The successful management of projects is crucial to the survival of many organisations.
A key element of good project management is the ability to understand and manage risks. However, projects are becoming larger and more complex. This brings a number of challenges such as managing risks from an increasing array of stakeholders, the need to consider risks that go beyond technical and financial and the need to consider how different risks interact with one another. New approaches to risk management are required to tackle such challenges.
The following two projects demonstrate how the Department of Management Science has been looking to develop new approaches for project risk management.
The Northern Isles New Energy Solutions (NINES) Case
The power station providing most of the energy for the Shetland Islands required replacement.
Scottish Hydro Electric Power Distribution (SHEPD) designed the Northern Isles New Energy Solutions (NINES) project to trial a range of smart grid innovations. The aim was to reduce capacity constraints and increase exploitation of renewable energy resources and also to inform the design of the new power station.
Staff from the Department of Management Science were invited to help SHEPD identify, structure, quantify and work through the implications of risks relating to the NINES project with regards to the different design options as well as taking note of the wider environment as seen by key stakeholders. This work involved a range of stakeholders in a series of risk workshops to obtain, structure and prioritise risks on the project. A decision tree was also built to support the client in thinking through decisions they were required to make with respect to the design, size and location of the new power plant.
Ackermann, F., Howick, S., Quigley, J., Walls, L. and Houghton, T.(2014) “Systemic risk elicitation: Using causal maps to engage stakeholders and build a comprehensive view of risks”, European Journal of Operational Research, Volume 238, Issue 1, Pages 290–299
Over the last 20 years, management science staff have been exploring, and modelling, large complex projects to understand the causes of excessive cost and time overruns. Projects that have been analysed include multi-million dollar engineering and construction projects undertaken in both Europe and North America. In most cases a contractor and project owner have been in dispute regarding who caused disruptions and delays to the project.
When supporting contractors in a dispute situation, management science staff have built models to demonstrate how events on the project unfolded. This includes tracing time and cost overruns back through causal chains to the initial events that caused the overrun. Staff have also supported project owners by auditing models that have been built on behalf of the contractor and presented to the owner as evidence in a dispute situation.
Although each of the projects are unique, our learning highlights common reasons for project overruns. This has led to an understanding of the types of risks that can have huge disruptive impacts on a project. Learning from this work has then contributed to the development of new risk management processes which seek to highlight, and mitigate against, common risks that have the ability to create excessive cost and time overruns.
Howick, S., Ackermann, F., Eden, C., and Williams, T. (2011) “Delay and disruption in complex projects” In Meyers, R. A. (Eds.), Complex Systems in Finance and Econometrics: 116-135. Springer New York.
Howick, S., Ackermann, F., Eden, C. and Williams, T. (2009)“Delay and disruption in complex projects” Volume 2, pp 1845-1864, Meyers, Robert (Ed.) Encyclopedia of Complexity & System Science, Springer New York.
Howick, S., Eden, C., Ackermann F. and Williams T. (2008) “Building Confidence in Models for Multiple Audiences: the Modeling Cascade” European Journal of Operational Research Vol. 186, pp. 1068-1083.
Howick, S. and Eden, C. (2007) “Learning in Disrupted Projects: On the Nature of Personal and Corporate Learning” International Journal of Production Research, Vol 45, No. 12, pp.2775-2797.
Ackermann, F., Eden, C., Williams, T and Howick, S. (2007) “Systematic Risk Assessment: A Case Study” Journal of the Operational Research Society, Vol 58, No. 1, pp. 39-51.