Service Maintenance and Repair (SMR) operations throughout the world will ultimately have the same objectives and challenges, one at the top of the list is to retain customers by turning them into loyal customers. No matter the size of the field service organization, achieving high first time fix rates is essential for customer retention. Technicians are often the unsung heroes that sit behind the scenes to deliver a duty of care to the customer by returning the vehicle in a safe and road worthy condition. There's also the added pressure to meet tight deadlines, and to maximize their efficiency in reaching optimal workshop utilization for the aftersales service department to return the profit and financial stability (billable hours / available working hours) x 100. High customer retention rates are crucial for maintaining financial stability and operational efficiency.
With such pressure to hit the KPIs (Key Performance Indicators) required to run a well-oiled business, something will inevitably break. Especially when not all technicians have the same level of expertise, compounded further with the ever-increasing shortage of skilled labor in the marketplace and the diminishing tendency for the younger generations wishing to pursue a career in the motor trade. Meanwhile, the vehicle car parc is getting older and the OEMs (Original Equipment Manufacturer) have roadmaps that will see many new models entering the market with innovative design architecture for the sophisticated hardware platform (chassis, electric vehicle battery placement, central electronic control unit) and complex software platforms with millions of lines of code to decipher. Efficient field service operations and robust service management strategies are essential to navigate these challenges.
First Time Fix Rate (FTFR) is a critical KPI for measuring the success of maintenance and service calls, significantly impacting operational efficiency and customer satisfaction.
With all of these factors considered, the industry is fast approaching a critical point and needs to find a way to attract the skills required to work on future vehicle types. It also needs a training program dedicated to enhancing the skills of the existing workforce to be able to work safely on vehicles, and at the same time, hit the flat rates (manufacturer operation times) on any given task without the added pressure of missing deadlines and rushing through the tasks by taking shortcuts or increasing the chance of human error or misdiagnosis. Implementing field service management software can streamline workflows and ensure high quality service delivery.
Automotive technicians ensure vehicles are safely returned while facing pressures to meet deadlines and maximize workshop efficiency.
Artificial Intelligence (AI), computer vision and mixed reality platforms are now playing a pivotal role in sustainable training by using neural networks and nudge theory techniques to collaborate with the technician in providing continuous backup and guidance at the point when the technician needs a helping hand. This however will not always help the technician when it comes to navigating around the vast amounts of technical information systems such as technical manuals, diagnostic DTCs (Diagnostic Trouble Codes), bulletins, knowledge base, wiring diagrams, electronic parts catalogues, warranty systems and so on. The sheer scale of information the technician needs to refer to for every make, model, year is daunting and often requires logging into multiple systems and searching through drops down and fields is at times no different to finding a needle in a haystack. No wonder the technician’s efficiency is always under scrutiny and often results in deadlines missed and customer promise times going out the window. Ensuring that technicians can resolve issues on the first visit is crucial, as it directly impacts the number of jobs fixed and overall operational efficiency.
A metric the OEMs and service operations are keen to hit is ‘fix it first time’ (FIF) ratios. FIF emphasizes the importance of diagnosing and repairing a vehicle correctly on the initial visit to the repair shop. Get this wrong then re-repairs will be necessary and serve as a costly reminder of why the quality of workmanship should never play second fiddle to overloading the workshop and over-promising to customers. Customers certainly won’t thank you if they have to bring their vehicle back a second time for the same fix, with customer satisfaction and CSI (Customer Satisfaction Index) scores taking a hit. Repeat visits not only increase operational costs but also reduce technician productivity, highlighting the importance of achieving fewer site visits.
The average industry benchmark for First-Time Fix Rate in car repair and maintenance shops ranges from 75% to 85%. This means that for every 100 repairs, 75 to 85 are resolved correctly on the first attempt.
Here are some reasons why FIF matters:
Regardless of the size of the field service organization, maintaining high first-time fix rates is crucial for retaining customers.
There are several factors in why increasing FIF is not straight forward.
To achieve improved FIF, repair shops should invest in more transparent and real time access to the extensive amounts of data through the technical information platforms and related information about the vehicle such as service history, insurance information, geolocation and so on. Intelligent technical systems using AI will use available network data to allow for predictive maintenance and play a key role in avoiding costly repairs and reducing the burden on SMR organizations. AI based diagnostic tools can also be effective in delivering recommendations via probability scoring to get to the root cause of the fault without the need to go one-by-one through each DTC. Effective handling of customer calls during initial interactions can also lead to better job matching and technician scheduling, ultimately resulting in increased customer satisfaction.
In summary, a more connected and seamless approach to technical information that benefits from the power AI pulling from all available data sources relating to the vehicle and its history, will help the experienced and less knowledgeable technicians be more efficient and more accurate in process of repairing vehicles. Best-in-class organizations that achieve significantly higher First Time Fix Rates (FTFR) see improved customer satisfaction, retention, and overall operational efficiency.
Please check out Getac’s Technical Platforms and get in touch if you would like to know more.
Russell Younghusband has been involved in supporting industry with mobile IT projects for over two decades. For the last 10 years, he has specialized in automotive business change and efficiency programs to support the OEMs and their franchised networks with customer retention and aftersales strategies.
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