Data Analytics: - Analytics Cycle III to V: Case Management, Analytics Review and Optimization

After all the analysis confirmed with the proper analyzable data set, we would then come to the step 3: - Case Management to manage and execute the follow up actions identified from the insights produced; step 4: - Analytics Review to review the effectiveness on the identified Analytics Rules and suggest improvements; step 5: - Optimization on executing the improvements to make the process be more efficient and effective. 

These three steps are critical to the Analytics Cycle as:

A.    Case Management is to manage and execute the follow-up actions from the analysis insights which are always help to continuously improve and contribute the actual business. 

B.     Analytics Review is to monitoring the progress and the performance of every single step on case execution; and to identify the best way to resolve the issues when applying the theoretical analytics ideas into the real business.

C.     Optimization is to execute and test the suggestion identified and, more importantly, to help on smoothing the case execution and to improve its’ effectiveness and efficiency.

These three steps are highly dependent with each other and might require to move back to step 1 or 2 if further data needed or fine-tuning the analytics rules when executing. On one hand, step 4 is mainly relies on the data produced from step 3 and, on the other hand, step 4 and 5 would potentially speed up and also help to improve the case execution process in step 3 and, more importantly, to improve the entire analytics project become more efficient and effective. 

Example on the e-Discovery process, after step 1 – ETL on loading all the acquired data into the system and step 2 – Analytics Rules to identify the right screening criteria, included, but not limited to, keywords list, time period filtering, etc.  We would then move forward to review and tag the hit items with proper step 3 – Case Management process; and could analyse the effectiveness and the performance of the works with step 4 – Analytics Review, such as reviewing the periodic progress report to understand the efficiency of the reviewers for management purpose, to identify the keywords’ performance, etc.  On applying step 5 – Optimization, one idea is that if a keyword always produces non-relevant hit, we could then leverage the sampling approaches rather than full-review on the related hit population which would potentially speed up the review process.  If you are interested in how we could improve the e-Discovery process, please be patient and I would share more possible analytics on e-Discovery process in the future e-Discovery related post.

In conclusion, here comes the end of the Analytics Cycle overview.  This is only one of the general flows on how Data Analytics and the Big Data approach could be applied.  But again, it always requires times and money investments to produce profitable and adorable result. In the future data analytics post, I would try to share some of the real-life analytics examples.  Hope all of you found this useful and I would be always happy to discuss if you are interested.  

Previous Step