Profit Environment

"Profit Environment is to our knowledge the only existing system able to calculate the present and future impacts of Human Factors upon your profits in dollar terms."

The Research behind Profit Environment

The PROFIT ENVIRONMENT CALCULATOR FUNCTIONS shown on dashboards and dollar value/ cost reports are developed (with permission) from the survey items used by Maister (2001), whose sample sources are described below. PROFIT ENVIRONMENT survey items are also informed by studies by Gallop (Buckingham & Coffman, 1999), Shea & Olsen (2004) and various others.


The research shows that the ratings by staff of the quality of product-and-service experienced by clients is the most direct and powerful Human Factors predictor of future financial results. This makes sense because this is the only aspect of the 'Profit Environment' of an organization that a customer directly experiences. It is also interesting because it reveals that staff do have a valid perception of the quality of products and service that their customers actually get.

It also shows that great client service is itself a product of other things. It is delivered by people who have already been energised to deliver it by the skills and behaviour of direct supervisors. The research shows that financial success is not a property of firms (the systems of the business as a whole) so much as a product of the personal behaviours and relationships of the individual manager within each operating unit.

Maister reports that the most financially successful operations "share a number of characteristics":

FPI Calculation and Structural Equation Modeling (Causal Modeling):

Four measures of financial performance were obtained from each of the offices studied (Column 1 below). These were combined through factor analysis into a single financial performance score (FPI).

Elements of the
Financial Performance Index (FPI)
  % variation in FPI that can be
explained by each factor (R-squared)
Two-year percentage growth in revenues .27
Two-year percentage growth in profit .81
Profit margin .24
Profit per employee .53

All FPI correlations are significant at the 0.01 level, as are the Goodness of Fit Index, Normed Fit Index and Comparative Fit Index in the causal model. This is the most rigorous significance level used by statisticians, indicating a less-than-1% chance that the findings are the result of chance.
       Structural Equation Modeling (also called ‘Causal Modeling’) is a method for testing whether variables have causal (rather than merely correlating) relationships. A computer program (AMOS) tests the degree to which the proposed path diagram is supported by the actual data. In this case the causal model is displayed by the interrelated movements of the dials on the PROFIT ENVIRONMENT dashboard.