At Enigen, collaborating closely with our B2B clients to enhance Asset Based Services is key to optimising their asset performance, increasing longevity, and improving efficiency, all while minimising operational costs. We achieve this by empowering our clients to effectively manage and maintain their assets through the strategic utilisation of connected Oracle solutions, coupled with advanced data analytics and artificial intelligence. In this insightful guest blog by Rick Shimko, Product Marketing Director for Oracle Fusion Service and Oracle Field Service, he demonstrates an example of this by explaining how manual processes and disconnected systems create limitations in service workflows. He presents a vision where the service lifecycle is fully automated using intelligent IoT-connected equipment and Artificial Intelligence.
Thank you to Rick for being our guest blog on the subject.
Contributor: Rick Shimko
Product Marketing Director, Oracle
Recently, I had a conversation with a friend who asked me about AI tools for business and if I recommend he invest in something like a copilot app for his team. My guidance was to think critically about the team’s readiness to make use of whatever AI tools they might leverage and the value it would create.
I also teased him a bit by saying “Do you know what’s better than a copilot? An autopilot.”
Self-driving airplanes, cars, and… service?
The formal definition for the word autopilot is “a device for automatically steering ships, aircraft, and spacecraft.” An interesting fact I discovered is the first known application of autopilot technology was in 1912, designed to reduce the strain on pilots who until then needed to be at constant attention in flight.
More recently we’ve seen advancements in self-driving technologies from companies like Tesla and Waymo in effort to make transportation and the movement of goods safer, more convenient, and cheaper.
You might be thinking, “that’s great, but what does that have to do with service?”
Well, we’re thinking about (and developing) solutions that can have the same impact on the service life cycle.
This is also where the convergence of automation and AI technologies can have a massive impact for businesses in asset-intensive industries like manufacturing and high tech, among others.
Autopilot for asset-based service
Today, many workflows in the service life cycle are constrained by manual processes and disconnected systems.
For example, we may only learn that a piece of equipment has an issue at the time a customer reaches out to alert us. Or, that the parts needed for a repair are not available until a service technician is already on-site and has diagnosed the issue. Or, that a customer is not available. Or, that the location of the asset is not accessible. Worse, what if that issue simply required a system restart, or a part replacement that could be performed by the customer without the need for a field service expert traveling to their location.
Enter a new vision for the service life cycle, one that is automated at every turn, for example:
- Smart, IoT connected equipment or assets that run self-healing routines, often fixing itself before a service disruption or failing completely
- When an asset suffers an unplanned disruption:
- Service requests are created instantly by an automated process
- Notifications to service teams and customer contacts are sent to preferred channels (ie. email, SMS)
- If the repair can be completed by the customer, parts are automatically ordered and shipped and guidance in the form of help articles (from a knowledgebase) are sent via email, SMS, or chatbot
- In the event a repair requires a field service expert to come onsite, the appointment is scheduled automatically, parts are ordered to either be delivered ahead to the customer site or to be loaded into trunk stock on the service technicians vehicle the day of the appointment and reminders are sent to the customer ensuring they are available, or at minimum the service technician will be able to access the asset’s location
- While on site the service technician follows a pre-built workflow to diagnose and repair, with AI-generated next-best action recommendations and contextually relevant knowledge article summaries provided to help accelerate resolution time
- In addition, service technicians are intelligently prompted to perform preventative maintenance tasks on other equipment on-site, reducing the likelihood of future service disruptions, and preventing future truck rolls solely for maintenance
- And, for good measure, all charges for time, labor, parts, and travel are automatically logged, warranties and discounts are automatically applied, and all data is synced with billing for lightning-fast revenue recognition
What’s exciting to me is this vision of service on autopilot is not a “someday in the future” science fiction story… we’re already here. The technology and applications needed to make this a reality exist today.
Welcome to the future of service life cycle management
At Oracle CloudWorld in Las Vegas, NV last September I hosted a session highlighting Oracle’s advancements in automating workflows in the service life cycle. (If you didn’t make it to the conference, you can watch a digital version of the session titled “Master Asset-based Workflows to Drive Anything-as-a-Service Success” here.
During the session we chatted about undeniable trends shaping service, ways to improve your operational readiness, and a before and after view of how service automation and AI impacts service workflows.
Start your transition to towards service on autopilot
Naturally, implementing the systems and processes to automate the service life cycle involves several business functions, and may happen over a multi-phase effort. Working with a partner who has expertise in similar deployments can help you identify the area of your service value chain that are most ready to adopt new technology and help you get started. But, with the amount of innovation available to plug into your service workflows, there’s no better time to start than now.
If you’d like to learn more, don’t hesitate to reach out to the Enigen team here.
About the contributor:
Rick Shimko is Product Marketing Director for Oracle Fusion Service and Oracle Field Service. He rejoined Oracle in November 2020 having previously worked for the company after the acquisition of TOA Technologies (now Oracle Field Service). Prior to the acquisition, he led the global marketing operations and demand generation team for TOA, building a strong knowledge and appreciation of the role service plays and the technology ecosystem that supports it. Rick resides in Cleveland, OH and has nearly two decades experience in B2B and SaaS software marketing across a diverse group of start-up, growth stage and enterprise companies.r Product Marketing Manager at Oracle. Focused on go-to-market initiatives for Oracle Sales, Carrie has extensive experience in setting strategy, driving execution, and obtaining measurable ROI for marketing and sales initiatives.