6.4 ACUBA Method
6.5.2 Limitations of applying the ACUBA method
Several limitations associated with the ACUBA method have been identified. The limitations relate to the technique used to weight the sources of cost uncertainty, establishing the acceptability criteria for product cost maturity and the ability to propagate uncertainty for individual cost components to an overall product cost maturity.
The weightings for each source of uncertainty are generated using qualitative methods. The ANP is identified as a way of establishing the relative importance of each source of uncertainty on a product cost estimate. For the ACUBA method the weights generated are treated as nominal values which are employed for each cost estimate to derive the maturity rating. The need to rely on expert judgement and subjective analysis for the process is identified as a key limitation. The relative weighting of cost uncertainty sources is likely to vary depending on the expert who is elicited. A statistical based technique such as regression analysis could be used to establish the weightings based on actual data accumulated for previous projects. However, this data (related to the actual final cost of each source of uncertainty versus the estimated cost) is not recorded by the organisation for the early design stage. To record this information a set of attributes would need to be developed for the selection of the most relevant weightings for the specific project and would require the collection of data over the entire development phase.
A benchmark of acceptable uncertainty at the end of a design stage is expected to be industry or project specific. The validity of the semantic relationships associating the quantitative uncertainty ranges have not been validated. The assessment of expected cost maturity at this stage of the design process uses the semantic definitions of cost maturity and is associated with the expected information available for at a particular stage. The notion of acceptability relates to the ability to understand the expected maturity of a cost estimate for a particular stage of the design development process. For a clear representation of the product cost maturity, the ACUBA method needs to account for propagation of uncertainty by acknowledging dependencies based on the knowledge available at the time. The technique proposed for the ACUBA method is to
139 use DSM, although the ability to elicit a clear set of dependency of information needs to be tested.
6.6 Summary
The cost maturity metric is an assessment of the confidence the estimator has in the estimate that has been generated. The ACUBA method attempts to identify the current maturity of the product cost, to illustrate the acceptability of the estimate maturity, and presents scenarios where the design team can obtain more certainty by carrying out additional design activities. The ACUBA method establishes the importance weightings for sources of uncertainty to the cost maturity. By establishing an acceptable cost uncertainty metric for the end of the concept design phase, a threshold level can be set allowing for the product cost maturity. The benefits and limitations of the ACUBA method have also been outlined. Subjectivity and qualitative assessments are more prevalent at the early concept design stage where little detail is available about the product and sources of cost due the immaturity of the design.
The practicality of each of the steps involved in carrying out the ACUBA method is investigated in the next chapter. The extent to which this approach is valid requires further investigation. At the early concept phase, where estimates are subjective, the maturity metric is also subjective. Determining the estimating effort required is based on the perception of acceptability rather than a quantifiable range. The weighting of sources of cost uncertainty on the product maturity for component estimates will need to be verified. In addition, there is a need for a standardised and agreed set of semantics for the maturity ratings and related questions to derive component maturity scores.
To derive the overall product cost maturity a clear and valid approach is required to propagate the individual component cost maturities that are quantified. The ACUBA method relies on deriving dependencies of information between key components using the design development plan, and the dependencies between design decisions and the expected production of information. The practical application and validity of this approach to establishing dependencies is investigated further in Chapter 7. In addition, the ability to identify the influence of each individual decision on component and product cost maturity will need to be evaluated.
140
7 Decision Support Using the ACUBA Method
7.1 Chapter Overview
This chapter forms the final part of the solution development for the method (Figure 64) applying the ACUBA method presented in Chapter 6 to the early concept design decisions of the case study project. This chapter aligns with Objective 5:
Validate the developed method.
Figure 64: Chapter 7 in the context of the thesis
Section 7.2 presents the preliminary activities associated with setting up the ACUBA process, focusing on two key aspects. Firstly, the selected semantic scales used to qualitatively describe the information maturity used to generate the component cost estimate is justified. The importance of different sources of information maturity on the cost maturity are then quantified. The case study application of the ACUBA method is presented in Section 7.3. A benchmark maturity assessment of the cost estimate is generated for the concept development stage. A decision matrix is then used to map the information dependence between the planned design decisions. Component and
141 product level maturity estimates are then presented based on the information available to the design team and the estimator. The results of the maturity assessment are then analysed. Simple optimisation is used to illustrate the ability of the ACUBA method to identify priority areas to improve the maturity of the cost estimate to a notional acceptable level. Section 7.4 presents a discussion on the implementation of the ACUBA method, limitations and further improvements required. A summary of the findings is presented in Section 7.5.