Businesses today need to constantly work on improving their products to have an edge over their competitors. To ensure this competitiveness, there needs to be a feedback mechanism where businesses interact with the users directly to gather first-hand feedback on their products. Continuous improvement is key to paving the way for consistency and growth in this hyper-competitive world. This not only gives insights into the product but also about its performance.
Many businesses consider warranty data a mere information about product repairs, replacements, and claims but, there is more to it. With data being collected at multiple touchpoints and constant interactions with the customer, there are vital signs that can help businesses understand product performance. This collected data has information about recurring issues, claims generated, replacements sought, customer complaints, feedback and much more. With such an ocean of cat information about the product, this can very well be a defining moment of the future of the product or even help brands rethink their product placement strategy.
For any product to perform well, it needs to be acceptable in the eyes of the customer. The customer gives the right feedback and that is the final word on its performance. Businesses, with the help of warranty analytics data, can get deep insights on issues and any upgrades customers are seeking out. With such analytics, they can also add new features to the product.
Warranty data is not just about the warranty claims but also about the product information such as identification with serial number, customer details with location and usage patterns, type of claim, and details of the issue or problems encountered by the customer.
Extracting Valuable Insights from Analytics
To extract insight from the data collected, businesses need to use analytics tools that help them gain information from the data collected. This process enables businesses to get better product information and ensure they can analyze trends and identify patterns through customer complaints or issues.
Let's see how exactly this information helps businesses:
Identification of Familiar Failure Issues
The data collected from warranty analytics can further enlighten businesses about any failures or issues that are most commonly reported and what parts or components are the most repaired or replaced. This would allow businesses to prepare and strategize accordingly to cater to these challenges and work towards improving or upgrading the quality of the causal parts.
Recognition of Patterns of Usage
Warranty analytics data shows analytics about the customer demographics and location which gives further details about the performance of the products in different environments. If a part or a component is failing or causing issues, businesses can check if it is caused by any environmental factors with the data available about customer demographics. This would enable the manufacturers to make decisions based on any regional factors and or work towards launching variants or versions catering to a specific region.
Design Flaws Are Detected Early
With the help of accumulated data from the warranty analytics, businesses can check for early signs of design flaws that could harm the product. We see a lot of products being recalled as they encounter design flaws. These product recalls are expensive and can result in losses to the manufacturer. Businesses need to be proactive in determining and identifying such issues to improve product performance.
Comparative Analysis of Design Change Impact
This data can be collected by comparing data from before and after design changes. Through the warranty analytics data, manufacturers can get better insights of both the product acceptance and performance in the market. This would pave the way forward for future growth if the product is accepted and is performing well and improvisations in the design or components if otherwise.
What Tools Can Manufacturers Use for Extracting Insights?
Now that we have understood the application of the warranty analytics data, we need to understand how businesses arrive at such a stage where these insights can be delivered. As we all know the data that would be accumulated through the warranty management process would be in the raw form and would need segregation and modeling, it becomes evident that there would be tools that can be used to perform such actions. Let us see what kind of tools can be utilized for the same:
Tools for Data Visualization
These are the tools that can help businesses work on complex data sets and help them transform such data into charts, graphs, and heatmaps. With such a representation, businesses can analyze trends and identify patterns.
Statistical Modeling
Any data makes more sense when there is a correlation between any factors, demographics or maybe features. This comparative analysis provides in-depth insights on product performance.
Using Data Mining Techniques
When using these techniques, it comes up with any relations with the data that were unknown or maybe overlooked. Such algorithms are useful when dealing with large data points and datasets.
Machine Learning
Machine learning is now one of the most sought-after technologies businesses are going for. This enables them to predict any future events based on the past data and throw light on any potential issues. This also helps manufacturers with proactive measures to control potential failures of components.
How Can Manufacturers Build A Data-Driven Design Process?
The analytics collected from warranty management is crucial in nature and this has been very evident from the points we have discussed so far. Post segregation, modeling, visualization and prediction of collected warranty analytics, we need to understand how manufacturers utilize this data to integrate with their design process. How can manufacturers implement their learning from the previous steps and ensure the product's success?
Let us see how:
Data Collection and Integration
To ensure that there is enough data for the manufacturer to gain insights from, there should be measures to collect enough data from every touchpoint. The data collection and integration have to seamlessly integrate into the databases of the product design to ensure access to and insights from the collected data.
Cleaning and Standardization of Data
The warranty analytics data would be accumulated in a raw state and would need to be cleansed. This cleansing process would ensure that the accuracy is impeccable and consistent. This consistency of the accurate data will enable manufacturers to analyze the data and get reliable insights from it.
Defining Data Analysis Goals
The manufacturers need to be clear with the goals. There needs to be a clear set of questions that the manufacturer needs to prepare to have the clarity they need from this activity. This could mean they would need to assess the outcome and what they want to do with this data. The ‘what’ and ‘why’ should be clear to perform the ‘how’.
Regulate Reporting and Analysis
The manufacturers need to analyze and assess the reports daily. This would mean they need to have a thorough analysis of the warranty data regularly. The manufacturer should also ensure that the reports that are being generated should be understood by all stakeholders in the design team.
Collaboration
To ensure maximum impact from the set processes of the data from the warranty analytics, there needs to be a collaboration between the data analytics team and the design team. The data analytics team needs to be an enabler that would provide insights to the design team. The design team needs to ensure that these insights are actionable and that every metric is being used to improve the product.
What are the Emerging Trends in Warranty Analytics?
Data is the new oil and it is rightly said that the next race is going to be all about data. With so many new technologies coming up, there is definitely a transformative power at play here. Image when warranty analytics comes to play. This would be a game changer for manufacturers and enable them to see better and further in the product life cycle.
Let us now dive deeper into the emerging trends in the field of warranty analytics:
Artificial Intelligence (AI)
Today, AI is at the center of everything! All we hear today has some other form of AI-infused in it. Any technology, data modeling and prediction is based on AI. So, the scope is unimaginable. This new-age technology brings forth a multitude of benefits for businesses and enables them to gather insights, and future predictions and analyze correlations between two data sets or even data points! With impeccable accuracy and compatibility with current systems and technologies, AI is going to be the most talked about transformation in today’s time.
Internet of Things (IoT)
With major transformations going on in the manufacturing sector, many of them are based on IoT. The transformative power of this technology cannot be overlooked as it can collect data from connected devices. This brings a plethora of opportunities for the manufacturing sector. Just imagine all the equipment from an assembly communicating with each other and that data acts as a single source of truth for manufacturers.
Natural Language Processing (NLP)
Natural Language Processing for manufacturers would mean getting better insights into the customer data and feedback pertaining to warranty claims. As a user experience-led practice, NLP leverages this warranty data to reveal insights about user experience and cross the boundaries of technical functionality to gain deeper insights.
Why do Manufacturers Need to Start Their Data-Driven Design Journey?
Today, the market is becoming fiercely competitive with multiple options for a single product. This market saturation has made the line of differentiation between products disappear and now it is often about the overlap of features. In such a scenario, the product details are something that would be the only differentiating aspect.
The data collected in the warranty management processes sets a strong tone for manufacturers to embark on a journey to leverage data. This would allow manufacturers to not use just guesswork and design products that are reliable and are built to enhance user experience.
Here is why manufacturers need to work on harnessing the ability of warranty analytics data to push forward toward a profitable future:
Reduced Warranty Costs
By using the warranty claims data, manufacturers can gain a deeper understanding of the scope of improvement in their products. This would mean their products would have higher quality standards which would mean reduced warranty claims. Such a practice would mean lesser costs diverted towards managing warranty and manufacturers can transform their cost-intensive warranty management to a profitable arm of the business.
Enhanced Product Quality
With products becoming similar, business is becoming more competitive. Manufacturers need to adopt ways to improve the quality of their product which would mean a greater acceptance rate among the customers. Leveraging data from the warranty claims would mean gaining insights into customer feedback about the product. This can enable manufacturers to build better-quality products.
Innovation at the Core
As manufacturers would have access to data from the warranty processes, they would be able to brainstorm new and improved ways to solve a problem. The teams would be better equipped with data and analytics, working to solve complex problems and predict future outcomes based on that data. This would also enable them to predict demands and keep a user-centric approach to their products.
Optimized Resource Allocation
With access to the data from the warranty processes, the manufacturer can understand which aspect of the product has a scope for improvement. This would also make them plan as to which product line needs more attention compared to others. Furthermore, this can empower a strategic team and resource allocation to collectively work towards improving the product. With such a strategic focus, the product will create definitive traction.
Our Final Take on The Topic
Warranty management has been a core process for all manufacturers since the time they have been producing such goods or services. But, the data part has often been ignored. With such immense potential, the data can be used for the amplification of profits. Enhancing user experience, product design and much more can be achieved through this process.
As a data-driven approach, it is based on facts and not guesswork. The data provides factual information about the product concerns and scope of improvement. Manufacturers can allocate teams as per the requirement and work on a solution. Greater focus and better strategy are just two outcomes that can be derived from the previous sentence but there is much more to accomplish by utilizing the data from warranty management.
It is more of an enabler to manufacturers than most of the processes today as this feedback is based on real-market user insights and highlights the actual issues that the end users face. The future has immense scope and can turn the warranty management processes into a revenue generation process with enhanced brand value and strong brand advocacy.
