In a previous post, we explained how the first stage of the Analytics Maturity Model, “Measure,” enables executives and front-line managers to obtain a quick, current status of the operational and business performance of their company.
The second stage of the Analytics Maturity Model, “Diagnose,” is where business leaders are able to visually interact and drill into their data to discover additional answers to questions that arose in the Measure stage, e.g., an increase or decrease in monthly revenue for a particular region.
Executives and other decision makers may also diagnose why an operational change occurred and examine the root cause of something that occurred.
For example, a product manager for a manufacturer of computer chips sees that a recent batch of chips has a 28% defect rate, an exponentially higher rate than the norm.
The product manager and other team members (engineers, quality control technicians) can drill down on the data to identify the source of the problem (equipment malfunction) and then use these insights to take immediate corrective action.
“Diagnose” can enable organizations to obtain answers to their most pressing questions. Marketing leaders can find out why a particular marketing campaign generated better-than-expected results.
The data may inform them that campaign performance was aided by a competitor that increased its prices during the same period. The data may tell the marketing leaders that the messaging used in the campaign resonated with the target audience.
Business leaders are able to obtain the answers they’re looking for during the “Diagnose” stage by seamlessly and iteratively interacting with the data.
The beauty of big data is that it enables front-line managers and other users to obtain a more complete picture as to why business or operational conditions are moving in a particular direction.
This includes the use of market data, financial and operational information, social customer sentiment, customer surveys, etc. Using a wide range of data sources enables decision makers to better diagnose what caused a particular business or operational outcome.
“Diagnose” is the stage of Analytics Maturity where analytics truly begins to stand out over the use of static BI (business intelligence) reports and spreadsheets. Understanding the state of the business and how it arrived there enables decision makers to look to the next step of Analytics Maturity, “Predict & Optimize,” to envision where the organization is headed and determine the best course of action.