Tristan Kromer

Innovation Accounting

Learn how to map customer journeys, build visual and financial models, and use statistical tools to communicate the value of your innovation efforts effectively.

Talk transcript of Tristan Kromer – recorded on 20 Mar 2024 Experimentation & Testing


Experimentation & testing Analytics & metrics Business models Business strategy Customer acquisition Data informed decisions Experimentation & testing Frameworks & methods Funding Product discovery Product management Risk management Validation


Innovation accounting is a critical tool for product teams, startups, and large organizations alike. It provides a structured approach to measuring and managing innovation, enabling teams to demonstrate the value of their efforts in financial terms that stakeholders and investors can understand. In this blog post, we delve into the insights shared by Tristan Kromer during his talk at the Product Loop meetup. We’ll explore the concept of innovation accounting, common challenges, and practical strategies to effectively communicate the ROI of innovation projects.

Understanding Innovation Accounting

Innovation accounting is the practice of using metrics and financial models to quantify the impact of innovation activities. It bridges the gap between the creative aspects of product development and the financial expectations of stakeholders. The goal is to provide a clear, quantifiable understanding of how innovative projects contribute to the organization’s bottom line.

One of the biggest challenges in innovation is the question of return on investment (ROI). At some point, every CEO, venture capitalist, or finance officer will ask for the ROI of your innovation projects. This is a tricky question, especially in the early stages of product development, where uncertainty is high and concrete financial outcomes are hard to predict.

Common obstacles are:

  1. Early-Stage Uncertainty: It’s nearly impossible to predict the ROI of an idea at its inception. Early-stage projections are often based on assumptions and lack sufficient data.
  2. Misalignment with Financial Metrics: Traditional financial metrics and business models do not easily accommodate the uncertainties and iterative nature of innovation.
  3. Communication Gap: There is often a disconnect between the language of innovators (e.g., sticky notes, customer personas) and the language of finance (e.g., net present value, ROI).

How to prove ROI of Product Discovery and Experimantation to your CEO

To address these challenges, Tristan Kromer proposes a structured approach to innovation accounting that involves translating qualitative insights from user research and experimentation into quantitative financial models.

1. Map the Customer Journey

Start with a detailed customer journey map to understand the entire process a user goes through with your product. Identify key metrics at each stage of the journey, such as:

  • Awareness: How do users learn about your product?
  • Engagement: What motivates users to try your product?
  • Conversion: What percentage of users convert from trial to purchase?
  • Retention: How many users return to use the product again?
  • Referral: How many users recommend your product to others?

By mapping these stages, you can identify conversion rates and key performance indicators (KPIs) that can be tracked and measured.

2. Build a Visual Model

Create a visual model that represents the business outcomes based on the customer journey. This model should include:

  • Conversion Rates: The percentage of users moving from one stage to the next.
  • Revenue Streams: The financial impact of conversions at each stage.
  • Costs: The expenses associated with acquiring and retaining customers.

This visual model helps in understanding how improvements at each stage of the customer journey can impact overall business outcomes.

3. Develop a Hypothesis-Driven Financial Model

Transform your visual model into a hypothesis-driven financial model. This involves:

  • Identifying Assumptions: Clearly state the assumptions behind each metric in your model (e.g., conversion rates, average order value).
  • Setting Ranges: Instead of using single-point estimates, use ranges to represent uncertainty (e.g., conversion rate between 10-15%).
  • Testing Hypotheses: Design experiments to validate or refute your assumptions. Use A/B testing, usability testing, and other methods to gather data.

4. Use Statistical Modeling

Leverage statistical tools to run simulations and generate a range of possible outcomes. This approach, known as Monte Carlo simulation, allows you to:

  • Express Uncertainty: Show a range of possible outcomes rather than a single, precise prediction.
  • Calculate Probabilities: Determine the likelihood of achieving specific financial goals.
  • Prioritize Experiments: Identify which assumptions have the greatest impact on your financial model and focus on testing those first.

5. Communicate Results Effectively

Present your findings in a way that aligns with the language of finance. Use graphs and charts to illustrate:

  • Expected Outcomes: Show the range of possible outcomes based on current data.
  • Impact of Experiments: Demonstrate how new data has refined your predictions and reduced uncertainty.
  • Progress Over Time: Highlight how iterative testing and learning improve the accuracy of your financial projections.

Practical Application: A Food Truck Example

To illustrate these principles, Tristan Kromer uses the example of a hypothetical food truck business. Here’s a simplified version of how you can apply innovation accounting to this scenario:

  1. Define the Customer Journey: Map out the steps a customer takes from learning about the food truck to making a purchase.
  2. Identify Key Metrics: Track metrics such as foot traffic, percentage of passersby who stop, percentage who buy, and average order value.
  3. Create a Visual Model: Develop a funnel model showing conversion rates at each stage.
  4. Build a Financial Model: Translate the visual model into a spreadsheet, using ranges to represent uncertainty.
  5. Run Simulations: Use statistical tools to generate a range of financial outcomes and identify which metrics have the biggest impact.
  6. Communicate with Stakeholders: Present your findings in a clear, quantifiable manner, showing both the potential and the uncertainty.

Adopting a structured approach to mapping customer journeys, building visual and financial models, and using statistical tools, product teams can effectively communicate the value of their innovation projects.

This not only helps in securing ongoing support and funding but also ensures that innovation efforts are aligned with business goals and capable of driving sustainable growth. Embrace innovation accounting to turn uncertainty into actionable insights and foster a culture of continuous learning and improvement.


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