When creating a forecast first ask yourself whether you are forecasting One Thing or Multiple Things. It’s not always clear which of these situations you are in but the approach you take to creating the forecast will differ significantly. This post will help you to figure out which approach to take. When forecasting Multiple Things the best approach to take is to use a Monte Carlo forecast. This approach creates a statistically significant probability distribution of delivery on various dates based on thousands of simulations using historical throughput data.

Over the past 15 years of working with various agile techniques, practices, frameworks, and strategies I’ve found that there is one thread that ties them all together. They are all focused on improving our ability to learn and to apply that learning to our future work. Test Driven Development creates a seconds long feedback loop to help us better understand our business logic and learn immediately whether the code changes we make have the intended effect.

One of the key practices supporting continuous improvement is making your work, and how you do the work, visible. This starts by tracking the progress of that work in a highly visual way, often by using a kanban board. Once that work is being tracked we can begin to gather that data and start to gain insights into where our biggest opportunities for improvement are, often by using the metrics defined in The Three Flow Metrics (Plus One).

Some of the best indicators of team performance are the flow of both new information into the team and of value out of the team. If we can improve visibility into these indicators, and therefore the opportunities for the team to improve the way they work, it becomes possible for the team to support their organization in ways they couldn’t before. There are three standard metrics that are core to understanding the effectiveness of any flow-based system.

Every organization needs some form of planning. Public companies often plan and budget quarterly. Large software companies like Google and Apple often have launch events scheduled far in advance. Other companies need to plan their launches around training cycles. Even small startups need to have some confidence that they can deliver their product before they run out of money. The problem that each of these organizations face is how to plan effectively - and cheaply.