The 2014 incidents and subsequent outages at the Shell Moerdijk plant received a lot of media and industry attention. Incidents like this significantly affect the petrochemical market, both in terms of price and product flows. In general, 2015 showed unprecedented production issues in the European chemical supply chain, over 50 force-majeures had been declared across all polymers. Given the age of the European petrochemical production sites, operational reliability remains recognized as a major challenge to the industry today.
Given this operational environment, there is a strong desire to obtain quantitative insights in the long-term effect of supply disruptions on the value, forecastability and volatility of EBITDA and the effect of potential mitigation options. However, chemical supply chains are highly integrated networks, implying that a disruption in one plant affects operations throughout the entire supply chain. Therefore, mitigation measures need to be evaluated coherently. Furthermore, there is high uncertainty about the location, timing, and impact of the next major disruption, adding additional challenges to the investment decisions. After all, ‘nobody gets credit for solving problems that did not happen’.
To improve the insight in supply disruptions and potential risk mitigation options, our latest published research – jointly conducted with my former student André Snoeck and my former colleague Maximiliano Udenio – provides a methodology to identify, categorize and quantify risks and the impact of disruptions. A specific risk mitigation option impacts several risks, whereas a specific risk can be mitigated by several mitigation options. The kernel of the project is the development and use of a two-stage stochastic optimization model to analyze these complex interdependencies and dynamics in an integrated way.
We draw three main conclusions based on our research:
1. Supply chain risk mitigation investment trade-offs in the uncertain and interconnected chemical industry are not trivial and require advanced quantitative methods, such as stochastic optimization.
2. Smartly placed small investments may outperform a much more expensive poorly placed investment. For instance, a combination of small buffer inventories with reduced response times for external supply might outperform multiple investments in redundant processing capacity.
3. Investments that mitigate multiple disruptions are undervalued when considering disruptions and mitigation options in isolation. For instance, individual disruptions might not justify investing in decreasing lead times of external supply. Our advanced model that captures the entire supply chain shows the aggregate value that the investment provides to the network.
4. There exists a trade-off between long-term expected costs minimization and short-term risk minimization, where the latter leads to a more aggressive investment policy. This implies that an increased focus on a stable and forecastable quarterly EBITDA actually justifies larger investments in supply chain mitigation options compared to a long-term focus on expected future EBITDA. Ironically, this implies companies under private equity aiming short-term returns may need to invest more in mitigation measures than companies aiming long-term returns.
There is a clear need for the European petrochemical industry to take supply chain disruptions seriously. Chemical supply chains are integrated, interdependent, and complex systems and evaluating risk mitigation investments should be complemented by advanced quantitative models. Such methods are not new to the chemical industry, advanced models are being used to optimize cracker operations for years. Leveraging this capability when dealing with supply chain disruptions will positively impact the value, forecastability and volatility of EBITDA.
This article was published on LinkedIn in January 2019
Note
The text above has been written for ease of public access, and may contain texts that have been simplified for this purpose at the expense of scientific rigor. In-depth and verified information can be found in our peer-reviewed journal article published in the European Journal of Operational Research. The article is based on a Master Thesis completed at Eindhoven University of Technology.