Mega Projects Performance & Predictive Analytics

Predictive Analytics have found fertile grounds in various sectors and applications over the past 2 decades; mainly in the financial and telecom services sectors and for such

applications in marketing, as for example, for customer churn prevention, fraud detection, cross & upselling campaigns, credit scoring, etc. 
Most recently, the new buzzwords and capabilities in the analytics world are the ones like Machine Learning and Artificial Intelligence.

In the manufacturing operations and maintenance, Predictive Analytics have been applied sporadically for preventive maintenance and even in more rare occasions for failure root cause analyses and online fault modeling for operator guidance and decision support.

Nowadays, the EPC industry is set to pay attention to Predictive Analytics as part of their #digitaltransformation and #EPC4.0 initiatives. In late 2018, a leading EPC, Fluor, announced an initiative to apply Predictive Analytics for project performance, and this is great news. Especially for those who pay the bill, that is, owner/operators of projects and #megaprojects.

Yet, you may wonder how this can be achieved. On one hand, history of projects data is needed.  The more projects’ history available, the better, and as long as the data is or can be normalized.

Secondly, such history should also contain extensive asset – specific work steps history for all phases; if possible, from FEL 1, 2, 3 stages, down to the detailed engineering, procurement construction and pre-commissioning phases.  When such data is collected, SEMMA (Sample, Explore, Modify, Model, Assess) methodologies can be applied to analyze and find related predictors and dependent variables, as for example cost, schedule and quality variations.

With the emergence of the above – mentioned initiatives (#digitaltransformation and #EPC4), in the EPC domain, it will be interesting to watch if and when owner/operators and EPCs take advantage of such possibilities. Megaproject performances over the years confirm that insight into past performances can be the mother of improvement.

Mega Projects, EPC 4 & Digital Transformation

Interesting white paper https://bit.ly/2GXB6hN on the subject of #EPC4 by German Think Tank. Very applicable and true for #megaprojects.

Despite the impressive results of #megaprojects, stakeholders (before, during and after) seem to agree that collaboration over all phases and all disciplines needs improvements, and so do the project data quality, integrity and interchange. Enter the hundreds of thousands of work steps involved in projects, this Think Tank team has a valid point. Obviously, #digitaltransformation and #EPC4 are related.  In their article, https://bit.ly/2GX6g8J, Forbes make also a great point, which,  although related to their own industry, rings a bell when it refers to silos of departments and data. Data that have to do with both ... assets and project work steps. Worth reading both links.