Construction productivity is often considered the lowest across all industry sectors. The latest report by McKinsey Global Institute highlighted that the construction sector globally has remained stagnant over several decades.
In the UK, the widening gap between the productivity of the UK economy as a whole and the infrastructure sector amounts to approximately 30% or £10 billion annually (Office of National Statistics). This gap aligns closely with the projected cost of funding Net Zero Carbon in the UK by 2050, according to the Institute for Government.
Closing this productivity gap would help provide the financial means to meet climate change obligations. This is a similar case in France and across the EU where increasing productivity could help save cost and address skills shortages according to the ING Group.
Whilst it would be naive to claim that a perfect digital Project Management Office on every infrastructure project would achieve this, integrating technology and data skills into the PMO can play a vital role in addressing the gap.
The Relevance of the Digital Project Management Office
The digital PMO integrates digital tools, data analytics, and technology across multiple PMO-related disciplines to maximise efficiency. It builds capability in synthesising information and presenting conclusions and inferences in an impactful and understandable manner.
An effective digital PMO needs skilled practitioners who can communicate across multiple domains such as project planning, scope definition and requirements management, contract administration, estimating and budgeting, change management, information management and so on.
“Governance mechanisms are key to maintaining the integrity and reliability of data, supporting informed decision-making across various business processes.”
What is Productivity anyway?
In this context, productivity is defined as value-added divided by people hours.
Data from the Chartered Institute of Building Productivity (USA-based Construction Industry Institute) and Assystem’s own industry survey (research complied from multiple practitioners globally) shows there are three factors for improving productivity:
1. Understanding variability
2. Communicating effectively
3. Forecasting outcomes reliably
“It is the digital equivalent to a library with books stored on the appropriate shelf, and indexing systems to relate publications to each other and track their usage and location. But it is all too common for practitioners to arrive on a project, close to handover, to find the digital equivalent of a haphazard pile of books on the library floor; unused, ignored, and invalidated. A value destroying image if ever there was one” says Iain Cameron, PMO technical Director UK.
A Digital PMO to Understand Variability
Using the initial business case, final business case and project cost and duration data, the digital PMO can group elements into statistically distinct groups called ‘reference classes’. The analysis allows practitioners to estimate the effect of ‘unknown unknowns’ even in the early capital commitment cycle. This technique is used and understood at the ‘project type’ level, but there is a global focus on developing the technique for more specific scope elements. This allows the digital PMO to contribute effectively to developing certainty of cost or time estimates.
Classifying scope is important here, and the digital PMO uses two main structures: Asset Breakdown Structure (ABS) and Location Breakdown Structure (LBS). The ABS is generally used across multiple projects while LBS is project specific. The intersection of both forms the Control Accounts, held within a Work Breakdown Structure (WBS) which can be divided further into Work Packages with delivery phases or applied to different contracts. This classification is established in a master data environment or data model, and the digital PMO assists in setting up and maintaining this structure.
For example, on a recent assignment, an infrastructure owner wanted to group scope into groups with primary units of measure against each group, to allow tracking of variability in cumulative and monthly performance during delivery. Using a control account structure where each lifecycle stage in each contract was also allocated to the ABS and LBS allowed this standardised approach. Further, this coding allowed visualisations of design intent to be easily filtered and searched across the programme, by asset or location.
A digital PMO to communicate effectively
In dynamic organisational settings, establishing a structured framework early on is crucial for efficient communication and information management. This framework, managed by the digital Project Management Office, simplifies data processes across the supply chain, reducing complexity and enhancing consistency.
The digital PMO’s functions, such as specifying information requirements, effective communication, and validating data, are all critical to the effective integration of the data.
This allows practitioners to be clear about the use cases for information and apply the concepts of ISO19650 to ensure that the level of information request is truly aligned with the level of information need. This helps avoid the metaphorical haphazard pile of books on the library floor; unused, ignored and invalidated; adding cost but no value to the supply chain.
Again, by way of an example, considerable personal productivity can be achieved in something as simple as collating relevant documents for a design review or section handover. Allocating documents to design or handover work packages within the ABS, LBS or control account structure allows related design, testing, commissioning, visualisation and asset-related documents to be quickly located and linked in a ‘visualisation hub’.
A digital PMO to forecast outcomes
Linking data together and using it to augment more traditional ‘earned value’ reporting and forecasting is helpful because it allows a comprehensive all-round view of project performance.
“This triangulation of hard numerical data, linked with simple on-demand dashboards or multi-dimensional visualisation against narratives highlights important performance signals. It can considerably improve productivity by, for example, making it considerably easier to retrieve information needed for a design review, commissioning rehearsal, or requirement validation.”
Linking multiple sources of data together and verifying their provenance with owners can allow insights that might not otherwise be obvious. For example, is the schedule analysis indicating a pattern of investment or resources that does not match current levels and is not actually planned at the ‘grass roots’?. If so, the schedule forecasts could be unreliably optimistic and need revisiting prior to the next period forecast.
Improving infrastructure productivity requires understanding variability, reliable forecasting, and enhancing stakeholder communication. These factors directly impact value creation and people hours, crucial for productivity.
To reduce people hours and increase value, key enablers include digital Project Management Office processes and data models, clear definition of information requirements, establishment of a digital PMO master data environment, and data validation before analysis. Effective communication, enhanced through visualisation, adds value. Simplifying data transmissions based on clear use cases ensures the digital PMO adds value, not cost.
Iain Cameron is PMO Technical Director at Assystem
