In May 2019, DCWC Infrastructure and Agonis presented a whitepaper entitled ‘Project Assurance through Integrated Quantity Surveying Teams’.
This paper concluded that:
State Governments are now turning to digital engineering (DE) modelling in an attempt to avoid an era of Infrastructure overruns and avoidable contractual disputes with embarrassing outcomes.
It is believed that with an appropriate level of design and corresponding documentation level for costing purposes, these models can be used to apply historic data and produce commercial outputs with a high degree of accuracy.
But is this really the case and will DE ever provide this desired outcome? And further, will there ever be sufficient data available in these models where ‘professional judgement and experience’ is no longer required?
The reality is that DE modelling will only ever produce around 70% of the data required for assurance in high value/high risk Infrastructure project outcomes.
Cost overturns have occurred primarily for two reasons:
When analysing these two primary reasons for cost overruns it becomes clear that the human factor cannot be removed entirely, and that the replacement of this factor with contingency and client allowances should not become the norm.
On the basis that the best professional judgement and experience was given to the Sydney Light Rail project, the $517 Million of mispricing and omissions in scope discovered in 2014 that could not be shown in the design and specification documents, represents:This clearly demonstrates that after repeated attempts at defining the project requirements, including that of an agreed contract price with a consortium, 25% to 33% of the project requirements would need to be determined not from DE modelling, but from professional judgement and experience.
Western Sydney Airport Corporation (WSA Co.) is implementing Building Information Management (BIM) modelling for the Western Sydney Airport to enable significant time, cost and quality improvements for the delivery of significant airport infrastructure.
These BIM processes will provide WSA Co. with an approach that allows digital information to become a key enabler of stakeholder engagement, decision making, improved asset knowledge, capability, and capacity planning.
GHD has been engaged to produce a Reference Design for Packages 1C (Airside) and Package 3 (Landside) for the 10 Million Annual Passenger (10 MAP) capacity that is capable of incremental growth to 82 MAP ultimate capacity with the relevant safeguard in the site-wide elements. Together with the reference design, GHD is preparing a BIM Execution Plan (BEP) and model to map these requirements. DCWC is working closely with GHD verifying quantities derived from their BIM Model, measuring additional quantities in conjunction with their advice, and expanding on data derived from the BIM Model to provide quantities for components below the ground that cannot reasonably be shown in the model. These joint activities are assisting GHD, and therefore WSA Co., in identifying any discrepancies between the BEP, the client requirements and the Reference Design Documents.
This process has clearly identified the need for both BIM Modelling and human input to ensure overall integrity of the model, consistency between the BIM Model and the design documentation, and accuracy of data. It also highlighted deficiencies in the current estimating software used by DCWC (Cost X) to measure quantities and the need to proceed with upgrades. Upgraded versions of Cost X now allow the importation of raw data from Digital Engineering software such as 12D and Autocad and Civils 3D etc., without having to convert this data to other recognised forms.
The belief that contingency allowances (derived through the risk management approach) and client allowances can be used to substitute the missing data from DE modelling is clearly false. Assuming a 40% contingency allowance (standard for all TfNSW projects), then the original price of $1,598 Million submitted in March 2014 would be inclusive of $456.6 Million for contingency and client allowances. Clearly, the $517 Million of mispricing and scope omission could not be covered by this amount and even if this sum were to do so, there would then be no allowance whatsoever in the final agreed contract price for inherent risk (uncertainty in quantities, rates and construction methodology) and contingent risks (site specific risks) such as latent conditions, unforeseen utilities, industrial relations and the like.
Using contingency and client allowances to replace professional judgement and experience is clearly the wrong example to follow.
While there is undoubtedly a need for Digital Engineering modelling in the future, this paper identifies the need for professional judgement and experience.
The general intent of the human factor in DE modelling is reiterated – to provide guidance to facilitate an informed and conscious position, to enable a well-considered works plan to increase the likelihood (provide greater assurance) of an efficient delivery outcome. The primary benefit to the client is that it achieves the intent of the Department of Treasury and finance guidelines for high value/high risk infrastructure projects.
A second benefit is that the robustness of the data and assumptions, used in the DE Modelling will be supplemented with ‘real life’ construction knowledge and experience.
Thirdly, as far as reasonably practicable, and where the DE modelling is lacking in elements that cannot reasonable be foreseen, professional judgement and experience can be used to make an assessment of missing scope and of the provision in the budget for inherent and contingent risk allowances.
Human influence will always be required in DE modelling to provide assurance to projects’ outcomes. Not to mention the reparation of non-tangible impacts of reputation, confidence and stakeholder engagement.
It makes no sense to plan for digital engineering modelling in the future where the human factor is excluded and all project outputs are based on historical data.
Each high value/high risk Infrastructure project is bespoke and carries its own set of high impact items unique to its functionality, purpose, and location. No two Infrastructure projects are the same.
It is also illogical to rush the requirements for these bespoke projects or to ignore the high impact items. These issues will only arise at a later stage, and the cost then to mitigate these issues will increase exponentially over time. No one wants to be the bearer of bad news and the historical data captured over time, and stored for use in DE modelling, will go a long way towards improving project outcomes.
The human factor will always be required to fill in where DE modelling is insufficient. Logically, assurance in project outcomes can only be achieved when these two factors are used cohesively.
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