Data consultants, are you already productizing your services?

Hey, data consultant!

We’ve been hearing from several Meltano community members and Arch design partners about productized services as a strategy to get out of the billing-by-the-hour grind and scale your consulting business to more clients and more revenue per employee.

The idea is that clients mostly need the same things (2/3rds standard, 1/3rd special is what we’re hearing), and a lot of your time goes to setting up the same basic ELT, data warehouses, and dashboards for common use cases like sales, marketing, and e-commerce. You’re probably already templatizing this to some degree (dbt models and LookML are easy to copy/paste!), but you’re still delivering each client their own bespoke data platform and getting paid based on the time it took you to build it — so there’s not a huge incentive to be faster than your clients consider reasonable if it would mean you get paid less.

It would be great if you could spend less time on the repetitive stuff you’ve seen 100 times and more time on the interesting bits that make each client unique — the fun challenges that got you into data engineering and/or analytics in the first place. Especially if, at the same time, you could get paid monthly for the *value* your solution and services provide and take on 3 times as many clients as you can currently — because if the 2/3rds that’s standard falls away, your data engineers and analysts suddenly have 3 times as much time to focus on different clients’ special bits.

That’s the promise of the productized services model, and its conceptual appeal is obvious. But we’re also hearing that in practice, turning your common ELT, DWH, and BI stacks into a repeatable product is far from straightforward when pretty much every tool in Modern Data Stack is fundamentally built for a single tenant (and having 50 clients means you end up managing 50+ EL tools, 50 dbt Cloud accounts, and 50 data warehouses).

We think the productized services model presents a massive opportunity for small and medium-sized data consultancies and should be much easier to adopt and scale. We’ve been building Arch primarily to help B2B SaaS vendors support more data integrations in their products, but data consultancies are telling us it’s also an excellent fit for the “multi-tenant data platform” use case (more info at the link!), as the productized part of their services is essentially a B2B SaaS.

If any of this resonates with you

… we’d love to talk to you and learn how better multi-tenant data tooling could make your days less repetitive and help you scale your services to more clients. Feel free send questions to, book some time directly on my calendar or sign up on the to stay up to date!


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