Leaderboard

Diagnostic Analytics is one of the data analytics techniques that analyses a dataset to arrive at root causes of events, behaviours, and outcomes. It is primarily conducted to provide insights on various factors that are responsible for a problem at hand and tends to uncover the “WHY” behind the data. The data source, quality and reliability is paramount while conducting a Diagnostic Analysis. Diagnostic Analytics primarily represents the Current State in a problem-solving domain which connects the dots between Descriptive Analytics (what is wrong?) and Predictive Analytics (what is likely to happen?). The findings of these provide further insights on Prescriptive Analytics (Future Course of Action). In a DMAIC framework of six sigma, maximum value can be derived from Diagnostic Analytics in the Analyze phase. Examples & Use Cases: RCA Techniques: 5 WHYs & Pareto analysis to find out of the root cause - For e.g. A 5-why analysis revealed increased usage of UPI transactions to be the root cause of CASA ratio decline in a leading bank. A pareto analysis showed that discounted products which correspond to 20% of the overall merchandise are contributing to around 80% of the sales. Clinical Diagnostic tests use patient's tests results data to generate a complete summary based on the insights derived post comparing it against the standard and also against patient's past data. The physician in turn could do RCA to derive meaningful conclusions as to why this is happening. Hypothesis testing: To test an assumption that better wages outside is contributing the most to the attrition in a leading organization. A sample of exit interview data was subjected to a statistical test (1 proportion test). The test result was found to be statistically and practically irrelevant and rejected the assumption. Correlation & Regression Analysis: Many stock broking platforms have built-in algorithms based on pattern recognition, correlation & regression analysis to derive meaningful conclusions so that their investors can make informed decisions. Anomaly Detection: Network analysis make use of built-in control charts to detect any anomalies that may shed further light on the assignable causes of frequent downtimes and network jams.

A very straight forward question after a long time Pradeep Kandpal has provided the best answer to this simple question. Well done!

I have been compiling a comprehensive list of contemporary methodologies for Business Transformation. I started this in the year 2005. Over time, I have made several modifications to ensure the list covers all established and emerging approaches. To ensure the list was inclusive, I deliberately avoided methodologies limited to a specific industry, such as enterprise architecture, or those useful only for a particular function, such as Customer Relationship Management. I also tried to avoid subsets, for example, by recognizing that BI is already part of Business Performance Management. Currently, the list includes ten methodologies that have proven to be effective across different industries and functions. These are - Lean Management Lean Six Sigma DMAIC or Six Sigma DMAIC Six Sigma DMADV Agile Leadership Digital Transformation (includes Business Analytics and Big Data) Business Performance Management (includes BI) Design Thinking Theory of Constraints Creativity and Innovation (includes product innovation, process innovation, business model innovation, and marketing innovation) Business Process Reengineering (BPR) I propose that we collaborate on developing this list by discussing it together. We can explore whether there are any reasons to modify, enhance, or change it based on our collective insights and expertise.