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TL;DR
Outcome-First Decisions is a framework that guides organizations to assess whether to keep, change, or kill initiatives based on current outcomes. It emphasizes pruning to improve efficiency and capacity.
A new decision-making framework called Outcome-First Decisions is gaining attention for its approach to portfolio management, emphasizing the importance of stopping projects that no longer produce justified outcomes. Developed by Thorsten Meyer, it offers a structured method to evaluate whether initiatives should be kept, changed, or killed based solely on their current results, not past effort or sunk costs.
Outcome-First Decisions centers around a simple but powerful question: given the current state of an initiative, is the outcome it produces worth its ongoing cost? This approach aims to combat the common tendency to continue supporting projects due to sunk costs, organizational identity, or effort justification. The framework employs the Worth Filter, which explicitly discourages backward-looking metrics and emphasizes forward-looking outcome assessments.
The framework provides three verdicts: keep, change, or kill. ‘Keep’ if outcomes justify ongoing investment; ‘change’ if the initiative has potential but needs modification; and ‘kill’ if outcomes do not justify continued support. The process is designed to be provider-agnostic, run locally, and is open source under the AGPL-3.0 license, ensuring transparency and adaptability. It is intended to be the final decision node in a portfolio review cycle, closing the loop on what organizations should stop supporting to reclaim capacity and improve overall efficiency.
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 Reshape Portfolio Management
This framework matters because it addresses the critical but often overlooked challenge of stopping initiatives that drain resources without delivering value. By focusing solely on outcomes, it encourages organizations to prune their portfolios actively, freeing capacity for new, more promising efforts. This disciplined approach can lead to more efficient resource allocation, better strategic focus, and reduced organizational inertia caused by emotional or sunk cost biases.
Implementing Outcome-First Decisions can help organizations avoid the hidden costs of maintaining dead projects, which silently consume attention, maintenance effort, and capital. It also institutionalizes the discipline of stopping, which is often the most difficult but most impactful decision for sustaining a healthy portfolio.
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The Need for Systematic Portfolio Pruning
Many organizations accumulate a long tail of ongoing projects, products, or commitments that neither succeed nor are actively killed. These ‘zombie’ initiatives continue to consume resources and attention, often justified by past investments or organizational identity. Traditional decision-making processes tend to favor starting new initiatives over stopping existing ones, leading to silted-up portfolios and opportunity costs.
Thorsten Meyer’s framework builds on the idea that the hardest decision in portfolio management is often the one to stop. It provides a structured, outcome-based approach to make these decisions more straightforward and less emotionally charged. The concept is gaining traction in the tech and organizational management communities as a way to improve agility and focus.
“The hardest decision in any portfolio isn’t what to start. It’s what to stop.”
— Thorsten Meyer
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Limitations and Risks of Outcome-First Decisions
While the framework promotes objective evaluation, it relies heavily on accurate measurement of outcomes. There is a risk of mismeasuring or gaming results, leading to premature killing or unwarranted continuation of initiatives. Additionally, it cannot eliminate emotional biases or provide the courage needed to make difficult decisions, such as killing promising but slow-starting projects. The framework’s effectiveness depends on honest and precise outcome assessment, which remains a challenge in practice.
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Next Steps for Adoption and Refinement
Organizations interested in implementing Outcome-First Decisions should start by integrating the framework into their regular portfolio reviews. Since the method is open source and provider-agnostic, teams can adapt it to their specific context. Further development may include refining outcome metrics, developing supporting tools, and sharing case studies to demonstrate its impact. As more organizations adopt the approach, best practices and potential pitfalls will become clearer, helping to standardize outcome-based pruning processes.
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Key Questions
How does Outcome-First Decisions differ from traditional portfolio reviews?
Traditional reviews often focus on past investments, effort, or organizational identity, while Outcome-First Decisions evaluate initiatives solely based on current outcomes and their value relative to ongoing costs.
Can this framework be applied outside tech organizations?
Yes, the principles are generalizable to any organization managing multiple projects or commitments, including non-profits, government agencies, and corporate portfolios.
What are the main challenges in implementing Outcome-First Decisions?
The primary challenges include accurately measuring outcomes, overcoming emotional resistance to stopping projects, and ensuring decision-makers are willing to act on outcome assessments rather than past investments.
Is the framework suitable for fast-paced environments?
Yes, since it is designed to be run locally and frequently, it can support rapid decision cycles and continuous portfolio optimization.
Source: ThorstenMeyerAI.com
