Business

When examining real workflow data, there’s a common pattern: clusters of tasks that have aged significantly, some clearly stagnating beyond recognition acceptable timeframes. These cases point to one of the most important yet very often overlooked metrics in flow management: WIP Aging. WIP (Work In Progress) Aging measures the elapsed time that a work item has spent in active progress but remains incomplete. This metric serves as an early warning system for workflow problems, helping teams identify where work gets stuck before it significantly impacts delivery timelines. Unlike cycle time, which analyzes completed tasks retrospectively, WIP Aging provides real-time visibility into current work, making it the single most actionable metric for proactive flow management. ...

TL;DR: Once you can read Throughput, you can use it for probabilistic forecasting. Monte Carlo Simulation turns historical completed work into ranges, percentiles, and a better conversation about delivery risk. This is a follow-up to the Throughput article. If you need the foundation first, start with Throughput: the flow metric behind team predictability. Here I will not re-explain the metric. Here we turn historical completed work into a forecast. Now let’s get to the practical question management loves to ask: “When will this project of X items be done?” ...

Throughput is the entry point into team predictability. First read the flow: time period, variability, work types, and the constraints around WIP. Forecasting comes after that. Premise Imagine walking into a bar on a Friday evening, exhausted, and ordering a beer flight. The bartender thinks: “Over the past hour we completed 12 orders; there are 4 in progress; this will be the fifth. Your flight will arrive in 20–25 minutes.” ...

Over seven years of running Story Points workshops, I’ve seen the same pattern: teams learn the technique, apply it for a few sprints, then gradually drift back to old habits. At my current scale — 47 teams, around 400 people in IT — 60% use Story Points, 40% don’t. What’s interesting: those 60% who do use them do it completely differently. Even 3 months after the training, only 20-30% use Story Points correctly (as intended). The problem isn’t the tool itself, but how we use it and what we expect from it. ...

(Experience from an AI-Based Fintech KYC SaaS Startup Focused on LATAM and Africa) Your regular challenge: When Sales, Marketing and IT Speak Different Languages Our SaaS startup served emerging fast-paced fintech markets (it still is). Speed + compliance were existential. Since most startups live on venture capital with limited runway, every delay in shipping value to the market means lost clients and regulatory risk. It also a huge roadblock on your path to become self-sustainable. So you need to be super frugal and efficient. ...