# Buyer’s Guide: Choosing a Software Engineering Intelligence Platform [ebook]

This post is part of our historical archive. It represents the beliefs, actions, products, and services of Code Climate as of its publication date. Today, Code Climate focuses on providing enterprise leaders the software development data, context layer, and playbooks needed to build the AI-native software organization their enterprise needs. Head to codeclimate.com to learn more.

**Jun 5, 2023**

**4 min read**

In 2022, IT spending for organizations worldwide [exceeded $4.4 trillion](https://www.forbes.com/sites/vijaygurbaxani/2022/04/08/what-gartners-44-trillion-it-spending-forecast-tells-us-its-a-software-economy/?sh=5196d21874cb), underscoring the essential role of tech in today’s economy. Gartner’s research shows that investment in technology is key to business success, spurring a heightened focus on the software engineering organizations behind that technology.

Engineering organizations are now under greater pressure to maximize ROI, effectively allocate resources, communicate with stakeholders on progress, and deliver quality software quickly. To achieve this, engineering leaders need visibility into engineering processes, where resources are going, and how their teams are working.

## The challenge of visibility in engineering

In the past, leaders have relied on homegrown solutions and surveys to assess the state of the engineering organization. These solutions can be error-prone and time consuming, requiring leaders to manually gather information from a variety of sources like project management tools and version control systems.

To gain critical context and dependable data, leaders should leverage a [Software Engineering Intelligence (SEI) platform](/content/blog/software-engineering-intelligence-platform/index.html). An SEI platform ingests, cleans, links, and analyzes data from teams’ existing systems, surfacing those insights via alerts, custom reporting, and intuitive visualizations. This gives leaders the visibility they need to evaluate tradeoffs, mitigate risk, enhance communication, boost engineering efficiency, and improve value delivery.

> Gartner predicts that 70% of organizations will have an SEI platform by 2026, up from 5% in 2023.

(Source: Innovation Insight for Software Engineering Intelligence Platforms, March, 2023)

How can engineering leaders best evaluate which SEI platform is the best option for their organization?

We’ve put together a comprehensive [buyer’s guide](/content/ebook/software-engineering-intellgence-platform-buyers-guide?utm_source=website&utm_medium=blog&utm_campaign=buyersguide&utm_id=buyersguide/index.html) outlining what leaders should look for in an SEI platform, including key features and capabilities.

Click to download the guide.

## We recommend assessing SEI platforms on the following categories:

- **Process and Team Health:** An SEI platform should provide a multidimensional picture of team health, while adapting to variations in team process.

- **Allocations and Business Value:** It’s imperative that an SEI platform help leaders accurately assess resource allocation and quantify engineering impact.

- **Efficiency and Predictable Delivery:** The right SEI platform should help leaders improve their team’s ability to deliver code consistently, predictably, and at high quality.

- **Team Effectiveness:** An SEI platform will offer insight into whether interruptions, wasted work, or other factors are impacting engineering’s ability to deliver value.

- **Data Hygiene and Analysis:** The best SEI platform will deliver trustworthy insights while working in tandem with the tools and workflows a team is already using.

- **Scalability and Customization:** An SEI platform should be able to meet the unique needs of complex, large, and ever-evolving organizations.

- **Security:** The best SEI platforms will prioritize the security of your data.

Code Climate’s enterprise-level insights platform is the only one to offer enterprise-grade security and scalability. From day one, Code Climate maximizes engineering impact with trusted and actionable insights for leaders and teams at all levels — from capacity and delivery to quality, culture, and costs.

**As outlined in the guide, Code Climate's platform provides unique advantages in four key areas:**

- **Clear Focus on Improving the Efficiency and Output of Engineering Teams:** Code Climate's platform provides critical visibility into development processes, including insights for coaching and for improving the overall health and efficiency of an engineering organization.

- **Security and Scalability for Large, Complex Organizations:** Code Climate adapts to our customers’ needs, and our security and scalability capabilities are built to handle the largest enterprises.

- **Personalized Customer Experience:** Code Climate offers a superior customer experience from Day 1, with white-glove support, thorough technical onboarding, multiple training options, and a consultative approach to change management.

- **Customizations That Adapt to How Our Customers Work:** Code Climate's platform is highly customizable, adapting to the way our customers work. The platform offers autonomy for each of your engineering teams so that they can best leverage metrics to improve performance.

[_Download the complete guide to choosing an SEI platform_](/content/ebook/software-engineering-intellgence-platform-buyers-guide?utm_source=website&utm_medium=blog&utm_campaign=buyersguide&utm_id=buyersguide/index.html) _and find out more about the advantages of SEI, including what to look for when evaluating each of the key capabilities, and a detailed breakdown of how Code Climate measures up._

About  
Code Climate

## Why a Strategy Matters

At the heart of every successful software engineering team is a drive for three things:

1. A culture of continuous improvement
2. The ability to move from idea to impact quickly, frequently, and with confidence
3. A software organization delivering meaningful value

These goals sound simple enough, but in reality, achieving them requires more than just wishing for better performance. It takes data, action, and, most importantly, a cultural shift. And here's the catch: those three things don't come together by accident.

In my experience, whenever a large-scale change fails, there's one common denominator: a lack of a cohesive strategy. Every time I’ve witnessed a failed attempt at implementing new technology or making a big shift, the missing piece was always that strategic foundation. Without a clear, aligned strategy, you're not just wasting resources—you’re creating frustration across the entire organization.

## Step 1: Define Your Purpose

The first step in any successful engineering insights strategy is defining why you're doing this in the first place. If you're rolling out developer productivity metrics or an insights platform, you need to make sure there’s alignment on the purpose across the board.

Too often, organizations dive into this journey without answering the crucial question: Why do we need this data? If you ask five different leaders in your organization, are you going to get five answers, or will they all point to the same objective? If you can’t answer this clearly, you risk chasing a vague, unhelpful path.

One way I recommend approaching this is through the **"Five Whys"** technique. Ask why you're doing this, and then keep asking "why" until you get to the core of the problem. For example, if your initial answer is, _“We need engineering metrics,”_ ask why. The next answer might be, _“Because we're missing deliverables.”_ Keep going until you identify the true purpose behind the initiative. Understanding that purpose helps avoid unnecessary distractions and lets you focus on solving the real issue.

## Step 2: Understand Your People

Once the purpose is clear, the next step is to think about who will be involved in this journey. You have to consider the following:

1. Who will be using the developer productivity tool/insights platform?
2. Are these hands-on developers or executives looking for high-level insights?
3. Who else in the organization might need access to the data, like finance or operations teams?

It’s also crucial to account for organizational changes. Reorgs are common in the enterprise world, and as your organization evolves, so too must your insights platform. If the people responsible for the platform’s maintenance change, who will ensure the data remains relevant to the new structure? Too often, teams stop using insights platforms because the data no longer reflects the current state of the organization. You need to have the right people in place to ensure continuous alignment and relevance.

## Step 3: Define Your Process

The next key component is process—a step that many organizations overlook. It's easy to say, "We have the data now," but then what happens? What do you expect people to do with the data once it’s available? And how do you track if those actions are leading to improvement?

A common mistake I see is organizations focusing on metrics without a clear action plan. Instead of just looking at a metric like PR cycle times, the goal should be to first identify the problem you're trying to solve. If the problem is poor code quality, then improving the review cycle times might help, but only because it’s part of a larger process of improving quality, not just for the sake of improving the metric.

It’s also essential to approach this with an experimentation mindset. For example, start by identifying an area for improvement, make a hypothesis about how to improve it, then test it and use engineering insights data to see if your hypothesis is correct. Starting with a metric and trying to manipulate it is a quick way to lose sight of your larger purpose.

## Step 4: Program and Rollout Strategy

The next piece of the puzzle is your program and rollout strategy. It’s easy to roll out an engineering insights platform and expect people to just log in and start using it, but that’s not enough. You need to think about how you'll introduce this new tool to the various stakeholders across different teams and business units.

The key here is to design a value loop within a smaller team or department first. Get a team to go through the full cycle of seeing the insights, taking action, and then quantifying the impact of that action. Once you've done this on a smaller scale, you can share success stories and roll it out more broadly across the organization. It’s not about whether people are logging into the platform—it’s about whether they’re driving meaningful change based on the insights.

## Step 5: Choose Your Platform Wisely

And finally, we come to the platform itself. It’s the shiny object that many organizations focus on first, but as I’ve said before, it’s the last piece of the puzzle, not the first. Engineering insights platforms like Code Climate are powerful tools, but they can’t solve the problem of a poorly defined strategy.

I’ve seen organizations spend months evaluating these platforms, only to realize they didn't even know what they needed. One company in the telecom industry realized that no available platform suited their needs, so they chose to build their own. The key takeaway here is that your platform should align with your strategy—not the other way around. You should understand your purpose, people, and process before you even begin evaluating platforms.

## Looking Ahead

To build a successful engineering insights strategy, you need to go beyond just installing a tool. An insights platform can only work if it’s supported by a clear purpose, the right people, a well-defined process, and a program that rolls it out effectively. The combination of these elements will ensure that your insights platform isn’t just a dashboard—it becomes a powerful driver of change and improvement in your organization.

Remember, a successful software engineering insights strategy isn’t just about the tool. It’s about building a culture of data-driven decision-making, fostering continuous improvement, and aligning all your teams toward achieving business outcomes. When you get that right, the value of engineering insights becomes clear.

**_Want to build a tailored engineering insights strategy for your enterprise organization? Get expert recommendations at our free insights strategy workshop._**   
[**_Register here._**](/content/cc/engineering-insights-strategy-workshop/index.html)

[**_Andrew Gassen_**](https://www.linkedin.com/in/andrewgassen/) _has guided Fortune 500 companies and large government agencies through complex digital transformations. He specializes in embedding data-driven, experiment-led approaches within enterprise environments, helping organizations build a culture of continuous improvement and thrive in a rapidly evolving world._

## Navigating New Technology Expectations in Software Engineering Leadership

### New Technology: AI, No-Code/Low-Code, and SEI Platforms

There's Generative AI, such as Copilot, the No-code/Low-code space, and the concept of Software Engineering Intelligence (SEI) platforms, as coined by Gartner®. The promises associated with these tools seem straightforward:

- Generative AI aims to accelerate, improve quality, and reduce costs.
- No-code and Low-code platforms promise faster and cheaper software development accessible to anyone.
- SEI platforms such as Code Climate enhance productivity measurement for informed decisions leading to faster, efficient, and higher-quality outcomes.

However, the reality isn’t as straightforward as the messaging may seem:

- Adopting Generative AI alone can lead to building the wrong things faster.
- No-code or Low-code tools are efficient until you hit inherent limitations, forcing cumbersome workarounds that reduce maintainability and create new challenges compared to native code development.
- As for SEI platforms, as we've observed with our customers, simply displaying data isn't effective if you lack the strategies to leverage it.

When I joined Code Climate a year ago, one recurring question from our customers was, _"We see our data, but what's the actionable next step?"_ While the potential of these technologies is compelling, it's critical to address and understand their practical implications. Often, business or non-technical stakeholders embrace the promises while engineering leaders, responsible for implementation, grapple with the complex realities.

### Navigating New Technology Challenges and Taking Action

Here's how Code Climate is helping software engineering leaders take actionable steps to address challenges with new technology:

1. Acknowledging the disconnect with non-technical stakeholders, fostering cross-functional alignment and realistic expectations. Facilitating open discussions between technology and business leaders, who may never have collaborated before, is crucial for progress.
2. Clearly outlining the broader scope of engineering challenges beyond just writing code—evaluating processes like approval workflows, backlog management, and compliance mandates. This holistic view provides a foundation for informed discussions and solutions.
3. Establishing a shared understanding and language for what constitutes a healthy engineering organization is essential.

In addition, we partner with our enterprise customers to experiment and assess the impact of new technologies. For instance, let's use the following experiment template to justify the adoption of Copilot:

- **We believe offering Copilot to one portfolio of 5 teams for one quarter will provide sufficient insights to inform our purchasing decision for a broader, organization-wide rollout.**
- **We will know what our decision is if we see an increase in PR Throughput and a decrease in Cycle Time, with no negative impact to Rework or Defect Rate.**

_Andrew Gassen leads Code Climate's enterprise customer organization, partnering with engineering leaders for organization-wide diagnostics to identify critical focus areas and provide customized solutions._