At first glance, there’s not an obvious upside to warranty claims. For many manufacturers, they certainly represent an expensive headache. Research indicates that, on average, claims account for around two percent of product sales revenue. Beyond the immediate costs of rectifying faults and compensating customers, the long-term impact on corporate and brand reputations can be even more damaging. However, for all the negatives, warranty claims also represent a rich resource. Properly leveraged, warranty data can enable early detection of product failures and when integrated with design and internal quality data can reduce detection-to-correction (DTC) with a faster, more accurate root cause analysis (RCA).
Smart operations deliver data gold mines
Growing recognition of the value embedded in claims is reflected in the increasing sophistication and rapid adoption of warranty analytics tools by manufacturers in both consumer and industrial domains. And as with the smart manufacturing solutions that we’ve discussed in previous posts, there is typically no shortage of data for enterprises to draw on.
Traditionally, channel partners such as dealers and resellers have been the major source of claim information. Even this can involve a wide range of formats such as CRM and ERP system outputs, as well as plain text. On top of this, many manufacturers can now gather data downloaded by engineers during service and maintenance operations. Moreover, the latest generation of smart products provide a continual stream of information via the cloud.
The ability to wrangle all these potential sources of information and convert them into clean data sets that can be analyzed efficiently is fundamental to any effective analytics tool. At Altair, our solutions are defined by vendor-agnostic platforms that remove data silos.
Root cause analysis for warranty failure
What then to do with this information? Root cause analysis is perhaps the most widely recognized benefit. Leveraging an RCA warranty failure module that integrates design, internal quality and warranty data allows for analysis that traces problems back to basic design defects, raw material problems, build issues, or shortcomings in quality control. In fact, in today’s complex manufacturing processes, it is often a particular combination of factors that lead quality problems – not just one failure. As well as enabling manufacturers to address such failings at source, mining warranty analytics can also measure and monitor the success of remedial action. There’s a clear link here with smart manufacturing; warranty claim data can be combined with real-time information from the shopfloor to help enterprises increase effectiveness of monitoring and maintaining product quality and reliability.
A question of priorities
For consumer enterprises in particular, warranty claims can run to high volumes. Prioritization is therefore vital. At Altair, machine learning (ML) algorithms enable recency, frequency, monetary value (RFM) principles to be applied to vast data sets, identifying precisely where manufacturers need to focus attention to gain the most benefit.
Optimizing service pack and warranty design
Of course, an increasing number of manufacturers no longer look to just the products themselves to generate a profit. Instead, service offers and spare parts must deliver the return. However, designing service packs and warranty policies is a complex science. Successfully optimizing packaging and pricing can transform loss-making obligations into significant income generators. At the same time, customer loyalty and brand reputation can be strengthened.
Once again, Altair’s data analytics tools provide the technology companies need, in this case it’s for the constructing of offers that balance conditions such as exclusions and availability with pricing based on consumer willingness to pay rather than crude, cost-plus techniques. They can also support the growing need for warranty policies and service packs that are personalized to the needs and characteristics of individual customers.
It’s often said that the worst possible outcome in business is for an unhappy customer to stay silent. Only when shortcomings are highlighted can they be addressed. To stem serious long-term financial and reputational damage, and reap more profit from after-sales provision, manufacturers need to adopt this mindset for warranty claims. In the latest generation of warranty analytics solutions, they have all the tools they need to make the very best of bad news.
Interested in finding out more? Explore how to make the most of warranty data here: altair.com/manufacturinganalytics.