This page maintains references to different case studies contributed or referred to by Decision Management practitioners.
- Credit Card Application
- Mortgage Recommender
- Hotel Booking
- Weight-based Record Matching
- Predictive Analytics in Retail
- Diabetic Patient Monitoring
Case Study “Credit Card Application“
|This study provides a working example of decision modeling using the new Decision Model & Notation (DMN) standard along with BPMN 2.0. The example explains how to model business decisions behind a typical credit card application||Nick Broom||open|
Case Study “Mortgage Recommender“
|This study takes an end-to-end approach to the craft of designing and implementing a decision application using state-of-the-art standards. Using the complex-enough problem of Mortgage Loan Recommendation as the story board, the problem is represented as a Business Process using the BPMN 2.0 standard, utilizes the new Decision Model & Notation (DMN) standard for representing decision logic and finally implements the decision with the OpenRules® BDMS||
Case Study “Hotel Booking“
|This sample application is for a hotel chain that is building its reservation system and wants to provide its clients with an application to search for and book rooms. The owners of the hotel need to define various business policies to calculate booking rates, such as early booking discounts or last-minute offers. They may need to modify these policies to adapt to different travel seasons and exceptional events, for example. They may also want to add more policies in the future on special offers or loyalty programs. To accomplish all this, the authors use Node.js and IBM Bluemix platform to build the proper Rules service.||open|
Case Study “Weight-based Record Matching“
|This case study has been discussed and implemented in this LinkedIn Discussion. The decision model is about weight-based record matching. A step in a process tries to find the best matching record (in a database with many records) to an incoming request. The matching is based on weight. Different fields (match criteria) have different weights, and the match weight is the total of the weights of all matching fields. Two Excel-based implementations are provided.||open|
Case Study “Predictive Analytics in Retail“
|The case of online retailer Flipkart.com to explain the process required to implement a predictive analytics project.Problem Identification: translating the business challenge into a “precise predictive analytics formulation” with measurable outcomes.
Measurement and Data: determining which measurements are of interest and can be applied. Considering how to access sufficient data and integrate data from multiple sources, focusing on the end goal of the analysis and potential insights rather than the quantity of data. Once assembled, the data set is randomly divided to test the model before deploying the model on completely new data.
Model: the model is built by trying different algorithms and models to search for patterns and correlations in the data, using various ‘data mining’ techniques and methods from artificial intelligence, statistics and other disciplines.
Deployment: adjustments may need to be made as new factors emerge during the deployment, but when the predictive algorithm is deployed, it will generates a probability for new customer interactions etc.
Case Study “Diabetic Patient Monitoring“
|This case study presents a rule model for assessing the risk for diabetic patients. The focus of this case study is on detecting and correcting errors of ambiguity and incompleteness in the rule specifications.||open|
Adding Your Case Study
Everybody may submit new case studies and suggestions for the modification of the existing models. However, only original authors of the decision models will be able to make changes and for keeping models up-to-date. To add a case study please submit your request and you will be contacted ASAP.
The URL with a case study description may refer to your website or you may send us your case study in a PDF format and we will safe it on this website.
Note. If you contribute a case study to this Community website, you will retain all IP rights and will be solely responsible for correctness of the provided information and indemnify the Decision Management Community and its Affiliates from any potential claims.