Build vs buy: a reporting system kit vs hiring a data engineer
- →Three options: build from scratch, hire a data engineer, or install a ready-made system.
- →A full-time data engineer runs into six figures a year; a system kit is a one-time cost.
- →Most agencies are best served by a ready-made system, with custom help only for complex needs.
Once reporting becomes a bottleneck, agencies face a build-vs-buy decision. There are three realistic paths, and the right one depends on your scale and how custom your needs are.
| Option | Cost | Best when |
|---|---|---|
| Build from scratch | Lots of internal time | You have spare senior capacity (most do not) |
| Hire a data engineer | Six figures / year | You have ongoing, complex, full-time data needs |
| Install a system kit | One-time | You want a proven system fast, without a hire |
| Custom implementation | Scoped per project | You need it built for you, once |
Building from scratch
Building works if you have senior analysts with spare time - but that time is rarely free, and reinventing KPI dictionaries, blueprints, and QA from zero is slow. The hidden cost is the weeks of internal work.
Hiring a data engineer
A full-time hire makes sense when you have continuous, complex data needs that justify six figures a year. For most small agencies that only need standardized reporting, it is more capacity than the problem requires.
Installing a ready-made system
A system kit gives you the templates, blueprints, SOPs, QA, and AI prompts as a one-time purchase you install with your own tools - the fastest path to standardized reporting without a hire. For genuinely complex, bespoke needs, a scoped custom implementation fills the gap.
The Agency Reporting Automation Kit is the ready-made path; Custom Analytics Engineering Implementation is the done-for-you path when you need it built for you.