Gaining Competitive Edge with Connected, Data-Intensive Warranty Systems

Since raw data hardly serves any purpose, it needs to be analyzed. One of the biggest problems with the warranty business is huge quantities of data getting generated every second. This data, coming from various sources, needs to be analyzed. Data makes sense when channeled to specific points of input. Once the data is processed into actionable insights, business units can develop enough intelligence to improve the decision quality.

How intensive is data?

Data normally comes from business transactions and social media, besides other capture points like sensors. Ideally, reporting and analysis should match the speed at which data is being generated. Data proves useful when various thoughtful points are developed for it to be translated into effective strategies—through real-time knowledge of workflow and market parameters.

Data-intensive warranty management solutions                                              

The term data-intensive computing is used to describe applications that are I/O bound. Such applications devote the largest fraction of execution time to leverage the movement of data. They can be identified by evaluating “computational bandwidth”—the number of bytes of data processed per floating-point operation.[1]

Warranty management applications being conceived these days belong to that category and handle big data to help us understand the core problems. One of the most important goals of such technology is to reduce decision-making liabilities.

For good decision making, it is preferable to use data that covers a vast expanse of the warranty ecosystem and enables insights closer to reality. Without big data, quantity and quality of insights become limited to just some transactions and the immediate ecosystem. A warranty management application must be connected to the maximum possible data input points for the best possible analysis. The application should cover all possible operational, monetary, mechanical, and market-oriented data sources such as public records of other competitors, telematics, manufacturing methods, and customer touch points.

Gaining customer preference, cutting cost, and competitive edge

With the help of a connected, data-intensive warranty management system, it is possible to cut down costs. Once we have surrounded our system with a set of technologies to handle big data, and thereafter enabled warranty analytics, we are able to analyze the causes of product failures and make improvements—eventually cutting the cost borne during warranty services. Data and analytics also help us to predict optimal allocation for warranty reserves more accurately. This results in smoother business operation with accurate budget allocation.

Data-capture technology also let us implement customer service through faster electronic medium such as mobile apps and cut a great amount of service costs. In the long run, the right analytics platform helps us facilitating effective monitoring of all activities, including Claims registered per user, in real time.

With software improving real-time visibility into our ecosystem and customer-facing processes, the rate of success in decision making is growing manifold. It also helps us in identifying the genuine claims faster with more accuracy. Eventually, generating more values for customers by reducing the endless waiting time for the verification to be completed. The damaged parts can be tracked and recovered, if needed, using radio frequency. And therefore, the supplier performance can be rated accurately. Using such an approach, notifications are timely, allowing value chain partners to identify areas of improvement and realize more value. This helps in improving overall efficiency to bolster the bottom line for a business.

 


[1] Reagan W. Moore, Arcot Rajasekar, et. al., Data Intensive Computing, (Association for Computer Machinery Digital Library, 2007), Chapter 5.1.

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