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Engineering Leader’s Guide to Predictable Project Delivery
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Building a Predictable Project Delivery Engine
Engineering Has a Predictability Problem
The industry average for planning accuracy is <50%. That means R&D leaders are wrong more than they’re right–leading to missed deadlines, unkept promises, and tough conversations with executive stakeholders.
This predictability gap also means other teams can’t do their jobs–like accurately updating customers or selling future product features.
The Predictability Equation
The general formula for delivering project predictability is to ensure stability, maintain execution velocity, and de-risk the engineering organization. While stability and velocity are key, risk (and striving to minimize it) is the variable that needs the most attention. Here are some common examples of risk:
Lots of unplanned work
Lack of focus on business priorities
A bad developer experience (DevEx)
It’s by removing risk that predictability is able to come to fruition.
How to Build a Predictable Delivery Engine
As predictable project delivery is the most likely (and best) outcome for engineering improvement initiatives, it probably comes as no surprise that getting there is a multi-stage process. To get to predictability, engineering teams will need to:
Learn How Syngenta Became Predictable at Scale
Using the success model outlined in the Engineering Leader’s Guide to Predictable Project Delivery, Syngenta–a global leader in agricultural technology–was able to reduce Cycle Time by 81% and increase Planning Accuracy by 33%. What’s more they did it while scaling their engineering organization from 150 to 400 distributed developers–all in the span of just six months!
These incredible results will help ensure that Syngenta can continue delivering innovation to their customers reliably and predictably as they work to empower millions of farmers around the world.
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