What Does “Analytics” Mean?

Fundamentally, an “analytic” is any quantifiable informational input to an analysis.  “Analytics”, then, supports and enables analysis … and analysis is a very fancy word for pondering and hopefully solving a particular problem, or reach one or more conclusions.

The word “analytics” has become a prevalent marketing term among software vendors and services providers.  To many of them, “analytics” is another word for “business intelligence” – which is often another word for the three key technology genres most often associated with common reporting capability:  data warehousing, OLAP reporting, and ETL utilities.

We believe Enterprise Analytics, as defined by Henry Fleming & Company, is a more useful term.

Enterprise Analytics Defined

What does this have to do with my business?

A lot.  We analyze with analytics almost every day, in every department, at every level of the organization.

Simple Metrics

  • At a very basic level, we are using analytics when we use the insights gleaned from “key performance indicators” to make a business decision.
  • Leading companies are deploying central enterprise metrics management systems – comprised of consistent metrics frameworks across the organization, and enabling business intelligence infrastructure.

Segmentation

  • A more advanced application of analytics would enable us to categorize our customers in a way that would help us focus on the right customers – and perhaps help us turn more customers into the right customers over time.  For example, by deriving which customers purchase the most profitable products, we can categorize by unprofitable, profitable, and highly profitable.
  • Many organizations apply segmentation techniques – for example, using ABC analysis to identify high turn or high profit inventory in the supply chain.
  • Leaders segment high value candidates, employees, customers, products, vendors, partners, projects, and so on – and they refresh their analyses at high frequency intervals.

Optimization & Prediction

  • An even more advanced use of analytics would enable a bank to categorize a customer when she calls for service; deduce which products the customer is most likely to purchase; and subsequently route her call to the customer service representative who is a) trained in selling such products, b) has been most successful in selling those products, and c) is likely to be available within the next five minutes based upon his current modal call norm.
  • This kind of optimization  - an “advanced analytics application” – is what most people have in mind when they use the term “analytics” as opposed to business intelligence.  Leaders are investing to optimize as many decisional nodes as possible.  Many are realizing they lack the fundamental metrics necessary to support advanced analytics of this nature.

Enterprise Analytics Capability

“Enterprise Analytics Capability” implies a comprehensive analytical infrastructure and approach across the organization.  This means:

  1. A governance model and infrastructure exists which plans, deploys, and oversees the enterprise analytics capability.
  2. Metrics are standardized and governed across all business domains, entities, and roles.
  3. Business intelligence technology infrastructure is deployed as necessary to support base metric, derived metric, and index calculations – the vital inputs to advanced analytical techniques.
  4. Advanced analytical techniques, such as prediction and optimization, are being utilized to differentiate from competitors by, for example, rapidly identifying customers’ changing needs; rationalizing vendor utilization based on performance, and balancing workforce planning with projected demand.
  5. Discrete organizational roles or “personas” are accommodated with the specific information they need for their role – the right information available at the right time, in the right context.