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Big data is an approach being explored in various areas of modern life from health care to crime prevention. Predictive algorithms are most widely developed in stock market systems, but also maturing quickly in weather forecasting and other fields.

Can PMOs use the tools, techniques and methods found in big data systems to good effect in improvement of project delivery and the effectiveness of portfolios?

Graph1Firstly, the data set collected needs to be of sufficient size to allow effective modelling of projects within your business setting. Over time data collected in the PMO can be used to increase the accuracy of project plans from both a resourcing and financial basis. This in turn will allow increased early warning of common problems.

The issue most portfolio management offices have is the time it takes to get more meaningful data samples. The short term solution to this issue would be to share raw data in a form that is helpful for project forecasting but structured in such a way as to not disclose commercially sensitive information. But there are few service offerings that allow the collection and sharing of information.

Graph2The use of predictive analytics for projects of all sizes is useful for many organisations, the project management specific tools that will be developed over the coming decade are likely to allow significant differences in the way projects are selected and initiated. They will make risk management more proactive driven by underlining knowledge not just the experience of the project management team. This approach will allow better estimating and increased certainty of delivery timescales.

Embracing Graph3such an approach early will help project and change managers get ahead of the current game. If your PMO were able to start data collection across projects, you can begin to establish a foundation for improvements.

We have the basic tools set to help you begin to use this approach. If you are interested in learning more of how you might apply this to your PMO click here