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    • Home
    • About
    • HR Offerings
    • ECG Leadership
    • Contact Us
    • ECG Clients Lists
    • Government Compliance
  • Home
  • About
  • HR Offerings
  • ECG Leadership
  • Contact Us
  • ECG Clients Lists
  • Government Compliance

Predictive Modeling & Data Analysis

Predictive Modeling 

Predictive modeling  typically takes the form of models that are used to drive better  decision-making.  They shape the background and develop fact-based  recommendations to address “business problems”.   These data points and  data patterns can identify strengths, weaknesses, opportunities and  threats (SWOT).   Employing transactional, demographic, historical,  text, economic data and statistical modeling (ANOVAs, MANOVAs,  Chi-Squares, Pearson’s R, Spearman Rho and regression analysis) enables  us to develop multiple factors and predict business outcomes with a high  level of statistical relevance, accuracy and business impact.

Often times, business problems include:

Attracting new profitable customers
Retaining and increasing revenue from existing customers
Transforming non-profitable customers into profitable customers
Avoiding Risks – financial, claims, fraud, collections, litigation and intellectual property compromises
Measure  and develop plans/methods to ensure operational efficiency, reduce  errors, costs and redundancy to enhance productivity, output and quality
Increase customer and employee satisfaction, loyalty and their ability to provide meaningful feedback
Resource Planning  - financial, people, material, knowledge structure and time
Human Resources Management – recruiting, staffing, retention, rewards, development, performance and culture 

Predictive Data Analysis includes:

Personal data
Business data
Social network data
Web behavior data

Leadership & Culture

The  overall arching umbrella to effectively employing and utilizing  predictive models and data analysis is to ensure an appropriate leadership mindset and the development of a metrics driven culture.


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