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It introduces four flow-focused metrics: Cumulative Flow, Throughput Analysis with Demand Analysis, Cycle Time, and Lead Time, outlining how each supports understanding. The discussion distinguishes leading indicators from trailing indicators, providing early-warning signals for feedback and course correction. 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This paper presents a useful set of metrics that reveal how work is flowing. It describes four metrics we find useful: Cumulative Flow, Throughput Analysis combined with Demand Analysis, Cycle Time and Lead Time.  \n1. INTRODUCTION  \nFor many of our teams that are adopting agile approaches to work, a common question they have is which metrics are appropriate. There are many metrics to choose from. We work with teams to focus on the end-­‐toend flow of work through their organizations, and what it means to deliver value to their customers. This paper describes a number of metrics that many of our teams have used successfully to generate insight into how they are working. The benefits include increased visibility throughout the organization about how they are working, and the progress they are making. By distinguishing between leading indicators and trailing indicators, some of these metrics offer “early warning” signals that allow teams to incorporate feedback and correct course. We have found that each metric offers specific benefits, and reveals something about the organization. The combination of some or all ofthe metrics offers a wider perspective.  \nSection 1.1 of this paper provides some background information and context for why we tried these metricsand adopted them into our development process. It describes some of the teams that use these metrics, and some of the challenges we were facing. Following that, each of the metrics is described in its own section. Each section includes a description of the metric and an example. I use A3 problem solving approaches (Sobek and Smalley, 2008) . The use of these metrics resulted in many cases from observed problems such as lack of visibility. To reflect the learning, the metric descriptions reflect most of the sections of an A3 problem report, including context (or background), problem description, impact, countermeasures, and actions. I also include some follow-­‐up learning, including the use of each metric as a trailing and leading indicator, and any perceived shortcomings. Section 6 describes some lessons learned, which includes some of the advantages we have seen, some of the challenges that still remain, and some recommendations based on our experience. The paper concludes in Section 7 with a review of the metrics and some references to other relevant papers and books.  \n1.1 Background  \nWe have programs where multiple teams contribute to the development of a product. Some of those teams develop components that are used by multiple product teams. The teams work in two-­‐week Sprints, and atypical program length can be 3 to 9 months. Value streams are organized as programs. Most programs have dependencies between teams and dependencies on teams or deliverables outside of the program. We have no programs with single teams. Average programs coordinate the work of 10-­‐15 teams, sometimes up to 25 teams. We try to ensure that most teams are collocated. Most programs include teams from multiple geographic locations and multiple time zones. We try to ensure that each geographic location has as much autonomy as possible, in terms of area of responsibility, required skills, and roles. We try to ensure that dependencies are minimized between sites. We generally work in a “fixed scope, variable content” mode. This gives us the certainty of planning for specific release dates, while acknowledging the exact content of the release cannot always be predicted in advance and will most likely change over time as we get closer to the release date.  \nOur teams faced several challenges, including communication, coordination, and alignment. This paper focuses on one particular challenge: visibility into the flow work. Demonstrations at the end of each Sprint often focused on","cbCain5sFwf12CBZ","https://ap.wps.com/l/cbCain5sFwf12CBZ","pdf",312659,"English","# 1. INTRODUCTION\n## 1.1 Background\n## 1.2 Workflow States\n## 1.3 Leading Indicators And Trailing Indicators\n# 2. Metrics (described in later sections)","[{\"question\":\"What problem does the paper target in agile and lean teams?\",\"answer\":\"Teams need visibility into end-to-end flow of work rather than focusing only on individual sprint outputs. The paper addresses how work fails to flow smoothly and how progress reporting can be insufficient.\"},{\"question\":\"Which four flow metrics does the paper propose?\",\"answer\":\"Cumulative Flow; Throughput Analysis combined with Demand Analysis; Cycle Time; and Lead Time.\"},{\"question\":\"How does the paper use leading and trailing indicators?\",\"answer\":\"Leading indicators provide early warning about potential future issues, while trailing indicators reflect what actually happened. The combination offers a broader perspective for feedback and course correction.\"}]","Metrics for Understanding Flow - write-up | PDF",1792977046]