Product development needs good requirements to build the right outcome. How does the concept of “modularity” give good requirements when the customer does not know what he or she wants? By balancing empowerment with structure, modularity turns uncertain customer input into actionable requirements while reducing friction and cognitive overload.
1. Customer Empowerment Through Choice
- Modular Building Blocks: Modularity offers predefined components that customers can mix and match. These aren’t blank slates but curated options, reducing cognitive overload. For instance, in a modular IoT device, customers choose from a set of sensors or connectivity options without needing to design the whole system.
- Guided Customization: Offering templates or “starter kits” narrows the focus for customers who might not know where to begin. For example, a manufacturer might provide presets for different industries (e.g., healthcare, agriculture) that customers can tweak.
2. Gathering Good Requirements
- Interactive Prototyping: Digital interfaces (e.g., configurators or visual tools) let customers experiment with combinations. This interaction reveals implicit needs and preferences as they test options, which feeds into refining product requirements.
- Incremental Feedback Loops: Lean manufacturing often relies on iterative cycles. By starting small (e.g., with a modular MVP), you can deploy a base product and gather specific, real-world feedback, instead of relying solely on abstract customer input.
3. Balancing Overload with Clarity
- Constraints Are Key: While modularity enables flexibility, too many choices overwhelm. Smart modular systems balance openness with well-defined boundaries.
- Customer Personas: Define personas to map likely combinations of needs. For instance, farmers in arid regions might consistently pick water sensors and solar power modules for IoT systems.
4. Modularity’s Role in Revealing Needs
- Data-Driven Insight or iterations: Modular systems often involve connected technology that generates usage data. This data highlights how customers interact with the system, which informs future design and feature prioritization.
- Emergent Needs: Sometimes, customers don’t know what they need because they haven’t experienced the system yet. A modular approach allows for post-sale customization and upgrades, addressing needs as they emerge.
Practical steps for your product development
- 🟧Build a Configurator: An interactive tool where customers can drag, drop, and visualize modular options. This simplifies the decision-making process and directly informs design priorities.
- 🟧Limit Initial Choices: Provide a tiered selection—basic, advanced, or custom. Too many options lead to paralysis; a few curated ones streamline engagement.
- 🟧Leverage AI: Implement AI assistants to suggest configurations based on initial inputs or industry benchmarks, acting as a “consultant” for the customer.
- 🟧Modular Documentation: Ensure every module has clear documentation outlining its purpose, integration points, and limitations to avoid misuse or confusion.
