Mendix, a Siemens business, announced the general availability of Mendix 10.18.
As engineering leaders, we've all become familiar with DORA metrics: deployment frequency, lead time for changes, change failure rate and mean time to restore. Many of us have looked to these metrics as how we measure the health and success of our engineering orgs.
In fact, our industry has started to view success through the lens of DORA metrics. That view is incomplete and, worse, often misunderstood. For a complete view on how to view DORA metrics and use them to improve engineering teams, we need to acknowledge some long-held misinterpretations.
3 Major Shortcomings for How Dora Is Being Used
1. Business leaders don't always understand how DORA metrics translate to business outcomes
If you've ever mentioned cycle time or deployment frequency to a non-technical leader, you'll immediately remember the blank stare you likely received in return. That's because these are still engineering metrics and non-engineering leaders don't necessarily understand — or care to understand — how the release of a tiny block of work to production helps you reach your monthly or quarterly business goals.
When we use DORA metrics, we aren't speaking about business outcomes. Business leaders want to know how quickly you're able to deliver a full feature, and they want reassurance that shipped features are meeting customer demands at the promised time.
2. Engineering improvement doesn't start with a deck
Having been a developer, I can confidently say developers tend to be interested in one thing: doing their job effectively without idle time in the middle.
When developers are expected to step out of their workflow to make connections between their work and business outcomes (as in when they're handed a deck tracking metrics like revenue and customer churn), it can be extremely frustrating.
We won't see true improvement in engineering organizations until we can quickly make those connections between developer experience and business success.
3. We're overlooking leading indicators of success
DORA metrics are fantastic at measuring lagging indicators of success. As an industry focused on these metrics, though, we're completely overlooking leading indicators — like the review process and pull-request size — that can help us make our teams and workflows quicker.
Bridging the Metrics Gap Between Engineering and Business Outcomes
While it may be difficult to directly connect engineering metrics to business metrics like revenue, there are a few metrics that can act as a bridge between engineering and business teams. These are metrics that focus on the speed at which you deliver new features and your ability to deliver on promises.
Although DORA metrics do not track follow-through or the speed at which new products ship, these metrics can reveal plenty about your engineering team's effectiveness. Here's how:
1. Investment Carvings
Investment Carvings show how much effort is going into a set of self-explanatory, predefined categories of resource deployment. These investment categories include things developers work on like Keeping the Lights On, Developer Experience, Feature Enhancements, and New Capabilities. They can help you understand where your team is compared to industry benchmarks and navigate the organization according to your needs.
2. Project Allocation
Project Allocation shows you what percent of your team is working on each project. This metric is critical to non-engineering leaders because it demonstrates that the team is prioritizing business-critical projects.
Meanwhile, it's critical to you because it provides the ability to say "no" or "not now" to projects of lower priority if your team's time is already spoken for. On top of that, it gives you ammo to ask for additional headcount if you spot gaps in labor allocation.
3. Project Planning Accuracy
Project Planning Accuracy speaks to how often you're able to deliver on promises. This metric is critical to business leaders because it proves they can count on your team to deliver on customer needs. It's critical to you because it shows you where you may be over-promising and under-delivering.
This metric is also one that works in harmony with DORA metrics — with deployment frequency, cycle time, change failure rate and mean time to restore — acting as leading indicators of Project Planning Accuracy.
Make Metrics Matter
As you begin measuring a wider breadth of metrics and bridging the gap between engineering success and the business at large, you'll quickly see engineering improvement, less hostility between engineering and other business functions, and ultimately happier customers and happier developers. Our industry has been using DORA metrics wrong.
Industry News
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Red Hat announced the general availability of Red Hat Connectivity Link, a hybrid multicloud application connectivity solution that provides a modern approach to connecting disparate applications and infrastructure.
Appfire announced 7pace Timetracker for Jira is live in the Atlassian Marketplace.
SmartBear announced the availability of SmartBear API Hub featuring HaloAI, an advanced AI-driven capability being introduced across SmartBear's product portfolio, and SmartBear Insight Hub.
Azul announced that the integrated risk management practices for its OpenJDK solutions fully support the stability, resilience and integrity requirements in meeting the European Union’s Digital Operational Resilience Act (DORA) provisions.
OpsVerse announced a significantly enhanced DevOps copilot, Aiden 2.0.
Progress received multiple awards from prestigious organizations for its inclusive workplace, culture and focus on corporate social responsibility (CSR).
Red Hat has completed its acquisition of Neural Magic, a provider of software and algorithms that accelerate generative AI (gen AI) inference workloads.
Code Intelligence announced the launch of Spark, an AI test agent that autonomously identifies bugs in unknown code without human interaction.
Checkmarx announced a new generation in software supply chain security with its Secrets Detection and Repository Health solutions to minimize application risk.
SmartBear has appointed Dan Faulkner, the company’s Chief Product Officer, as Chief Executive Officer.
Horizon3.ai announced the release of NodeZero™ Kubernetes Pentesting, a new capability available to all NodeZero users.