PMOz Book of Abstracts (Sept. 2013) (Sept. 2013) | Page 9

Tuesday 17 September, 2013 11:40 – 12:20
Autopsy of a failed agile project or Death of a thousand cuts Evan Leybourne Author Directing the Agile Organisation

It is commonly accepted that at least 60% of all ICT project fail by one or more criteria including; schedule, budget, maintenance & return on investment. While agile projects fare better, this still implies a large number of failed projects. This presentation will forensically examine a failed agile project with the goal of helping project managers avoid similar issues in future. Issues (and possible resolutions) that will be discussed include; customer engagement, staff skills & capacity, stable environments, low team morale, and scope creep. The specific attributes of failure I will be looking at are; 1. Lack of customer engagement: Without a fully engaged customer, with well-defined user stories, it is impossible to deliver to the customer’s needs. 2. Unfocused development: Developing a combination of customer driven and non-customer driven work in order to develop a stable framework causes significant delays in measuring business value. 3. Poor project scope at inception: Lack of clarity on the end goal (and which stories were most important) reduces developer productivity and can prioritise the wrong stories. 4. Understaffed: Reduced team size (or incorrect team structure) can cause significant delays in development, especially if this is in key roles. 5. Competing Priorities: For example, team members may only be able to realistically allocate 50% of their time due to BAU commitments. This can be hard to manage to the scrum master. 6. Underlying architecture design: If the underlying framework is poorly documented and underdeveloped, this can cause delays and issues early in the project. 7. Unstable development environments: There can be significant productivity loss if the development, test and UAT environments are not available on demand. 8. Poor quality (or inconsistent) test data: Poor test data can cause inaccurate tests results (both false positives and negatives) resulting in additional rework after a feature is released. 9. Low team morale: If team morale is not address (for example, due to lack of delivery and a low understanding of project value) team productivity is reduced and in turn can lead to even worse morale. 10. Lack of business SME’s for rule definition: The customer needs to provide access to a subject matter expert to avoid unnecessary rework and project defects. So, how can you identify these issues early and mitigate them before they become serious? This presentation will propose several possible mitigations, methods for bring a project back from the brink of disaster, and finally exploring why some projects are not suitable for agile methods.

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©PMOz 2013