Doing revenue/cost drivers correctly?

Your framework for revenue and cost drivers is solid and aligns with many of the best practices discussed in WSO's top-rated content on DCF modeling and valuation. Here's a breakdown of your approach and answers to your specific questions:

Revenue Drivers:

1. "Anchor the endpoints, justify the shape, accept uncertainty in the middle":

   • This is a widely accepted approach. As highlighted in WSO's DCF resources, the intermediate years often involve judgment and economic logic rather than hard evidence. For example, segmenting revenue by drivers like price, volume, and mix is a thoughtful way to approach this. Using trends, base effects, and maturity levels to guide your assumptions is both practical and defensible in interviews.
   • To enhance rigor, you could incorporate more granular data, such as historical KPIs (e.g., subscriber growth for Netflix, ARPU trends) or management guidance from earnings calls. This adds credibility to your intermediate-year assumptions.

2. Intermediate-year precision:

   • You're not overthinking it. The discomfort you feel is natural because forecasting inherently involves uncertainty. The key is to ensure your assumptions are logical, consistent, and supported by qualitative or quantitative reasoning. For instance, if Netflix's subscriber growth is slowing, you might justify a front-loaded deceleration curve based on market saturation.

Cost Drivers:

1. Operating costs and reinvestment:

   • Your two-bucket approach is sound. Using operational ratios for mature businesses and explicitly projecting reinvestment aligns with WSO's guidance. Cross-checking against the growth = reinvestment rate × ROIC identity is a great way to ensure consistency, but it’s more of a sanity check than a strict rule. In practice, analysts often focus on whether reinvestment assumptions align with the company's historical trends and industry benchmarks.

2. Reinvestment/ROIC identity:

   • While this identity is academically robust, in practice, it’s used more as a validation tool rather than a primary driver. For example, if your reinvestment assumptions imply an unrealistic ROIC, it’s a signal to revisit your inputs. However, don’t let it overly constrain your model—real-world businesses often deviate from theoretical norms.

Defending the Final Forecast Year:

• "Converging toward maturity" is a reasonable defense, but you can strengthen it by referencing industry benchmarks or comparable companies. For instance, if Netflix is nearing saturation in developed markets, you might argue that its growth rate in the final forecast year should align with GDP growth or the broader entertainment industry’s growth rate.
• Additionally, consider qualitative factors like competitive dynamics, technological advancements, or management’s long-term strategy to justify your assumptions.

Smell Test in Interviews:

• Your logic would likely pass the smell test, especially if you can articulate your reasoning clearly and tie it to real-world data or trends. Interviewers are less concerned with perfect precision and more interested in whether your assumptions are thoughtful, consistent, and grounded in reality.

Final Tips:

• To further refine your approach, consider incorporating Monte Carlo simulations or scenario analysis to account for uncertainty in your assumptions. This is particularly useful for companies like Netflix, where future performance is influenced by unpredictable factors like content success and competition.
• Always be prepared to explain the "why" behind your assumptions. For example, if you assume a deceleration curve for revenue growth, be ready to discuss the underlying drivers (e.g., market saturation, competitive pressures).

Your reasoning is on the right track, and with a bit more emphasis on tying assumptions to data or qualitative insights, you'll be well-prepared for both modeling and interviews. Keep up the great work!

Sources: DCF Modeling Course ~ Pre-training text.pdf, DCF Myth 3.2: If you don't look, its not there!, Help with Writing ER Reports for Beginners (Value Investing)