This episode of the Sunny Side Up podcast packs the whole expanse of technology into a conversation with one of the industry’s longtime innovators. George Gatsis, who has been leading seamless enterprise-level business and digital transformations dating back to the days of mainframe computing. He shares his insights on ever-accelerating rates of tech development as well as the impacts of AI, big data, and machine learning – all nascent but here to stay. Also, George suggests two critical elements to effectively managing remote workplace environments (trust and metrics) and recommends some valuable reading you’ll want to check out.
George has been in the EdTech industry for over 25 years working with software professionals, building turnkey software organizations and commercial software solutions. For most of this time, George has worked for Follett running their K12 commercial platforms division. This has allowed George to pursue his passion for driving culture and operational excellence, developing world-class teams, and creating award-winning software platforms. He has sat on several boards including the Alliance for Learning (A4L), and the Student Data Privacy Consortium (SDPC), spearheaded several acquisitions and built strong customer relationships across North America.
“As we get into machine learning … things are changing really on a daily basis. So we need to invest in our people to push them to learn new things and get out of their comfort zones.”
When George first started out, computing was done with cards and readers – light-years from where things went once the micro-computers and desktops emerged. Initially, the software was for floppy disk drives and in the “dark ages” of software development. Things moved much more slowly and were miles away from the internet of things. When development started to accelerate, standard procedures had to evolve to keep up (out of this came the “Agile Manifesto,” which quickly caught on as an industry game-changer).
Around 2000, in the dot.com bubble timeframe, the internet displaced LAN and web-based development and languages became the norm, as opposed to the old client-server architectures. The space was suddenly unlimited – and the scrambling to redefine things like storage began. The costs came down dramatically and the landscape has been utterly transformed.
Engineers are always looking at and talking about new technology. On the one hand, they want the newest and greatest, but on the other hand, they don’t want anything to change. These things are diametrically opposed. At its heart technology is about people and tools. As George got deeper into his career his technical expertise became secondary to managing team members and ensuring they had the process, techniques, and capabilities necessary to deploy new tools. It’s a daily challenge to get people out of their comfort zones, ready to adopt new technologies so that they don’t become outdated. Replacing obsolete technology and archaic legacy systems is essential to moving forward efficiently.
We’re looking at the early days of machine learning and can expect equally stunning acceleration. People are looking at robotics and AI/ML but the theories around their applications are far from unified. That’s probably going to happen in the next six months, twelve months, or eighteen months. I think it’s going to explode. It will be interesting to see what this AI capability does to the programming industry itself. Machine learning will change the face of many professions/sectors. Blockchain is also an emerging factor of the sort redefining many traditional spheres and practices.
George’s team was already very distributed, with only a fraction reporting to the office on any given day, over the past five+ years. Agile practices with simple, well-defined processes to establish metrics about productivity are key. It’s critical that the culture’s leadership incorporate a hybrid mentality, including trusting workers as well as instituting measures for accountability. It’s important, however, to measure the right things and ensure that teams hold themselves accountable.
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