Or, What Nintendo’s Game Boy has to do with Analytics 

Back before the success of the Nintendo Switch or the motion-controller craze of the Nintendo Wii, there was a device that encapsulated a central driving philosophy of Nintendo and was key to its long-term success in the video game industry. Like other elementary-aged kids of the 90s, you’d usually find me carrying a Game Boy, getting quick games of Mario, Metroid, Tetris and Pokémon in during car rides where I carefully tilted the screen to make sure the sunlight illuminated those crude, but magical, green-tinted pixels. By today’s standards, it was archaic. Simple graphics with no backlight in a large gray brick that used AA batteries. 

The secret to that game system’s success was not in its technology — there were superior options even at that time if you wanted more detailed graphics or even just color. No, the success was in the unique combination of mature, cheap technologies that created an innovative and cost-effective package. The Game Boy was smaller and easier to carry than its competitor’s offerings. It required fewer batteries and they lasted longer, allowing for extended gameplay and cheaper ownership. By making the Game Boy durable, affordable and portable, Nintendo created a product that resonated deeply with consumers and that helped the device become a global phenomenon. 

Innovative Use of Mature Technology 

The man behind the Gameboy was Gunpei Yokoi who would go on to become a legendary figure at Nintendo. His unique philosophy avoided chasing after the most advanced technology and instead focused on delivering a better experience with known technologies. He called his philosophy “Kareta Gijutsu no Suihei Shikō” (often translated as “lateral thinking with withered technology”). This approach didn’t seek to use outdated technologies, but to maximize the value of well understood and cheaper technologies to deliver a compelling product. In short, it prioritized the creative use of existing tools over exploring the latest innovations. His philosophy led directly to the Gameboy and continued as a primary influence in Nintendo’s other iconic and successful products. 

In the world of data and analytics, as well as in product development, there is a strong allure to always chase after the latest, most advanced technology. It’s fun! Who doesn’t want to learn about AI? I certainly do. But companies often do not see the return on investment when heavily pursuing cutting-edge tools and platforms without a clear need and strategy. In fact, this high-tech approach can often lead to complications, inefficiencies, and even failures, particularly when the technology is untested or overly complex. We saw it with “Big Data” and Hadoop, we saw it again with Machine Learning/Deep Learning, and we’ll see it again with Generative AI. All these technologies are amazing and have their place, but we need to be purposeful and considerate of our investments. So let’s dig deep into this alternative path to see what applications we might find.

What is “Withered Technology” in Data and Analytics? 

In Yokoi’s philosophy, “withered technology” refers to commodity technologies that are abundant, well-understood and relatively inexpensive. These are not necessarily outdated technologies, but rather, those that have been around long enough to be thoroughly vetted and refined. In the context of data and analytics, this might include tried-and-true tools like SQL databases, traditional ETL (Extract, Transform, Load) processes or even spreadsheet software. Even when looking towards more advanced things like vector databases for search applications, there’s a strong argument to just use Postgres anyway. These tools may lack the flashiness of more recent innovations like AI-driven analytics platforms or real-time streaming data processing, but they have the advantage of being well-known, reliable and cost-effective. 

More specifically, the analytics space has matured, and it’s possible to rapidly assemble compelling products from open source or cheaper, commodity platforms. For example, in embedded analytics you could consider tools like Superset or Evidence backed by a fast analytic database like DuckDB with little to no licensing costs on stable, reliable technologies. 

The Power of Lateral Thinking in Analytics 

In Yokoi’s philosophy the value isn’t from the technologies themselves, but from creatively applying them. In the realm of data and analytics, this could mean leveraging existing data infrastructure in new and innovative ways or combining traditional tools with new approaches to solve complex problems.

In a recent project, we combined technologies such as Superset, Airflow and Curator with a form creator to help a non-profit to capture complex information from their users alongside their analytics in a cost-effective package. Instead of looking for an expensive platform or alternatively investing in expensive custom development, we were able to rapidly deliver value by treating off-the-shelf components as building blocks to make something that solved their specific problem in a compelling and cost-effective way.

The Pitfalls of Chasing Cutting-Edge Solutions 

Many companies are being drawn in by the promise of AI and are seeking to solve huge problems with it in the hopes to gain a competitive advantage by being early adopters. However, this approach is fraught with risks. It can be expensive, complex to implement and require specialized skills to manage. There are also hidden pitfalls the industry is still figuring out such as how to deal with the frequent evolutions and changing landscape. Not to mention that some of the models are simply getting worse over time. Even more foundational, many companies need to work on fundamental data quality concerns so that there’s meaningful and worthwhile information for retrieval and training.  

It’s also important to realize that much of the work of AI will get done by your existing vendors. Much of the algorithmic magic of machine learning is already incorporated in your business through the tools you already use, and which were adopted without much effort. Resources that you could throw at an AI project are often better utilized for solving your fundamental data and user problems with the creativity and problem-solving of lateral thinking. 

Solve User Problems Laterally 

Gunpei Yokoi’s “lateral thinking with withered technology” philosophy offers a powerful lesson for the field of data and analytics. By focusing on mature, reliable technologies and applying them in creative ways that meet users’ needs, businesses can avoid the pitfalls of chasing cutting-edge solutions that may be expensive, complex and unproven. 

Incorporating this approach doesn’t mean ignoring the latest advancements, but instead being strategic about where and how you invest your resources. The true power lies in understanding your users, understanding your tools and applying your creativity.  

As you navigate the ever-evolving landscape of data and analytics, remember that sometimes the best path forward is not the most technologically advanced one, but the one that allows you to deliver value quickly, efficiently and creatively. Embrace lateral thinking, and you might just find that the tools you need to succeed are already at your disposal. If you want to approach your next project laterally, ask us about running a Design Sprint with your company.