Analog/Digital

In Brief

Analog/digital is a product research technique where you deliver a physical or manual version of your product before building the digital version. You sell or provide the analog form to real customers, observe how they use it, and collect feedback on what works and what does not. The output is hands-on learning about which parts of the workflow matter most, which can be simplified, and whether a digital version is worth building at all.

Description

Many industries have seen a convergence of their existing products with a digital component. Information or software add extra value to an existing product type. In his Harvard Business Review article, Mark Bonchek says, “Digital business models are a bit of a misnomer. It’s not digital technology that defines them; it’s their ability to create exponential value. The music and video industries, for example, weren’t redefined by converting analog to digital formats. Just ask Sony about Minidisc players and Netflix about their DVD business.” Founders who want to de-risk assumptions around the form factor a product or service should take will be well-served with this technique.

Because AI-powered development tools like Cursor, v0, and Bolt can now build digital versions much faster and cheaper than traditional software development, the temptation to skip straight to a digital product is real. Resist it. The analog phase exists precisely to learn what to build. AI just lets you build it faster once you have learned. This is the rationale Tim Brown describes in Change by Design (Harper Business, 2009): you build to think, and physical artifacts surface design problems that pure planning misses.

Bill Buxton makes the related point in Sketching User Experiences (Morgan Kaufmann, 2007): there is no high or low fidelity, only appropriate fidelity. An analog prototype is the appropriate fidelity for testing whether the workflow itself delivers value, before you invest in pixel-perfect software.

While it can be used in different areas, here are a few examples of when/where it is best applied:

• Internet of Things (IoT): Design and sell the physical object first, before adding the distributed software (e.g., monitoring).
• Enterprise software: Design or map out the existing process in great depth using paper or other analog formats, and ideally streamline it as much as possible before creating a software version of it.
• Users without computers: Design a paper-based version (or an event) of an information product before selling it in a digital format.

The benefits of taking this approach are:

• You stay flexible before committing to a large digital product-development project, especially in software.
• You see how customers actually handle the product, not just what they say in interviews.
• You learn the design criteria and economics of the physical form first, before trying to make the product digital.

This is a common pattern in enterprise lean startups, particularly with bigger companies having a lot of legacy processes.

Note: This is not the same as Randy Komisar’s analog/antilog thought experiment from Getting to Plan B (Mullins & Komisar, Harvard Business Press, 2009), which is a desk exercise for formulating a value proposition. The goal here is to gather actual user feedback, based on something physical that approximates the final form of the product.

How to

Prep AI Prompt

1. Identify your riskiest assumption. Confirm that what you need to test is about the value proposition, workflow, or cost structure, not just a technical question. Analog-digital testing works when you need to learn whether the process itself delivers value, before investing in software.

2. Define the learning goal. Write down the one decision the analog run should inform. Common framings: “Does this workflow deliver enough value to justify automating it?” “Which steps add value and which are friction we should remove?” “What does the customer actually do with the output?” Without a goal, you will collect impressions instead of evidence.

3. Pick the analog format. Match the format to the workflow you are testing. Paper forms and spreadsheets fit document-based workflows. Email, phone, and in-person handoffs fit marketplaces and matching. Printed guides, workshops, or live events fit information products. Physical mockups (foam board, 3D print, off-the-shelf hardware) fit IoT and connected devices.

4. Recruit 5–10 users. Pick users who would plausibly buy or use the digital version once it exists. Confirm they have a real task to complete using the analog version, not a hypothetical one.

Analysis AI Prompt

Digital is not good for its own sake. Make sure that you are adding useful features and benefits as you add to the product’s complexity.

1. Score each step on value delivered vs. friction caused. Which steps did users complete eagerly? Which did they skip or complain about? High-value, high-friction steps are the strongest digitization candidates.

2. Separate workflow value from interface value. Sometimes the workflow is right and only the interface needs work. Sometimes the workflow itself is wrong and a polished interface would just hide the problem. Decide which one you are looking at before you scope the digital build.

3. Compare the analog economics to the digital economics. What does it cost to deliver the analog version per customer? What would the digital version cost? If the analog form already meets the customer’s need at a workable cost, a digital version may not be worth building yet.