Avoiding The Software Innovation Trap
Guest Column | By Daniel Bichara, FastSensor
The software revolution began during the late 1970s with the introduction of affordable personal computers and the VisiCalc spreadsheet. This unleashed the technology industry and boosted the potential and value of innovation teams while drastically improving R&D cycles.
It was such a successful revolution Visual Capitalist founder and editor Jeff Desjardin said, “The oil barons have been replaced by the whiz kids of Silicon Valley.” Indeed, the five largest companies in the world by market capitalization — once oil companies — have been replaced by technology companies including Apple, Alphabet, Microsoft, Amazon, and Facebook.
At the same time, Gordon Moore published “Moore's Law” which predicted the increasing capacity of processing power that remains true after decades. Though, as noted by University of Michigan computer scientist John Holland during the 2000 conference on the future of technology, the “software has not followed a curve like Moore's Law.” The reason for the apparent failure is the same reason fueling the success of the technology industry — and may threaten small and medium SaaS businesses.
The 70s were indeed the birth of the modern software industry. In 1969, the first message was exchanged between computers in different locations, the foundation of the World Wide Web invented by Tim Berners-Lee 20 years later; the Apple II reached stores and became a sensation; and Bill Gates dropped out of Harvard to co-found Microsoft.
During the same decade, Professor Lehman and colleagues from the Department of Computing of The Imperial College of Science, Technology, and Medicine in London started formulating laws describing a balance between forces driving new software developments and forces slowing progress of software development now known as “Lehman's Law of software evolution.” In his seminal work, Lehman stated eight laws over 20 years, analyzing correlations of the software evolution process.
The second law — Increasing Complexity — concludes the complexity of the system increases as it evolves and requires additional work to maintain control. So, while the implementation of new features consumes the available working time of the programming staff, the management of the added complexity overwhelms the team and impacts its productivity. In a couple years, the overall time dedicated to manage the complexity may easily exceed the time to improve the product.
The sales team may suggest new features would help increase revenues by creating traction with customers and new opportunities. Part of the additional revenue can be redirected to hire more resources and bring equilibrium. Although, Lehman's fifth law reminds us software evolves all associated with it, requiring sales personnel and end users’ mastery of the new content and behavioral change to produce the desired outcome.
Excessive growth diminishes that mastery, i.e., impacts customer satisfaction or fails to generate additional revenues. The challenge of learning something new won't create traction but friction. That law required extensive observation which took an additional six years and was published in 1980, though it is my favorite quote regarding the relation between sales, satisfaction, and software development.
Everyone welcomes functional enhancements, but we must be cautious about the escalating motto "innovate or die" which many forward-thinking technology companies promote. The constant pressure for new features increases the risk small and medium SaaS companies may fall short in resources in order to manage the spiking complexity.
At first, we may think software development stops when it reaches the app store, however product life cycles require much more from the programming team. They must handle all of the externalities due to device and operating system updates, while maintaining backwards compatibility. The customer wants to have the best performance when running on the latest iPhone, but they must also keep the experience consistent for users running old devices and outdated OS versions.
On average, Microsoft releases a new, major version of Windows every two years starting in 1995. Every new release turned into net new sales for PC manufacturers. In the same way, since 2009, Apple and Google drive cell phone revenues as they release a new major version of their operating systems every year.
The dictatorship of obsolescence driving technology revenues exposes software development to shorter maintenance cycles and, regarding Lehman’s Law, exponential growth in complexity. In direct relation, doubling the number of releases in the last 10 years has multiplied the cost attached to the specific version maintenance related to external factors.
The same innovation driving Apple’s and Google’s profit is a mousetrap for the average SaaS business. In other words, don’t just innovate for the sake of innovation.
About The Author
Daniel Bichara is founder, CEO and head of innovation at FastSensor.