Hi Joe, love the framing of enterpriseland vs productland!
Many enterprises aspire to use data products to drive their products/services and revenue growth i.e. make the shift into productland. But too often they fail because they’re still applying enterpriseland methods, assuming they’ll work in productland.
Thriving in productland requires a fundamental shift in mindset and strategy — it requires different ways of working and operating model.
Kaplan's BSC still works for me - financial/operational/customer(or experience) are the three framing outcomes. I also like to think of uses as decisions - but more broadly. We also use data for decisions in workflow, and in the field. Those are less analytical and more operational. So, the operational and experience outcomes are also important in either product- or enterprise land. Will we violate a compliance policy today? Will we ruin a customer experience? Downside is a powerful motivator for good data practice as well.
Great framing. But what about when both paradigms exist at one company? You have a BI team creating reports and performing other Enterprise land functions. And you have product eng teams shipping features, and someone on that team is thinking about the data model. I wonder if there is tension when a Head of Data has to manage both types of deliverables & personas - DEs building BI pipelines and DEs embedded on product teams. Do they manage them differently since they support two different domains as you highlight? Or do DEs on product teams roll into VP Eng, more easily delineating responsibilities between Eng and Data? Lots to unpack!
As Mike Carlo says, “Does
this make money, or save money?”
Words from the master https://youtube.com/shorts/oOQSYoBJCXI?si=M5csd1wZrWfkKMVq
Damn, love the Enterpriseland and Productland definitions. Thanks for this
it's like Legoland, but...different
Hi Joe, love the framing of enterpriseland vs productland!
Many enterprises aspire to use data products to drive their products/services and revenue growth i.e. make the shift into productland. But too often they fail because they’re still applying enterpriseland methods, assuming they’ll work in productland.
Thriving in productland requires a fundamental shift in mindset and strategy — it requires different ways of working and operating model.
Exactly
Kaplan's BSC still works for me - financial/operational/customer(or experience) are the three framing outcomes. I also like to think of uses as decisions - but more broadly. We also use data for decisions in workflow, and in the field. Those are less analytical and more operational. So, the operational and experience outcomes are also important in either product- or enterprise land. Will we violate a compliance policy today? Will we ruin a customer experience? Downside is a powerful motivator for good data practice as well.
Great framing. But what about when both paradigms exist at one company? You have a BI team creating reports and performing other Enterprise land functions. And you have product eng teams shipping features, and someone on that team is thinking about the data model. I wonder if there is tension when a Head of Data has to manage both types of deliverables & personas - DEs building BI pipelines and DEs embedded on product teams. Do they manage them differently since they support two different domains as you highlight? Or do DEs on product teams roll into VP Eng, more easily delineating responsibilities between Eng and Data? Lots to unpack!
Awesome!
Young data engineers like product land…