Measuring Code Effectiveness In The Digital Transformation Era

Lead Marketing Strategist

An INFJ personality wielding brevity in speech and writing.

Edsger Wybe Dijkstra said, “How do we convince people that in programming simplicity and clarity —in short: what mathematicians call “elegance”— are not a dispensable luxury, but a crucial matter that decides between success and failure?”

Imagine what Dijkstra would have said looking at the technology chaos that surrounds “Digital Transformation” today. With a number of technologies coming together to provide customer experience, Digital Transformation today poses major challenges for organizations from an engineering standpoint.

Here are some of them:

I am using a Continuous Delivery strategy to push out releases to market on time but how do I know if my codebase is adding asset value and not technical debt?
Our integration with other service providers is doing a release once in every 4 weeks. Should I upgrade to the latest version or not? What does it mean to my business and my customers?
I am collecting metrics from my codebase and measuring effectiveness. How do I measure the effectiveness of those components that work with my code in delivering the digital experience?
I am collecting a number of engineering metrics. How do I know if these are helping me in the digital transformation journey and eventually in improving my business?
Management wants data that shows improvement between releases while my engineering team is looking for metrics that are meaningful. How do I use the engineering metrics to derive business metrics that the management is interested in?

These are some of the most common questions we have come across in every organization that goes through the digital transformation journey. We realized that in Digital Transformation assignments, it is not enough to just collect metrics but it is important to collect the right metrics, measure their effectiveness and use them to derive a set of business metrics that help organizations know how they are faring.

The result is a set of 26 engineering metrics that we identified, which over a period of time can be measured to derive some significant business metrics for organizations.

Here is a snapshot of some of the key engineering metrics from the 26 we identified:

Some of these can be in your organizations today but as mentioned earlier, the most important call to action from here is to derive a set of business metrics that help organizations benchmark the status of digital transformation efforts and take corrective and preventive actions based on them.

How are you helping organizations in their digital transformation journey?

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