We need a radical overhaul in how we deliver projects, and now is a good time to start, writes Martin Paver
When we emerge from the COVID-19 crisis, the government will be introducing several measures to stimulate the economy. Will the new world order provide the trigger we need to be bold and think differently about how we deliver projects? I certainly hope so, but investment in new approaches will be hard to come by. We need realism and to build momentum organically.
I am convinced that advanced data analytics lies at the heart of this. Now, more than ever, we need to be able to model the impact of delays on our portfolio, conduct scenario analysis, share our experiences of the impact of emergent risk, understand supply-chain dynamics and maintain critical capacity. We need to move beyond the world of spreadsheets.
APM’s recent Salary Survey found that 60 per cent of project professionals are using data analytics to some extent in their work. And momentum is building via the Project Data Analytics Community, a non-profit community offering designed to share best practice on leveraging data within a project, programme and portfolio environment. Nearly 6,000 people have now joined this initiative.
In wider society, we have seen the positive impact of community, with people working selflessly to combat the effect of the coronavirus. If we want to transform how we deliver projects, we need a similar approach. But we all need to recognise that our professional futures will look very different. We need to disrupt or be disrupted.
To get involved in the Project Data Analytics Community, click here. Join the big conversation on future trends in project management at APM’s Projecting the Future page.
Posted by Martin Paver on 18th Jun 2020
About the Author
Martin Paver BEng(Hons) MBA CEng MIMechE FAPM ChPP is the founder of the Project Data Analytics community of 6,000 people who have an interest in data driven project delivery.
He is the CEO and founder of Projecting Success, a consultancy that is pushing new boundaries in advanced project data analytics.