Optimizing availability of critical infrastructure

Background
Our client is responsible for critical infrastructure. The company has specialized technical capabilities which are highly leveraged by making use of external skills and delivery capabilities. Total value of underlying assets is more than €10 billion; while budgets for maintenance, replacements and enhancements exceed the €1 billion level. To stay relevant, steps are required to make the infrastructure smarter (for instance by adding relevant sensors and connecting/ collecting data). Increasing user value alone will not be enough: a more cost-effective approach is needed as well.

The crux
Novel ways of securing availability of the ‘enhanced’ assets are required to deliver optimal value for money. Several levers to seek this were identified and applied:
Steering on output: traditionally, the infrastructure was maintained based on input contracts. These specified the amount and type of maintenance needed. Contractors had limited incentive to work smarter or build expertise. To turn this approach around, first output levels were defined that are desired for satisfactory operation of the infrastructure. These included the peak capacity that the infrastructure was to accommodate, and the desired (un)availability (both planned and unplanned). Subsequently, contracts were awarded to contractors based on their ability and price to maintain the infrastructure at or above these output levels. This stimulated contractors to build expertise, work smarter and significantly improved the effectiveness of maintenance.

Seeking the desired trade-offs between non-availability and cost. In many cases unit cost of maintenance and repair proved highly dependent on the ‘scale on the project level’. Preparation, logistics and execution of replacement have a significantly lower unit cost when performed on the right project scale. Taking a multi-year, multi-unit perspective, opportunities for less frequent, larger replacement projects were revealed. These have both a substantially lower ‘total cost of ownership’ and a significantly lower non-availability – a counter-intuitive combination. With increasingly smart asset components, the fact-base for these decisions becomes even more precise and conclusive.

Defining the optimal scope and conditions for contracting. From a viewpoint of the potential contractor, economies of scale and scope were determined based on the output requirements (service level agreements) and basket of anticipated activities with their economics. Also, the market landscape of contractors was evaluated. This led to choices in geographic scale (size of contract area) and functional scope (combinations or segregation of functional areas). Time period and bonus/ malus incentives were determined.

How we did it
Management requested support in making the key decisions on the shift to output-steering on its extensive asset-base. In a series of projects, over a two-year period, we provided the economic insights required to make the managerial decisions on the above-described topics. In essence, we structured the decision-making by segmenting the big questions into logical elements. For each of these elements we created a logical and transparent perspective on economics by combining the client’s technological knowledge and operational experience with the actual accounting facts (project accounts of many projects, business unit accounts, …..). For larger elements we went deep into the specific cases. For frequent small elements we developed solid statistics.
Ultimately, our work also led to a set of functional specs for a future decision-support system for the company.