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They can’t have it all right? So the next time you’re sorting through a long, long list of requirements with a group of stakeholders, c ...
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- Identify goals and participants.
Understanding the nature of the project, including key purpose, a ...
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The MoSCoW Method is highly subjective, not providing clear criteria for the various categories, nor providing distinctions within a category. For example, if ten requirements are identified as ‘must-haves’, there is no further prioritisation of them within the method.
Life sciences platform.
This case study from Browser, a user-centred consulting firm, describes how they helped their client to establish a life science platform using the MoSCoW Method.
The MoSCoW method is a product feature prioritisation technique that takes a slightly different approach to alternative such as RICE scores, impact effort matrix or the kano model.
Use the following examples of connected and complementary models to weave the MoSCoW method into your broader latticework of mental models. Alternatively, discover your own connections by exploring the category list above.
Connected models:
- RICE score, impact effort matrix and Kano method: as alternatives ways of prioritising.
- Pareto principle: in establishing how to identify the 20 that delivers the 80.
- Eisenhower matrix: which is a more individually targeted approach based on similar concepts.
Complementary models:
- Agile methodology: an iterative approach that works well with this form of prioritisation.
- Empathy map: to consider the potential impact on a specific audience group.
- Zawinski’s law: a warning to prioritise and avoid product bloat.
- Lean thinking: considering how to deliver real value with fewer resources, and potentially features.
- Minimum viable product: to test core basic ‘must have’ features from a customer perspective.
- Golden circle: to identify the core purpose of your business to guide product feature decisions.
- First principles: understanding the core offer of a product and need of a customer.
The MoSCoW Method was developed by Dai Clegg who, with a rich history of big data and data modelling for a range of large corporates, now works for Evidence for Development — an NGO dedicated to reducing poverty with evidence-based decisions.
Clegg originally developed the method for prioritisation in timeboxed projects during his time with Oracle and it was later donated to the Dynamic Systems Development Method (DSDM).
My Notes
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