App Development company in San Francisco often insists on relying onto credible outcome measure to quantify and improve the productivity and efficiency of their software development teams. Improvements in these numbers do not warrant that your customer satisfaction levels will rise by leaps and bounds; but if a developer feels more productive, they’re more than likely to deliver better work faster.To understand how to enhance productivity, it is important to understand and determine what factors lead to perceptions of productivity; by effect of which we can help a software development team feel more productive more often.
The metric measure should monitor continuously to make incremental improvements to processes and production environments. Tallying the number of lines of code and the number of software bugs is not a reliable measure. It is a performance metric representing activities, not outcomes. Activity metrics tell organizations very little about the true bearing on business goals and focus on the busyness of the team instead of signifying business value dished out. Flow metrics relatively corelate better with the generation and protection of business value.
For agile and lean processes, the basic metrics are leadtime, cycle time, team velocity, and open/close rates. These metrics assist with planning and notify decisions about process improvement. This process itemises how long it takes for the team to go from an idea to delivered software andhow long it takes to make a change to the software system and/or deliver that change into production. These metrics also reveal how many “units” of software the team typically completes in an iteration/sprint and how many production issues are reported and closed within a specific time period. The general trend matters more than the specific numbers.
Production analytics include a calculation of Mean Time Between Failures (MTBF) and Mean Time to Recovery/Repair (MTTR). Aging reports on the other hand, reveal how long work has been sitting in the pipeline or stays stagnantly undone. Looking at all the work that’s been in the system for more than 30 days (or 60 or 120 days) shines a constructive light on how much waste is in the system. This example compares the average duration of work items and highlights the ones that are taking longer than the average.
Keeping pace with the future requires change. Mapping metrics is a useful consideration when it comes to transforming the way teams work to produce desirable outcomes that help improve decisions. When time-to-market is apreferred outcome, measuringflow time is a saviour; however, when efficiency is the concern, calculating flow efficiency to see where bottlenecks exist, comforts as it improves flow.
If teams are dealing with unplanned work and/or conflicting priorities, measure the amount of Work-In-Progress (WIP) to expose over allocated teams. When it comes to efficiency, time is wasted when there is too much focus on resource efficiency versus flow efficiency.If important unfinished work (such as fixing security vulnerabilities) is neglected, measure the age of partially completed work to expose risks. Metrics should be used to learn and only if they provide evidence of serving effective improvements.