The role of data analytics, artificial intelligence (AI), and process standardisation on infrastructure cost estimates and assurance is expected to be transformative. These technologies will significantly enhance the accuracy, efficiency, and reliability of infrastructure project costs, leading to better decisionmaking, cost control and overall project success.
Some key aspects to consider include:
In this output, the steering group sought to obtain answers to four key questions below from a multidisciplinary perspective as usual.
On audits it is imperative to continuously monitor compliance, especially considering the evolving nature of data analytics and AI technology.
On alliance and open-book cost contracts in the UK, striking a balance between GDPR compliance and maintaining transparency is pivotal. In practice this often involves anonymising and protecting sensitive data, particularly when dealing with people project cost, to preserve stakeholder privacy. Ensuring consent and non-disclosure is often essential, in line with GDPR’s principles of data protection and limitation by gathering only necessary data for project cost assurance and audits. The implementation of robust datasharing protocols, including encryption and access controls, is critical for the protection of sensitive information. GDPR mandates transparency in data processing, which supports the objective of openness on infrastructure projects. On audits it is imperative to continuously monitor compliance, especially considering the evolving nature of data analytics and AI technology. This includes keeping abreast of regulatory changes, adhering to data protection best practices and incorporating ethical considerations in AI-powered cost estimations. Key accountability measures, like appointing a data protection officer and carrying out regular impact assessments, are fundamental to transparently managing cost estimates in infrastructure projects.
Cecelia Fadipe, CFBL Consulting
Data protection is critical in an audit process to ensure that information shared, accessed and validated is only done in a way that aligns with the purpose of the audit. GDPR, as the formal structure around the concepts of data protection, provides the requirement for key roles and responsibilities to be formed and to make sure that both the data provider and the data receiver are aware of the impact that data misuse could result in. GDPR should not be a barrier to audit and transparency but the principles of lawfulness and purpose limitation should be used to keep the data collated specific to the audit purpose.
Imran Akhtar, Turner & Townsend
Some of the key principles that underpin alliance and open-book cost contracts are transparency and accountability, particularly when it comes to a contractor justifying and demonstrating the costs that have been incurred.
The nature of these contracts involve the employer (or an independent auditor) requesting documents to check and verify a contractor’s costs, this can often clash with the requirements of data protection legislation. For example, on the disputes side, we have experience of contractors refusing to provide certain evidence of payment (certainly with respect to NEC contracts) for fear of this disclosure putting them in breach of GDPR.
Some of the key principles that underpin alliance and open-book cost contracts are transparency and accountability, particularly when it comes to a contractor justifying and demonstrating the costs that have been incurred.
The GDPR prohibits a ‘data controller’ from processing personal data unless one of the specified exceptions applies and a data processing agreement is entered into. Processing is defined as any operation being performed on personal data, such as collection recording, disclosure by transmission and use. It is easy to see therefore how data, such as an employee’s payslip, which might be requested to justify certain costs, would fall within the definition of personal data and be subject to GDPR. So, how can technology assist with this and allow alliance and open book cost contracts to remain collaborative and transparent whilst ensuring compliance with legislation? Both AI and data analytics could certainly assist with identifying and selecting the specific data required from payslips (using the example above) and scheduling this out, whilst maintaining the confidentiality of the employees.
This would have the benefit of saving time and also provide reassurance to the reviewer/auditor that the data had been extracted from the documents requested, ensuring that the process remained transparent.
Claire Randall-Smith,
Eversheds Sutherland
Where the parties sign up to a costreimbursable payment mechanism they have already implied a willingness to be transparent with costs. This means that the client’s representative, most likely a QS or independent auditor, will be able to ‘follow the money’ to ensure that what is being billed in any application for payment is bone fide. It is an industry convention that cost-reimbursable contracts will lead clients to undertake a level of assurance including examining some sensitive data. As an example, under an NEC option C contract the client should be given assurance that the applied salary costs under the people cost component are shown on the contractor ledger and linked back to the actual payment made to an employee.
It is an industry convention that cost-reimbursable contracts will lead clients to undertake a level of assurance including examining some sensitive data.
Under controlled conditions, the QS or auditor should be able to witness evidence of these transactions. Resistance to allowing proper access to cost information, whether that be for GDPR or otherwise, must be overcome. GDPR is an important issue and the proper controls need to be in place, this does not equate to an excuse to be less transparent or accountable for providing verified cost information.
In any event, it makes sense for contractors to promote transparent and efficient assurance processes from the outset of any project.
There are some key reasons for this:
Tom Leach,
Southern Water
GDPR is a set of EU rules on data protection and privacy. The difficulty is with construction contracts in particular alliance contracts where the requirement to review audit and assess each other’s data is contractual. An established approach, protocols and NDAs all need to be utilised when encountering an open book agreement.
Charlotte Edwards,
Atkins - SNC Lavalin
AI and data analytics will transform data and cost accuracy on major infrastructure projects. AI can enhance data quality through automated checks, ensuring accuracy with inputs and fortifying data integrity. It is crucial in data validation and cleansing, verifying and correcting datasets for accurate cost estimation. Limitations of AI include trust, integrity and judgement discerning sensitive data.
Real-time data monitoring by AI can quickly identify anomalies, enabling prompt corrective action. Predictive analytics, driven by AI, can help forecast future cost trends, aiding with risk identification. Machine learning can help analyse large datasets for cost optimisation and effiicient resource allocation. AI can assesses project data for accurate risk assessments and proactive mitigation measures. Automated audit sampling and compliance checks can help ensure adherence to standards, enhancing reporting accuracy. AI can help with fraud detection and combined with blockchain technology, will strengthen data integrity. Continuous learning in AI systems will allow more accurate adjustments in cost estimates as projects phases evolve. AI’s decision support systems will help by providing real-time, actionable information, emphasising the need for open- book transparency and relevant commentary in AI models for accountability and cost reporting.
Cecelia Fadipe,
CFBL Consulting
Analytics: The use of AI technology introduces new ways for information and data to be collated, analysed and used for producing infrastructure cost estimates for the purposes of planning and preparing project budgets. The capability of AI to enhance computer take-off as well as its ability to integrate 2D with 3D BIM take-off will increase estimate accuracy. The use of AI will enable estimators to provide clients with real-time data, in a consistent and reliable format. The following broad technologies will help achieve efficiencies and optimisation in safeguarding data integrity and cost accuracy when producing estimates.
This is increasingly becoming more prevalent in some major programmes where clients are introducing data platforms to collate all cost data submitted by the Tier 1 supply chain.
This logic could be developed for each supplier and further through the supply chain allowing a much more forensic approach to cost analysis with relatively little effort compared to more manual efforts. Machine learning could also be used across multiple datasets and data points (i.e., cost, programme and contract data) using both structured and unstructured data to continuously develop logic and a more robust estimating approach.
The importance of having a digitally savvy and skilled estimating team is paramount to ensure scripts and automated take-offs are built with sound logic and in compliance with best practices and appropriate e standard methods of measurement. Reporting: Technology has already positively disrupted how cost estimates can be communicated to stakeholders. The use of software like Cost X, Cost Os and Power BI represents new ways to visually present information, findings and analytics that were not as prevalent ten years ago. Providing a visual representation of information, particularly in relation to large and complex datasets allows the user to more easily digest the key messages. Going further, dynamic and live estimate reporting and dashboards are providing a greater level of control to key individuals within the client organisation (as well as the supply chain) to make better-informed decisions using the whole dataset and not subsections of it.
Elliot Patsanza,
Ridge & Partners
AI is becoming an increasingly present aspect to major civils. I heard of a project that is trialling a system where AI is producing permits for the start of shift briefings and the start of works. The AI produces the basic template then it’s adjusted by the engineers. Commercial aspects are slow off the ground to embrace AI. We should be using AI to generate the monthly basic commercial requirements, such as zero payment certs to prevent smash and grabs. Self-billing and applications for payments could be able to utilise AI. This could save the commercial team valuable time.
The importance of having a digitally savvy and skilled estimating team is paramount to ensure scripts and automated take-offs are built with sound logic and in compliance with best practices and appropriate e standard methods of measurement.
I have experienced the desire from clients to build databases, to input into an AI system. We were asked to populate actual costs against estimated target rates. This data along with other project data was collated and used to estimate future works. When I later got asked to price additional works, the client had a value generated from the AI. The result was the client had an unrealistic project value and I had to spend time detailing why my estimate had accounted for elements that the AI had not. My conclusion was that the data inputted by the projects must have been misleading. For AI to correctly work, the data source must be accurate.
Charlotte Edwards,
Atkins - SNC Lavalin
Standardisation is vital for enhancing efficiency and assuring costs. It brings consistency in project execution, ensuring uniform adherence to established procedures and methodologies across various projects, thus elevating quality and productivity. This uniformity aids in efficient resource allocation, enabling teams to optimally utilise materials, equipment and people through consistent specifications. The result is improved efficiency, increased cost savings, streamlined procurement, strategic purchasing decisions and reduced delay risks due to more standardised specifications.
Moreover, standardisation bolsters collaboration and communication by setting common standards for scoping, delivery and reporting. This establishes a shared understanding of project requirements among stakeholders, effectively minimising disputes and potential delays. It significantly contributes to enhanced quality by stipulating defined requirements for materials, construction methods, reducing faults, rework and additional costs linked to these. Crucially, standardisation plays an essential role in risk mitigation, facilitating early identification and proactive management of potential risks throughout the project lifecycle. By employing standardised risk assessment checks and processes, project construction teams can minimise the chances of unexpected risks, cost and delays, contributing to increased cost assurance overall.
Cecelia Fadipe,
CFBL Consulting
Standardisation of data, particularly across a client’s supply chain, can be massively useful to enable better quality benchmarking and understanding of where costs have been incurred. Unfortunately, the reality is that all major contractors in the industry work across multiple clients, sectors and data requirements which often means that configuring a cost management or enterprise resource planning (ERP) system to one data standard is not possible. This challenge is further compounded by the fact that some costs (materials, equipment) are rarely ordered in a business by works activity rather they are typically ordered by location or overall contract. For example, concrete may be ordered to a site location or coded to the overall contract reference but it will rarely be specifically ordered to a site for a specific purpose. It is then up to the commercial and site teams to produce a form of allocation of cost but this then potentially limits the ability to benchmark and compare cost performance. Assurance plays an important role in validating these processes via ‘set up’ audits of the supply chain to assess the quality, control and consistency of how a contractor manages and allocates their costs.
Imran Akhtar,
Turner & Townsend
Standardisation is the use of processes or procedures, products or components, with regularity and repetition. In recent years, the construction industry has slowly embraced digitisation and standardisation of some of its key processes – something which has been accelerated by the pandemic and the need to increase productivity and work remotely or at a social distance.
Tools such as BIM, laser imaging detection, ground penetrating radar and also the use of digital twins, are used more and more often on construction projects to help digitally design projects before they are built.
Tools such as BIM, laser imaging detection, ground penetrating radar and also the use of digital twins, are used more and more often on construction projects to help digitally design projects before they are built. This helps to make beffer project decisions, help productivity (and minimise errors), reduce costs and improve quality. However, there are certainly challenges with standardisation (particularly with respect to design and construction methods) mainly because projects can be so complex, varied and subject to their own specific conditions. Often there is no one size fits all, and it is important to recognise that some things need to be adaptable and flexible to suit the individual needs of a specific project.
The challenge is therefore to combine the quality of bespoke design and construction on a project with the benefits of these standardised processes, without resorting to the mass production of the past. Provided that this inherent need for individuality and flexibility is recognised and can be included where required, then standardised processes can significantly benefit productivity and cost assurance.
Claire Randall-Smith,
Eversheds Sutherland
As a consultant, I work with lots of different businesses across different sectors of construction – employers, main contractors, subcontractors and suppliers. In my experience, there is very little standardisation of cost data from project to project, let alone across the construction industry.
There are broad similarities and there are existing standards like International Cost Management Standards (ICMS) but the reality is, that each business will attempt to standardise in a manner that suits their needs. So a UK-based water treatment design, build and operate (DBO) contractor with a Spanish parent company will costcode in such a way that the parent company may require and a UK family-run architectural metalwork subcontractor will cost-code for its board’s requirements and possibly for data analytics for insight purposes.
My thoughts are, as with most things, government-funded organisations must lead the way with standardisation which is a prerequisite for tendering for the whole supply chain on those projects. This will ensure that, over time and throughout the supply chain, there is a concerted effort to standardise. It would also be useful if government organisations across different industries were also aligned in adopting the same standard.
There would be numerous benefits. Staff will be more able to work and apply the same standards across different industries, AI and computer-aided analytics can be applied without first tidying up and cleansing the data and auditors can streamline their processes and outputs. Even data input could be improved because developers could build apps that site supervisors could use to input records in real time that would flow directly to a cost system that would also align with the standards and drive out wasted time and improve claims for loss, expense and prolongation costs.
Gary Bone,
Blake Newport
The introduction of standard contracts has improved the commercial management of construction projects. However, the basics are being missed. What tends to happen on the major projects I have worked on, is that contract terms and conditions (T&Cs) are passed down to the supply chain. The main contract normally has a clause stating, ‘subcontracts can’t be any more onerous than the main contract’. This clause safeguards the supply chain to a point. The flow down of these T&Cs does make smaller less equipped parties accountable for picking up the requirements of the main contractor. Small and medium enterprises (SMEs) have to deal with onerous requirements that are costlier than they might be aware of or require them to adapt sooner to the changes in the industry. These contractual requirements normally get slid in within the health and safety section or the works information of the contract documentation. The commercial team are usually unaware of them or reluctant to highlight them at the tender stage. Putting the onerous back on the supply chain to read the contracts carefully.
Standardising and implementing a fair open and honest approach would be beneficial to all in the industry. I feel more effort needs to be made in becoming more collaborative, upfront discussions, where all parties involved in the implementation of the contract agree on the requirements and how they are going to do the work. The management of those works, what’s required from whom and when. Clear attendances and plans from start to completion of the works. The basics of commercial management are getting lost in all the processes, reports and requirements of the project. Attitudes such as ‘understanding the deal’, ‘right first time’ and ‘best for the project’ all need to become second nature as the H&S ‘don’t walk by’ has become. This will provide all the rewards of getting the project done on time, to budget with minimal change.
Charlotte Edwards,
Atkins - SNC Lavalin
Strategic use of historical data is essential in improving cost estimates and increasing the value of future construction projects. Historical cost analysis, by examining past projects with comparable parameters, offers valuable insights into cost patterns and factors influencing future costs, establishing a realistic baseline for future projections. Benchmarking, which compares the performance of current projects against past ones, can enable project managers identify areas for improvement in cost management and set more realistic budgets based on past project successes. Parametric estimating is another useful tool, by employing statistical correlations between historical data and specific project factors to refine data-driven cost estimates and identify key cost influencers. Historical data is key for risk assessment and mitigation, where proactive mitigation measures are based on previously encountered risk, thereby enhancing the accuracy of cost projections. Lessons learned training can contribute to a culture of continuous improvement, documenting experiences and encouraging regular review and revisions of cost-estimating methods. Aligning best practices with strategic goals ensures that investment decisions are data-driven and significantly contribute to achieving project objectives; boosting overall project value.
Cecelia Fadipe,
CFBL Consulting
Using cost data intelligently is key for any organisation to enable better decision-making, identify areas of cost risk and opportunity and have more well-informed conversations with their supply chain. Past data forms part of this but this data requires refreshing on a reasonably regular basis rather than relying too heavily on inflation or uplift factors, more critical now than ever.
The difficulty is without detailed project knowledge of that historical rate, you are guessing at the adjustment needed to the rate for the new project.
Organisations often find themselves in year four of a five-year spending period struggling to obtain and use up-to-date data to utilise in their future planning, ultimately resorting to data collected many years ago to try and form a view on prices that will be incurred in the medium term. This has rarely proven to be a robust approach and creates a cycle of injecting poor quality in and receiving poor quality out. A data strategy is key to putting some structure around this challenge ensuring that all individuals within the organisation understand the intent around the use of data and that this is something that is able to be shared with the supply chain as early as possible. Data requirements and standards should ideally be made aware to the prospective supply chain during the tender phase and requirements and standards included in the contract to maximise compliance.
Imran Akhtar,
Turner & Townsend
If costs were captured in a standardised form, then this would loop back to project feasibility estimates, tender costs and tender evaluations. The construction industry is often criticised for overspending against budgets which would indicate the budgets are too low in the first place. This drives overly optimistic tenders and a claim culture. If the budgets were informed by better past data it would add realism to the decisions to go ahead with the project in the first place. Politics can often play a part in those decisions but data-led budgeting would help in providing transparency in those political decisions. The other by-product would be that contractors’ contract sums would be more realistic, thus providing a sensible profit margin. This will reduce claim culture where contractors use post-contract claims to generate a profit. If there are fewer claims there will be less costs and downtime associated with prosecuting and defending claims.
Gary Bone,
Blake Newport
I usually price additional works or estimate new works using the rates on the project I am working on. Making sure I make allowances or apply various factors to that rate. Using historical data is only beneficial for budget estimates when applying a price range. The difficulty is without detailed project knowledge of that historical rate, you are guessing at the adjustment needed to the rate for the new project.
AI could be used to provide a high-level estimate for works without design maturity. If the data used by the AI is accurate. I find using past data to benchmark rates useful in demonstrating value for money to clients. Benchmarking can highlight and identify anomalies or reasons for inflated values. AI could be beneficial to do this task.
Charlotte Edwards,
Atkins - SNC Lavalin