Building the Continuous Feedback Engine Using Proxy Metrics

Why feedback is the real engine of improvement

Every improvement cycle starts with feedback from the previous cycle and ends with feedback.
Without timely and trusted signals, teams guess whether their changes made a difference. That is when dashboards grow while learning slows.
A continuous feedback engine shortens the loop between action and insight. It helps people make better decisions faster and with more confidence. This is a universal idea that not only works for development but for any area that requires improvement.

From proxy metrics to feedback flow

In The Principles of Product Development Flow, Don Reinertsen describes proxy metrics as indicators that stand in for overall and measurable system performance.
You cannot affect top level metrics directly but you can improve the proxies. For example, Cycle Time. Batch Size. Queue Management.
These signals matter when they are tied to action. Continuous Delivery by Jez Humble and David Farley provides that action. Automation, small batches, and frequent releases convert signals into motion.

The Batch Size example

Here is the simple message.
Smaller batch sizes allow a clearly scoped piece of work to finish sooner.
Larger batch sizes create a more traditional way of working that moves many pieces together and slows learning.
Small batches speed up knowledge creation and reduce delays in understanding. People see cause and effect sooner and, information surfaces earlier. Decisions improve because evidence arrives quickly.

Designing your continuous feedback engine

You do not need a large program to start. You need clarity and rhythm.

1. Define your flow path.
2. Introduce fast feedback loops.
3. Track a few proxies.
4. Make feedback visible with a simple Dashboard.
5. Review on a cadence.

Learning and knowledge creation are critical

Traditional organizations measure to show. Adaptive organizations measure to learn.
When proxy metrics connect to delivery rhythms, knowledge creation is part of daily work. The key question becomes simple … What did we learn and how will we adjust now?

Why combining these ideas works

Reinertsen provides clarity on what to watch. Humble and Farley provide the mechanisms to act.
Together they close the gap between knowing and doing. They help leaders and teams turn data into direction, direction into experiments, and experiments into momentum.

What comes next

In the next article I describe leadership rhythms and the flow of decisions. The goal is a single operating model where metrics, cadence, and culture reinforce one another.

Are you interested in how to do this?

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