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Abstract
Manufacturing organisations must routinely deliver efficiencies in order to remain competitive.
Many have embraced continuous improvement methodologies, such as Lean manufacturing and
Six Sigma in order to achieve these goals. However their ability to realise sustainable competitive
advantage from continuous improvement is hampered by the lack of structured objective
approaches for optimal project portfolio selection that link strategy to targeted improvement
efforts. As a consequence, scarce resources are inappropriately allocated, opportunities are lost
and there is sub-optimisation of the system as a whole.
There are three gaps in the extant literature (i) the majority of published methodologies begin
with a finite set of explicitly defined alternatives and attempt to maximize the portfolio
outcomes without any definition of an optimized future state, (ii), portfolios are limited to
choices from an a priori set of alternatives and are therefore unlikely to result in an optimal
outcome and (iii) the extant methodologies generally do not include appropriate measurement to
judge outcomes. Furthermore, there are significant limitations to the approaches used by
industry for project selection and a degree of dissatisfaction with the methodologies employed.
The most significant of these is the gap between strategy formulation and portfolio generation.
A normative framework that should be used to structure project portfolio methodologies is
therefore presented.
To resolve these issues, a scalable generic methodology for visualizing and evaluating optimal
future states and to evaluate projects and portfolios of projects in the context of those future
states is presented. The methodology described employs Multiscale, Object Oriented Modelling
and Simulation with Optimal Design of Experiments to create n-dimensional Pareto Frontiers
from the set of all feasible production outcomes within given manufacturing configurations and
for given strategic scenarios.