During my ongoing stint in Quantitative Risk Analysis (QRA) world, regularly I used CPM based Scheduling Risk Analysis (SRA) tools to quantify time reserves using Safran Risk and Primavera Risk Analysis (PRA). However, there are more flexibility involved in Spreadsheet based QRA tools, particularly useful during Cost Risk Analysis (CRA). Here, I published a brief analysis of most of the QRA tools available and tried to score them against quantitative parameters to identify highly functional tools to use during CRA.
To support the human decision making and overcome biases in estimating timelines or budgets, Quantitative Risk Analysis (QRA) is heavily used across various industries such as Banking, Finance, Manufacturing, Energy etc. to find out confidence levels in meeting desired targets. Globally, there is an outcry from Top executives that project management industry lacks application of analytical tools to process the past and current data to assess performance and allocate required funding including suitable contingencies. Due to the lack of knowledge of Quantitative techniques, most of the employees get bound to use VLOOKPS, PIVOTS, COUNTIFS etc. which are all MS Excel built in functions, which made me to ponder over our inefficiency to shift into more analytical and data modelling approach using some add-ins for excel.
Due to advancements in programming languages such as Matlab, python and R, there is a growing community of users shifting into these techniques for data modelling for risk analysis, however it is still a challenge to learn coding and customize as per individual project requirement. There is a steep learning curve to explore these techniques, especially for construction project professionals with no prior programming experience.
Considering the potential of Statistical functions and its power of analysis on any given set of data sample or population, Excel is not user friendly with functions to evaluate current performance as well as foresight success of achieving desired milestones. It boils down with uncertain outcomes that team members cannot oversee unless evaluated using complex Excel formulae and data tables.
With respect to my experience of Construction Projects, Quantification of risks is done using Schedule Risk Analysis (SRA) or Cost Risk Analysis (CRA) or Integrated Schedule & Cost Risk Analysis (ISCRA) after incorporating CPM (Critical Path Method) schedule mapped with Project specific and systemic risks or Parametric & Expected Value (P+EV) calculations. Notwithstanding, most of the times Cost Estimates and overall budgeting process is performed in Excel spreadsheet after gathering relevant data such as Direct & Indirect Costs, Daily Running Costs, Work Package contingencies and management reserve. All these cost reserves call for heavy analysis in MS Excel using either pivots or VBA queries.
In order to determine contingency, it is required to perform Cost Risk analysis for project specific as well as systemic risks. This often starts with conducting focused sessions, interview, risk workshops along with project team members. Here, I want to specify that management needs to shift from conventional Excel templates built using PIVOTS and their basic formulae to more sophisticated data modelling aids such as
Each of these Quantitative Risk tools are measured against various probabilistic & other statistical parameters to generate a score as ‘1’ if it fulfills the selected parameter while “0” if it does not fulfill the parameter. Tool with highest score is capable in performing most of the Quantitative Risk analysis functions.
Category – 1 Technical Specifications
Category 2 - Reporting Specifications
After Combining ratings from Category 1 & 2 above, following overall scoring is generated as following
It is found out that ModelRisk by Vose Software scored highest, followed by @ Risk by Palisade in terms of technical as well as reporting functionality based on Quantitative analysis parameters.
Your thoughts are welcome on any of these products !!
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Disclaimer:
The views expressed in this article are those of the author and do not reflect or represent the official policy, position or recommendation of any individual or organization. Any written or verbal recommendation has a general nature and should not be used for any decision making without further assessment for specific project and organization requirements.
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