Metrics
1. The rise and rise of end-to-end software delivery metrics
Delivery metrics were well used in the pre-Agile ‘waterfall’ era. But that changed with the arrival of Agile software delivery twenty years ago.
The Agile Manifesto sets out a better way to deliver software. It is based on some core ‘democratic’ principles that empower individuals and teams to be self-determining and to define their own work schedules and processes. As such it has (on balance) been very successful and has been adopted by over 80% of enterprises globally in some form.
A core element of this culture of self-determination has been a healthy scepticism of top-down metrics and analytics.
However, the Agile approach is now 20 years old and well past the ‘honeymoon period’. As a result, larger enterprises particularly (who face the challenge of implementing Agile at scale) – now recognise that data analytics can play a crucial role in effective Agile software delivery. Hence the current explosion of interest in software delivery metrics.
As shown in Figure 1 below, the pressures of the ‘new normal’ world have only accelerated the recognition of the importance of analytics to improve delivery effectiveness.
It is widely recognised now that software delivery metrics and analytics can help improve delivery effectiveness in multiple ways:
- remaining Agile and delivering software more dependably (predictably), in keeping with the timing requirements of customers;
- improving the quality and security of both the software itself and the process of software delivery;
- increasing velocity and increasing the throughput of value delivered (reducing Time to Value);
- and empowering teams to self-improve over time.
As such, delivery metrics can play a critical role in many widely experienced challenges (use cases) in delivery organisations as shown in Figure 2 below.
