“Agile” is a hot concept in product development and project management these days, especially in software development.  Use of the term and the methods, which hinge on frequent small, incremental product changes rather than lengthy release cycles and ambitious requirements, has exploded in the past couple of years. Everybody in software development is talking about Agile these days.

Marty Abbott, Co-Founder AKF Partners, and a former CTO of eBay, spoke about Agile in Chicago not long ago, presenting the first in a series of technology seminars sponsored by cars.com. As he described key elements of Agile - small, multidisciplinary teams working independently toward their goals, freed from corporate political concerns and willing to walk away from unsuccessful projects - his words began to seem familiar, very familiar. Not familiar in the “this is the 100th presentation I have heard about Agile” sense, but something deeper, older and harder-to-place.

Maybe I wasn’t the only one with that feeling. Proponents of Agile development methods often refer to “Manifesto for Agile Software Development,” a document which laid down the principles of Agile development in 2001, but it is well-known that incremental development methods date back much earlier, at least back to the 1950s. Someone asked about the earliest examples of Agile. Abbott, a one-time military officer, identified the US Army Special Forces’ use of small, autonomous teams as the earliest example he knew. Today’s Special Forces grew out of 1940s-era military and intelligence operations.

Then it hit me. Marty Abbott’s description of Agile development teams echoed remarks I had heard from Sarah Miller Caldicott. She also described development processes involving small and independent teams. Many elements were the same – multiple projects, walking away from failed approaches and turning attention to alternatives. But Sarah Miller Caldicott, a management consultant and author, was not speaking of Agile software development. In fact, she was describing an organization that predated software – the laboratory of inventor and businessman Thomas Alva Edison.

Edison, credited as inventor of the light bulb, phonograph, telegraph and many other devices, established an industrial research laboratory in New Jersey as early as 1876. That puts the elements we now call “Agile” in practical commercial use in the 19th century. What’s more, one could easily make the case that the industrial research laboratory is modeled on the practices of academic research and scientific method, which dates to the 17th century. In short, the name “Agile” may be pretty new, but the ideas are pretty old.

So, is there practical advice to be found in this little tale? There is! When you have problems and you’re looking for new solutions, ask yourself if you’ve taken full advantage of the old ones. Even the inventor of the light bulb, an innovator, took advantage of the centuries-old ideas of the laboratory and scientific method to address the needs of his time.

People often ask me what’s new and hot in data analysis. Never at a loss for words, I’m happy to explain the subtleties of decision trees, sing the praises of text analytics or ponder the challenges of image and video analysis.

 If you have a need, I’ll match it up to analytic methods. Here’s the thing: most organizations can go a long way forward using old, well-accepted analysis techniques. Does that mean there is no place for new and innovative techniques? Perish the thought!  Today’s exotic new technique will be tomorrow’s everyday business tool, to be sure. Yet the vast majority of businesses, government agencies and nonprofits make so little use of analytics today that they still have plenty of opportunity to benefit from traditional and basic data analysis methods.

Did you take a class in statistics back in college ten or twenty years ago?  Are you putting all the techniques you learned there to good use in your workplace today? If not, then you are in the same boat with most people.  Most of the thousands of business problems presented to me during my career could be addresses with analytics covered in a typical introductory statistics class, or with other techniques that may be a little different, but not particularly new, exotic or difficult to master.

Here’s a little challenge: stop by the library and pick up a basic statistics book. Choose one that is recently published (current statistics books are more clearly written and better illustrated than they were decades ago) and new to you. You don’t need to read it cover-to-cover, but sit back and peruse the examples. Ask yourself how they resemble issues that you face at work.

Take a fresh look at old methods and, like Edison, you will see things in a new light.

About Marty Abbott:


About Sarah Miller Caldicott and her intriguing family history of innovation: http://www.powerpatterns.com/family-history.html

©2011 Meta S. Brown