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This is a great summary of where to get to in how you budget projects. http://www.agileadvice.com/2011/02/04/agilemanagement/calculating-a-budget-for-an-agile-project-in-six-easy-steps/ Most importantly, Using the definition of “done” add pre- and post- Iteration budgets Every agile team is supposed to be “ cross-functional ” but in reality, there are limits to this.  For example, in most software project environments, teams do not include full-time lawyers.  This limited cross-functionality determines what the team is capable of delivering in each cycle – anything outside the team’s expertise is usually done as either pre-work or after the iterations (cycles) are finished.  Sometimes, this work can be done concurrently with the team.  In order to understand this work, it is often valuable to draw an organization-wide  value stream map  for project delivery.  This map will show you the proportion of time spent for each type of work in the project.  Subtract out all the work tha

Estimated size needs to include all work done by any silo'd team to get the next iteration on the vertical slice to a done-done state in a agreed upon production or production like environment. That means that this includes qa, dba and sysadmin effort to get this out the door not just what a silo'd dev team does. That way the estimate accounts for the time it takes to wade through the red tape of db change requests, glitches in continuous integration, system config changes, qa effort including customer feedback and anything else that creeps up on the scope of delivering your Minimum Viable Product. Estimating across silos has several additional beneficial outcomes. 1. Metrics gathered from estimates can be used to retrospect the entire process and effort through delivery. 2. It's a start toward deeper collaboration and breaking down knowledge silos - anyone can call bs on an estimate as they learn more about what it takes to execute a change in a part of the system they a

This first article explains why you might want to store logs and BI data in a machine readable format. https://journal.paul.querna.org/articles/2011/12/26/log-for-machines-in-json/ The second two get at how you might do that and be able to transition/re-purpose your existing relational stores into a cloud based scalable framework.  http://docs.mongodb.org/ecosystem/tutorial/use-aggregation-framework-with-java-driver/ http://www.bityota.com/3-steps-to-analytics-on-mongodb/ Logging might present a relatively low profile target for schema-less implementation and give you a chance to expose your organization to an important technology for modern web development. With your foot in the door you might convince them to add usage auditing and before you know it you are doing up front analysis on usage in front of your next project.