In the first blog installment of this series, we discussed manufacturing industry verticals that are great candidates for using Artificial Intelligence and focused in on the typical processes of a product manufacturing organization. Our second installment continued with an examination of the support desk process, data available to manufacturers, and the challenge of knowledge silos. Let’s continue with a deep dive into field service issues.
The field service step is crucial to most, if not all, non-portable durable goods manufacturers. Think appliances, HVAC, furniture, production machines and equipment, and vehicles (especially industrial vehicles). In the case of portable durable goods that can be easily shipped for a return merchandise authorization (RMA) process, there is still a service cost. However, it is more fixed and predictable, with the worst-case scenario often being a total replacement of the product. This pales in comparison to the cost of dispatching a field service technician to a location (aka a “truck roll”) for diagnosis and/or repair.
We mentioned in Part 2 of this blog series that first contact resolution (FCR) is achieved on average about 20% of the time, which means the first truck roll is often a diagnosis trip. Why? The parts to execute the repair are only present on the truck 50% of the time. This results in parts order lag time and yet another truck roll to close the process and get the customer’s product operational - adding significantly to the incident cost and trying the patience of the customer, who is without an operational product during this period. It is the worst-case field service scenario for the manufacturer, but the numbers don’t lie: 40% of the time, this is exactly what happens. KPIs such as FCR are vital to controlling revenue loss. Aberdeen Group’s 2013 field service report showed that organizations with an FCR above 80% experienced a 6.2% increase in revenue compared to those with a sub-80% FCR. They suffered a 2% decrease in revenue. But wait, there’s more…
Most large manufacturers use sub-contractors to execute field service operations. It is often significantly cheaper in a geographically dispersed customer base to certify local service centers on the products and let them manage their own staff, assets, and stock of replacement parts. Transactions between the sub-contractor and manufacturer are usually done with a warranty claim detailing the customer issue and the parts and labor used to service that customer. We will take a look at the warranty claims process in a moment, but first let’s examine the complexities that work against manufacturers that use sub-contractors:
- Sub-contractors are in business for themselves. Unfortunately, in some cases there are losses to the manufacturer associated with the way sub-contractors submit claims, such as additional parts being used when not needed, or falsification of work.
- More often than not, the sub-contractor considers the incident resolution to be their IP. This works against the manufacturer solving any issues prior to the diagnosis truck roll, because it is in the sub-contractor’s best interest to do most of the work and get paid for it.
- In most cases, sub-contractors are not incented to maintain adequate stock levels for completing diagnosis and repair in a single visit. After all, they get paid for two truck rolls if they have to order a part. It is also counter-productive for subcontractors to stock parts that may get replaced and therefore would become obsolete.
- It is not a stretch to say that sub-contractors act as an extension of the manufacturer’s brand - putting a significant portion of the warranty claims process out of the manufacturer’s hands. From a sub-contractor’s perspective, it is easier to blame the manufacturer and position themselves as a customer advocate than it is to work with the manufacturer on problem resolution. What suffers is the brand, along with the customer’s relationship with the manufacturer.
Even though all of these downsides exist, it is still the financial “lesser of two evils” to leverage sub-contractors and try to manage and incent them toward positive results. The most significant concern is sub-contractors that don’t share incident resolutions, as this prevents manufacturers from shortening the overall time to resolution for the customer and building the body of knowledge within the manufacturer’s organization.
The industry average indicates that 65% of product service calls into a service desk are covered by warranty, and therefore are a complete cost center to the manufacturer. Let’s apply some dollars and cents to that metric:
- Product service per-ticket costs often outstrip their IT service management (ITSM) counterparts by 2x. Industry average for an ITSM ticket is typically US$62.50, while a product service ticket is around US$120.00.
- For example, a mid- to large-sized appliance manufacturer sees upwards of 1M tickets per year total, and at 65% yielding no profit (covered by warranty), that would mean 650,000 are at cost.
- That means our appliance manufacturer is spending ~US$78M (650k tickets x US$120.00) servicing their product line, which has to get built back into the product cost, which in turn makes the product more expensive.
As you can see, this forces a manufacturer into a severe cost control posture in order to stay competitive.
Traditional Warranty Cost Control
There are two primary traditional strategies for applying cost control to warranty claims. One is pre-sale, and one is post-sale. The pre-sale strategy is a comprehensive approach that involves more cost-effective parts, more critical qualifications as to what is covered by the warranty, and new model release scheduling (which encourages the customer to upgrade before there are significant warranty claims). This approach has many benefits in addition to reducing warranty costs, but pre-sale is not really the focus of this blog series.
The second approach is post-sale and involves the handling of warranty claims submitted by those requiring compensation, usually a sub-contractor or a customer. This approach is primarily taking advantage of what is traditionally a financial-only process. By leveraging some manual or automated “stage gates” or validation criteria to the payout, the manufacturer can apply some cost control. Examples might include:
- Parts not matching work performed, or too many parts required
- Parts being ordered after work performed date
- Frequency of warranty claims exceed normal fail rates by n%
- Overall cost of repair out of band from similar repairs by n%
Unfortunately, at this point the only recourse the manufacturer has is to either not pay the claim (for an immediate cost control action), or to revise a process, part, or warranty coverage to protect from the anomaly in the future. This is a very reactive approach. The larger opportunity of applying a proactive approach, such as identifying and acting on historical trends hidden in claims data, slips by the manufacturer in the myopic financial-focused process.
In our next and final blog installment, we will examine how Artificial Intelligence can transform manufacturing customer support and warranty claims processes for the better.