We helped it get lean. And smart.
We jumped on board as the company’s co-pilot, helped turn data into insight and action, and reimagine its maintenance systems from nose to tail. Our Lean DigitalSM approach landed that perfect mix of industrial internet of things (IIoT), digital technology, design thinking, and smart analytics. All of which helped the company harness its sensors and systems better. Here’s how it worked.
Manage everything from one place
The first step was to whittle the business down to a lean, mean flying machine. Which means it had to move away from its mishmash of vendors and tools, and had to get everyone on the same system. Also, it needed its technicians to all do the same things.
We helped the company use lean principles by setting up an integrated fleet support engineering and analytics center of excellence (CoE), that leverage process re-design, global delivery and automation to effectively handle high volumes and velocity of machine-to-machine and other data, at scale, to enable Data-to-Insight-to-Action for predictive and proactive maintenance.
The company started by documenting 400 of its processes—everything from how to extract an engine to how to change a flat tire. It also created backups for more than 90% of their processes.
Soon, the company was ready to route everything through its new CoE. But it couldn’t safely make the switch overnight and it took three months to get it off the ground. We started with several soft launches before the planned start date. This let the business do dry runs of the new controls and make sure it could handle any real-world scenario that came up.
Turns out, the company could. So it made the switch from its traditional processes to the new system on schedule, with no surprises. Now, the aviation firm manages everything from the CoE. And with 25% fewer people.
Measure and track what matters
From its brand-new bird’s eye view, it could start tracking what was important to the business and its customers. For that, it needed our Digital Smart Enterprise Processes (SEPSM), a framework where we use granular data analysis, benchmarks, and metrics to identify how our clients can get the most from digital.
Out of its 400 processes, we found 12 key performance indicators (KPIs) to watch weekly. These ranged from how long it takes to put engines back into a plane to how quickly it answers customer questions.
The company can now give its customers peace of mind that it is doing everything as quickly and safely as possible. And has the numbers to back it up.
Make alerts more accurate
Before, the sensors in engines worked in a vacuum. Each one kept an eye on its own numbers and was quick to trip if something went out of range. If the temperature dipped below a certain degree, a temperature alert would go off. Even if the altitude sensor showed that the plane was up high, where it’s supposed to be cold.
That’s why 96% of the time, it was a false alarm. To bring that number way down, we tied the sensors together with advanced analytics and machine learning. Now, if the temperature dips, the altitude sensor says it’s okay because the plane is flying.
This made alerts more accurate—and less likely to cry wolf.
Auto-respond to customer questions
The aviation firm’s customers ask more than 5,000 questions a month. Before, it had to respond to each one by hand, after tracking down the answer.
We channeled queries through a single web portal and introduced robotic process automation. Now, a robot does the time-consuming work. It uses text mining to match a customer’s question with the best answer. Then it generates a response based on natural language programming.
Which means technicians spend more time servicing engines. And customers get their answers quicker.
Add new engines—in hours instead of days
The web portal is now a one-stop shop for customers. It’s made it much easier to add new aircraft. Customers used to fill out a long, manual form about their engine. And it could easily take days to track down all the details. Now, they can use a quick web tool that pre-populates most of the fields. Which means that they now record 99% of their engine changes within 24 hours.