Traditionally, warranty management has been a type of quality assurance contract, between a company and a customer, to mitigate the risk of buying a product that might fail or not meet expectations. Whether a company produces software, medical devices, consumer electronics, automobiles, or toys, it is expected to stand behind their products and provide assurance to customers that quality, safety, and reliability will meet expectations for a stated or implicit amount of time.
When a product defect results in a consumer exercising a warranty, goods might need to be repaired or replaced— directly impacting a company's bottom line and brand image. Depending upon the effectiveness of an organization's warranty management program, this impact could be positive or negative. An alternative viewpoint, in a Warranty Week article (see Resources), suggested "Warranty is an opportunity for a company to listen to its customers, and improve the integrity of its brand image."
The shift in focus to a brand image and customer intimacy perspective provides insight into the IBM Smarter Commerce business model, which links marketing, supply chain, mobile commerce, social networking, and e-commerce efforts. Smarter commerce involves technologies that create a more knowledgeable and empowered consumer, whose needs and expectations stretch the capability of legacy solutions and measures of customer satisfaction. To address this change, a new, more holistic metric called the customer lifetime value (see Resources) can help companies better understand and quantify the long-term financial benefits of a customer relationship based on retention, historic spending, and future spending.
The more confidence a consumer has in the products and associated warranties offered by an organization, the higher the likelihood the consumer will be retained as a customer and the higher the customer lifetime value score. The challenge for many organizations is building the processes and the enabling technology platform to gain insight into their warranty program so that it can contribute to strong customer intimacy. Establishing such a platform is the core concept behind a warranty management platform based on a smarter commerce foundation.
In 2011, the International Data Corporation (IDC) proposed a warranty management capability maturity model to help companies develop a systematic approach for dealing with warranty management. This model is patterned after the well-known Capability Maturity Model Integration (CMMI) from the Software Engineering Institute (SEI). The warranty capability model contains maturity levels ranging from ad hoc (level 1) to optimized (level 5). Transitioning into the integrated (level 4) and optimized (level 5) maturity levels requires an organization to effectively use its structured and unstructured data. Let's look at how the model applies using an example scenario.
The scenario involves the introduction of a new model from an automotive manufacturer. Typically, the first direct interaction after the sale or lease transaction between the automaker and customers of the new model is a scheduled or unexpected service event. For an unexpected service event, service personnel will:
- Share information with the customer.
- Set expectations.
- Describe the work being done.
- Possibly explain the warranty coverage.
Technicians will also log vehicle data, and include their observations and conclusions regarding the root cause necessitating the repair. The technicians' notes might include:
- The transactional record of any parts ordered.
- The circumstances under which the warranty condition occurred.
- Descriptions of defective parts.
- Suggestions for how to avoid a recurrence.
- What to do if the repaired or replaced parts require future service.
Failing parts, assembly mistakes, or other costly initial quality problems typically take time to surface and become known to other areas of the manufacturing organization, thereby delaying the opportunity to take corrective action. When the problems gain visibility, it's usually the impact, and not the cause, that's first observed (because orders for replacement parts and assemblies are easily tracked within structured warranty and parts systems). What is not so easily identified is the reason for the failures. Technician troubleshooting and service notes are subjective, free-form text; they might have many variations to describe the same or similar problems. Effectively aggregating, and making sense of this information in context with the structured data, is necessary to truly understand whether a warranty problem is attributed to:
- A particular supplier.
- A manufacturing or quality process.
- Improper transport of vehicles to the dealerships.
- Any other possible causes.
Information recorded by mechanics will be useful the next time the vehicle is in for service, and it will help the dealership manage parts inventories. But, there is also significant opportunity for other participants in the manufacturer's network to exploit the information. For example, suppliers could be informed when a pattern of poorly performing parts begins to emerge, possibly initiating design or production changes. Dealers or manufacturing marketers may use the data to formulate a marketing campaign to encourage customers to take proactive action prior to a problem. Or, they could provide incentives of discounts or promotions to attract customers into their services departments, providing possible opportunities for cross-sell or up sell of additional accessories or warranty extensions.
There could be many reasons for the different results that companies see from their warranty management programs, but three things are clear:
- Effective warranty management has an impact on customer intimacy.
- The enabling capabilities of a warranty technology platform, using structured and unstructured data, determines the level of analysis and insight that can be gained and turned into actions.
- Customer satisfaction related to their experience has a direct impact on future revenues.
In our scenario, if a trend of service logs that mention improperly installed parts in the new car model is uncovered, the insight should be shared immediately with the manufacturer's assembly teams to make adjustments. Correlating and extrapolating unstructured data buried within free-form text can also be of immense value to the marketing function. Early awareness of defective vehicles lets the manufacturer manage customer communication, and proactively share with customers, suppliers, dealers, and analysts how the problem is being addressed. Managing the communication can help protect the brand's reputation.
Consumers commonly use public forums and user groups to comment on experiences with products, sharing positive and negative feedback directly with the world. It is essential that manufacturers monitor, and take advantage of, these sources for everything from ideas for innovation to customer sentiment and early indicators of quality concerns. Consumer input, along with the technician notes from service activities, can provide manufacturers with a truly inward and outward looking perspective. The more proactive a manufacturer can be in detecting and addressing quality issues early on, the better it can service and satisfy its customers and provide assurances that it stands behind its cars.
The most effective way to gain better control of warranty costs, improve product quality, and enhance reliability is to unlock the knowledge that's spread across all service, design, production, and warranty information. An optimal solution gives you visibility into all sources of valuable product service data, both internal and external, to get a clear, comprehensive view of the root causes, costs, and exposure from warranty obligations. This solution includes:
- Structured data traditionally housed in warranty management systems and accessed through reporting solutions.
- The handwritten notes from technicians.
- Problem reports and resolutions in emails.
- Customer feedback and complaints submitted in both paper and electronic format.
- Other unstructured data sources.
A predictive, analytic approach that can leverage structured and unstructured data, and provide necessary information to achieve desired business outcomes, is needed. Smarter commerce application software components from IBM can be integrated to provide this predictive analytic solution for warranty management.
Smarter commerce is all about redefining the relationship between suppliers, vendors, and customers in an integrated value chain supporting business-to-business and business-to-consumer interactions. As shown in Figure 1, an IBM Smarter Commerce soltuion value chain is comprised of four key business domains; buy, market, sell, and service.
Figure 1. IBM Smarter Commerce solution value chain
A smarter commerce approach transforms a company's management focus from customer satisfaction to customer intimacy and improved brand image. For warranty management, this means improving use of all available customer touch points—from initial investigations, to product sales, to service support for gathering information, to support analysis and actions.
A smarter commerce solution for improving customer lifetime value relies on a pattern-based design methodology. The process allows each company to tailor a solution that's developed and deployed to meet the constraints of their environment. Historically, pattern-based design has been the forte of software development, e-business, and service-oriented architecture. With Smarter Commerce, the focus moves toward integration of application software components versus the building of services and custom applications, as defined in Figure 2.
Figure 2. Smarter Commerce warranty solution architecture
In this transition, the basic definitions associated with patterns (see Resources) are preserved:
- Providing a solution to a common problem.
- Establishing a model or plan for guiding the making of things.
The elements of a pattern have also been retained as a type of pattern recipe, including:
- Name: Meaningful title related to solution pattern for future reuse.
- Business context: Clear articulation of the business problem that will be addressed by implementing the solution pattern.
- Selection guidance: Description of what conditions would exist for consideration of using a particular pattern.
- Solution architecture: Establishment of key functions that comprise the solution context from the IBM Smarter Commerce domains that fit the business context.
- Solution realization: Recommendation of viable application software technology components that satisfy the solution definition.
Table 1 shows the warranty solution pattern.
Table 1. Table 1. Warranty solution pattern
|Name||Warranty management pattern|
|Solution architecture||Integration of enterprise market management (EMM) and warranty management application software components (see Figure 2).|
|Solution realization||Identifies the technology options to implement and realize the solution. For an IBM based solution, this would include technologies from software offerings that include EMM, enterprise content management, and B2B commerce middleware.|
Armed with the smarter commerce warranty management pattern, organizations have the foundation to realize a platform that can help achieve their needs based on their environment.
The key attribute of the warranty pattern is to integrate the functions and capabilities delivered through enterprise marketing management (EMM) and warranty management application software components. This integrated solution enables the analysis and decisions that can positively impact the customer lifetime value score with an effective warranty management program. The rest of this section describes the application software component for EMM and warranty management.
EMM application software can help organizations to better understand and communicate with their customers. Effective marketing, in today's world, means maintaining a persistent and interactive dialogue with customers across the various mediums they're using (in-store, social networks, traditional advertising, and Internet). In our warranty example, this dialogue could be viewed in at least four contexts:
- Generating demand around initial purchases.
- Describing benefits of buying extended warranties.
- Promoting offerings and discounts related to additional purchases, accessories, or services.
- Proactively notifying recommended actions for the customer.
To provide structure for achieving this dialogue, IBM defined the EMM framework shown in Figure 3. The framework defines four functional areas: awareness, decisioning, execution, and operations. The functional areas can be integrated with capabilities in the buy, sell, and service domains of a smarter commerce solution to support a business strategy to improve the customer lifecycle value metric.
Figure 3. EMM framework
Awareness and decisioning are perhaps the most influential in deploying an initial warranty management solution. They are the cornerstones that provide the key capabilities of analysis and recommendations that an organization should consider for action.
- Awareness involves gaining insight and understanding of the customer's
behavior across multiple online and off-line channels. The insight
lets companies optimize their marketing approach. In an ecosystem
where the customer is at the center of activity, awareness supports
the research and buying processes for new and existing customers in a
way that creates a sense of loyalty. In all cases, awareness is gained
by integrating data from various sources so marketing professionals
can complete analysis and take proactive actions.
Recent influences on data sources that enable awareness are from the explosion of social media and geospatial services provided by companies such as Twitter, Facebook, and FourSquare (see Resources). These technologies empower consumers to provide comments and share information that's less controlled by the company and more by the perceptions, experiences, and interests of the community. Innovative companies are looking at ways to leverage this type of information to build predictive models from which marketers can receive automated recommendations on campaigns, products, and communication channels.
In our warranty case pattern, customer experiences communicated in blogs, tweets, and articles that might lead to warranty issues could be integrated with data received from traditional sources (service logs, customer service calls) to provide a more comprehensive and proactive interaction with existing and potential customers.
- Decisioning complements the outcomes from awareness. Decisioning
focuses on the capabilities and actions marketers can use to be
targeted and effective. To enable application software in this area,
you need to understand:
- Client behavior by segmentation
- Product offerings
- The most effective communication channels, at the right time, and in the way the customers want to receive information.
- Real-time key performance indicators (KPIs), such as sales, unique visitors, average order value, conversion rates
- Competitive benchmarking results
- Current and historical shopping interests
- Current trends
- Business rules
Consumers have a lot of warranty and customer service information available from blogs, articles, and third party services (product reviews, warranty rebates, and discounts). With today's application software, companies providing or supporting the products can also use this information. Successful companies will embrace these trends and find ways to perform analysis that leads to actions that ensure a positive customer lifetime value metric. With its Smarter Commerce portfolio, IBM provides a comprehensive solution with multiple technology entry points. IBM has industry leading products that cover cross-channel campaign management, digital marketing optimization, and web analytics technologies (see Resources).
Forrester Research defines case management as:
"…a semi-structured, but also collaborative, dynamic and information-intensive process that is driven by outside events and requires incremental and progressive responses from the business domain handling the case. Examples of case folders include a patient record, a lawsuit, an insurance claim, or a contract, and the case folder would include all the documents, data, collaboration artifacts, policies, rules, analytics, and other information needed to process and manage the case."
Individual instances of a quality or design failure are managed inside a case structure using the smarter commerce warranty pattern. Each occurrence that merits investigation instantiates a case. Depending on its severity, different domain experts might be assigned to investigate and resolve the matter. Potentially critical warranty patterns, for example, may be assigned to a team of product designers, process engineers, or quality and warranty specialists to research. Product management and perhaps someone from the risk area, meanwhile, can be alerted to the situation and remain informed as the investigation proceeds. All business interests are now represented in the process.
The case management solution included in the warranty management pattern unifies information, processes, and people to provide a 360-degree view of the case. In addition to content and process management, this approach relies on application software components that enable content analytics, business rule definition, case management, and predictive analytics. Those benefits provide increased insight, and prompter actions, for optimized customer lifetime value metric outcomes. As shown in Figure 4, the solution framework for case management is comprised of four functional areas: content analytics, rules engine, case management, and predictive analytics.
Figure 4. Case management solution framework
The smarter commerce warranty pattern is based on a case-driven quality process. Ideally, manufacturers will use all data at their disposal to identify quality issues in the early stages, or even predict failures before they arise, as shown in Figure 5. Content analytics involves:
- Analyzing and correlating structured data in context with unstructured data.
- Identifying patterns and anomalies that span beyond a single system.
- Developing rules that can automate appropriate actions to be taken.
Figure 5. Proactive detection of quality trends
Issuing queries against a database, or searching a content management system, can effectively support many information needs—if business users know what to ask. Similar to how traditional data mining can extract meaningful associations from databases, content analytics allows manufacturers to make correlations across a wide range of structured and unstructured data. Manufacturers can detect causal relationships, trends, and other valuable patterns that would remain hidden without a specialized set of capabilities.
Content analytics solutions can understand the meaning and context of human language, rapidly process information to improve knowledge-driven search, and surface new insights from enterprise content. For example, analyzing the often subjective repair notes from service providers in context with parts data, assembly history, cost data, technician experience, parts sources, customer discussion via social media, and other information sources can yield knowledge and trend information about why certain parts or models have quality issues. Automating the detection, and determining the most appropriate action to take based on these trends, are key to effective warranty management. They provide rapid insight into important relationships buried deep within the data.
Advanced text mining and analytic techniques are needed to:
- Link unstructured and transactional data.
- Account for different formats and linguistic inconsistencies.
- Find the patterns of greatest importance to the manufacturer.
The attributes of these patterns, such as frequency, cost, and impact, can then be used by the rules engine to automate assignment of the most appropriate response.
After exceptions or possible trends have been identified in warranty-related systems, the insight gained must be quickly made actionable based on rules that are consistent with a company's priorities, policies, and objectives. The priority of a warranty issue may vary by cost, complexity, risk, scope, or many other factors. Determining priority requires the application of rules with visibility across different data structures. For example, specific products or parts might need to be linked with historic and projected sales volumes, component and sub-component dependencies, and other data to respond appropriately.
A business rules management system (BRMS) with a robust rules engine is an essential technology within case management. It allows organizational policies (and the repeatable decisions associated with those policies) to be defined, deployed, monitored, and maintained separately from application code. A business rules engine enables flexible decision automation for applications and processes, such as warranty management, that are subject to complex, variable, and evolving business rules. The importance and priority of each matter can be dynamically determined.
Case management unifies information, processes, and people to provide a complete view of a warranty case. Encapsulating warranty-related activities into a case lets manufacturers:
- Leverage the expertise of subject matter experts.
- Automate decision processes wherever possible.
- Extract insight from the underlying causes of quality issues, thereby reducing the likelihood of their recurrence.
Often, rules and regulations mandate retaining a record of certain types of product and warranty-related communication with the customer, including internal documentation of the process by which similar situations were addressed. If litigation arises, such as a class action suit, failure to produce this electronic audit trail can result in huge punitive settlements against a manufacturer. A case management environment also helps capture industry best practices in frameworks and templates to empower business users and accelerate return on investment.
Thus, structured and unstructured content needs to be organized and accessible. Case participants should be able to quickly see the full context of each customer interaction and circumstance to determine the best resolution for the case (and for future instances with similar requirements). A primary enabling technology within case management is a content management platform that can retain, share, and leverage information from a variety of documents and information sources. Some information is unstructured data in documents that were either scanned or originated electronically. It also includes the human-centric knowledge extracted from email, social applications, the free-form notes of service technicians, and electronic and physical customer feedback forms. An effective content management platform lets knowledge workers access all available information and real-time expertise so they can make quick, and more importantly, right decisions.
For customer satisfaction and brand image, what's important is not the occurrence of an issue but how well a company responds based on their insight. A case management solution lets a company effectively interact with all stakeholders in a case, resulting in positive customer satisfaction and increased customer lifetime value metrics.
While it's important for the case team to identify the cause of a quality problem and define an action plan, the loop isn't closed yet. You must follow up on actions taken to measure their effectiveness and impact on future warranty costs. One can understand the benefits, opportunity costs, repeatability, and value of corrective actions by analyzing and comparing the resolutions of cases against their outcomes. Handling of warranty-related issues can improve over time, resulting in:
- Greater efficiency.
- Eventual reduced warranty expenses.
- Better addressing of customer needs.
Data collected within a warranty-related case is valuable for the resolution of an immediate quality concern. That data is also instrumental in forecasting cost implications and predicting potential areas for other, future failures.
Predictive analytics capabilities supplement the case management framework within the design pattern. They apply models to the structured and unstructured data across cases to detect additional opportunities to avoid quality problems and limit risk. The patterns it uncovers can prompt additional case-driven action, once again spawning collaborative, information-driven teams to find and resolve adverse quality trends before they become larger problems. Innovative predictive analytics platforms help manufacturers identify a production problem early by determining the root cause, calculating how much it will cost to fix, and then taking the appropriate steps to correct it. These platforms can also accurately project the amount of warranty reserve funds required, allowing financial controllers to plan better.
Using a combination of forecasting, planning, and predictive modeling capabilities, the software:
- Looks for patterns of customer complaints, and for delivery, product, or part failures in real time.
- Provides alerts about developing trends that may indicate a production or performance problem to the appropriate decision makers.
In addition to ensuring product quality, warranty analytics solutions can reduce 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 product quality is not affected and warranty claims can be minimized (see Resources).
Using a case framework for a warranty management approach allows organizations to respond more rapidly and effectively to quality exceptions. Using analytics to detect issues early on, and managing them through to their resolution with consistent, rule-driven handling, saves money and limits risk to a company's brand reputation. And the ongoing capture of the processes, knowledge, and experience to solve problems helps equip teams to resolve future cases progressively smarter and faster. IBM's warranty solution also lets management monitor case volume and track team progress relative to each case.
IBM's case management platform employs established capabilities from the WebSphere®, collaboration solutions, enterprise content management, and business analytics product families—delivered in a powerful, easy-to-use application. In addition to its inherent analytics, collaboration, rule and process strengths, the case platform offers a wide range of integration capabilities. Go to IBM Case Manager to learn more.
In this article, you learned about an innovative approach to improve the effectiveness of warranty management programs. The article explored how to improve the customer lifetime value score with a smarter commerce solution that enables analytics on structured and unstructured data. The analytics lead to recommendations and actions.
The solution pattern is based on an IBM Smarter Commerce framework, application software solutions, EMM, and warranty management. When combined, these components provide the core capabilities of awareness, decisioning, content analytics, rules management, case management, and predictive analytics. IBM has a full portfolio of services and technologies associated with EMM and warranty management that can help any company improve their customer lifetime value score through a proactive approach to warranty management.
Definition" (Ed Staats, Warranty Week, Jul 2007): Gives a market
research view of warranty.
lifetime value: Read on Wikipedia about the net present value of
the cash flows attributed to the relationship with a customer.
- "A Week to Remember: Warranty Capability Model Published" (Sheila
Brennan, Computerworld, May 2011): Explore the Warranty Management
Capability Maturity Model and get the details of the Capability Maturity
- Patterns: Applying Pattern Approaches: Read this part of the IBM
Redbooks Patterns for e-business Series to learn more about using the
patterns for e-business.
- "Tales From The Marketing Wars: Peter Drucker On Marketing " (J.
Trout, Forbes, Jul 2006): Read a commentary about marketing and
- "Geosocial and Location-Based Services are Taking Over in 2012"
(JD Rucker, Drivingsales, Nov 2011): Learn about the rise of geosocial and
location-based interactions between people and the businesses around them.
enterprise marketing management (EMM) solutions: Learn more about
EMM solutions, services, and products.
- IBM SPSS predictive analytics solutions for warranty claims :
Read how to significantly reduce warranty costs, improve product quality,
and enhance customer satisfaction.
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James Jamison is a technical sales executive in the Software Solutions group. He is responsible for the Smarter Commerce Solutions Architect team in North America. James has over 21 years of experience leading teams in the development and integration of product life cycle management and commerce-related solutions across the aerospace, defense, chemical, telecommunications, and transportation industries. James’ primary focus areas are smarter commerce, systems engineering, architecture Integration, pattern based engineering, and software engineering. He is an IBM Distinguished Engineer and member of IBM's Academy of Technology.
Chuck Snow, who has a background of nearly 15 years focused on content management, designs solutions to complex problems for customers in a variety of industries. As an Integrated Solutions Specialist, Chuck conceives opportunities for content management to support and extend the value of other offerings within IBM's Industry Solutions portfolio.