Cost estimating in these times of austerity
The SWWE branch were pleased to be able to invite Dale Sherman, Qinetiq’s Head of Profession for Cost Engineering, and chairman of the Society for Cost Analysis and Forecasting (SCAF), to talk about the challenges of cost estimating in today’s economic climate.
Dale started proceedings with an explanation of knowledge based estimating (KBE), which combines knowledge, skills, data (historic, finance and technical), analysis tools, people who can understand and interpret information, and consistent application of processes.
He explained how maturity assessments can be used to assess an organisation’s estimating capability and showed that organisations operating at level 4 and above clearly perform better, with lower schedule slippage and cost escalation.
AWARD is one tool available for conducting a cost engineering health check, and Dale outlined the use of electronic voting techniques to assist Delphi structured communication techniques to reach consensus on areas of weakness and areas for improvement.
Dale explained the three common cost estimating approaches:
- analytical (detailed bottom up approach)
- analogy, (near neighbour comparison)
- parametric, (identified cost drivers and relationships)
Analytical estimating is highly detailed and built up from product, work and organisational breakdown structures (P, W, OBS). It is highly complex and can give a perception of accuracy, but can build in multiple layers of contingency. It is also time consuming and expensive.
Analogy is a subjective approach and compares features of similar systems, often based on crude linear relationships. It is useful for conceptual level estimating as it does not require a lot of data.
Parametric estimating removes biases using cost estimating relationships (CER), such as cost to cost and performance to cost. It is relatively quick, but does need good historical data. There are ‘black box’ commercial tools available, but it is often preferable for experts to build bespoke models.
Dale explained that the choice of model depended largely on the time available. Early in a life cycle, rough order estimates are appropriate and analogy and parametric may be preferable. More accuracy is needed later in the life cycle and analytical approaches are often more appropriate. Triangulation of methods can also be used to provide greater confidence.
Dale used the example of the FACET tool to highlight a parametric approach and discussed several case studies.
Dale then turned to look at the Austerity Hand Book and highlighted procurement approaches and hints and tips for reducing costs.
These included sharing development costs through international collaboration, reducing risk and costs by reusing existing designs and technology, reducing re-occurring costs through modularity and commonality, the use of incremental acquisition vs ‘big bang’, taking advantage of commercial forces to reduce costs and risk of mature technologies, optimising schedules to eliminate overlaps and gaps between project phases, taking advantage of longer production runs to gain cost savings through the learning curve, and also to monitor in-service costs to predict the ‘bath tub curve’ wear out point to introduce new technology / equipment before in-service costs escalate at the end of service life.
In summary, cost estimating is an expert field that project managers need to have a good understanding of: the different approaches, their advantages and disadvantages, if they are to satisfy themselves that the estimated costs, and timescales they are expected to deliver to are realistic.