This is part of a series of abridged white papers intended as quick reference sources for busy managers interested in the subject matter and faced with limited time to absorb lengthy research documentation.
It is based on research undertaken by Plandek drawn from anonymised data observed across a range of clients – from small start ups to large corporates with large scale, distributed Agile teams.
Purpose of this Paper
The analysis presented below is focused on the software development process – and is particularly relevant for Scrum Agile environments.
It is designed to give delivery managers a practical guide to the KPIs (easily seen within the Plandek dashboard) that most accurately indicate future issues within a particular team or project.
Reviewing these early warning signals regularly gives team leaders and delivery managers the ability to intervene early, in order to improve project outcomes.
The Top 5 Early Warning Signs to Identify and Review in Software Development Teams
The following analysis is based on Plandek research undertaken in-house and in consultation with a number of clients, partners and interviewees principally based in the UK, consulted between September 2017 and April 2018. All the metrics discussed are easily viewable within the Plandek analytics platform.
The top 5 KPIs found as indicative of future problem projects are as follows (in no particular order):
1. Lengthening cycle times - rising on-hold time within development 2. Rising return rates (tickets returned from QA/UAT to development for further work) 3. Reduced sprint target completion (and rising WIP queues) 4. Increased “parallel” work outside sprints 5. Persistent scope creep
Problem projects are defined as projects with rapidly declining velocity, late delivery and unplanned overspend.
All the metrics discussed are easily viewable within the Plandek analytics platform. Plandek currently integrates with the Atlassian stack – the analysis is therefore focused around companies using Jira as their principle workflow management tool.