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Evaluate Revenue Assumptions


Revenue Planning Home | Measure Different Revenue Streams | Evaluate Revenue Assumptions | Accurately Manage Revenue Budgets | Continuously Forecast Revenue | Consistently Analyze and Report Revenue


What effect will changing the revenue driver have on sales targets?

Revenue calculations typically incorporate multiple revenue drivers. Depending on the targeted industry these revenue drivers can vary drastically. Examples of common drivers utilized by organizations to derive revenue amounts include price, quantity, units, rate, square footage, days, beds, hours, and volume. When organizations are evaluating business models and refining assumptions, it is highly informative to look at key revenue drivers to identify problem areas and manipulate business assumptions as required.

To identify problem areas and ultimately analyze revenue, it is invaluable for organizations to consistently monitor and measure key revenue drivers. Understanding the key reason why revenue targets are not being met can help unveil potential deep-rooted problem areas and ultimately produce more effective decisions that will assist in meeting projected targets.

Why is it critical to analyze & evaluate revenue drivers?

  • Identifies unknown variances
  • Breaks down components influencing revenue
  • Easily measures company performance against key drivers
  • Different product/service offerings can be presented to customers
  • Reduces uncertainty about business decisions; all factors are explicit
  • Competitive strengths become apparent and are better developed
  • Ongoing comparisons to the competition and industry trends

Why PROPHIX for managing revenue drivers?

  • Completely tailored to the business model
  • Automatic adjustments through centralized formulas
  • Unlimited drivers and assumptions can be applied
  • Adjustments can be made without jeopardizing data integrity
  • Sales personnel can make changes without IT involvement
  • Adaptability & flexibility are essential components of the business model

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