Understanding Productivty

Reliable, actionable metrics are critical for identifying where the problems lie in your software development processes. Unfortunately, many organisations fail to use effective metrics during analysis. Using poor quality metrics may lead to unactionable data or worse, inspire changes that harm productivity rather than improve it.

Reliable, actionable metrics are critical for identifying where the problems lie in your software development processes. Unfortunately, many organisations fail to use effective metrics during analysis. Using poor quality metrics may lead to unactionable data or worse, inspire changes that harm productivity rather than improve it. This article will review the importance of using appropriate metrics during developer analysis. We’ll highlight why some of the most commonly used KPI metrics for software development might not provide accurate or relevant information to managers.

The Importance of Using the Right Metrics

By utilising high quality and actionable performance data, everyone benefits. Recruiting managers hiring new personnel will be able to highlight the skill gaps within an organisation, DevOps teams will have better information when trying to optimise workflows, and senior managers will have a clearer picture of software delivery performance.

• Reliable: Of all the potential flaws in bad metrics, the worst is for the data to be inconsistent or open to interpretation. Leaders must be able to trust that the metrics they receive are accurate — otherwise, any changes they make based on that data will be ineffective or harmful.
• Objective: Of all the potential flaws in bad metrics, the worst is for the data to be inconsistent or open to interpretation. Leaders must be able to trust that the metrics they receive are accurate — otherwise, any changes they make based on that data will be ineffective or harmful.
• Actionable: Of all the potential flaws in bad metrics, the worst is for the data to be inconsistent or open to interpretation. Leaders must be able to trust that the metrics they receive are accurate — otherwise, any changes they make based on that data will be ineffective or harmful.

Without the correct metrics, team leaders and managers will struggle to get an accurate picture of the software development problems blocking their team’s productivity.

Metrics to Avoid When Identifying Software Development Problems

1. Counting Lines of Code

Counting lines of code (also known as LOC or SLOC) is one of the oldest KPI metrics for software development, but it’s also one of the most flawed.

The sole advantage of LOC as a metric is that it’s simple and easily automated. However, the metric offers no strategic value. LOC very clearly indicates how much work a developer has done in a specific period, but it has no way of measuring quality. It’s also very limited as it’s only able to show how many lines were added, not the amount of effort needed to make those changes. Furthermore, the metric is rarely applicable across different programming languages.

If your team’s only problem is that some members are not contributing, this metric will quickly indicate where the problem lies. However, if you want to identify the intellectual effort that’s gone into making a change or to manage technical debt, LOC will be of little help.

2. Function Points

Counting lines of code (also known as LOC or SLOC) is one of the oldest KPI metrics for software development, but it’s also one of the most flawed.

The sole advantage of LOC as a metric is that it’s simple and easily automated. However, the metric offers no strategic value. LOC very clearly indicates how much work a developer has done in a specific period, but it has no way of measuring quality. It’s also very limited as it’s only able to show how many lines were added, not the amount of effort needed to make those changes. Furthermore, the metric is rarely applicable across different programming languages.

If your team’s only problem is that some members are not contributing, this metric will quickly indicate where the problem lies. However, if you want to identify the intellectual effort that’s gone into making a change or to manage technical debt, LOC will be of little help.