#QB10x10 Infrastructure: Quantifying Uncertainty and the Butterfly Effect

By Oliver Fleming, COO Asia and Marco Diciolla, Analytics Engagement Director, QuantumBlack

We continue our 10x10 series in celebration of QuantumBlack’s 10th anniversary with a piece exploring how data has transformed the infrastructure sector.

Infrastructure projects have always been one of the strongest economic forces for the long-term prosperity of countries around the globe. From airports, highways, transport, oil and gas plants to housing developments; the infrastructure sector impacts all of us and can change lives.

Historically, companies in this sector have relied on experience and market information to inform their decisions. However, the industry now faces major challenges. Projects are increasingly complex and more ambitious than ever, the mobility revolution is ushering in a generation of autonomous and electric transport options, and new energy sources pose questions around how we power the society of the future.

This series of articles would usually chart the changes that data has brought to an industry over the past decade, but in truth the infrastructure sector has seen few changes in this area. Despite a wave of fresh developments and challenges, the industry continues to work from an outdated operating toolkit. Although there are some exceptions, investment in analytics and digital technology remains low, resulting in — unsurprisingly — low productivity gains.

Infrastructure has not yet started to scratch the surface of the potential performance improvements that advanced analytics can deliver. Analytics has already transformed a variety of sectors from sport to automotive, and at QuantumBlack we have seen first-hand how quickly early adopters gain competitive advantage. Over the next decade we expect to see the sector embrace the power of analytics to unlock opportunities and in turn it will transform its core operating model.

Managing the butterfly effect through a data ecosystem

In order to appreciate how transformative future changes can be, we need to understand how these businesses operate today.

Typical infrastructure projects involve a vast array of players — subcontractors specialising in all phases, from initial concept and funding through to design, construction and eventual management of the asset. Each comes with their own individual objectives and value chains, feeding into complex projects that often span years.

With so many moving parts, infrastructure projects tend to be a hotbed of uncertainty. Even small errors from one subcontractor can have a knock-on effect, resulting in delays, budget overspend and even safety issues in the wider project.

Yet the complexity of infrastructure projects is precisely why this sector is ripe for an advanced analytics revolution. Creating a shared data ecosystem would consolidate the mountains of information each contractor generates and provide opportunities for marginal gains at each stage, alongside learning opportunities for future projects.

This ecosystem would install a collective goal in place of the piecemeal objectives which currently dominate every project. For example, a shared ecosystem focused solely on supply chain during the construction phase would enable all material arrivals and handovers to be tracked and highlight opportunities to optimise for time or budgets — rather than relying on a delivery contractor to log a step, before flagging to the construction contractor.

Of course, various subcontractors may have certain commercial sensitivity and elements of their activity which will remain solely in their purview. But there should be a golden thread of connectivity — whether that’s to optimise for time during construction or creativity during design — that benefits the project as a whole.

Opportunities to optimise efficiency extend past design and construction into the asset operation phase. Continual monitoring and tracking of an asset such as a rail network will help understand the living needs of an infrastructure system, providing chances to identify and address bottle necks which are more difficult to highlight with manual observation.

This ecosystem mindset would help quantifying the uncertainty that runs rampant in infrastructure and understand the causal structures within every project. But in order for this shared data economy to be realised, individual companies need to adapt first. Those who are quick to take on industry leader role will not only drive the change but will also stand to capture competitive advantage the quickest.

A new organisational operating model

In order to seize the opportunities that analytics present, infrastructure companies will need to start adopting a more agile, collaborative mindset commonly found in tech organisations. Below are some key elements to remember for any infrastructure company taking its first steps into advanced analytics:

• Incomplete data is better than no data: There is a common misconception that huge volumes of data must be harvested to gain value from it. At QuantumBlack we believe that variety is better than quantity. Start with what you have — and be creative with it. Use external data sources when possible to complement your analysis and gain new uncovered insights.
• Prioritise value: It is important to choose the right starting point that can quickly demonstrate the impact that analytics can deliver. Focus on value and key questions that are central to business to build momentum.
• Adopt the ‘VC’ mentality: The complexity of projects provides an almost uncapped potential to deliver value. Build a vision for your organisation that comprises a portfolio of opportunities and assess their value and feasibility against that vision. Deploy a cascade methodology that allows your team to develop analytics capability and scale-up projects over time.
• Embrace change: The current culture and processes of many infrastructure organisations poses a challenge. The industry tends to put trust in individual experience and expertise over a more quantitative data driven decision process. Few companies hire data scientists and it is rarer still to see technical people embedded within the core business. The result is that these individuals end up pursuing academic papers instead of being focused on business outcomes. Leaders need to push for a mindset shift across every level of the organisation in order to accelerate significant change.

Who dares, wins

Infrastructure’s complex value chain affords tremendous opportunities to drive performance through analytics — and more importantly, learnings for future activity. The technology and talent are both available today, but the industry will need a significant shift in mindset if it is to take advantage of either in the next decade. Adopting a focus on ecosystem over individual objectives and re-evaluating how to appeal not just to data scientists and engineers but all data-relevant disciplines such as UX designers will be key.

If this cultural shift occurs, we can expect analytics to unlock and far more productive era for infrastructure. A fresh roster of projects completed on time, on budget, with a better safety record and with learnings for future will benefit the industry as a whole but could also win the sector some much-needed public support after years of white elephants dogged by problems and delays. Data-optimised infrastructure opens doors for governments to be far more ambitious and forward-thinking with the national projects they undertake.

The sector needs to first improve their productivity challenges and data-driven solutions are an obvious driver of such a change. The only question that remains is who is going to lead this change and bring infrastructure into the digital age?