This year marks the 35th anniversary of the most famous video game hero: Super Mario. I’ve discussed video games a few times here before, and I think there’s a lot to learn about service from the simulated, self-contained worlds contained within the cascading ones and zeroes of the digital world. This is true of AI, operations, and certainly true of parts and resource management. Video games, especially simulations, like my beloved Civilization 6, provide a complex microcosm with which to test theories of resource management, optimization, and scenario forecasting. But what about Mario?

Mario, and his games, are slightly different, both in terms of the character of Mario, as well as the game mechanics themselves. Characteristically, Mario is the rare video game character with a stated career, and it happens to be in the home services space. Mario is famously a Plumber. Yes, he apparently went to Med school at some point but we’re not getting into that. In a video game landscapes full of knights, mercenaries, soldiers, and theoretical physicists, it’s somewhat refreshing to see a blue-collar guy stand as the official mascot for video gaming, and it offers a great deal of avenues for exploring Mario’s character here.

Of course, I can’t actually think of any instances in which Mario does any plumbing in any of his games, unless you count traveling through pipes, which I rarely have seen actual plumbers do. For that reason, the service angle looks fairly tenuous from a character perspective, so let’s look at the mechanics.

Mechanically, although Mario has been featured in kart racers, fighting games, puzzle games, sports games, roleplaying games, mobile games, and others I’m certainly forgetting, the core Mario experience has been the simple platformer: a game in which a small character moves, usually from left to right, jumping onto various—you guessed it—platforms in order to complete a series of levels. From his debut as “jumpman”, taking down Donkey Kong in arcades, through his meteoric rise on the Nintendo Entertainment System, Mario’s primary action has been to jump, and to navigate simple maps. Simple as it may be, let’s take a look at this through the lens of service.

Now, while the original Super Mario Bros. remains the quintessential Mario experience, my favorite game has always been Super Mario Bros. 3. I also feel, with its complex world maps and many secrets, it’s a perfect template for service technology solutions, specifically optimization. The game world is made up of eight sequential boards. Here is World 1:

Courtesy of mariouniverse.com

Each of the numbered squares here are levels, that, upon completion, are “resolved”. Yes—just like service appointments. Now the player, as they’re going through the game, will be setting their own “agreements” for how they want to “resolve” each of the items on the eight world boards. Usually, for the player, it’ll fall into one of three categories: Experience, Completionism, or Efficiency. “Experience” players execute on their own whims, going from level to level as they see fit. It’s like a technician setting their own schedule based on appointment needs. “Completionists”, try to finish everything, every job, every item grab, even if it prolongs the experience or needlessly prioritizes the wrong tasks. Think of this as a planning leader with poor optimization. “Efficiency” players are looking to resolve higher-level conflicts as quickly as possible, while leaving some of the lower-level conflicts to other technicians (Luigi, perhaps?) or for a later date in favor of more pressing/profitable options. We’re going to focus on optimizing for efficiency.

Typically, “efficiency” players become what they are by playing and learning the game. The more you play a Mario game, the more you understand the world layout. Remember—these early games existed before you had the ability to save on a cartridge, so each time you turn your console on, you start back at Level 1. This allowed players to get good and learn secrets through repetition.

This is great if there’s time and capabilities in place to do so. When you’re relaxing with a video game, it’s fine. When you have 500 technicians to manage and 3,000 jobs to complete, you don’t have the luxury of trial and error. To illustrate this, here is level 1-3 (you can click on the picture to enlarge):

A novice player would likely take some variation of the following path to complete the level:

And that’s fine, but an efficiency-minded player should know that there’s a secret item hidden in this level that would permit them to skip ahead several worlds, thus decreasing the amount of time needed to complete the most pressing objective: Beating the game and saving the princess. Imagine, then, that a novice player had a technology tool that directed them to take this path instead:

This would allow the player to collect the warp whistle, which lets them skip ahead, more efficiently completing their task.

This knowledge, which, on its face may seem counterintuitive, perhaps even take more time in the immediate, is the crux of what AI-powered optimization offers in service, as well. As Mike Gosling from Cubic mentioned on our podcast late last year, technicians, when handed a list of jobs, often build plans that seem on paper to be the most efficient. But a smart system understands the underlying complexities, can be calibrated to prioritize specific outcomes (uptime, jobs completed, estimated job value, etc) and make decisions that at first blush may not seem like the most logical ones, but can often present the most viable path through a complex world. Is this as fun as playing through all the levels you’re skipping? Not necessarily, but we’re not going for fun, we’re going for efficiency.

That’s optimization from a purely scheduling and routing perspective, but let’s take that a step further and look at the full picture of optimization. To do that, let’s look at another level.

Thinking about Mario as a service technician, and levels as service jobs, it’s clear that this job is fraught with certain challenges. For instance, there is no ground. If Mario misses a jump he will lose a life. This would imply that an optimization system would do one of two things. One scenario: It’d make sure the right service person was available with the right skills. Luigi canonically has a longer and more precise jump than Mario’s, so he might be a better fit for this job. If this is Luigi’s day off, the alternative would be ensuring Mario has the right tools for the job. In Super Mario Bros. 3, Mario can wear something called the Tanooki suit, which gives him the ability to fly. By ensuring access to the right parts, optimization systems can make sure that the job is completed the first time…no lost lives.

Surprisingly like Mario levels, service needs and appointments are increasing in complexity. It’s great when seasoned technicians, like seasoned players, know what each encounter will require, know the most optimized routes, and can make the right decisions. But in an industry with high workforce turnover, that’s not always an option.

In gaming, the technology to optimize systems, provide the best routes, and arm you with the items you need to do jobs right the first time would be what’s called a cheat—cheating the system the designers intended to make the game easier. In service, good optimization might be exactly the cheat code you need to take your business to the next level.

Tom Paquin
Author

Contributor, Future of Field Service