Develop a comprehensive understanding of your organization's Analytical Readiness



Our Maturity Grader is based on responses to three major assessment areas:

  • Data Management
  • Executive Support
  • Technology Adoption

We then consolidate these metrics into a final score which attempts to reflect a popular competency assessment proposed by Thomas Davenport and Jeanne Harris in their well-known book, "Competing on Analytics - The Science of Winning".  Their book describes the five stages of analytical comptency as follows:

  • Stage 1: Analytically Impaired - Lack of analytical skills or executive interest. 
  • Stage 2: Localized Analytics - Uncoordinated activities or silos.
  • Stage 3: Analytical Aspirations - Good intentions with slow progress.
  • Stage 4: Analytical Companies - Widely use analytics internally.
  • Stage 5: Analytics Competitors - Use analytics as a competetive advantage.



Based on your performance, our Suggested Action Plan Report is designed to help you:

  • Improve Data Management
  • Use analytics to Create Competetive Advantages
  • Increase Executive Support
  • Reduce Data Silos
  • Mitigate "report-and-forget" culture
  • Develop flexible data management processes 

How can any size business adopt some of these game-changing techologies?

Today, any company can easily access Business Analytics as sophisticated tools are becoming very affordable thanks to open source technoloy and increased adoption.

With the maturing of cloud computing, deploying solution is alos becoming less of a challenge.

Up until now, a central missing element was the expertise to build and manage complex models.  This is no longer the case, as our objective is to provide the necessary support.




A new trend has emerged in recent years based on the large amounts of data that continues to grow as a result of the rapidly declining cost of computer memory.  It should be no surprise that data-driven decision making works better than using managers’ intuition. Research clearly shows that analytics oriented organizations outperform their peers but making sense of the data becomes an increasingly challenging task.  A recent IBM CFO study shows that analytics-driven organizations had 33% more revenue growth, 12 times the earnings (before interest, tax, depreciation, amortization) and 32 percent more return on capital invested

This is where Business Analytics (BA) becomes handy providing data mangement, integration, multi-dimensional analysis, visual discovery, data mining, and predictive analytics to improve productivity in nearly every business function.

Business analytics is an all-encompassing name for a new discipline resulting from the integration of Business Intelligence and Predictive Analytics.  BA not only includes the classic Business Intelligence functions of reporting what happened, it expands to include drill-down to how it happened, finding out the cause of why it happened, and alerting management as soon as key metrics move in the wrong direction.

In addition, BA includes a highly sophisticated subject called Predictive Analytics.  It uses large cleansed historical data to look forward.  Specifically, Predictive Analytics finds patterns in data to forecast what has a high probability to happen in the future.

BA applications include operational intelligence, strategic and competetive analytics, customer acquisition and retention, risk management, fraud detection, and demand driven forecasting, among others.

Having a clear view of the profitable customers, products, regions, and market segements is fundamental to understand the causes and expand upon the successes.  Equally important is to find those customers, brands, markets, segments, and competitors responsible for draining cash and quickly stop the bleeding.

We hope you find this information helpful.