In the first article of our First-Time Fix series, we established the impacts of failing to fix service requests on the first visit. In this article, we will uncover the common causes for first-time fix failures by looking at the actual measurements and causes with true data, rather than the anecdotal information that many service leaders have had to base their previous decisions on.

In my experience, utilizing dashboards and reports we can push the reasons for first-time fix failures into 5 buckets.

1. Spare Parts

This is the area that most people would highlight as a cause for first-time fix failures. Since most service organizations have limited capacity or tools to conduct appropriate triage, they often have to send the technician to perform the triage on-site or take an educated guess as to what parts they will need.

Due to this, technicians may believe that by hoarding or carrying extra inventory they are better servicing their customers. While this could be true, they are generally carrying too much inventory or indeed the wrong inventory. This causes knock-on effects such as higher backorders for other technicians, slow-moving stock leading to higher obsolescence write-offs, and a reduction in cash flow that could be better utilized elsewhere within the company. It can also create a rift between the service organization and the Supply Chain organization that makes it difficult for them both to meet their Key Performance targets.

A balance needs to be found that benefits both groups and creates a partnership. The right part with the right technician at the right time, thereby ensuring the highest levels of first-time fix without bloating field inventory.

spare parts servicemax

2. Skill Sets

It seems quite simple: send the trained technician and the likelihood of a first-time fix failure diminishes. However, how recently was the technician trained on that product or had exposure to that particular asset?

Do the dispatchers know if the technician’s skill sets match the service need, or are they just sending the closest or any available technician? Do the dispatchers actually know the Installed Base and what product the technician will be working on? Do they understand if there are any security or certification requirements to enter the facility? How do you continually track technician effectiveness to determine the appropriate training requirements? It is not as easy as just aligning skill sets, especially for a dispatcher who could be managing 50 plus technicians at any one time.

3. White Space Management

Often there is no link between the management of the calendar and the length of the repair or maintenance. If you send a technician to a call at 3 pm (working day 9 am to 5 pm) but the job usually takes 4 hours, you are either going to incur 2 hours overtime or the technician will need to return the next day for the second visit.

In this instance, if the dispatchers understood the mean time to repair (MTTR) and response time constraints, they could have made an informed decision and scheduled the call for the next morning. This scenario would have then opened up the 2 hours between 3 pm and 5 pm for the technician to either attend a call that is a better fit, assist on a remote triage session, return unused inventory, or complete some online training sessions.

servicemax scheduling

ServiceMax Scheduling

4. Incorrect Data

How often does a technician get onsite only to find out that they have arrived at the wrong address, don’t have the information on the contact, or that the machine has been relocated? More so, how many times do other administrative issues cause the first visit to be unsuccessful? The chances are that many of these issues can be caught with a simple change in the business process as enabled by a supporting software solution. 

5. Customer Issues

In connection with the issues above, most organizations do not have processes or tools to capture these or to review them with their customers. Internally, it is important to understand the cost of these issues against the contract or cost metrics, but it is also essential to discuss these with the customers to enable a higher level of asset uptime. Once again, these areas present low hanging fruit and can be resolved with some simple investments in the business process.

While this does not cover every possible cause for a first-time fix failure, these five main buckets are a great place for organizations to start capturing data and measuring the true impact and costs. With this information, you can create an action plan to reduce those failures and identify the ideal first-time fix ratio for your business.

Stay tuned for Part 3 of this First-Time Fix series that will detail the actions service organizations can take to improve results across these common causes for first-time fix failures.

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ABOUT Kieran Notter

Kieran NotterKieran Notter is VP of Global Customer Transformation at ServiceMax. He is acknowledged as a service industry domain expert with 30 years’ experience. He specializes in field service revenue and working capital improvements, with a particular passion for supply chain operations. He is highly effective at partnering with customers to deliver tangible, practical results across their service operations. Having previously worked for companies including Kodak, Bell & Howell and, most recently, Pitney Bowes he understands the importance of a logical approach that is supported by real-time analytics. His considerable experience in implementing and using systems such as SAP, Servigistics (PTC), Oracle (Siebel), Salesforce and ServiceMax enables him to recognize a client’s challenges and facilitate solutions that lead to sustainable growth. His recent consultancy engagements have delivered improvements, such as reducing field service inventory levels by 45 percent while maintaining a higher first-time fix rate.