Emcien grew up in the manufacturing space, helping companies use data to optimize product configurations, and we continue find new ways to help them solve their toughest challenges today.
What follows is the story of one client who used Emcien to launch a prescriptive maintenance program that slashed unscheduled downtime.
About Our Client
Mike Salter is the Director of Client Services at a Fortune 1000 global technology company. The company designs, manufactures, sells, and services financial services technology, and ATMs are the flagship product in Mike’s division.
What Keeps Mike Up at Night
Mike has a big umbrella, but he has two chief concerns.
He needs to meet SLA requirements about ATM uptime (the percent of the time ATMs are working just fine) and “first-time fix” rate (frequency with which problems are fully resolved on the first visit).
And he must minimize cost-to-serve for resolving unscheduled downtime issues.
Some Things Needed to Change, and Fast
When Mike reviewed his department’s performance with the VP of Client Services in 2016, they saw some concerning numbers.
First, they were performing below the standards set in the SLA for both uptime and first-time fix rate.
Second, service costs were high and unsustainable. Each truck roll cost $300 and each incident took an average 1.8 truck rolls to resolve, making the cost to resolve one downtime issue a whopping $540.
Mike felt that he was always playing catch-up. The speed of product development and trouble tickets was overwhelming. He knew he could not solve his problems by throwing more bodies at it. In fact, his service team had doubled in 7 years and the cost-to-serve was still growing.
Both Mike and the VP agreed that something needed to be done immediately.
Step 1: Why Is This Happening?
Mike knew he needed to identify what was going wrong, when, and where, in the operations of department.
He wanted to talk to his people, so he convened a group of leaders from the service group.
He also wanted to look at the data, so he cracked open the incident management system his service team used to track downtime issues and service responses.
Sure enough, the problems started to become clearer.
Uptime – ATMs in the Field
There were so many instances of unplanned downtime that Mike and his team couldn’t see a pattern to it. Or to the parts that were causing it. Because they couldn’t see a pattern to downtime, they couldn’t predict it.
So while they knew they could improve uptime and also cut costs by expanding their preventative maintenance program and resolving more issues before they could occur, the cost to do so would be prohibitively high.
This is because they couldn’t anticipate what machines were at-risk, so they’d have to inspect a large percentage of machines and components, and there were just too many for that to be a cost-effective strategy.
Uptime – ATMs in Development
Despite all the apparent unscheduled maintenance, it seemed like the new ATMs the company rolled out were just as prone to downtime as the older machines.
This was because the company did not know what the problem components were. The product team made decisions without this critical information, so while some features improved on new models, the root cause issues causing downtime for many ATMs weren’t addressed.
As a result, the company continued to roll out ATMs that would experience issues, make customers unhappy, and inflate service costs, continuing a vicious cycle.
First-time Fix Rate
On the day of a scheduled repair, the service team would arrive at the customer’s location to inspect the ATM.
It was critical they fixed it right the first time to minimize call-back maintenance (a provision of the SLA), and keep customers happy. So they needed to make the right diagnosis, have the right parts and skills to address it at the scene, and then fix it correctly.
But technicians didn’t always know what the problem was even after they inspected the machine. What component or components were malfunctioning? The technicians would make a determination, but because of the complexity of the machine, even the most experienced and skilled techs got it wrong more often than they themselves would like.
Then, they needed to have the part, tools, and technician with the required skill-set with them in order to resolve the problem on the first visit. But because they didn’t know the problem before they arrived on site, they frequently wouldn’t have what they needed to remedy the situation once the diagnosis was made.
Ideally, they’d stock their trucks to be fully prepared for every possible scenario, but they had limited space, so it wasn’t possible.
What’s more, they didn’t always know the best fix for the malfunctioning part or component. Should they replace it outright? Simply clean it? Did it need to be adjusted or re-calibrated? Again, they used their best judgment, but were unfortunately wrong more often than they could afford.
As a result, many times they left a customer site thinking they’d corrected the issue only to get a call from the customer saying the machine was still down and they needed to come out again.
The bulk of the company’s service costs were generated by field agents making multiple trips between the customer and the service center.
Because a field agent didn’t what part or component needed servicing until they inspected the machine, they often had to drive back to the service center to grab the right parts, tools, and team member with the right skills set – or order parts and wait for them to come in – and then drive back out to the customer when they had what was needed to fix the ATM.
And when their first-time fixes didn’t work, the whole process was repeated again and again until it was resolved. It was a very time and truck roll-intensive process.
Diagnosis: Lack of Answers = Reactive Position
It was clear to Mike that the company was flying blind when it shouldn’t be. The service team — and the product team — didn’t have the answers they needed, when and where they needed them, to right the ship.
Because they didn’t know what machines would have downtime or which components were causing the problem, they couldn’t head off issues before they happened, fix them correctly or cost-effectively, or make better ATMs that were less prone to issue.
Instead, they were forced into a reactive position, where they had to wait before they could respond. They had to wait for an issue to be identified before they could service an ATM. They had to wait for a diagnosis before they could get the right parts and team members lined up.
And because they didn’t know in advance what the best fix was, they would have to attempt one and then wait to see if a customer called back.
Step 2: Turning to BI
So Mike turned to BI to empower his team with answers.
The BI tool took the data from Mike’s incident management system a step further. It showed a lot of information about unscheduled maintenance – the times, days, weeks when most downtime occurred. The geographies where downtime occurred most frequently. How the downtime had increased over time. And this information was displayed visually, so it was easier to understand.
But they still didn’t know what ATMs would need unscheduled maintenance, what was wrong with them, what parts and tools are needed, how to fix the part…so they couldn’t act.
Step 3: How Emcien Helped
Emcien took their incident management system data and gave them a prescriptive maintenance capability: the clear action items they needed, conveniently inside the apps and systems they use, so they could act to continuously improve their service and costs.
Emcien moved Mike’s team from a passive, reactive position to a powerful proactive position where they know exactly what is going to happen in the future…and exactly how to fix it.
As a result, field service agents, service managers, and product teams have the answers they need to make improvements to performance every day.
Those improvements, taken together, added up to big results in uptime, first-time fixes, and cost-to-serve.
Get All the Details
Want to know exactly how Emcien used Mike’s data to give them clear actions? How it solved the problems they identified? The exact results Mike was able to report back to his VP? Watch our pre-recorded webinar to get all the details.