Predictive Analytics

INCREASING LIFTS BY 10-50%. REALLY. (2 minute video)

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INCREASING LIFTS BY 10-50% PERCENT.

IT'S TIME. (INTRO VIDEO.)

THE LIMITATIONS OF CONVENTIONAL  APPROACHES

PREDICTIVE ANALYTICS USING DECISION SUPPORT ENABLEMENT (DSE)

THE PHASES and STEPS

OF A DSE PREDICTIVE ENGAGEMENT

KEY BENEFITS

EXAMPLE CLIENTS

CONTACT / QUESTIONS

VIDEO

CENTER

CONSULTING

PLATFORMS

SOFTWARE

SOLUTIONS BY INDUSTRY

THE LIMITATIONS OF CONVENTIONAL PREDICTIVE ANALYTICS APPROACHES

Conventional "best practice" consulting approaches) to predictive analytics demonstrate one or more of the following limitations:

 

  • The data collected is incomplete or inadequate. The datamart:
    • Lacks important predictors especially
      • Critical behavioral predictors from behavioral tracking (new generation phone app capture)
      • Attitudes that drive behaviors
    • Needs desperately to be cleaned!
  • The datamart itself (whether in the cloud or not...)
    • Is legacy (but has important information within it.)
    • The solution is NOT to rebuild it...though your consultant salivates at that idea!
  • The modeling effort:
    • Is from the last century.  On average the typical DB analyst only builds a dozen models per week.
    • Doesn't build a solution space of all possible models and data transforms.
    • Doesn't  have hundreds of algorithms to choose from.
    • Doesn't  have dozens of validation tools to choose from.
    • Doesn't  automatically produce a model "assembly line."
    • Doesn't  build and test millions of models per week.
  • The modeling hardware:
    • Doesn't operate at the lowest computational cost (dollars per model run.)
    • Doesn't securely harness idle computational cycles in hundreds of computers on your corporate network to form a virtual supercomputer.
  • The consulting firm :
    • Imagines that they are your equity partner - and charges you that way.
    • Gives you the fish (the answer)...but not the pole (the Ultra-High Performance Data Mining System.)

REINVENTING PREDICTIVE ANALYTICS USING

DECISION SUPPORT ENABLEMENT (DSE)

What if you could leap-frog the limitations listed above by:

 

  • Upgrading your datamart INNOVATIVELY and INEXPENSIVELY by backfilling missing predictors such as:
    • Critical behavioral predictors from (new generation phone app capture)
    • Attitudes that drive behaviors (via AIM: Attitudinal Imputation Modeling.)
    • NOT Rebuilding it, but by building a LOW COST, PARALLEL MODELING MART (Via  inexpensive RAPID EXTRACTOR middleware.)
  • Using a New Generation Big Data Modeling Platform ( BigDataSolve ). BigDataSolve:
    • Builds a solution space of all possible models and data transforms.
    • Has a library of hundreds of algorithms and sub-algorithms to choose from.
    • Has a library of dozens of validation tools to choose from.
    • Creates a solution space of hundreds of millions of models.
    • Automatically builds and tests millions of models (via a model "assembly line".)
    • Securely creates a virtual supercomputer (by harnessing idle computational cycles on your corporate network.)

 

And... What if the consulting firm who provides this capability:

    • Charges one-third the cost of standard, low-performance consulting?
    • Delvers not just the "fish" (the answer) but also the fishing pole (the Ultra-High Performance Data Mining System)  when the project is over?

 

Decision Support-Enabled Predictive Analytics achieves all these outcomes and more.  The result? Far higher predictive lifts....at a far lower cost.  Delivered you way.  That's enablement.

PHASES AND STEPS OF A DSE PREDICTIVE ANALYTICS ENGAGEMENT

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KEY BENEFITS (Place your pointer over the benefits to see the short description.)

EXAMPLE CLIENTS

Retail Banking

We have deployed predictive analytic studies for many of the top 20 U.S. and Canadian banks.

Learn More

Healthcare

We have deployed a modest number of predictive analytic studies for large regional healthcare companies.

Learn More

Retail Banking

HealthCare