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Q&A: Advanced analytics in capital projects

April 2021  | SPECIAL REPORT: INFRASTRUCTURE & PROJECT FINANCE

Financier Worldwide Magazine

April 2021 Issue

FW discusses advanced analytics in capital projects with Anil Chhabria, Hugh Dullage, Hani Girgis and Rob Scopes at Deloitte.

FW: In what ways has the capital project-delivery process changed over the past few decades? How would you describe its evolution during this time?

Chhabria: The capital projects industry has been historically quite conservative – some may even say the way projects are delivered have not changed at all. In the last couple of decades, a number of institutional bodies have provided best practice guidelines and certifications to encourage a more structured approach to delivery. This also includes a strong focus on health and safety. Encouragingly, in recent years we have been pleased to see the adoption of more advanced and collaborative tools and techniques for project delivery, including data-driven operating models underpinned by digital technologies, such as the cloud, digital twins and building information modelling (BIM). Additionally, and while the use of agile methods in capital projects is still uncommon, there are some early adopters.

Dullage: The construction industry has been relatively slow to adopt new ways of working. It is an industry made up of mainly small to medium sized enterprises. The margins are very low, normally less than 2 percent for major contractors, and the commercial risks can often be significant, so the investment in technology and innovation has been limited. In the last 10 years there has been a much wider adoption of technology in client organisations, particularly in the major infrastructure delivery organisations, which is starting to support a more data driven, analytical approach to managing the delivery of capital projects. However, there is still a huge opportunity to digitalise and automate many of the current processes in the supply chain, which would help to improve the speed and cost of delivery, along with reducing waste and making the process safer.

Girgis: Public sector capital projects organisations have long been focused on funding and investing in traditional techniques, tools and processes to boost their overall programme delivery. There has been historic underinvestment in digital initiatives which has resulted in a slower adoption of digital change and disruption compared to other industries. However, since the turn of the last decade we have witnessed an increasing willingness and confidence from parties to undertake complex digital transformation initiatives. In recent times, increases in the number of mega projects is paralleled by the industry’s growing appetite and appreciation for the value delivered by sophisticated data and analytics practices.

Scopes: Numerous studies into the construction industry have shown that it is imperative that the industry’s clients play a major role in delivering necessary change. Throughout the 1990s and 2000s the public sector doctrine in the UK was dominated by private finance, namely the private finance initiative (PFI) and public-private partnerships (PPPs). This brought more output specifications, and the diligence necessitated by bond finance. This led to project owners taking a broader view and empowering the supply chain to innovate and deliver. These complex structures have fallen out of favour, and we have seen the growth of mega projects. This has led to project owners returning to the detail, and recognising their often non-transferrable risk, such as systems integration, as seen in some UK mega projects. This greater level of client involvement is one ‘condition for success’, to drive improvement in the industry’s performance.

“As organisations evolve, they need to move their focus from historical ‘what and why’ questions to more forward-looking predictions and outcomes. This will require them to take a more proactive, data-driven approach.”
— Anil Chhabria

FW: In your experience, do capital projects frequently exceed budget estimates and encounter delays? Are there any common underlying causes?

Dullage: There is often commentary around major projects being delayed or exceeding their budgets. However, it is important to consider the challenges major programmes face, particularly in terms of their scale, complexity and unique nature. These challenges are also exacerbated by the fact that many capital projects are delivered by a completely new team of people coming together to deliver a bespoke solution with a completely different range of challenges and risks each time. The uncertainties that surround projects are never fully understood in the early stages when budgets and timelines start to be identified for the business case.

Girgis: Unfortunately, delays and exceeding budgets has been a common theme across the industry spectrum. While complexity and scale of challenges are accepted and appreciated at the point of estimation, organisations have failed to ascertain, address and eliminate the challenges without impacting the overall plan. Many high-profile projects of the last decade have encountered several delays and, in some cases, continue to run over budget. Project delays and cost overruns may be due to many individual, or a combination of multiple, factors which may span between scope changes, planning issues and inaccurate estimation, unanticipated site conditions and disputes between client and contractors due to weak commercial agreements. Although these causes are common, the underlying challenge which amplifies the impact is poor data and analytics practices that prevent organisation leaders from effective, timely and insightful decision making.

Scopes: There have been numerous academic studies into cost overruns in this industry, so the evidence is undeniable. However, one issue that remains is that the industry has not been effective in communicating the design and cost maturity at which the cost estimate is struck. In the case of mega projects, while it is clear there is much work to do, it should be noted that budget estimates that are done early in the project are not precise figures. And once projects are in flight, there is the adoption of quite sophisticated probabilistic analysis, allowing contingencies to be set. However, in the absence of good quality analytical data, this often gives rise to false comforts. Data and data quality need to be seen as valued assets, rather than a matter of housekeeping and compliance.

Chhabria: There is an overwhelming set of evidence that confirms that most major capital programmes tend to incur cost and schedule overruns. These also suggest several common overarching factors. Looking at the planning phase, preliminary incorrect estimates, very often on the optimistic side, set the project up for a difficult start. At the same time, during the execution phase, over-optimism may continue, and the failure to acknowledge the actual costs and timescales thus delays the required actions. From a project architecture perspective, it is common to find isolated teams and unintegrated tools, including technology, which prevents the recognition and utilisation of a ‘common language’. This is, in turn, exacerbated by poor data quality and tardiness of the information that managers and directors need so dearly to inform their judgement.

“The improved availability and adoption of both empirical and ‘live’ analytical data will help drive a better estimation and understanding of performance.”
— Rob Scopes

FW: What benefits can advanced analytics bring to capital projects? How can such technologies help those undertaking projects to assess, procure and deliver them more efficiently?

Girgis: When done right, advanced analytics can enable an organisation to become truly insight driven. It has the ability to transform the decision making and planning ability of a project, which can lead to minimisation and even prevention of delays and cost overruns. From a project monitoring perspective, complete transparency of spend and performance can be achieved, which will allow for early identification of challenges. Additionally, the mature analytical capability of a client organisation leads to efficient and optimum management of its supply chain – again, a common challenge witnessed across the industry. At its core, the appropriate adoption of advanced analytics practices can enable organisations to become proactive instead of reactive.

Scopes: The potential benefits of advanced analytics are transformational and widespread. Due to the industry’s non-repeatable nature, the industry has what we call a ‘technology debt’. The industry is now ‘catching up’ with other industries, however, and this has the potential to confer significant benefits at each stage of the project lifecycle, from strategically asking ‘are we doing the right projects?’ through to ‘are we doing the projects right?’ Furthermore, the benefits can accrue to both clients and suppliers to the industry. The improved availability and adoption of both empirical and ‘live’ analytical data will help drive a better estimation and understanding of performance and will provide a platform for performance improvement.

Chhabria: As organisations evolve, they need to move their focus from historical ‘what and why’ questions to more forward-looking predictions and outcomes. This will require them to take a more proactive, data-driven approach. One key benefit presented by the data-driven approach is that it helps organisations to improve the accuracy of how the project’s assets are set up, delivered and maintained. Leveraging the amounts of data held by an organisation, advanced analytics can help teams to establish structured and repeatable analytics processes. This also assists them in understanding and learning from past performances and accurately predicting current trends. Ultimately, organisations can model different ‘what if’ scenarios. This modelling potential helps asset-heavy organisations to better understand the expected performance of an asset by using evidence-based data, instead of relying on generally accepted benchmarks.

Dullage: One of the powerful features of advanced analytics is that they can be applied across the project lifecycle. For example, during the design steps, analytics can help optimise the use of materials and constructability. Looking at the execution phase, analytics can yield benefits in better scrutinising performance and identifying patterns in data, for example analysing spend data to identify potential errors or even fraud. Some of the most exciting areas are where we are seeing AI being applied to data sets, such as cost or schedule data, to identify future risks and build much stronger predictive capabilities which allow us to mitigate them. Using analytics in the actual construction site can also be very beneficial – it can bring together data sets such as weather and health data from wearable technology, to help identify potential risks to health and safety during construction so that they can be better mitigated.

FW: What kinds of challenges might arise when integrating advanced analytics into a capital project? How significant are issues such as data quality, for example?

Scopes: An overarching challenge is culture and clarity of accountability. It is an interesting mix. To drive innovation, one needs to strike a culture of seeking out new ideas and experimenting. Yet to deliver tangible benefits, there must be a hard-edged clarity on who is accountable for making things happen. For example, who in the C-suite is responsible for driving innovation through analytics? Does the organisation have a chief digital officer (CDO)? There are also challenges about how and where to start. Another issue the industry faces is the lack of absolute repeatability. Unlike manufacturing, or consumer goods, where there is a very repeatable process to analyse and optimise, construction tends to be more bespoke in its solutions to different challenges. Every project is different.

Chhabria: The diversity of data sources, especially in the context of large enterprises, is phenomenal. Data comes in different types, with various levels of complexity and structure, which, more often than not, complicate processes and practices down the line. With this number of sources, as well as the large number of stakeholders that interact with the data, appropriate quality is certainly a challenge from the very beginning. Delivery bodies that fail to adopt a thorough data strategy may find that their information is incorrect, which could mislead project managers and directors. There is also the challenge of culture and adoption. It is not rare to find pockets of resistance to new ways of working and to embrace an agreed common approach in managing the systems and analytical practices. This may prevent data from being shared or used appropriately, creating tensions between teams.

Dullage: When there is an under-investment in technology due to low margins, the overall level of maturity in technology and data quality is low and this hinders the application of advanced analytics. When maturity is low and data quality is poor, the potential of advanced analytics will be curtailed, if not erased entirely. These are challenges that need tackling throughout the lifecycle and from top to bottom through the delivery model for capital projects. The public sector is well placed to take a lead in addressing some of these challenges and we are seeing parties investing in automating their data collection and validation capabilities so that they have reliable data from across the supply chain. Once they have reasonable data, the opportunities to apply advanced analytics grows exponentially. This, in turn, is building capability across the industry and driving new levels of expectation.

Girgis: Like any established and mature organisation, tackling common digital challenges should be first considered through an enterprise-wide lens. A common challenge for some public sector organisations has been the lack of consistency in digital maturity and technology infrastructure across the organisation. A fragmented technology stack hugely dents the organisation’s ability to solve a challenge once and for all. Multiple sources of the truth and a disconnected technology sphere means, when undertaking the fix, organisations can be overwhelmed with the scale and complexity of the challenge. Some even scale back the fix due to sheer fear of failure. The trick is to tackle these challenges early and with a ‘right first time’ attitude. Otherwise, failure to impose vital rigours, such as data quality frameworks, can significantly threaten the validity, accuracy and integrity of the data in its ecosystem, leaving the organisation open to extreme scrutiny down the road.

“Should parties start to see the benefits available from more innovative approaches and advanced analytics, they will start to demand and pay for them from the supply chain because the value will be self-evident.”
— Hugh Dullage

FW: What advice would you offer to those seeking to design and implement an effective capital project programme which utilises advanced analytics? What are the key considerations and steps to take?

Chhabria: Focusing on the business problem or goal is fundamental. This is so that clear business requirements can be gathered and mapped against the correct analytics tools. It is also important to assess how this newly introduced analytics solution integrates with the overall architecture. The introduction of these types of tools may introduce a change within organisations, which must be carefully managed. It will involve communicating widely the benefits of data analytics for the project, upskilling those who will use the selected tools and synchronising them with the relevant operations. Lastly, it is critical to remember that capital projects tend to be multi-year undertakings and therefore continuous review of the use and benefits of data analytics will highlight areas of refinement.

Dullage: It is essential that expectations are set from the outset that automated, data-driven processes will be applied in every aspect of the programme. Agreement across the key actors is, therefore, paramount. Most importantly, visible sponsorship from senior leaders will provide the necessary backing so that these processes are adopted. Identifying limitations to adopt analytics across the value chain of the programme and being honest about them will assist in drafting improvement plans to overcome them early on. Clients need to consider incentivising innovation and be prepared to co-invest with their supply chain in a way that will deliver joint savings through the life of the programme, and beyond.

Girgis: The most critical aspect in achieving success when implementing effective capital project programmes is to ensure the sponsors buy-in to the end vision and truly appreciate the future benefits of it. It is also paramount that there are synergies and alignment between the C-suite members on the organisation’s digital roadmap. We encourage parties to always invest in digital initiatives which can result in scalable and sustainable enterprise capabilities that can be leveraged as the project moves through its lifecycle. A key element to enabling parties to focus on the right initiatives is to ensure the benefits derived from a successful implementation are continuously monitored to measure the true return on investment (ROI). Traditionally, the industry has been sceptical of change, but this outlook must change, and organisations should embrace methodologies designed to give confidence through early prototypes or iterative builds before undertaking a large, complex implementation.

Scopes: In terms of ‘what’ to focus on, a critical analysis of what benefits might be derived, and to whom the benefits confer commercial advantage, is critical. In terms of ‘how’ to start and progress, adopting agile techniques, such as proofs of concept, starting small, failing fast, before scaling seems to be the path to sustainable success. Regarding the ‘what’ to focus on, for example, for project owners the focus is likely to be on macro factors at a programmatic level, such as overall schedule, cost and risk, whereas for contractors the focus is more likely to be on more tangible site-level performance analysis, such as workforce optimisation, plant telemetry, plant utilisation, productivity and so on. Performance improvements in these areas will drive the bottom line. Furthermore, regarding capital investment to maintain assets, the prize will be to move from condition-based maintenance regimes to predictive risk-based approaches.

“Project owners and their supply chain counterparts have a growing appetite to fully unlock the benefits of advanced analytics rather than stay stagnant in the ever-evolving technological landscape.”
— Hani Girgis

FW: In a highly complex and competitive construction environment, what risks face those companies that fail to embrace new technologies such as advanced analytics?

Dullage: Inevitably, as some parts of the industry start to adopt new technologies and demonstrate the value they can bring, others will follow. There are risks associated with being an early adopter, but there may be less in construction as many of these technologies will have been implemented in other industries previously. So, the greater risk is likely to be in continuing with older, less efficient, safe and sustainable practices. Should parties start to see the benefits available from more innovative approaches and advanced analytics, they will start to demand and pay for them from the supply chain because the value will be self-evident.

Girgis: Given the focus and scrutiny under which major public sector capital projects operate, the adoption of new and appropriate technologies is no longer a choice but a necessity. The cost of failure is so high that any technological help which aids the projects to minimise or prevent delays and cost overruns must be leveraged to avoid reputational damage and, more importantly, to continue acquiring investment. Failure to deploy such beneficial technologies within an organisation can lead to a missed opportunity to significantly increase workforce efficiency and productivity. The government is putting increasing pressure on its major projects to employ and implement the latest and greatest technological innovations and set an example for the next generation of mega projects. Failure to follow suit will see organisations run the risk of being left behind.

Scopes: There are risks for all players in the construction value chain, from clients, through tier one contractors, to tier two and three contractors and suppliers. For public sector clients, there is ever more scrutiny of proposed spend. This can be in the form of ‘efficiency challenges’, or the ever-increasing ‘more for less’ demanded in the regulated asset sector. Without embracing new technologies, these organisations risk not making the case for much needed investment in capital infrastructure. In the ultra-competitive, low-margin, volume-driven world of contracting, there is a necessity to embrace these new technologies where there is demonstrable value to win work and preserve the necessary volume. Even for those on long-term frameworks, the requirement to drive year-on-year efficiencies required by regulators will necessitate new practices.

Chhabria: One of the main risks organisations may face is believing that applying the same methods will derive different results. The adoption of new technologies, such as the use of advanced data analytics, may be the key to unlocking much needed productivity improvements. In an increasingly competitive landscape, failing to implement new technologies may erode a company’s competitive advantage. Whereas some first movers are already reporting success stories, others risk witnessing their operations become obsolete. There is also a risk that, as projects become more complex and the volume of data increases, project practitioners may lack the tools to manage the exponential influx of information and understand the existing interfaces. This may have an indirect impact on project decision making. Lastly, for an industry with narrow margins historically, missing the opportunity to reduce costs by using the latest technology may put organisations under additional financial pressure.

FW: Looking ahead, how do you expect the demand for advanced analytics to grow as part of capital programme management in the years ahead? What are the key new innovations and analytics solutions on the horizon?

Girgis: Looking at the current landscape across the industry, it is possible to claim that the demand is already here. Across the industry, project owners and their supply chain counterparts have a growing appetite to fully unlock the benefits of advanced analytics rather than stay stagnant in the ever-evolving technological landscape. Dependent on the project’s stage in its lifecycle and the organisation’s digital maturity, there are varying levels of demand in the market between management information (MI) reporting analytics, self-organising analytics and predictive analytics. From an innovation perspective, techniques and solutions based on machine learning, cluster analysis, descriptive analysis and behavioural analysis will have a positive impact on the industry.

Scopes: A condition for success is long-term pipelines of work, which allow project owners and supply chain partners to invest, experiment with repeatable processes and to learn. Therefore, we would expect to see innovation driven from long term mega projects, from the regulated asset sector and the utilities where work is let for a control period over several years. Ultimately, costs are driven by labour, plant and materials. Labour utilisation and optimisation could be delivered through wearables, which are now ubiquitous and which provide safety benefits. Plant can be better optimised through the analysis of telemetry and utilisation, but also driverless muck-shifting plant which has already been trialled. Materials and the associated logistics are already experiencing a revolution through off-site manufacture, but the use of artificial intelligence (AI) could make great strides in optimising these off-site factories.

Chhabria: Organisations are already building their digital capabilities and exploring disruptive technologies with the aim of taking delivery and operations to new frontiers of efficiency and control. This is not a surprise as research has been showing a growing market within capital projects for new technologies, including data analytics, for the last five years. Walking around a construction site can provide a snapshot of what is to come. As the cost of devices drops, organisations are already piloting internet of things (IoT) solutions, such as wearables, sensors and drones. Back in the office, it is expected that the adoption of platform, infrastructure, data and software-as-a-service will make organisations more flexible and able to address their business needs. As organisations bring in more tech-savvy resources, these solutions make it easier to pilot AI solutions that can, for example, assist designers in creating design options faster based on the knowledge inherent in their databases.

Dullage: Advanced analytics are already firmly on the agenda for most major capital programme organisations, and while maturity levels are still relatively low, as the benefits become more apparent it is likely that demand will rise. Opportunity areas are plentiful. AI will, at some point, be used to optimise delivery plans and predict the outcomes of capital projects. For delivery teams and asset owners, digital twins powered by analytics will bring together multiple data sources to model assets and processes through construction and operations. 5G should also be highlighted, as it will aid in connecting fully IoT devices to automate and control on-site activity. One can also expect further digitalisation of existing processes to improve efficiency and data quality. Finally, blockchain and smart contracts will be very useful tools to support commercial management.

Anil Chhabria has over 20 years’ experience in IT delivery where in the last six years his focus has been in developing and innovating enterprise project controls solutions driving improvements in major programmes. He has experience in multiple sectors including telecommunications, defence, transportation and oil & gas, where he was involved in shaping, leading and delivering complex industry-leading integrated programme controls solutions. He can be contacted on +44 (0)20 7303 4943 or by email: achhabria@deloitte.co.uk.

Hugh Dullage leads the capital projects consulting team in Deloitte’s advisory business and specialises in helping clients define their strategy and build their capability for delivering major capital programmes. He has a particular interest in innovation and how it can be applied to improve the delivery of capital projects. His recent experience includes some of the UK’s biggest infrastructure programmes covering high speed rail, wastewater and fibre roll out. He can be contacted on +44 (0)20 7007 1311 or by email: hdullage@deloitte.co.uk.

Hani Girgis is the global digital lead for infrastructure and capital projects. In this remit, his focus has been on the programme management, planning, design, implementation and delivery of large-scale data and analytics driven technology programmes in the capital projects space. He has supported major UK capital projects clients across transport, defence and rail sectors. He has also led key mega projects in the Middle East. He can be contacted on +44 (0)20 7007 9916 or by email: hgirgis@deloitte.co.uk.

Rob Scopes leads Deloitte’s programme leadership practice in the public sector and focuses on leading transformation programmes to deliver operational efficiency for clients with significant infrastructure and real estate assets. He has advised on many of the UK public sector’s mega projects in the capital projects space. He has 30 years of broad experience, having worked and qualified as a chartered civil engineer. He can be contacted on +44 (0)20 7007 8629 or by email: rscopes@deloitte.co.uk.

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