to the mid-1980s virtually all business information systems were hosted on mainframes, with a small fraction based on PDP-11s, Wangs, and other non-mainframe computers. As the 1990s dawned minicomputers, microcomputers and personal computers were becoming common in the business workplace and it became clear that non-mainframe computing models offered new, different, and better ways for people to interact with computers. The best known of these was the adoption of GUIs vs terminal-based interaction. No less important was the per-character/keystroke interactive model introduced first by minicomputers. Things were changing for the better as these innovations made it possible to implement highly responsive human-computer interactive modalities.
After two years as a consultant I moved into product management. I wanted to be part of the new future of human-oriented computing and help bring the promise of computer-assisted learning, cognition, and knowledge augmentation to real people. In product management I was able to help evolve and improve our products as Project Manager for PC/FOCUS, PC/HLI, and FOCUS for Unix. In the Unix division I was the product manager for FOCUS for Unix and the product architect for a new type of FOCUS, one that took advantage of the emerging possibilities offered by the combination of GUIs and non-mainframe models of computing, for which we invented a new object-oriented, network-centric programming language called GUISE.
Unfortunately, IBI failed to recognize and fully adapt to the changes that were happening in computing, and during the period 1992-1993 an entire generation of people left the company to pursue other opportunities.
At the beginning of 1994 I went to work as a consultant to The World Bank, supporting and modernizing their worldwide Imprest Accounting System, written in FOCUS—mainframe FOCUS at Headquarters, PC/FOCUS in over one hundred country offices around the world.
That lasted for several years, and I’ve worked for The World Bank a number of times since. During the run-up to Y2K I developed tools and techniques for parsing the systems’ FOCUS code into data and analyzing that data for date-sensitive storage and code dependencies, and remediating the data and code to avoid Y2K problems. This is an example of non-traditional data analysis; more on this is to come.
In another engagement some years later I was recruited to install their initial Tableau Server installations and help with their initial Tableau adoption. This was a wonderfully satisfying engagement in which the Bank’s business personnel, country officers, economists, statisticians, and others were able to use Tableau to achieve results far beyond their expectations.
For the past fifteen-plus years I’ve been consulting with public and private organizations, supporting their data analytical needs, and began using Tableau for my own work in 2006. During this time I’ve encountered a wide variety of environments and approaches to computer-assisted information management and analysis. Some of these have been tremendously successful in helping people with their information needs. Others have not been as successful as they could or should have been; the failures have far more often been human-induced than due to technical deficiencies.
Analytics That Works is a response to the forces that keep analytics from achieving its full potential in many environments and organizations.