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Helicopter view based on simple algorithms

Portfolio Prioritization is an ongoing challenge — it’s quite tricky to  maximize the value of the portfolio for a given resource expenditure. The ultimate goal is to reduce the cost of a product discovery mistake, in order to bring products to market faster. 

What are the tools you use to make a choice on 100 hypotheses to test with limited resources and time? In this article my friend Ksenia describes the product portfolio assessment methodology she uses and would be grateful for feedback. Please grab your thoughts in comments!

  1. Basically, we take NVP as a base of Product Rankings and deduct all the risks. 

Just to remind, the equation for calculating net present value is as follows:


image.png

  1. Here are the groups of risks we consider to be deducted from the NPV. Please feel free to use this approach within your company and share your feedback. 

Each type of risk has its own weight depending on the level of “proof” and arguments your Product Managers can demonstrate and the depth of the work they have done. You know all of these risks — the challenge is to determine the weight that’s varying from industry to industry and depends on the product framework you use.

  • Risk related to novelty 
  • Risk related to a mistake with new product concept 
  • Progress risk 
  • Risk related to competitors
  • Risk related to consumer preferences change
  • Risks related to consumer conservatism 

 

  1. So, the Product Rankings Algorithm is following:
  1. First, you calculate NPV for each product or feature
  2. Then, for each type of risk you need to estimate KPIs and proof / confirmation you’ll ask from your PMs
  3. and the weight of this risk inline with your industry
  4. Finally, summarize all the risks and deduct them from NPV

We calibrated weights for E-commerce, EdTech, Telecom, Fintech and other digital. Prior to developing a stand alone tool we started with a Jira plugin. Feel free to ask and try it for free ➡️ 

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