Ever stare at your team's Jira board and wonder... are we actually getting better at shipping software? You're not alone. With the engineering software market expected to reach around $246.51 billion by 2034 with a CAGR of 18.45%, engineering teams everywhere are wrestling with this exact question: should we build our own engineering analytics platform… or just buy one?

It's a decision that keeps CTOs up at night. And honestly? There's no one-size-fits-all answer.

But here's what I've learned after watching countless teams navigate this choice: the "right" answer depends on understanding your specific situation, resources, and what you're really trying to achieve. Let's break it down.

The Engineering Analytics Landscape in 2025

First, let's get real about what we're talking about. Engineering analytics platforms track the metrics that actually matter for software delivery - things like deployment frequency, lead time for changes, mean time to recovery, and change failure rate. These aren't vanity metrics... they're the indicators that correlate with high-performing teams.

The Engineering Analytics Services market is experiencing robust growth, driven by the increasing adoption of Industry 4.0 technologies and rising demand for data-driven decision-making. This expansion is fueled by the proliferation of connected devices generating massive amounts of data and the growing adoption of cloud-based analytics platforms.

The Case for Building Your Own Platform

Why Teams Choose to Build

Let's be honest - there are compelling reasons to build your own engineering analytics software:

Complete Control and Customization Custom software meets your exact business needs. You control every aspect - from features and design to functionality and deployment. This means creating exactly what your team needs, integrating seamlessly with your existing tech stack and unique workflows.

Competitive Advantage As Next Idea Tech puts it: "Buy for parity, build for competitive advantage."

Data Ownership and Security When you build internally, you maintain complete control over your data. No third-party access, no compliance concerns with external vendors, and full transparency into how your sensitive engineering metrics are handled.

The Reality Check: What Building Actually Costs

But here's where things get tricky. According to Gartner's 2024 IT Strategy Report, technical decision-makers who optimize the build vs buy process achieve 30% faster time-to-market and 25% cost savings. But that's only when they make the right choice.

Time Investment Custom software development costs in 2025 typically range from $40,000 to $300,000+, but time is often the bigger constraint. A comprehensive engineering analytics solution takes 4-18 months to develop and deploy. During this period, you're missing opportunities to optimize your delivery process while competitors using vendor solutions are already gaining insights.

Resource Requirements With the average US developer salary at $90k per year, you'll need data engineers, analytics specialists, user experience designers, and project managers. That's significant team dedication for what might not be your core business function.

Ongoing Maintenance Burden Applications that see heavy use or serve critical functions need 40-80 hours of support each month. Bug fixes, security updates, and new feature development will be ongoing processes. Ongoing maintenance can skyrocket the total cost of ownership (TCO), and failure to allocate resources can lead to software vulnerabilities, performance degradation, and compatibility issues. If crucial developers leave your company, you may lose all expertise to handle maintenance.

The Case for Buying a Software Development Metrics Platform

Speed and Proven Results

According to Forrester's Software Development Trends Report (2024), 67% of failed software implementations stem from incorrect build vs. buy decisions. Here's why buying often makes more sense:

Immediate Value With platforms like Weave, you can start gaining insights into your engineering team's performance within days, not months. The platform's LLM-powered analysis begins revealing hidden strengths and bottlenecks immediately, helping you make data-driven decisions while competitors are still planning their custom solution.

Proven Expertise and Domain Knowledge: Engineering analytics requires deep understanding of software development workflows, metrics interpretation, and visualization best practices. Weave has invested heavily in developing specialized algorithms for engineering work analysis, bringing years of domain expertise that would be expensive and time-consuming to replicate internally.

Cost Efficiency That Actually Works

Buying software shifts maintenance duties to the vendor who handles updates, fixes bugs, and supports users. However, vendor-supported solutions still need internal resources for integration and customization. Your long-term success suffers if you don't budget for support after deployment.

This is huge. Instead of building and maintaining analytics infrastructure, your engineering leaders can focus on what matters: acting on insights to improve team performance and project delivery.

Key Decision Factors for 2025

1. Strategic Impact vs. Complexity Matrix

The bigger the impact new software can have on your business, the more likely you are to want to build it yourself, especially if you have the skills, available resources, and time. But sometimes, the project is complex, includes multiple systems, and requires expertise you don't have.

For most engineering teams, analytics software falls into the "high impact, high complexity" category - but it's not their core competency.

2. Resource Reality Check

Ask yourself:

• Do you have dedicated data engineers available for 12+ months?

• Can your team afford to wait 18 months for insights?

• Is building analytics software core to your competitive advantage?

• Can the revenue your business generates comfortably cover the costs of building, maintaining and upgrading custom software with significant ROI?

3. Technical Integration Requirements

Modern engineering teams use dozens of tools - Git providers, CI/CD systems, issue trackers, communication platforms. Your analytics solution needs to seamlessly connect with this existing workflow.

Weave excels here, integrating with your development tools to provide comprehensive insights without disrupting established processes or requiring major workflow changes.

Making the Decision: A Practical Framework

Research shows proper decision frameworks reduce development costs by 40%. Effective analysis helps companies optimize resource allocation while maintaining market advantages.

Choose to Build If:

• You have unique requirements no existing platform can meet

• You have 4+ months to wait for results

• You have dedicated engineering resources available long-term

• Building analytics software provides competitive differentiation for your core business

• You're comfortable with ongoing maintenance and support responsibilities

Choose to Buy If:

• You need insights quickly (within weeks, not months)

• You want to focus engineering resources on your core product

• You prefer proven, battle-tested analytics capabilities

• You value ongoing platform improvements and vendor support

• Your team lacks deep analytics and data visualization expertise

The Hybrid Approach: Best of Both Worlds

Here's something interesting that's emerged recently - many successful teams are taking a hybrid approach. They start with a platform like Weave to get immediate insights and understand what metrics actually matter for their specific team. Then, if needed, they build custom extensions or integrations on top of the proven foundation.

This approach gives you:

• Immediate value from day one

• Proven metrics and analysis techniques

• Learning opportunity to understand what works before investing in custom development

• Lower risk than building from scratch

• Flexibility to customize as you scale

Why Weave Stands Out in 2025

Unlike traditional platforms that rely on resource-intensive metrics frameworks, Weave uses advanced LLMs and machine learning specifically designed for engineering work analysis. This means:

• Faster insights without computational overhead

• Deeper understanding of team dynamics and bottlenecks through intelligent analysis

• Actionable recommendations that actually improve delivery, not just pretty dashboards

• Seamless integration with your existing development workflow

• Cost-effective operation without the expense of complex traditional metrics

The platform tracks what engineering leaders actually need to know: team output patterns, project delivery bottlenecks, time investment analysis, and hidden strengths and weaknesses - all without the complexity and resource drain of traditional approaches.

The Bottom Line for 2025

For most engineering teams in 2025, buying a proven software development metrics platform makes more sense than building from scratch. Tech executives have changed their approach to software investments in 2025, with about 62% thinking it's time to be bolder with technology investments. This shows a major change in how companies look at building versus buying software solutions.

The speed to value, proven expertise, and ability to focus on your core business typically outweigh the appeal of complete customization. The software industry keeps growing at 11% each year through 2029, with global IT spending up 9.3% in 2025 - but that growth comes from making smart technology decisions, not just spending more.

Weave offers the best of both worlds: sophisticated analytics capabilities built specifically for engineering teams, with the flexibility to adapt to your unique workflow and requirements. You get enterprise-grade insights without the enterprise-level complexity, timeline, or resource commitment.

Ready to see how Weave can transform your engineering team's performance? The platform's AI-powered analysis starts working immediately, revealing insights that help you make better decisions about your team and projects from day one.

Want to explore how engineering analytics can impact your team's delivery performance? Visit workweave.ai to discover Weave's intelligent approach to engineering work analysis and see why teams choose proven solutions over lengthy custom builds.