Welcome and Introduction

This chapter gives you an overview of PIM DEASoft-V3 and what it offers
 
 
 
Welcome and congratulations on acquiring the third version of Performance Improvement Management (PIM) DEA software.
 
This advanced DEA software builds on the previous versions of our DEA software to enable you to make the best possible analysis of your data, using the latest theoretical developments in Data Envelopment Analysis (DEA).
 
DEA is a method of producing a relative aggregate performance measure where there exist sets of organizational units which have multiple ‘inputs’ and ‘outputs’. DEA is all about finding a frontier from the input-output data which shows the best level of performance that is actually feasible.
 
If you are new to DEA you could familiarize yourself with the basic concepts of DEA by reading any textbook covering it, e.g. Thanassoulis (2001).
 
If you are familiar with DEA and want to read about more recent developments in the area you could consult Thanassoulis et al (2008).
 
Extensive bibliography on DEA is available also at http://www.deazone.com/books/DEA-socioEcoPlanning.pdf  and information about DEA and its application can be found at Ali Emrouznejad's Data Envelopment Analysis Homepage (http://www.DEAzone.com)
 
 
PIM’s DEAsoft-V3 software gives you the capacity to assess efficiency and productivity, set targets, identify benchmarks and much more allowing you to truly manage the performance of organizational units.  You can also use the software away from organisational units to make choices between multi-attribute alternatives e.g. see:
A. Papagapiou, J Mingers and E. Thanassoulis, (1997) “Would you buy a used car with DEA? Applying DEA to purchasing decisions”, OR Insight, Vol 10, No 1, pp.13 - 19.
 
PIM DEASoft-V3 is easy to use and powerful. It has an extensive range of the most up-to-date DEA models and it can handle large sets of data.
 
 
With PIM DEASoft-V3, you can easily handle most tasks such as:
 
  • Assessment of units under constant or variable returns to scale;
 
  • Assessment of units under non-increasing or non-decreasing returns to scale;
 
  • Assessment of units with restrictions on the input /output weights;
 
  • Estimate performance targets with varying priorities over the improvement of inputs  and outputs;
 
  • Assess some units when some variables are exogenously fixed and returns to scale are variable;
 
  • Assess the super efficiency of units, including automated identification of units above a user-specified efficiency threshold, their removal and re-assessment of the remaining units;
 
  • Identify whether increasing, constant or decreasing returns to scale hold locally for units efficient under variable returns to scale;
 
  • Compute Malmquist productivity indices and their decomposition into boundary shift and efficiency catch-up. Boundary shift can be identified both under constant and variable returns to scale;
 
  • Compute Cross-efficiency matrices using optimal weights of selected units to compute the efficiencies of other selected units.
 
With PIM DEASoft-V3 you can produce a variety of results including:
 
  • Tables of efficiencies;
 
  • Tables of Pareto efficient input-output levels for assessed units;
 
  • Tables of benchmark (efficient) units for each inefficient unit to emulate;
 
  • Tables of input - output weights to estimate their marginal rates of cross substitution;
 
  • Summary statistics (mean, variance, maximum, minimum etc) of efficiencies;
 
  • Production Possibility Set (PPS) chart for visual assessment when the number of inputs and outputs permits it.
 
 
All reported results can be:
 
  • Exported directly into Excel, Word, PDF, HTML format;
 
  • All graphs can be saved as images.
 
 
PIM DEASoft-V3 can handle large sets of data including:
 
  • The use of Excel to import data;
 
  • The use of data files formatted for input to PIM DEASoft-V2;
 
  • The use of categorical variables to select subsets of units to be assessed by a given DEA model in batch mode;
 
Multiple DEA models can be set up, involving different input and output variables from a global data set to be executed in batch mode.