Transnet, the primary freight logistics company in South Africa, relied on @RISK to assess infrastructure expansion, to better understand the risks that might arise during large-scale and complex capital projects.
Managing the delivery of all necessary goods within a country is not a simple task. It can require the careful coordination of ships, ports, railways, and pipelines to ensure that citizens, no matter where they are, get the goods and services they need. Expanding this system to accommodate more people and growth can be a daunting task, and requires careful analysis of the potential risks that could threaten the schedule, cost, and efficacy of the project. In this example, Transnet, the primary freight logistics company in South Africa, relied on @RISK to assess the expansion of their infrastructure, using the software to better understand the risks that might arise during large-scale and complex capital projects.
Background on Transnet
Transnet is wholly owned by the Government of the Republic of South Africa, and is the custodian of the country’s freight railway, ports and pipelines infrastructure. According to Transnet’s market demand strategy, the organization must make a capital investment of $28.9 billion between 2013 and 2020 to build capacity to meet validated market demand that will enable economic growth.
Transnet Capital Projects (TCP) is responsible for the development and execution of capital projects related to port, rail, and pipeline infrastructure. TCP currently has approximately 130 projects in its portfolio, which can include conveyor belt installations, quay walls, rail rehabilitation, wash bays, new railway lines, pipe rack installations, fire equipment installations, and building rehabilitation, among others.
Francois Joubert, the National Program Risk Manager with Transnet Capital Projects, was charged with determining the key risks across the different projects in the TCP project portfolio. “It is a complex project environment. The projects are spread out over the country, they involve many different internal and external stakeholders, the nature and scope of the projects vary greatly, and the cost ranges anywhere from ZAR2 million to 6.5 billion (US$187K- US$609M).”
Some of the attributes contributing to the complexity of appear in the next table:
“A project can be a like-for-like replacement, requiring a team of three people, costing less than 5 million Rand (US$465,000), and have a duration of three weeks,” says Joubert, “or it can be a port infrastructure project with multiple stakeholders, costing 6 billion Rand (US$558M), involving 150 people, and requiring complex engineering and procurement which takes five years to complete.”
Decision Analyst, Unilever
@RISK at Play
TCP already had a quantified project risk management approach implemented using @RISK in which the risk register template could model the following types of consequence:
- Time delay only
- Time variable cost
- Time variable cost + Additional Capital
- Additional Capital
Joubert was tasked to use the existing risk registers and identify the following:
- Where in the risk breakdown structure (RBS) and project type do the most significant risks appear?
- In which risk types and project types do the most significant risks appear?
- What is the influence of project start delay risks on the project portfolio?
To enable this approach, the 86 risk registers were copied into a single risk register. Each of the risks were linked to a three-Level RBS, their risk type, and whether they delayed project execution or not. Each of the projects were in turn put into a specific project category. The final model contained 1064 different risks, falling into five risk types, belonging to 86 projects, and categorized into 16 project categories. The screenshot below shows how the final model made provision for ten different attributes which were analyzed using @RISK.
“Using the @RISK functions RiskBinomial, RiskPoisson, RiskPertAlt, RiskLognormAlt, and RiskOutput, combined with a whole range of Lookup and SumIfs statements, some named ranges, and with conditional formatting, I was able to build a representative model,” Joubert explains.
The results have been presented to Transnet and are going to be used to identify the root causes of these portfolio risks.
Joubert says that Palisade software made this project possible. “It’s an excellent decision-making tool; it provides scientific, defendable numbers for contingency, risk ranking, etc.,” he says. “There are too many useful features to count—but its flexibility of use, particularly because it is Excel based—may be the most valuable.”