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MoSCoW method

The MoSCoW method is a technique employed in and agile development to categorize requirements or features into four distinct categories—Must have, Should have, Could have, and Won't have—thereby enabling teams to focus on essential deliverables while managing and timelines effectively. This approach ensures that critical elements are delivered on time, with lower-priority items addressed only if resources permit, promoting efficient in constrained environments. Originating in 1994, the method was developed by software developer Dai Clegg during his tenure at , initially for projects, and was subsequently donated to the (DSDM) consortium, where it became a core practice. Integrated into DSDM's agile framework, prioritization supports iterative development by assigning priorities early in the project lifecycle, often during facilitated workshops involving stakeholders, to align expectations and mitigate risks of . The acronym's —particularly the 'o'—is a deliberate mnemonic device with no specific meaning, emphasizing the method's simplicity and memorability. In practice, Must have items represent non-negotiable requirements essential for project success and user acceptance; Should have features significantly enhance value but can be deferred if necessary; Could have elements offer nice-to-have improvements deliverable only with surplus time or resources; and Won't have items are explicitly excluded from the current scope, often reconsidered for future iterations. This structured categorization facilitates —a DSDM technique for fixed-duration delivery cycles—and has been widely adopted beyond in fields like and to balance needs against realistic constraints. Key benefits include improved , reduced ambiguity in requirements, and higher project delivery success rates, though it requires clear consensus to avoid misprioritization.

Origins and Background

Historical Development

The MoSCoW method originated in 1994, developed by Dai Clegg while working as a consultant at Oracle UK, as a prioritization technique for (RAD) projects facing tight deadlines. Clegg introduced the method in his book CASE Method Fast-Track: A RAD Approach, co-authored with Barker, which provided practical guidance on applying RAD within structured frameworks. Shortly thereafter, Clegg donated the to the (DSDM) Consortium, where it was integrated into the foundational elements of DSDM version 1, published in 1994. Key milestones marked the method's maturation within DSDM and beyond. It featured prominently in iterative development and practices from the outset, but received refined emphasis in the 2007 release of DSDM Atern, which broadened DSDM's applicability to non-software domains while reinforcing MoSCoW as a core tool. By the early , as DSDM evolved to address general challenges, the MoSCoW method expanded from its software-specific roots to support in diverse contexts. In 2014, the DSDM Consortium released the DSDM Agile Project Framework, dropping the "Atern" branding and updating the method to better align with contemporary agile practices. The technique's evolution from a DSDM-specific component tied to —where requirements were categorized to fit fixed delivery cycles—progressed to a versatile standalone approach by the early 2000s. By the 2010s, it achieved wider institutional recognition, including integration into PMI's resources and guidance as a recommended aid.

Context in DSDM

The (DSDM) emerged in the during the early 1990s as one of the earliest agile methodologies, created by a of organizations to overcome the limitations of traditional approaches in projects with strict time constraints. This framework was specifically designed to enable faster delivery of software systems while maintaining control over scope and resources in environments where deadlines were non-negotiable, such as business-critical IT initiatives. By emphasizing between business and technical teams, DSDM addressed the inefficiencies of sequential development models, which often led to delays and overruns in fixed-timeline scenarios. At the core of DSDM are principles that directly influenced the need for structured prioritization tools like , including iterative to allow solutions to evolve incrementally through loops, to enforce fixed delivery periods that prevent endless expansion, and a focus on to ensure efforts target outcomes that deliver measurable benefits rather than exhaustive feature lists. These principles arose from the recognition that conventional methods struggled with changing requirements and resource limitations, often resulting in incomplete projects or where additional features eroded timelines without adding proportional value. , in particular, required a mechanism to manage what could realistically be achieved within bounded periods, prompting the of MoSCoW to classify requirements without outright elimination, thus safeguarding project momentum. The method specifically addressed DSDM's methodological needs by providing a way to combat in time-constrained settings, categorizing requirements such that must-have items do not exceed 60% of total effort, leaving the remainder for should-have and could-have elements. This approach ensured that objectives were met on schedule while allowing flexibility for desirable enhancements, aligning with DSDM's philosophy of delivering viable solutions early and iteratively refining them. Within DSDM's lifecycle, MoSCoW is applied during the feasibility to assess and rank high-level requirements for viability, and in the functional model to prioritize prototypes and deliverables, ensuring with timeboxes and business priorities throughout.

Core Components

The Four Categories

The MoSCoW method categorizes requirements into four distinct priority levels to facilitate effective and delivery within constraints. These categories—Must have, Should have, Could have, and Won't have—establish a clear that guides by distinguishing essential elements from desirable or deferred ones. This ensures that critical aspects are addressed first while allowing flexibility for timeboxed deliveries. Must have (M) requirements are those fundamental to the project's success, forming the minimum usable subset without which the solution would be unacceptable or fail to achieve its core objectives. Assignment to this category is based on criteria such as legal mandates, essential functionality, or features without viable alternatives, where omission would render the project a . For instance, basic operational capabilities or standards typically fall here, as they guarantee the solution's viability. Should have (S) requirements include important elements that significantly enhance the solution's value but are not vital for basic success; their absence allows short-term workarounds, though the overall effectiveness is reduced. Criteria for assignment emphasize substantial benefits with moderate impact if deferred, such as improved features that support but do not define core operations. These are prioritized after Must haves but pursued when resources permit to maximize utility. Could have (C) requirements encompass desirable additions that offer minor enhancements without compromising the project's primary goals, included only if time and effort remain after higher priorities. Assignment relies on low-risk, low-effort criteria where the items add or optional value, like aesthetic refinements to interfaces, but can be easily dropped without consequence. This category supports opportunistic inclusion to elevate quality when feasible. Won't have (W) requirements are explicitly excluded from the current or , often representing out-of-scope ideas or future enhancements to set realistic expectations and prevent . Criteria include misalignment with immediate objectives or dependency on later phases, ensuring focus on deliverable items; for example, advanced integrations planned for subsequent releases. This category aids in managing stakeholder alignment by documenting deferrals. The categories interrelate as a strict priority , with Must haves taking precedence over Should haves, followed by Could haves, and Won't haves fully deprioritized for the timeframe. To maintain deliverability within fixed timeboxes, the DSDM recommends allocating no more than 60% of effort to Must haves, with the remaining effort typically allocated to Should haves (~20%) and Could haves (~20%), while Won't haves receive zero allocation in the current cycle. This distribution balances ambition with realism, enabling iterative refinement as needed.

Prioritization Guidelines

The assignment of MoSCoW categories typically involves key stakeholders in facilitated workshops to ensure alignment on priorities, where , levels, and effort estimates guide the categorization process. For instance, requirements with high —such as those critical to or foundational functionality—are classified as Must Haves to mitigate potential project failure. This collaborative approach fosters consensus and reduces later disputes by incorporating diverse perspectives early. Categories assigned via MoSCoW should be reviewed and potentially adjusted at the end of each or timebox to reflect evolving conditions, such as changes or new insights from . Promotions from Should or Could to Must are reserved for items that become newly critical to delivery viability, while demotions occur if initial assumptions about value or feasibility shift. This ongoing evaluation maintains focus on delivering the minimum usable subset of requirements while adapting to feedback. Best practices for MoSCoW prioritization include limiting Must Haves to approximately 60% of total requirements or effort to allow buffer for unforeseen issues and ensure feasibility within time constraints. Each category assignment must be documented with a clear rationale, including supporting factors like value and risk, to promote and among the team. Visual aids can enhance and facilitate quick status assessments during reviews. The decision framework for emphasizes weighing interdependencies among requirements—for example, prioritizing a single Must Have that unblocks multiple Should Haves to optimize overall progress—and aligns with the principle, where fixed time periods drive flexible scope adjustments to guarantee on-time delivery of core value. This structured weighing of factors like dependencies ensures balanced and predictable outcomes.

Implementation

Step-by-Step Process

The implementation of the MoSCoW method begins with Step 1: Requirements gathering, where project teams collect all potential requirements through structured interviews, , or the development of user stories to ensure a comprehensive list of needs is captured early in the project lifecycle. In Step 2: Initial categorization workshop, the convenes in a facilitated session to list all gathered requirements and assign each to one of the MoSCoW categories (Must have, Should have, Could have, or Won't have) through group discussion and , ensuring alignment on priorities based on and feasibility. During categorization, teams should aim to allocate no more than 60% of total effort to Must have items and around 20% to Could have items to maintain for delivery. Step 3: Baseline agreement follows, involving the documentation of the categorized requirements into the Prioritised Requirements List (PRL), which is then reviewed and formally signed off by the project sponsor and key stakeholders to establish a committed for the project scope. MoSCoW prioritization is applied at multiple levels: the overall project, each project increment, and individual timeboxes. Step 4: Iteration planning, within each timeboxed of the DSDM at the timebox level, the team allocates resources primarily to Must have items to guarantee delivery, incorporating Should have and Could have items only if time and buffer allow, while parking Won't have items for potential future consideration without derailing current progress. Finally, Step 5: Delivery and review entails executing the planned work, delivering the prioritized outputs at the end of the , and conducting a to reassess remaining requirements, potentially recategorizing items based on new insights or changes for the subsequent cycle. Priorities are reviewed at the end of each timebox and increment.

Practical Tools

Practical tools for implementing the method include standardized templates that structure the process. The matrix is a common template, often created in spreadsheets with columns for listing requirements, assigning categories (Must, Should, Could, Won't), providing rationale for each assignment, and estimating effort levels to inform feasibility. This format allows teams to visually organize and review priorities during sessions. Software tools facilitate ongoing tracking and collaboration in MoSCoW prioritization. In , teams integrate MoSCoW by adding custom fields to issues for selecting M, S, C, or W categories, enabling filtered views and reports to monitor progress across priorities. supports the method through labeled cards or dedicated lists for each category, allowing drag-and-drop reorganization as priorities evolve during sprints. Facilitation techniques enhance group consensus in applying . Workshops typically involve physical placed on a board to brainstorm and categorize requirements collaboratively, fostering discussion on trade-offs. For consensus-building, is employed, where participants allocate a limited number of dots (e.g., stickers or digital markers) to vote on category placements, prioritizing high-impact items while mitigating dominant voices. Digital whiteboards like replicate this with virtual and built-in voting tools, simulating in-person dynamics. Customization of these tools is essential for diverse team environments, particularly remote ones. Collaborative platforms such as Lucidchart allow adaptation of MoSCoW matrices with real-time editing, embedded voting, and integration with tools like Slack for asynchronous input, ensuring accessibility across time zones.

Applications

In Software Development

The MoSCoW method aligns closely with agile methodologies, particularly in Scrum, where it is employed during backlog grooming sessions to categorize and refine user stories based on their priority. In these refinement activities, product owners and development teams classify items as Must-have, Should-have, Could-have, or Won't-have to ensure consensus on what delivers the highest value within upcoming sprints, with Must-have items often forming the core of a minimum viable product (MVP) to validate essential features early. This approach facilitates focused discussions on user story acceptance criteria and dependencies, helping teams forecast sprint capacity without overcommitting to lower-priority elements. In , MoSCoW prioritization offers distinct benefits by emphasizing core functionality, which reduces accumulation through deliberate choices between immediate feature delivery and refactoring efforts. By designating technical improvements as Should-have or Could-have items, teams can address them incrementally without derailing release timelines, thereby maintaining code quality over time. Additionally, the supports incremental delivery within fixed-release cycles, such as those in timeboxed iterations, allowing for phased rollouts where Must-have elements form the initial baseline and subsequent categories enhance it progressively. Practitioners often combine MoSCoW with agile estimation techniques, assigning story points to Should-have and Could-have items to gauge relative effort after securing the Must-haves, which aids in balancing workload across sprints. Progress is tracked using burndown charts filtered by category, providing visibility into completion rates for high-priority items and enabling adjustments if lower-priority tasks encroach on . This integration enhances predictability in software iterations by linking prioritization directly to measurable outcomes. Historically, MoSCoW saw early adoption in (RAD) projects following its integration into the (DSDM) in 1994, where it structured requirements for fast-paced software delivery under tight constraints. In modern contexts, it has been adapted for environments to prioritize tasks, with critical features designated as Must-haves while deferring lower-priority enhancements. For example, in a 2025 project to add a support to an existing within a 4-week timeline using agile sprints, Must-haves included message interfaces, backend , database storage, access, and user authentication; Should-haves covered API validations and a refresh ; Could-haves like scalability enhancements were optional; and Won't-haves excluded and real-time streaming.

In

In (NPD), the MoSCoW method plays a key role in prioritizing features for product roadmaps by categorizing requirements to align with customer needs and business goals. Must-have (M) items focus on essential elements that meet core customer expectations and ensure product viability, while Won't-have (W) categories defer speculative or low-value ideas to future iterations, allowing teams to concentrate resources on high-impact deliverables. This approach helps product managers build focused roadmaps that balance innovation with feasibility, particularly in resource-limited environments. The method also aligns with lean startup principles by guiding the creation of minimum viable products (MVPs), ensuring that must-have and should-have items form the validated core while could-have elements are tested iteratively to minimize waste and accelerate market entry. Key benefits include enhanced management of cross-functional teams, such as , , and , by providing a shared language that fosters alignment on outcomes. It facilitates go-to-market decisions under resource constraints by emphasizing ROI through clear categorization, enabling faster launches without compromising essential functionality. In hardware product launches, for instance, should-have (S) items like customizable accessories can enhance market competitiveness and user appeal without delaying the release of must-have core components, such as battery life and durability in consumer electronics. This prioritization ensures timely delivery while positioning the product for differentiation in competitive landscapes.

Variations and Extensions

Common Variants

Common variants of the MoSCoW method have been developed to address limitations in the original framework, such as handling temporary deferrals, providing quantitative measures for , controlling , and integrating with other scoring systems for greater . These modifications maintain the core categories of Must have, Should have, Could have, and Won't have while introducing targeted adjustments to enhance flexibility and precision in prioritization. Weighted MoSCoW incorporates numerical scoring to the categories, such as assigning increased weights to critical features based on (e.g., 5× multipliers for high-risk items like features). This quantitative layer enables tie-breaking among items within the same category and supports aggregated scoring for overall project assessment, making the method more analytical while retaining its qualitative foundation. Teams apply these weights during workshops to calculate total scores, aiding in ranking when qualitative judgments alone prove insufficient. The Reverse MoSCoW, also known as the Inverted MoSCoW framework, flips the traditional approach by prioritizing what a product won’t build, focusing on exclusions to streamline and avoid . This variant emphasizes ruling out features first based on product vision and strategy, with categories including Won't-Have (absolutely not), Could-Have (unlikely), Should-Have (under specific conditions), and Deferred Consideration (maybe later), forcing to rigorously defend inclusions based on value, risk, and alignment with goals. It is particularly useful in agile contexts to prevent overcommitment and align stakeholders on minimal viable scope. Hybrid variants combine with scoring (Reach, Impact, Confidence, Effort) to blend categorical prioritization with data-driven evaluation. In this approach, items are first categorized using to establish broad priorities, then scored via within each category to refine rankings quantitatively—for instance, calculating a score as (Reach × Impact × Confidence) / Effort to prioritize Must haves by potential return. This integration enhances objectivity, reduces bias in stakeholder discussions, and is effective for complex projects where both qualitative scoping and numerical assessment are needed. A common extension involves assigning approximate percentage allocations to categories during timeboxing, such as aiming for 60% Must have, 40% Should and Could have combined, to guide resource planning and ensure focus on essentials within fixed iterations.

Contemporary Adaptations

In the 2010s and beyond, the MoSCoW method has evolved to incorporate elements of , agile scaling, and emerging global challenges, adapting to hybrid work environments and data-driven . These contemporary modifications emphasize with modern frameworks, leveraging for efficiency, and addressing sustainability imperatives. One prominent adaptation is the integration of with (OKRs), known as "MoSCoW for OKRs," which aligns feature prioritization with organizational goals to ensure strategic focus. In this approach, initiatives supporting OKRs are categorized using MoSCoW criteria, where "Must Have" items directly contribute to core objectives, "Should Have" enhance key results, and lower priorities are deferred if they do not advance measurable outcomes. This method promotes transparency in decision-making by explicitly linking priorities to business goals, as demonstrated in practices where teams map backlog items to OKR progress. For instance, a software team might designate user registration and login as a "Must Have" to meet an OKR on user onboarding completion rates, while optional enhancements fall into "Could Have." AI-enhanced variants of MoSCoW have gained traction, utilizing to automate category suggestions based on historical project data, stakeholder inputs, and qualitative analysis. Tools like Copilot4DevOps in employ to evaluate requirements against MoSCoW standards, performing impact analysis and recommending priorities such as flagging high-risk items as "Must Have" from past delivery patterns. This reduces and accelerates workshops by generating initial categorizations, allowing teams to refine suggestions collaboratively; for example, might auto-classify a feature as "Should Have" if similar items historically drove 20-30% efficiency gains in comparable projects. Such integrations streamline prioritization in large-scale agile environments, enhancing accuracy without replacing human oversight. Sustainability-focused adaptations of the MoSCoW method extend it by incorporating environmental impact as a criterion, particularly for downgrading "Could Have" or "Won't Have" items with high carbon footprints. In and (CSR) teams, requirements are assessed not only on but also on ecological consequences, such as or resource use, ensuring alignment with green goals. This variant prioritizes initiatives that minimize environmental harm, for instance, classifying eco-friendly alternatives as "Must Have" in product roadmaps while deferring non-essential features that increase . Adopted in sectors like manufacturing and tech, it supports broader (Environmental, Social, and Governance) objectives by embedding into core prioritization logic. Remote and hybrid adaptations have emphasized digital-first workshops to enable in distributed teams without compromising . These adaptations often include asynchronous input phases to accommodate diverse schedules, ensuring "Must Have" emerges from varied perspectives and enhancing the method's efficacy in remote-first organizations.

Evaluation

Advantages

The MoSCoW method enhances clarity and communication in by providing a straightforward acronym-based that categorizes requirements into Must Have, Should Have, Could Have, and Won't Have, thereby reducing associated with vague or numerical schemes like high/medium/low. This simple structure fosters buy-in through collaborative workshops where business representatives justify priorities, aligning them with organizational goals and (ROI). The method's flexibility supports iterative delivery in agile environments, such as DSDM, by enabling requirements to shift categories as new information emerges, without necessitating full renegotiation of the project scope. This adaptability is particularly valuable in timeboxed increments, allowing teams to focus on delivering a Minimum Usable while accommodating changes to maintain . MoSCoW promotes efficiency through its principle, which prioritizes delivering value early by allocating effort predictably—typically limiting Must Haves to 60% or less of capacity to create buffers. Research on DSDM implementations indicates positive impacts on development time and productivity, with surveys reporting faster time-to-market compared to traditional methods, enabling organizations to respond more rapidly to market needs. The approach scales effectively from small teams to enterprise-level s by decomposing complex requirements into manageable priorities at multiple levels (, increment, timebox), promoting risk mitigation through front-loading critical Must Haves and reserving capacity for contingencies. This scalability ensures consistent application across diverse contexts, enhancing overall predictability and rates.

Criticisms

The assignment of requirements to MoSCoW categories often relies on team consensus, which introduces subjectivity and potential , particularly when stakeholders have varying levels of expertise or differing interests. Without strict, predefined criteria, disputes can arise during , leading to inconsistent outcomes across projects or teams. The method's four-category structure can oversimplify complex prioritization needs, failing to capture nuanced differences in importance or account for interdependencies between requirements. For instance, requirements that appear in isolation may influence one another, yet MoSCoW does not inherently address these relationships, potentially resulting in suboptimal delivery plans. This limitation becomes evident in large-scale projects where long-term costs or evolving needs require more granular analysis. The "Won't Have" category, while intended to scope out non-essential items for the current iteration, can introduce rigidity, as teams may be reluctant to revisit or adjust these items even if circumstances change. This fixed framing can limit flexibility in dynamic environments like agile development. MoSCoW lacks built-in quantitative metrics for , depending instead on qualitative judgments that complicate progress tracking and comparison to numerical approaches like weighted scoring. This absence makes it harder to measure alignment with business value or justify decisions to leadership, often requiring supplementary tools for validation.

Comparisons

With Alternative Methods

The , developed by Japanese professor in the , categorizes product features based on their impact on into three primary groups: (expected features that cause dissatisfaction if absent but no delight if present), performance needs (features that increase satisfaction linearly with improvement), and delight needs (unexpected features that generate excitement but do not dissatisfy if missing). This customer-centric approach relies on surveys to classify requirements according to how their presence or absence affects user emotions, emphasizing long-term delight over immediate project constraints. In contrast to the method's focus on scoping deliverables within time-bound project phases through qualitative categories like Must, Should, Could, and Won't, the Kano model prioritizes based on emotional satisfaction dynamics, making it better suited for iterative where user feedback drives enhancement of delight factors rather than strict scope exclusion. RICE scoring, a framework introduced by the product team at in 2016, provides a quantitative for prioritizing initiatives by calculating a score using the formula (Reach × Impact × Confidence) / Effort, where Reach estimates the number of users or events affected, Impact assesses business or user value on a numerical scale, Confidence reflects data reliability as a percentage, and Effort measures required person-months. This approach aims for objectivity by assigning numeric values to otherwise subjective judgments, enabling teams to rank features on a for . Unlike the 's categorical, qualitative grouping that facilitates quick alignment within fixed timelines but risks bias from discussion, RICE promotes data-driven decisions through its formulaic structure, though it demands more upfront estimation and is less ideal for scenarios requiring explicit deferral or rejection of items. The Eisenhower Matrix, originating from a 1954 speech by U.S. President distinguishing urgent from important matters and later adapted into a 2x2 grid for , classifies tasks into quadrants based on urgency (time-sensitive) versus importance (long-term value): do first (urgent and important), schedule (important but not urgent), delegate (urgent but not important), and delete (neither). In , it serves as a simple visual tool for daily or weekly task , often applied to or small backlogs. This binary grid contrasts with the MoSCoW method's multi-tiered hierarchy tailored for requirements prioritization in iterative development, as the matrix excels in handling immediate workload pressures but lacks the nuanced escalation (e.g., Could vs. Won't) needed for complex project scoping and . Value versus Complexity, also known as the Impact-Effort or Value-Effort , is a 2D plotting technique used in agile environments to evaluate features by mapping their potential business or user value (high/low) against implementation complexity or effort (high/low), identifying "quick wins" in the high-value/low-complexity quadrant, "big bets" in high-value/high-complexity, "fill-ins" in low-value/low-complexity, and "money pits" to avoid in low-value/high-complexity. This visual framework highlights trade-offs in , often plotted on a simple during sessions to guide backlog refinement. It differs from the MoSCoW method by focusing on relative trade-offs through spatial rather than discrete categories, effectively surfacing efficiency opportunities but omitting MoSCoW's dedicated "Won't" designation for clear exclusion of non-viable items in constrained scopes.

Integration with Agile

The MoSCoW method enhances processes by providing a structured approach to refining the during sprint planning and grooming sessions. Must-have (M) items are prioritized as non-negotiable essentials required to meet sprint goals and deliver core functionality, ensuring the team focuses on high-value outcomes without . Should-have (S) and could-have (C) items function as stretch goals, allowing flexibility to incorporate additional features if time and capacity permit, while won't-have (W) items are deferred to an "" for future consideration, maintaining hygiene and alignment with the product vision. This categorization facilitates collaborative discussions among product owners, stakeholders, and the development team, enabling clearer on what to include in each sprint. In systems, supports visual workflow management by tagging tasks with categories on the board, which helps enforce work-in-progress (WIP) limits tailored to priority levels. For instance, must-have and should-have items can flow freely through columns to maintain momentum on critical work, while could-have items are capped at a low number in progress to prevent overload and ensure the team does not dilute focus on higher priorities. Won't-have items remain outside the active board until reevaluation, promoting continuous flow and without rigid timeboxes. This integration leverages Kanban's emphasis on to make dynamic and transparent, reducing bottlenecks and improving throughput. Integrating with agile frameworks bridges traditional techniques—rooted in methods like DSDM—with iterative agile delivery, fostering better alignment and adaptive planning across releases. By categorizing requirements early, teams can balance immediate delivery needs with long-term value, enhancing overall without abandoning structured . However, challenges arise in agile contexts, particularly over-prioritization, where inflate the number of must-have items, leading to unrealistic scopes and diluted focus—often resulting in 20 or more "musts" in a single . To mitigate this, practitioners recommend periodic reviews to reassess categories and combining with quantitative methods like Weighted Shortest Job First (WSJF) in large-scale agile environments, where WSJF's economic formula (cost of delay divided by job size) refines 's qualitative buckets for more precise sequencing at the level. This approach ensures while addressing 's subjectivity.

References

  1. [1]
    MoSCoW Prioritisation - DSDM Project Framework Handbook
    MoSCoW is a prioritisation technique for helping to understand and manage priorities. The letters stand for: Must Have; Should Have; Could Have; Won't Have ...Missing: origin authoritative sources
  2. [2]
    What is the MoSCoW Method? - TechTarget
    Mar 29, 2023 · The MoSCoW method is a four-step approach to prioritizing which project requirements provide the best return on investment (ROI).Missing: authoritative | Show results with:authoritative
  3. [3]
    MoSCoW Method of Prioritization explained - Toolshero
    May 12, 2017 · Origin and advantages of the MoSCoW Method. The method was developed by Dai Clegg, a developer working for the software company Oracle.
  4. [4]
    Our History - Agile Business Consortium
    Innovation was key and DSDM introduced new techniques to software delivery including MoSCoW (Must, Should, Could and Won't haves – IP donated by Dai Clegg) ...
  5. [5]
    [PDF] Dynamic Systems Development Method (DSDM)
    DSDM was first created in 1995 by a consortium that wanted to explore different ways develop software. The DSDM Consortium is a non-profit organization that ...<|control11|><|separator|>
  6. [6]
    DSDM | Dynamic Systems Development Method - agileKRC
    Feb 20, 2023 · Launched in 1995, DSDM is the longest-established Agile method. It is also the only Agile method to focus on the management of Agile projects.
  7. [7]
    MoSCoW method - ProjectManagement.com
    Sep 26, 2018 · The MoSCoW method is a prioritization technique used in management, business analysis, project management, and software development to reach ...
  8. [8]
    The MoSCoW method explained - prince2
    Sep 30, 2025 · MoSCoW is a prioritisation technique that categorises requirements or tasks into four groups: Must have: Essential items that are critical for ...
  9. [9]
    The Eight Principles of DSDM - Agile Business Consortium
    DSDM advocates the use of several proven practices, including: Facilitated workshops; Modelling and Iterative Development; MoSCoW Prioritisation; Time boxing ...Missing: prioritization | Show results with:prioritization
  10. [10]
    How Dynamic Systems Development Method Led to Agile Project ...
    The first version of DSDM was invented circa 1995 as a response to the lack of discipline in the Rapid Application Development methodology. The DSDM Consortium ...
  11. [11]
    Chapter 4: Principles - Agile Business Consortium
    MoSCoW prioritisation and timeboxing are used to ensure that testing is appropriate and under taken without introducing unnecessary risks. In an IT project, the ...Missing: prioritization | Show results with:prioritization
  12. [12]
    Dynamic Systems Development Method (DSDM)
    May 6, 2023 · One of the significant updates to the methodology came in 2007 with the release of DSDM Atern, which aimed to make the framework more accessible ...<|control11|><|separator|>
  13. [13]
    Chapter 11: Iterative Development - Agile Business Consortium
    Iterative development is a process in which the Evolving Solution, or a part of it, evolves from a high-level concept to something with acknowledged business ...
  14. [14]
    DSDM: Definition, Benefits, Principles and Practices | Indeed.com
    Jul 24, 2025 · DSDM helps companies accomplish their projects on time by using techniques such as timeboxing. Timeboxing refers to the process of establishing ...
  15. [15]
    Why DSDM Is the Optimal Choice in Times of Limited Investment
    Feb 24, 2025 · Prevent Scope Creep: By locking time but allowing scope adjustments, timeboxing ensures essential tasks are done first. Build Predictable ...
  16. [16]
    MoSCoW prioritisation for Timeboxes in Agile projects
    Nov 25, 2021 · As a general rule, the Must have requirements shouldn't take over 60% of the available time and effort in a project or timebox. Must have. The ...
  17. [17]
    The MoSCoW method for prioritization - Highberg
    When prioritizing requirements in a project, DSDM recommends no more than 60 per cent effort for “must-haves” requirements and a sensible pool of “could ...Missing: 80%
  18. [18]
    DSDM Guide - Dynamic Systems Development Method - Tools QA
    Jul 7, 2021 · Functional Model Iteration- All functional phases discussed in previous stages, all the technical requirements are decided and prioritized.What Is Dsdm? · Dsdm Principles · Project Structure In Dsdm
  19. [19]
    Dynamic Systems Development Method (DSDM) | Definition, Five ...
    Rating 4.8 (42) Mar 28, 2025 · 3. Five phases of the DSDM lifecycle · 3.1. Feasibility study · 3.2. Business study · 3.3. Functional model iteration · 3.4. Design and build ...
  20. [20]
    MoSCoW Prioritization - Wiki | BAwiki
    MoSCoW Prioritization was originally invented by Dai Clegg of Oracle, but was subsequently donated to the Dynamic System Development Method (DSDM) Consortium.Missing: origin | Show results with:origin
  21. [21]
    What is MoSCoW Prioritization Method? Overview, Benefits, Tips
    Nov 17, 2023 · MoSCoW is an acronym for “must-have,” “should-have,” “could-have,” and “won't-have (this time).” The two “O's” were added to simplify the ...
  22. [22]
    Chapter 9: Workshops - Agile Business Consortium
    This section gives some guidance on which DSDM roles would fill the roles of a Workshop. Facilitated Workshop roles are defined as: Workshop Owner, Workshop ...
  23. [23]
    MoSCoW Prioritization: Essential Guide for Project Management
    Rating 5.0 (199) Dec 3, 2024 · Learn how to effectively prioritize project requirements using the MoSCoW method. Master Must-Have, Should-Have, Could-Have, and Won't-Have ...
  24. [24]
    MoSCoW prioritisation is on effort - Digital Communications team blog
    Aug 5, 2016 · This guide shows how the 60/20/20 proportion of must, should and could requirements in Agile MoSCoW prioritisation is against effort not ...Missing: rule | Show results with:rule<|separator|>
  25. [25]
    Chapter 13: Timeboxing - Agile Business Consortium
    60-80% of Timebox ... Timeboxing is one of DSDM's key practices and is used in combination with the practice of MoSCoW prioritisation to ensure on-time delivery.13 Timeboxing · 13.1 Introduction · 13.3 A Dsdm Structured...Missing: functionality | Show results with:functionality
  26. [26]
  27. [27]
    Introduction to MoSCoW Prioritization - Lucidchart
    MoSCoW analysis was invented by Dai Clegg of Oracle UK consulting, who developed the technique to determine prioritization within projects that had severe time ...Missing: origin | Show results with:origin
  28. [28]
    9 product prioritization frameworks for product managers | Tempo
    Here's what a value vs. effort scorecard looks like in Strategic Roadmaps: (Pssst! Value vs. effort is one of two prioritization templates available in ...1. Rice · 2. Value Vs. Effort · 5. The Moscow Method<|control11|><|separator|>
  29. [29]
    Using the MoSCoW Method to Prioritize Projects - ProjectManager
    Aug 29, 2023 · The MoSCoW method is a technique that helps organizations prioritize what should be done first in a project. It is done in four steps that follow the acronym ...
  30. [30]
    Dot Voting: A Simple Decision-Making and Prioritizing Technique in ...
    Jul 7, 2019 · Dot voting is a tool where participants use colored dots to vote on the importance of options, prioritizing items in a group setting.Missing: Lucidchart | Show results with:Lucidchart
  31. [31]
    FREE MoSCoW Template & Example for Teams | Miro 2025
    Use our free MoSCoW Template to track evolving priorities and their impact on impending deadlines.Missing: software | Show results with:software
  32. [32]
    Moscow prioritization - Scrum.org
    Nov 26, 2019 · I have a question regarding backlog grooming. I have completed product prioritization using MoSCOW method. I have it prioritized it as follows.Missing: best | Show results with:best
  33. [33]
    How to Prioritize Product Backlog Using MoSCoW Method
    The MoSCoW method (also known as MoSCoW prioritization or MoSCoW analysis) is a prioritization technique to reach a common understanding with stakeholders.
  34. [34]
    How to Reduce Technical Debt: Key Strategies - vFunction
    Apr 9, 2025 · Utilize methods like MoSCoW to prioritize between technical debt and feature requests efficiently.
  35. [35]
    5 Agile Estimation Tips To Help With Backlog Prioritization
    Jun 7, 2024 · 2. MoSCoW. Must-have, should-have, could-have, and won't-have are the buckets used to prioritize a backlog with the MoSCoW technique. The ...Missing: grooming | Show results with:grooming
  36. [36]
    MoSCoW Principles: A Prioritization Technique for Scrum - LinkedIn
    Sep 1, 2025 · A burndown chart helps agile project management teams keep track of what's been done, what needs to be done and how much time is left in the ...
  37. [37]
    Dynamic Systems Development Method (DSDM) - Nimblework
    Jul 16, 2020 · In 2014, DSDM released the latest version. The new DSDM manual recognized the need for DSDM to work alongside other frameworks used for service ...
  38. [38]
    DevOps Planning - Purple Griffon
    Apr 29, 2025 · According to Atlassian, CI/CD is a cornerstone of effective DevOps practices. ... The MoSCoW method categorises features into: Must have ...
  39. [39]
    What is MoSCoW Prioritization? - ProductPlan
    The MoSCoW method is a prioritization framework used to help key stakeholders understand the significance of initiatives in a release.Missing: authoritative | Show results with:authoritative
  40. [40]
    MoSCoW Prioritization: How to Use It in Product Management
    Jan 29, 2025 · At its core, the MoSCoW method is about categorizing work into four clear priorities: Must have, Should have, Could have, and Won't have (this ...Missing: authoritative | Show results with:authoritative
  41. [41]
    How to Leverage the MoSCoW Method for MVP Prioritisation - Altar.io
    The MoSCoW method categorizes features into Must-Have, Should-Have, Could-Have, and Won’t-Have (for now) to prioritize MVP features.
  42. [42]
    MoSCoW Prioritization Technique in Product Management
    Oct 18, 2025 · MoSCoW Prioritization Technique is a structured method used by product managers to rank features or requirements based on their importance.
  43. [43]
    [PDF] Comparative Analysis of Requirements Prioritization ... - ИСП РАН
    The hybrid prioritization framework combining MoSCoW, Weighted Scoring, RICE and Kano methods demonstrates significant value across multiple domains where ...
  44. [44]
    The Inverted MoSCoW Framework | Scrum.org
    The inverted MoSCoW framework reverses traditional prioritization, focusing on what a product team won't build rather than what it will.
  45. [45]
    Prioritizing your OKR Initiatives | by Dan Kiskis, PhD
    Jun 3, 2022 · In addition to being a good, simple prioritization scheme, MoSCoW has the advantage of making your priority decisions transparent. This is a ...
  46. [46]
    Copilot4DevOps - Azure DevOps AI Assistant - Modern Requirements
    Analyze the quality of requirements and related details using various methods (6C, MoSCoW, INVEST, PABLO, etc.). ... Perform Impact Analysis to get a prioritized ...
  47. [47]
    Prioritizing with MOSCOW: AI-Assisted Qualitative Analysis for ...
    MoSCoW prioritization is a technique that helps teams categorize requirements into four groups: Must, Should, Could, and Won't.
  48. [48]
    Moscow Method for Sustainability and CSR Teams - Lark
    Apr 24, 2024 · The Moscow Method serves as a valuable framework for sustainability and CSR teams, providing a structured approach to prioritize and manage ...
  49. [49]
    (PDF) The Impact of Agile Methodology (DSDM) on Software Project ...
    Mar 6, 2018 · There is positive impact on development cost, time and productivity by switching from traditional waterfall model to agile model. This paper ...
  50. [50]
    Product Backlog Ordering - Beyond MoSCoW - Scrum.org
    Feb 13, 2025 · The MoSCoW (Must Have, Should Have, Could Have, Won't Have) has been a popular mechanism for prioritization from traditional management days. It ...Missing: method | Show results with:method
  51. [51]
    What Is MoSCoW Prioritization? Definition and Implementations
    Won't-Have (for now): These are low-priority ... The MoSCoW method was introduced by Dai Clegg in 1994 while working at Oracle. ... This rigidity can ...
  52. [52]
    What is Product Prioritization Framewoks? - GeeksforGeeks
    Jul 23, 2025 · The MoSCoW method helps product managers prioritize features and requirements by categorizing them into these four categories based on their ...
  53. [53]
    Kano Analysis: the Kano Model Explained - Qualtrics
    Oct 1, 2021 · The kano model helps you to identify unspoken needs before prioritization. A product or service is more than just its functionality; it's ...Missing: seminal | Show results with:seminal
  54. [54]
    (PDF) The Kano Model: How to Delight Your Customers
    In this paper, we explore the use of model-driven engineering to simplify the deployment of ML models on edge devices, specifically smartphones. We present ...
  55. [55]
    Most Popular Prioritization Techniques and Methods - AltexSoft
    May 16, 2019 · The Most Popular Prioritization Techniques and Methods: MoSCoW, RICE, KANO model, Walking Skeleton, and others.Moscow Method: The Simplest... · When To Use Moscow · Eisenhower Matrix: A...
  56. [56]
    RICE: Simple prioritization for product managers - Intercom
    Jan 5, 2018 · RICE is an acronym for the four factors we use to evaluate each project idea: reach, impact, confidence and effort.Missing: academic | Show results with:academic
  57. [57]
    Six product prioritization frameworks and how to pick the right one
    The MosCow Method is a four-step process for prioritizing product requirements around their return on investment (ROI). It stands for “must haves,” “should ...Missing: facilitation | Show results with:facilitation
  58. [58]
  59. [59]
    Eisenhower Matrix - Overview, History, and Categories
    The Eisenhower Matrix was derived from a quote attributed to former U.S. leader Dwight D. Eisenhower. Eisenhower Matrix Diagram. Who is Dwight D. Eisenhower?
  60. [60]
  61. [61]
    5 Prioritization Methods in UX Roadmapping - NN/G
    Nov 14, 2021 · This article outlines 5 methods for prioritizing work into a UX roadmap: Impact–effort matrix; Feasibility, desirability, and viability ...
  62. [62]
    A comparison of prioritization methods - Highberg
    Compare 5 prioritization methods—Kano, MoSCoW, Eisenhower, Value vs. Effort, and WSJF. Learn their strengths, best use cases, and how to choose the right…
  63. [63]
    Prioritization Techniques for the Product Owner - Scrum.org
    Aug 28, 2023 · In this article, we will explore some complimentary practices which the Product Owner might use to as an input when deciding how to order the Product Backlog.
  64. [64]
    Tools - Kanbanstudy
    In Kanban, the MoSCoW method can be used to prioritize requirements in the backlog, manage capacity by identifying which items should be prioritized or ...<|separator|>
  65. [65]
    The Problem with MoSCoW Prioritization | by Umar Nasir - Medium
    Nov 24, 2024 · While MoSCoW prioritization can be useful in specific contexts, it often leads teams astray by encouraging feature-first thinking.
  66. [66]
    WSJF - Scaled Agile Framework
    Oct 9, 2023 · Weighted Shortest Job First (WSJF) is a prioritization model used to sequence work for maximum economic benefit. In SAFe, WSJF is estimated ...Missing: MoSCoW | Show results with:MoSCoW