Business AnalyticsIBM Software IBM SPSS Predictive Operational Analytics

IBM SPSS predictive analytics solutions for warranty claims Significantly reduce warranty costs, improve product quality and enhance customer satisfaction

For many companies, increasing customer expectations combined with advances in manufacturing and production technology have resulted in operational complexity. Manufacturers may lack the planning capabilities and resources needed to address these issues, which in turn can adversely affect product or delivery quality, leading to higher warranty costs—and ultimately a greater number of dissatisfied customers.

Warranty-related expenses can amount to anywhere from .5 percent to 7 percent1 of product revenue for large companies, so even small improvements in the warranty process can amount to millions of dollars in savings and lead to significant gains in profitability. Small and midsize manufacturers can achieve similar results. Many companies are also recognizing that their warranty programs can become important competitive differentiators that drive customer satisfaction and retention.

The warranty analysis process is typically the first post-sale interaction between manufacturers and customers, and can be a crucial first step in improving operational areas such as logistics, quality control and equipment maintenance. Warranty data provides valuable insights that enable companies to identify the root cause of a claim, such as whether it is a delivery or production-related issue. Analysis of a firm’s data may reveal that a defective part is responsible for a high number of warranty claims, and that the defect is actually the result of a production quality issue. Armed with this knowledge, the manufacturer can pinpoint the cause of the production problem and implement an appropriate solution, eliminating unnecessary claims.

Highlights• Determinetherootcauseofwarranty

claims.

• Proactivelyenhanceproductqualitywhilereducingwarrantycosts.

• Accuratelyprojecttheamountofwarrantyreservefundsrequired.

• Identifypotentiallyfraudulentwarrantyclaims.

• Detectandminimizeproductordelivery

failures.

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Business AnalyticsIBM Software IBM SPSS Predictive Operational Analytics

Figure 1:Thetypicalmanufacturinglifecycleconsistsofmultiplestepsandtouchpoints.Intheautomotiveindustry,forexample,asupplierpurchasesrawmaterialssuchasoilandleatherandmanufacturestheseats.Theseatsaredeliveredtotheoriginalequipmentmanufacturer,whichinstallsthemintheautomobile.Finishedcarsarethenplacedontotrucksfordeliverytoretaildealerships.Consumersareacruciallinkinthisprocess,becausetheinformationtheyprovideaboutdefectsordeliveryissuespostpurchaseenablesmanufacturerstoidentifyandcorrectproblemsattheirsource.

Predictive analytics—the proactive approach to warranty managementProactive warranty management requires powerful analytical capabilities. Today forward-thinking organizations are deploying predictive analytics to track and analyze all of the variables that can affect a product or delivery failure and the associated warranty costs, so that they can start the problem-solving process earlier than ever before.

IBM SPSS Predictive Warranty Analytics provides manufacturers with the tools to transform warranty claims data into actionable intelligence by integrating enormous volumes of structured and unstructured warranty data from

across the enterprise—including customer information, call center and technician notes and sales, performance and production data. Using a combination of forecasting, planning and predictive modeling capabilities, the software looks for patterns of customer complaints and delivery, product or part failures in real time, and then provides alerts about developing trends that may indicate a production or performance problem to the appropriate decision makers.

The warranty reserve funds of all U.S.-based manufacturers were $33.8 billion at the end of 2010.2

Raw Materials

Consumer

Supplier

Root-causeAnalysis

Warranty Analytics

Customer

Manufacturing

Distribution

PredictiveMaintenance

Product Quality

Analytics

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Business AnalyticsIBM Software IBM SPSS Predictive Operational Analytics

Quickly find and fix product failuresWith the new emphasis on controlling warranty costs, companies are struggling to understand and correct issues in the most cost-effective manner. IBM SPSS Predictive Warranty Analytics helps manufacturers identify a production problem early on by determining the root cause, calculating how much it will cost to fix, and then taking the appropriate steps to correct it.

When an automobile manufacturer learned that side mirrors were repeatedly breaking off, it turned to IBM SPSS warranty analytics solutions to resolve the issue. Using the software to analyze structured and text data from dealerships, the corporate website and social media sites, the company found that a specific machine used to manufacture the mirror sub-assembly had not been maintained properly and was producing low-quality parts. By making operational adjust-ments, the company eliminated the risk of producing future defective parts that could increase warranty exposure. What’s more, the company was able to notify customers who were likely to experience the failure but who had not brought their vehicles in for service yet, improving customer satisfaction.

In addition to ensuring product quality, IBM SPSS warranty analytics solutions can help reduce the costs associated with production line maintenance. By using predictive analytics to analyze machinery inputs and outputs, manufacturers can forecast when certain components or devices may break down or need maintenance, so that product quality is not affected and warranty claims can be minimized.

Toyota Motor Corp. paid approximately $4.2 billion in warranty claims in 2010.3

A premium automobile and motorcycle manufacturer with numerous production facilities worldwide set out to reduce error rates and repeat repairs by improving manufacturing and service quality. To accomplish this, the company needed an integrated view of production data, as well as data management and analysis capabilities. IBM SPSS technology provided the manufacturer with the tools to proactively identify systematic error patterns and their dependencies. The company was subsequently able to reduce warranty cases from 1.1 to 0.85 per vehicle and realized a five percent reduction in warranty cases, for an annual savings of €30m.

Detect fraud early in the warranty lifecycleAnother important benefit of IBM SPSS warranty analytics technology is that it helps manufacturers detect and minimize warranty claim fraud. In many cases of fraud, anomalies can be seen in data. But given the steadily increasing volume of warranty information, subtle patterns may be easily overlooked.

IBM SPSS solutions help mitigate losses from warranty fraud by enabling organizations to more quickly identify suspicious behavior within large amounts of data. By combining powerful analytical techniques with knowledge of the war-ranty process, manufacturing companies can recognize the characteristics or inputs that tend to increase warranty fraud, and use these insights to create an appropriate intervention strategy for each probable instance or type of fraud.

For example, an industrial products manufacturer using IBM SPSS warranty analytics software may notice a significant number of returns during the last week of each month for three consecutive months. Using the software’s anomaly detection capabilities, the company could analyze the quality technician’s logs in conjunction with production line information. This information may reveal that the parts in question left the production facility meeting all specifications, indicating that the returned parts either were not manufactured by the company or were damaged during the delivery process.

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Define optimal warranty terms and conditions Deciding what type of warranty policies to offer can be challenging for manufacturers, who need to create cost-effective policies that also satisfy customer expectations. A poor warranty policy can result in financial losses or even imply inferior product quality.

The warranty period for automobiles was 90 days in the 1930s and this has steadily increased over the years to 10-year warranty terms for certain models and parts.4

IBM SPSS Predictive Warranty Analytics can help organizations determine the optimal warranty term, based on cost, improving terms and conditions for all parties: customers, suppliers and manufacturers. By enabling firms to evaluate data on past and present claims, warranty writers can determine the most cost-efficient service and replacement guidelines.

Include warranty programs in customer satisfaction and retention strategiesIn a fiercely competitive global marketplace, many manu-facturers are beginning to view their warranty programs as more than just repairing or replacing defective products. They are recognizing that these programs can be valuable opportunities to build customer loyalty and enhance brand reputation.

As a premium manufacturer, The BMW Group aims to win customers over with innovative, original designs and quality, so it is essential to continually evaluate and assess its products and services and take customers’ opinions on board.

The company relies on IBM SPSS software to analyze data on vehicles and repairs, vehicle error memories and dealer feedback in combination with other information. What sets this solution apart is the fact that data is no longer considered in isolation, but in combination, providing completely new insights.

The results of the analyses and customer feedback are immediately channeled back into BMW’s working processes and distributed to a wide circle of users, helping the organization reduce error rates, save costs and improve customer satisfaction.

Business Benefits

IBM is the leader in predictive analytics solutions that help manufacturers:

• Identify and resolve delivery and quality issues earlier in the product lifecycle, leading to fewer warranty claims.

• Detect patterns of fraudulent warranty claim behavior and develop appropriate policies and controls.

• Improve customer satisfaction by offering more reliable products and more attractive warranty terms.

• Strengthen competitive advantage through more positive brand image, higher service levels and lower total cost of ownership (TCO).

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Business AnalyticsIBM Software IBM SPSS Predictive Operational Analytics

Drive deeper insights across the enterpriseIBM SPSS Predictive Warranty Analytics is the ideal solution for operations, engineering and financial analysts in automotive, industrial, retail, consumer product or other manufacturing firms that want to reduce costs and improve processes by getting to the root cause of warranty problems. It can also be instrumental in helping companies avoid customer service and brand reputation issues, and is useful as an executive reporting, forecasting and strategic planning tool.

Companies that adopt this solution will have the capabilities to build a successful warranty management program that allows them to:

• Reduce the costs associated with warranty claims.• Increase corporate agility.• Drive repeat business.• Maximize customer satisfaction.

By combining warranty analytics with other IBM SPSS Predictive Operational Analytics solutions, such as predictive maintenance or quality control analysis, manufacturers can extract even more value from their warranty programs. Products such as IBM Maximo asset management software and IBM Cognos business intelligence and financial performance solutions and dashboards can easily integrate with IBM SPSS solutions to provide companies with powerful tools to enhance business performance and outcomes.

About IBM Business AnalyticsIBM Business Analytics software delivers actionable insights decision-makers need to achieve better business performance. IBM offers a comprehensive, unified portfolio of business intelligence, predictive and advanced analytics, financial performance and strategy management, governance, risk and compliance and analytic applications.

With IBM software, companies can spot trends, patterns and anomalies, compare “what if” scenarios, predict potential threats and opportunities, identify and manage key business risks and plan, budget and forecast resources. With these deep analytic capabilities our customers around the world can better understand, anticipate and shape business outcomes.

For more informationFor further information or to reach a representative please visit ibm.com/analytics.

Request a callTo request a call or to ask a question, go to ibm.com/business-analytics/contactus. An IBM representative will respond to your enquiry within two business days.

Endnotes1 “Eighth Annual Warranty Report, Totals & Averages,”

Warranty Week, April 1, 2011, http://www.warrantyweek.com/archive/ww20110401.html.

2 “Eighth Annual Warranty Report, Totals & Averages,” Warranty Week, April 1, 2011, http://www.warrantyweek.com/archive/ww20110401.html.

3 “Toyota’s warranties & recalls,” Warranty Week, June 30, 2011, http://www.warrantyweek.com/archive/ww20110630.html.

4 Murthy, D. N. P. and Blischke, W. R., Warranty Management and Product Manufacture, Springer, 2006.

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Produced in the United States of America September 2011 All Rights Reserved

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