Time and again we come across numerous articles, speeches and blogs on the transformations that project data analytics (PDA) could bring to delivering projects. There is no doubt in this as long as the nuances of data capturing are thoroughly developed and implemented consistently across the project profession.
Most of the information that is available on the benefits of PDA tends to ignore data capturing consistency and its importance is often missed out.
‘Rubbish data in is rubbish data out’ is a phrase that's commonly referenced by many who believe that the PDA life cycle is not meticulously developed. Having said that, I believe that project data analytics, reporting and the associated results can be well managed through appropriate software and skilled professionals. The remaining grey area is around consistency in ‘data capturing’.
To better understand this, let’s assume that PDA is education. We all know the importance of education and agree that it’s a pivotal part to our learning. Similarly PDA is vital to our understanding of projects; it’s the next big thing. When we think in this context then:
- Schools = PDA training centres
- Trained teachers = highly skilled PDA practitioners and data scientists
- Good sources i.e. books = lots of software and data related applications
- Curriculum = consistent data capturing templates
A curriculum is important because it imposes a level of discipline and if that isn’t followed, your path to education, or project data analytics in this parallel, could be haphazard. Lack of consistency when capturing data can create a skew or inaccuracy in the results and hence any reliance on that data to make decisions could pose challenges.
In a blog written by Martin Paver CEO of Projecting Success, he shares that “we’ve been working with the construction and oil and gas sectors to develop the concept of a data trust: a facility that enables us to securely pool data for the benefit of the collective.”
This construction data trust is formed of multiple construction companies who have pledged support and cooperation in data sharing. This is a vital step in improving projects, and more sectors should consider creating a data trust or data sharing programme. But it potentially leaves us with question of consistency in data capturing. Are all the organisations who share data, capturing it in the same way?
I have developed, monitored and reviewed multiple programmes and often look back at the data and actuals to develop plans for new programmes I work on. At the moment, using historic data to develop a programme is taken with a pinch of salt because in most cases one size doesn’t fit all.
There could be various parameters, situations and incidence changes that impacts the data we are using - which may not always be relevant for the project that you are using this data on.
For instance, a piling operation on open ground with no site restriction could be much faster compared to a piling operation in a marine environment in the winter season. If we use the data from one environment, to plan and manage a project in a different environment, it can cause issues and incorrect analyses. This is why we must ensure we have the right set of data parameters captured; it’s very important to standardise a data capture template across the industry.
Data analytics can help projects perform better; data that is fed into AI can help improve problem solving for example. If, as an industry we could come together and develop templates, which are consistent to capture data, we could enable even more project success.
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