Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    How Data Analytics Is Reshaping Patient Financing Decisions
    How Data Analytics Is Reshaping Patient Financing Decisions
    13 Min Read
    business using business intelligence
    How to Use a Competitive Intelligence Dashboard to Turn Market Data Into Smarter Marketing Decisions 
    9 Min Read
    unusual trading activity
    Signal Or Noise? A Decision Tree For Evaluating Unusual Trading Activity
    3 Min Read
    software developer using ai
    How Data Analytics Helps Developers Deliver Better Tech Services
    8 Min Read
    ai for stock trading
    Can Data Analytics Help Investors Outperform Warren Buffett
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Designing and implementing a web-based warranty system
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > CRM > Designing and implementing a web-based warranty system
Business IntelligenceCRMData MiningPredictive Analytics

Designing and implementing a web-based warranty system

JamesTaylor
JamesTaylor
3 Min Read
SHARE

Copyright © 2009 James Taylor. Visit the original article at Designing and implementing a web-based warranty system.Frank Kozlowski of Kohler presentedf on a web-based warranty system. When they set out to develop the system their goals were to move to a start-of-the-art, easy to use system that was web-based so dealers could enter claims directly […]


Copyright © 2009 James Taylor. Visit the original article at Designing and implementing a web-based warranty system.

Frank Kozlowski of Kohler presentedf on a web-based warranty system. When they set out to develop the system their goals were to move to a start-of-the-art, easy to use system that was web-based so dealers could enter claims directly anywhere in the world (they have 12,000 dealers). They wanted to reduce their cycle time from claim to warranty (from 15 days to 1 day) and improve their data accuracy by getting data entered directly. Finally they wanted to prevent fraudulent claims. The system also needed to minimize the use of programmers when administering the system. At the same time it had to handle multiple policies, implement complex payment rules and support multiple languages. Finally it needed to support their short and long term business future – new products that might be implemented. Their solution was to select the Snap-On solution.

Key learnings from the project:

More Read

Actionable Information Management Principles: The Reality
socialytics (so-shel-lit-iks) – the Holy Grail of social media
Targeting readers who hate my book
Similarities and Differences Between Predictive Analytics and Business Intelligence
Quest for knowledge
  • Understand and document the process you have and the process you want.
    And I would add that you should make sure you will be able to change the process yourself
  • You need to focus on data conversion – cleansing, integration, how much history and so on. When to convert, where to store it, how will you use historical data (for quality for instance)
    I would add that rules-based data cleansing and conversion can be very effective.
  • New systems have new fields and your historical data will not have values for these fields – you will have to do some intelligent selection of defaults
    Of course you can use rules to set these values too if you don’t want to use the same value everywhere.
  • Figure out the kinds of reports you need, and who can produce fixed or ad-hoc reports, and what that means for your data
  • Quickly identify your “misses” – because there will be some. Poor communication is the biggest problem
    Of course, if your solution has rules and workflow engines that allow you to make changes then you will be able to rapidly evolve the solution even if you do “miss” originally

I haven’t had a chance to see the Snap-On solution yet but it looks like it uses policy (rule) and workflow engines that allow non-technical users to evolve the product.

Previous


Link to original post

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Operational Data Becomes Business Value in the Age of AIoT
Operational Data Becomes Business Value in the Age of AIoT
Big Data Exclusive Internet of Things
ai for social media
How AI Helps Businesses Get More From Social Media
Artificial Intelligence Exclusive
How Data Analytics Is Reshaping Patient Financing Decisions
How Data Analytics Is Reshaping Patient Financing Decisions
Analytics Big Data Exclusive
AI driven big data company
How AI-Driven Workflows Are Changing the Way Companies Think About Data Risk
Artificial Intelligence Data Management Exclusive Risk Management

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

CIOs Need to Make Information Management a Real Priority

6 Min Read

Three Ways to Get Your Predictive Models Deployed

10 Min Read

Search map: interactive visualization of query clusters

1 Min Read

Relying on Data Can Lead to the Wrong Decisions Says CFO.com

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?