Discovering the truth within the Government Major Projects Portfolio

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Discovering the truth within the Government Major Projects Portfolio

The UK Government publish an annual report on their top 143 projects but does it really illustrate the performance of the portfolio? James Smith has been instrumental in collating information distributed across nearly 90 separate spreadsheets to develop insights into how data analytics can help to shine a light on performance and challenge how approx £450 billion investments into public projects is reported. He will also be sharing some emerging insights from similar data within the US and Australia which help to illustrate the art of the possible and how this could influence project and portfolio level reporting within the UK.

He will take us through the challenges of defining the problem statement, into automated web scraping and data extraction, then into some of the issues with data visualisation. Lastly, he will be sharing some fascinating insights into the data, areas of interest and some of the challenges that need to be considered.

It promises to be a fascinating presentation that delves into a topic of huge relevance to all of us; if the portfolio increases by 10% it is the equivalent of one year of the annual defence budget and overseas aid budget combined.

We would like to change the format a little for this meetup to make it more interactive so everyone can make as much of a contribution as they want to. Immediately after James' presentation we will also be holding a short (45 min) workshop to exchange ideas on how to exploit some of the methods and also share ideas on potential improvements.

Please also sign up at the event location here ( https://skillsmatter.com/meetups/10621-discovering-the-truth-within-the-government-major-projects-portfolio#community ). It is important that you sign up with CodeNode too so that you secure entry.

Dr James Smith is the lead Data Scientist within Projecting Success and has a broad remit spanning data extraction through to machine learning; he has a passion for using emerging methods to transform how projects are delivered. He has an applied mathematics PhD and specialised in Orthogonal Polynomials and the Painlevé equations. He spent 2 years lecturing mathematics at the University of Kent before making the natural transition to Data Scientist in 2017. He is currently focusing his skills on some of the more technical challenges at Projecting Success.