Toyota pushes IT automation into overdrive

Automation has long been the lifeblood of IT work. In pockets throughout the organization, the call to automate processes has always been a key driver of IT agendas, whether it be to overhaul targeted processes within the sales or marketing function, or within IT itself.

But the rise of digital capabilities such as AI and robotic process automation, along with the drive to digitize operations across the enterprise via digital transformation, has pushed some IT organizations’ automation agendas into overdrive, heralding a new era of “hyperautomation,” in which all facets of business operations, from mundane tasks, to product development, to manufacturing, are viewed as internetworked processes ripe for automation gains.

Toyota Motor North America, which has embraced the cloud for more than 20 years, is one such enterprise pursuing hyperautomation. Within the past three to four years, the company has been relying more heavily on Amazon Web Services — as well as many independent automation tools — to achieve a ramped-up automation agenda that sees nearly all business operations now automated on the cloud, says Brian Kursar, chief technology and data officer and group vice president of digital technology at Toyota Motor North America.

“The big change now is this hyperautomation,” says Kursar, who oversees about 2,500 IT professionals at Toyota. “I tell my teams that automation is our salvation.”

The mantra seems to be working. Toyota claims hyperautomation has saved the company $10 million thus far, at a rate of roughly $5 million annually. One single team saved 6 weeks of labor through the efforts, representing a savings of $250,000, according to the company, which has at least 100,000 automated scripts running on schedulers on its ETL platforms across thousands of databases alone. 

“It’s definitely a companywide initiative,” Kursar says.

Driving efficiencies with hyperautomation

Gartner coined the term “hyperautomation” nearly a decade ago to refer to automation across all business units.

While more than 80% of businesses employ some automation, relatively few enterprises have achieved hyperautomation, and fewer than five enterprises — Ericsson and Johnson & Johnson among them — globally generate savings from their hyperautomation programs exceeding $100 million per year, says analyst Frances Karamouzis, distinguished vice president at Gartner.

Hyperautomation “is a disciplined approach for doing three things: rapidly identifying, vetting, and automating as [many processes] as possible,” Karamouzis says. “It could be a business process or an IT process. And to do that, people use a whole myriad of technologies. They use AI. They use RPA. They use iPaas. They use low code.”

Toyota isn’t quite there yet, even as the company’s ramped-up automation agenda spans business, development, and manufacturing processes. CTDO Kursar is keenly focused on Toyota’s cloud engineering and development practices, which enable all business units to exploit cloud automation features for their needs in ways that are easy to implement.

By implementing AWS foundational services such as Backstage, for instance, developers and end users can write Python scripts and build applications without worrying about whether “they’ve closed the right ports and set the correct permissions in containers,” Kursar says, adding that having the security of the development platform built-in opens automation efforts to many employees.

Business analysts and developers can also use a wide variety of development tools to create automation workflows, ranging from low-code platform for non-developers to higher-end RPA and AI machine learning model automation tools. Developers also have access to a worklet development kit for the automotive industry, dubbed Chofer.

In addition to providing significant cost savings, Toyota IT’s hyperautomation in the cloud makes far more data — and investment — available to business groups for analysis, creating models, and unlocking data insights, Kursar says.   

“Very early on, we were so focused on keeping the lights on and building platforms. If the business is too busy running the business, we don’t have money for analysis,” the CTDO points out. “The reinvestment [from hyperautomation] has gone into investing in data scientists who can create very complex machine learning models that drive even more cost savings and value.”

And that is “one of the greatest accomplishments of this hyperautomation,” Kursar says. “These smart engineers can focus on driving insights to provide decision support for our business.”

Taking an automation-first approach

Kursar confirms that automation is also used by product engineers in Toyota’s manufacturing process. Toyota — and all other automakers — are far from self-building automobiles, but many are integrating automation into the design, specifications, and quality assurance processes.

One of Toyota’s build tests for vehicles is thermal imaging to test the welding of the frame. It is “very time consuming,” he says, but the implementation of automation not only saves the company millions of dollars but results in a higher-quality output — now every vehicle is tested in this manner.

Toyota operates roughly 15 manufacturing plants in North America and is currently building a new plant in North Carolina with Panasonic to support its electric vehicle (EV) batteries. “Everything going in there is going in with a data-first, automation-first [blueprint],” Kursar adds.

IDC maintains that more than $150 billion was spent on automation between 2017 and 2021. Yet, only roughly a third of enterprises are more than 50% into automation goals for basic software development, IT, and business processes, such as claims processing, according to a recent IDC report detailed at IDC Directions 2023 in March.

“For many companies, automation starts with processes they already fully understand. However, machine learning and AI are allowing engineers to better understand how small nuances in operating parameters can make a big difference in the business outcome,” says Dave McCarthy, a vice president at IDC.

Many C-suite executives are now focused on what IDC terms Enterprise Automation 2.0, defined as a “unified approach to closed-loop automation where artificial intelligence continuously supports decision-making and automated actions that proactively optimize and enrich outcomes to maximize the business value of the automation,” says Ritu Jyoti, group vice president of AI and automation at IDC.

Next-generation automation 2.0 will span an entire organization, and include generative AI and business processes such as process and task mining, RPA, workflow automation, BPM, application integration,  API management, data integration, and event brokers, the IDC report states.

Most of these — including machine learning model creation — are currently in process among many in Gartner’s Hyperautomation 100 Club. But soon, as enterprises continue to use digital transformation processes to save money and differentiate their offerings, it will become ubiquitous at thousands of companies, experts predict.

“Automation is the way we can be better than our competitors,” says Toyota’s Kursar. “By automating as many processes as we can, we can then really focus on high value and differentiating work.”

Automotive Industry, Cloud Computing, Digital Transformation, Robotic Process Automation