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How to Strengthen Your Strategic Assumptions with Engineering Benchmarks

Aston Whiteling | May 18, 2022

Engineering Operations

Productivity

Strategic Alignment

benchmarking

This article relates to a Jellyfish Product feature. If you’d like to see it in action, you can book a live demo here.

 

Adaptability.

 

That’s the name of the game, right?

 

In the hyper-tooled, process-driven world of Software Engineering, being able to recognize the ideal workflow, process and tooling scenarios for your teams is what establishes your organization as elite and, crucially, keeps you ahead of the competition.

 

But how can you be certain your assumptions are valid? As an engineering leader, the beliefs you hold underpin important decisions in key, strategic areas; even with years of experience and historic success, it’s still best practice to reinforce your notions with data compiled from a range of sources, and not to just rely on your gut and anecdotes. 

 

The issue with this approach has always been getting your hands on actionable data.

Sure, industry leaders will provide broad stroke insights into how they run their operations, often while on-stage bragging about their success at a tech conference, but the important stuff – the nitty-gritty, metric level data – still seems a closely guarded corporate secret. 

 

This is one of the reasons that Accelerate – the business handbook released by Google’s DevOps Research and Assessment Group (DORA) that kick started a DevOps metrics revolution – was so successful. Data-driven insight is the foundation of strategic thinking. Understanding how your organization stacks up across key measures is critical for the seamless execution of engineering strategy. 

 

As this data isn’t being openly shared, you might wonder – what’s the best way to access it? The answer: Engineering Management Platforms (EMP) that provide an expansive set of metric-based Benchmarks.

 

On the Mark

 

Benchmarking as a feature is increasingly being sought after across the Engineering Management space. As the industry moves toward metric-driven engineering, modern technical leaders – guided by the high level of performance data that can already be inferred from the likes of git or jira activity – seek not only an understanding of historic team performance, but the context of that performance in comparison to their industry equivalents.

 

Achieving this isn’t always intuitive. 

 

Engineering leaders, perhaps more than any other executive, are born in the crucible of the operational function they oversee. They’ve engaged in countless stand-ups, spent evenings pouring over code to implement an emergency fix and, in doing so, built up a fierce camaraderie within their teams, all whilst simultaneously maneuvering around  crunch-based delivery expectations enforced by a business hierarchy that doesn’t necessarily understand them. Sure, sales leaders spend time in the trenches closing deals – but, by nature, they’re more aligned with the social politics of business than, say, engineers who find themselves promoted to a VP role. 

 

Engineering leaders have scars. And the stories behind those scars are often used as a driving force when it comes to their decision making. 

 

But what makes a truly elite engineering leader is the ability to recognize both the need for calculated, data-driven decisioning, as well as the necessity to communicate that decisioning to their fellow executives. 

 

The first part comes easy; the technical nature of the role often lends itself to data-driven conclusions. But, due to the aforementioned schism in professional experiences, the communication aspect can be more of a challenge. 

 

Benchmarking is the bridge across that chasm.

 

With easy-access metric data from la creme de la creme of engineering, technical leaders can directly correlate their decisions to team performance and assuredly hold that performance up as competitive against other industry leaders. They can also quietly adopt an inverse policy; when a metric isn’t chugging in the right direction, they can make informed choices in order to course correct and achieve a closer-to-optimal model.

 

The learning derived from the experience? That’s just the cherry on top. 

 

When leveraged successfully, Benchmarking allows engineering leaders to project confidence to fellow executives when explaining their strategic decisions, whilst also understanding any specific area of operations in which they are lagging at an industry level.

 

There is, however, a key caveat when talking about platforms that offer Benchmarks like this… 

 

What do you Bench? 

 

… Benchmarks are only as good as the dataset which powers them. 

 

If the platform offering Benchmarks doesn’t have a large, suitably diverse or high quality stable of customers, then being in the 99th percentile in comparison doesn’t really mean much. 

 

Something to keep in mind anytime a smaller, less established vendor is trying to tout their Benchmarking capabilities or promote a ‘Benchmarking page’ where they lack in-app functionality.

 

Jellyfish is the industry leader in the Engineering Management space. As such, we’re incredibly lucky to count thousands of teams (including a host of other industry leaders), across a variety of verticals, among our customers – including ZoomInfo, Toast, Acquia, Salsify and many more.  

 

This ensures we can provide the most accurate, relevant and comprehensive Benchmarks to our entire customer base.

 

If you’d like to learn more about Jellyfish Benchmarks or see them in action, check out our benchmarking demo video or book a live platform demo today. 

 

Aston Whiteling