I am looking for heads up for Statistical tools to make informed decisions in constriction apart from basic mean, median & mode 

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Clement Gunasekar CCP
Senior Project Controls Engineer
Turner & Townsend
Bristol
07866145513
clement_dominick@yahoo.co.in
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Monte-Carlo Simulation (MCS) is the most common technique for conducting statistical analysis for decision making in construction, beyond mean, median and mode. 

Tableau can be used to visualize the MSC outputs to aid decision-making. You can do all sorts when running Python scripts, including MCS, but I'd be cautious of using unverified models and those that could not be assured at this point. Typically, @Risk by Lenovo (excel based) and Oracle Primavera Risk Analysis is used for Quantitative Cost and Schedule Risk Analysis respectfully. Other popular tools are Safran Risk and Acumen Risk. 

Reach out if I can help in anyway. 

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Jareth Reeves
Director
ProBid
Birmingham
07706353657
Jreeves@pro-bid.co.uk
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Hi Clement,

I would like to share the below information that may help you:

Good Faith (LLC) has launched a global-first software for performing Forensic Delay Analysis, ClaimEOT. Moreover, ClaimEOT provides daily delay insight and identifies dynamic critical paths on any delay day. Thus, it can be used for Project Control, Claims Management, and Dispute Management.

ClaimEOT's features can be understood from the video (which can be found on their web page https://claimeot.goodfaith.app/home/overview).

You can reach me if you wish to know further details.

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Sagaya Kuttappan
Director
Good Faith (LLC)
Dubai
+971553689767
gf.sagaya@gmail.com
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Hi Clement, I realize I am a bit late, but I know of two libraries you can look at:

SciPy and reliability (which mostly extends SciPy for use in reliability engineering) 

There is also numpy and pandas for more general-purpose data wrangling / analysis.

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Konner Horton
Atlanta
khorton@aldeaservices.com
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Hi Clement,

Depending on the analysis and outcome you are looking for you can definitely use both.

Tableau is specially useful for quickly plotting and assessing your data, including identification of outliers, without any programming skills. It has also forecasting algorithms and trend features that can be really helpful in a few clicks.

For something more robust then Python or R languages will be the recommendation, but again, depends on your specific case.

Best Regards,

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Joao Dias, MSc, PGDip, PSP, PMI-SP
Director, London UK
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