Quality screening in an information technology process

Abstract

Purpose

The purpose of this paper is to propose a methodology that may aid in assessing information technology (IT) quality characteristic optimisation through the use of simple and robust tools with minimal effort.

Design/methodology/approach

Non‐linear saturated fractional factorial designs proposed by Taguchi receive robust data processing by the efficient nonparametric test of Jonckheere and Terpstra.

Findings

The paper finds that e‐mail quality improvement is achieved by collecting data through an unreplicated‐saturated L₉(3⁴) design. Active influences are attributed to the e‐mail volume and the receiving hardware type.

Research limitations/implications

The overall efficiency of the method is greatly enhanced due to incorporation of a nonparametric analysis tool that is known to perform effectively when data availability is minimal. The method does not succumb to normality and multi‐distributional effects which may easily handicap the decision‐making process when derived from other mainstream methods.

Practical implications

There are obvious professional and pedagogical aspects in this work aiming at IT quality practitioners offering facilitation towards implementing robust techniques while suppressing quality costs. It is noteworthy that nonparametric data processing improves on the ability to make predictions over Taguchi's regular Design of Experiments (DOE) formulation for small sampling conditions.

Originality/value

This method embraces designing efficiency by non‐linear orthogonal arrays with multi‐level order statistics providing the weaponry to deal with quality optimisation in complex environments such as those in the IT area. The value of this work may be appreciated best by quality managers and engineers engaged in routine quality improvement projects in the area of information systems which also augments the general database of quality‐related testing cases.

Citation

Besseris, G.J. (2010), "Quality screening in an information technology process", The TQM Journal, Vol. 22 No. 2, pp. 159-174. https://doi.org/10.1108/17542731011024273