Lessons on Product Strategy

  1. Interviewee profile
  • familiar operating in the space between USD 0-100 million revenue

Startup’s three top concerns

  • Product market fit
  • Distribution
  • Business/Monetization model

Types of Tech companies

  • Software – network companies
  • Software – efficiency companies
  • Hardware

Drivers that create a fast moving environment which makes possible fast Pace of innovation

  • Network capacity
  • Moores law – hardware capability
  • more product n services gets created that were previously not possible
  • This is on top of Demographic changes – traditional companies will generally deal with this

Five year plans needs to take into account the chip/network innovation trajectory

A typical cycle of planning

  • 3 year visions
  • plan for next 4 quarters
  • ship on a weekly basis
  • vision could always change

Time horizons for execution iterations

  • Pre-production market fit – typically looking at 3 months outlook
  • Pre-distribution – go to market – typically looking at 1-2 years (become more traditional cycle)

RnD that is ahead of the curve to understand where the trend is else we become obsolete

Software is going into a lot of traditional industries that is changing the game

  • Uber

Frameworks/principles to develops strategy

  • strategy = differentiated value proposition
  • customer segmentation
  • value proposition to segment
  • how are we different
  • capabilities developed within the company
  • what are we not doing
  • product is a major part of the strategy = a differentiated product is extremely important especially for network based companies
  • how are we building and leveraging network effects
  • distribution mechanism
  • potential competitive moat
  • data networks
  • collect n use data they are collecting it is a huge asset
  • communications networks
  • everybody wants to communicate on it
  • how build and design network values

Measurements

  • because is technology base – can deploy much faster deploys everyday some new value to
  • instrumented correctly impacting the market everyday
  • combine data and feedback to company
  • marginal distribution cost is zero
  • data implementation and rapid experiment
  • design Thinking is becoming popular – core part of software technology space
  • startups need discipline to implement this (competitive advantage) shorter planning cycle

Business model

  • Can experiment pricing since zero distribution cost

source: From an interview done with Ved

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