Software Tools

ProAptive Metrics Analysis Software

ProAptive Metrics Analysis Software enables the user to improve performance by analyzing performance data appropriately so that the correct decisions are made to support an effective strategy for performance improvement. Our data analysis software is unique in that it is not only user friendly, but will guide the user into selecting the correct data analysis method and automatically suggests the actions to be taken to improve performance.

“Incorrect data analysis begets incorrect decision-making, poor leadership due to tampering, which all cause poor performance and sub-optimized financial results.”

Origin

This data analysis software was designed and mathematized by Heero Hacquebord. It has a successful history in use by Apt Leadership clients, and was researched and conceived over a period of 30 years consulting and training. Scores of statisticians and data analysis professionals have tested and used ProAptive data analysis in their professional and leadership applications.

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Description

ProAptive Data Analysis Software enables effective performance improvement through:

  1. Correct data analysis method that drives continual improvement.
  2. Continual improvement decisions that are superior to many traditional data analysis methods.
  3. Analysis of all types of data.
  4. Correct data analysis; by not incorrectly assuming that your data is a “normal distribution”, as most other data analysis methods do.
  5. Analysis of certain data types for which no other data analysis control charts could be found.
  6. Automatic narrative analysis of your data, explaining what action to take to improve performance.

An example of how our Data Analysis Software is able to create accurate and reliable data analysis

The control chart shown in figure 1 is one of the 7 control charts that our data analysis software uses to ensure correct analysis of all data types. This particular control chart is used specifically for analyzing rare events such as; accidents, defects, errors. In this example we see why ProAptive is the correct data analysis software to use if we want to make correct interpretations and decisions:

  1. The data is not a normal distribution; in fact it is a skew poisson distribution. Notice that the control limits are therefore not symmetrical. ProAptive adjusts the control limits based on the skewness of the data. Symmetrical control limits in this case would not render accurate and reliable analysis of the data.
  2. Because the number of man hours worked obviously affects the number of accidents, ProAptive calculates, plots and analyzes the statistically adjusted number of accidents based on the man hours worked. ProAptive uses standard statistical theory to adjust the number of accidents based on the variation of the man-hours worked from month to month. See row R4. To plot and analyze the actual number of accidents would be incorrect, because the opportunities (man-hours worked) vary from month to month.
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Figure 1: Statistical Process Control Chart for Accidents in a Manufacturing Plant