Introduction: Data visualisation (DV) is the process of creating and presenting a chart given a set of
active data and sets of attribute and entity constraints. It rapidly and interactively
investigates large multivariate and multidisciplinary data sets to detect trends,
correlations, and anomalies.
Data Visualisation is the latest analytical tool for both technical computer users and
business computer users. Total Quality Management (TQM) is continuous
improvement in the performance of all processes and the products and services that
are the outcomes of those processes. In quality management, DV is one of the three
new tools that complement the existing seven, which are flow charts, Ishikawa or
cause and effect diagrams, Pareto charts, histograms, run charts and graphs,
scattergrams and control charts. It lets quality control engineers readily see the real
reasons for quality problems by presenting the data in up to six dimensions.
Methodology:
A survey by mail questionnaire was conducted to collect data from one hundred
Victorian manufacturing companies. Responses were received from 52 companies out
of the total of 100. The sample size for each analysis may vary from 52 to 49.
The source for company information was Kompass Australia 1994/1995. The
statistical analysis tool used was Statistica.
Major Findings:
The TQM program implementation tends to be more complete in companies with more
employees.
Wordprocessing software is adopted by all companies in TQM practice, mostly for
producing a quality instructional manual. Spreadsheet and database packages are the
second and the third most commonly used software.
Companies that have completed their formal TQM program implementation generally
use computer software in more aspects of their TQM practice than companies at lower
TQM stages though not always.
Two-dimensional DV techniques are more commonly used than three-dimensional
ones with the 2-D colour and 2-D shade the most widely used by all. The 3-D
animation tool needs to be explored.
DV features are generally important for all the users. The ability to handle complex
data is more important for companies at a higher stage of TQM program
implementation than companies at lower stages.