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n South African Journal of Industrial Engineering - Can complexity analysis support business performance insight? : general article

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Abstract

Most people intuitively understand complexity, but being able to analyse it scientifically is not a common practice. For business executives, 'complexity' must be one of the most important concepts to understand, as it directly impacts business performance. From a business improvement perspective it is critical to quantify complexity, as engineering optimisation models require some level of clarity and understanding for decision making. Excess complexity prevents a proper understanding of the business system, which makes accurate forecasting impossible, and so increases the risk of failure. This paper uses Shannon's entropy to measure and gain insight into complexity, and shows how it can be used to gain better insight into the performance of a business system - especially when dealing with non-linear relationships between business components.

Alhoewel die meeste mense kompleksiteit verstaan, is die ontleding daarvan op 'n wetenskaplike manier nie algemene praktyk nie. Vir die uitvoerende direkteure van maatskappye is 'kompleksiteit' een van die belangrikste faktore omrede dit die prestasie van die onderneming direk beïnvloed. Gesien vanuit die perspektief van besigheidsoptimisering, raak dit krities dat kompleksiteit kwantitatief uitgedruk moet word sodat die nodige ingenieursmodelle ingespan kan word vir besluitnemingsdoeleindes. Indien die besigheidstelsel te veel kompleksiteit ervaar, maak dit die verstaan van die stelsel onnodig moeilik, wat op sy beurt weer veroorsaak dat voorspellingsmodelle onbruikbaar raak. Dit verhoog die kans op mislukking van die onderneming. In hierdie artikel word 'Shannon's entropy' gebruik om kompleksiteit te meet om sodoende beter insig in besigheidsprestasie te verkry - veral wanneer daar nie-lineêre verwantskappe bestaan tussen die verskillende komponente.

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/content/indeng/23/2/EJC123958
2012-07-01
2016-12-04
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