Back-testing across three projects shows forecasting accuracy rises with team autonomy, controlled WIP, and data-driven flow management.

Leading EDJE helps project-driven organizations deliver software that measurably improves business outcomes by value-ordering work, aligning strategy to sprints, and using evidence-based metrics and forecasting to make trade-offs transparent.

When an unexpected pause disrupts a project, getting back on track can be harder than it seems. In this post, we share lessons from our own two-week project interruption, the challenges we faced on resuming work, and 7 practical steps for regaining momentum—from strong leadership alignment to rebuilding team connection and purpose. These strategies can help any team recover faster, stronger, and with greater resilience.

Evidence-Based Management (EBM) and Agile Forecasting work hand in hand to help organizations make smarter, data-driven decisions. EBM ensures teams measure value delivery through empirical data, while Agile Forecasting leverages probabilistic methods to predict future outcomes. Together, they improve predictability, risk management, and stakeholder confidence, enabling teams to deliver measurable results aligned with business goals.

This article explains why Agile Forecasting is a game-changer. It examines how agile forecasting helps teams set achievable goals, manage risks more effectively, and build trust with stakeholders by delivering transparent, data-driven insights.

This article explores how Agile Forecasting, powered by Monte Carlo Simulations and flow metrics, provides teams with accurate, data-driven predictions to balance Agile's flexibility with the need for predictability in IT planning.

AI prototyping projects can be effective ways of exploring new concepts, but concluding them effectively is important too.

There's a lot that can go wrong with AI. Let's talk about how to minimize that risk.

Let's talk about how to successfully run AI prototyping projects

In this article we'll move along in that process and discuss launching AI prototyping projects in a way that sets them up for success.