Why is Data Analytics important to PMOs

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Trends in big data and business analytics are growing year on year.   Project Management and PMOs need to stay up with trends to maintain and increase performance from projects.  Data analytics is at the core of changing the way PMOs can add value.

Where to capture data

Using data to change the way projects are delivered is not new.  But the level of capture and analysis possible continues to increase.  Many Project Management Offices do not retain data or analyse trends.

There are 2 main areas data might be collected for use in improvement of project and change value.  The first opportunity is in project execution.  Here we have a wealth of data that is recorded on project progress, risks , issues , testing, stakeholder feedback and others that can provide the foundation for qualitative analysis.  It’s an opportunity missed to not use this data.  Yet most lessons learned, and project process improvement still relies on people involved in projects to give mostly subjective feedback.  This leaves us with a weak impression of what went well and what can be improved.

Using data on business process and market trends is the second core area.  Business and industry sector information is not in the direct control of PMOs.  But with the right tools could be invaluable in helping to select the better projects.  Leading PMOs down a path to help maximising return on investment.  Sales and marketing hold the market and sector data.  Process improvement groups might be a solid source for internal procedures.  Clearly picking the best cost reduction and efficiency projects is attractive.

Improving Project process and performance

Any project environment where plans are built and maintained, and other project controls are actively used have a huge pool of data that is ready to be mined.  Information on task areas that differed from the original plan is just one example. Items that were ahead of schedule or took less time than planned can help to tune future plans.  Those activities that took longer can be analysed to identify the issues and remove or reduce them.  Risks can be more visible up front.  Extend this thinking to all aspects of delivering projects and you can establish a self-improvement cycle.  Outputs can be improved with feedback from testing stages and data recorded about errors.  This can  lead to mistakes and errors being trapped earlier in projects.  Lesson learned processes can become automated cycles that inform all new projects.  The project process itself can evolve and adapt to changing needs.

Improving Project selection and benefit

While improving project process to deliver projects better is desirable.  This value is likely to be insignificant when compared to driving the right blend of projects.  Using market data and internal company data to drive the best projects will offer significant return.   Blending a mix of projects to enable companies to improve overall process, both internal and external is key.  Over time this leads to better products and services and a stronger market share.  Organisations of all types will need to embrace these approaches.  Once they start to show significant improvement those who do not commit to this type of approach will not compete.

 

PMOs that are just admin centres booking meeting rooms and collecting project status reports cannot survive in the data driven world.  They will be disbanded, or worse still,  the organisations they serve will fail to deliver change.