Fast, On Time, or Fully Utilized? Choosing What to Optimize in Engineering Delivery

Fast, On Time, or Fully Utilized? Choosing What to Optimize in Engineering Delivery

In this episode of "How Many CTOs Does It Take?" podcast, hosts Scott Porad and Brad Hefta-Gaub discuss a leadership conversation where three senior stakeholders wanted different outcomes from engineering: delivering faster, maximizing utilization, or delivering on time—highlighting unclear norms and expectations in the software delivery system. The hosts argue you can't optimize all three at once, note that maximum utilization is a poor goal (systems perform better below 100% utilization), and debate prioritizing speed versus schedule. Scott favors being on time with about 80% accuracy to avoid sandbagging and support business dependencies like launches, while Brad generally prioritizes going fast, especially in early-stage or learning-focused contexts, with "within reason" expectations. They add an unspoken distinction between innovation organizations and manufacturing organizations, and observe that projects often go off schedule due to unclear requirements, shifting scope, or faulty early assumptions.

00:00 Cold Open 01:04 Velocity Tradeoffs Debate 03:07 On Time 80 Percent Rule 03:56 Innovation Versus Manufacturing 05:03 Why Utilization Misleads 06:43 Stage Dependent Speed 09:32 Quality And Launch Systems 11:56 One Project Always Late 12:51 Why Projects Derail 14:41 Front Load The Hard Parts 15:50 Wrap Up And Outro

Resources:

#TechPodcast #EngineeringPodcast #DevTalks #PodcastForDevs #HowManyCTOs #Podcast #CTOs #CTOPodcast #ChiefTechnologyOfficer #Technology #Engineering #SoftwareDevelopment #SoftwareEngineering #TechLeadership #EngineeringLeadership #EngineeringCulture #TechDebates #AI #AIAssistedCoding #AIAssistedProgramming #AIProgramming #AICoding #Velocity #Productivity #Utility #ResourceManagement #GoFast #GoFastBreakThings #ProductManagement #SpeedVsAccuracy #InnovationCulture #Innovation #EfficientTeam #Efficiency

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