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TL;DR
Outcome-First Decisions introduces a framework for evaluating whether to keep, change, or kill initiatives based on their current outcomes. It emphasizes pruning over starting new projects to optimize resources. The approach is open source and designed to close the decision loop in portfolio management.
A new decision framework called Outcome-First Decisions is designed to help organizations evaluate ongoing initiatives by their current outcomes, not past investments or effort. It aims to facilitate pruning of projects that no longer justify their costs, addressing a common problem of resource drain on inactive or failing initiatives. The framework is open source under the AGPL-3.0 license and is gaining interest among operators seeking disciplined portfolio management.
Outcome-First Decisions is a small, opinionated framework that judges each initiative by its current outcome and whether it is worth its ongoing cost. It introduces the Worth Filter, which prompts decision-makers to assess whether to keep, change, or kill a project based solely on its present performance, disregarding sunk costs or emotional attachments. This approach aims to combat the tendency of portfolios to accumulate inactive projects that drain attention and resources. The framework is provider-agnostic, runs on local compute, and is designed to be used frequently, enabling continuous portfolio pruning. It emphasizes that the hardest decision is often to kill an initiative, but doing so can free capacity for more valuable work.While the framework promotes objective decision-making, experts caution that outcomes can be mismeasured or gamed, and that emotional biases remain a challenge. It does not provide the judgment to distinguish slow-starting projects from failures, nor does it eliminate the emotional difficulty of ending initiatives. Nonetheless, proponents argue that Outcome-First Decisions institutionalizes the critical discipline of stopping, which is often overlooked but essential for efficient portfolio management.
Outcome-First Decisions — keep, change, or kill
The hardest decision isn’t what to start — it’s what to stop. Judge every initiative by the outcome it produces now, not the effort already spent.
Independent commentary, produced with AI assistance under human editorial oversight. The views are the author’s own and may change. Outcome-First Decisions is open source under AGPL-3.0, provided “as is” without warranty; see the repository LICENSE. The framework’s verdicts are reasoning aids based on the inputs given and may be wrong — decision support, not decisions; verify independently before acting. Product and company names are trademarks of their respective owners; mention does not imply endorsement.
Why Outcome-First Decisions Reshapes Portfolio Management
This framework matters because it addresses a common yet under-practiced discipline: stopping projects that no longer produce value. By focusing on current outcomes rather than past effort, organizations can reclaim capacity, reduce waste, and redirect resources toward more promising initiatives. It encourages a culture of disciplined pruning, which can lead to more agile and efficient operations. The open-source nature of the framework allows widespread adoption and customization, potentially transforming how organizations manage their portfolios.
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Background on Portfolio Pruning and Decision-Making Challenges
Many organizations struggle with maintaining a balanced portfolio of projects, often continuing initiatives due to sunk costs, organizational inertia, or emotional attachment. Traditional decision-making tends to focus on starting new projects rather than ending existing ones. The problem is compounded by the difficulty of objectively evaluating ongoing initiatives, especially when the signals are ambiguous or delayed. Recent discussions in operational management highlight the need for disciplined pruning and outcome-focused evaluation, leading to the development of frameworks like Outcome-First Decisions.
“Outcome-First Decisions is about making the hardest choice easier: stopping projects that no longer produce value based on current outcomes.”
— Thorsten Meyer, creator of the framework
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Unresolved Challenges in Applying Outcome-First Decisions
It is not yet clear how accurately organizations can measure and interpret outcomes, especially for slow-starting or long-term initiatives. There is also uncertainty about how decision-makers will respond emotionally to frequent pruning, and whether the framework can be adopted at scale without resistance. Additionally, the risk of mismeasuring outcomes or gaming the system remains a concern, potentially leading to premature or delayed kills.
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Next Steps for Adoption and Refinement of the Framework
Organizations interested in Outcome-First Decisions are expected to pilot the framework within their portfolios, adapting it to their specific metrics and decision cycles. Further development may include tools for better outcome measurement and case studies demonstrating successful pruning. Community feedback and real-world testing are likely to refine the approach, with potential integration into existing portfolio management systems. The open-source nature encourages collaborative improvement and broader adoption.
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Key Questions
How does Outcome-First Decisions differ from traditional portfolio management?
It emphasizes evaluating ongoing initiatives based solely on their current outcomes and whether they are worth their ongoing costs, rather than past investments or effort.
What are the main benefits of using this framework?
It promotes disciplined pruning, reduces waste, frees capacity, and helps organizations focus on initiatives that produce tangible value now.
Can this framework be applied to all types of projects?
While designed to be provider-agnostic and flexible, its effectiveness depends on how well organizations can measure and interpret outcomes relevant to their context.
What are potential risks or limitations?
Risks include mismeasuring outcomes, emotional resistance to ending projects, and the possibility of prematurely killing slow-starting but valuable initiatives.
Is the framework available for use now?
Yes, it is open source under the AGPL-3.0 license and can be implemented immediately, with ongoing community-driven improvements.
Source: ThorstenMeyerAI.com
