There is no free lunch when digital technologies are involved. In other words, often the answer will be “it depends” because the context and other aspects can dictate a different approach also for similar scenarios.

Data alone creates value by allowing an organization to run its processes. There are also lot of scenarios in which decisions can be made automatically as long the rules don’t need human interaction.

When one talks about data for analytical process, then it makes sense to talk about harnessing the data to create more value for the organization.

I asked this with another occasion: How many decisions have you seen lately rooted in data? What’s the percentage of the data-driven decisions compared with the total of decisions made? How much does the data used reflect reality?

I’d argue that one needs to understand the roles and not the users of the data. Building a data culture can be done independently of the users or roles as it has more to do with the general capabilities and skillset that need to be built in respect to data. Conversely, there can be roles with special needs.

I’m puzzled about the relationship between data culture and software crafting or IT outsourcing.

Use cases are not a cultural characteristic, though practices are. Outsourcing is a decision in general, though in the case of autonomous departments, some departments might choose to outsource while others to develop in-house. However, I wonder how much these decisions are part of an organization’s culture.

When talking about DIKW, is about how the information is further aggregated to obtain knowledge, respectively wisdom. Is not about structure (as depicted in the diagram) but about semantics. The data tools’ output is further data or information, which when brought into context and a mental model can create value.

For me data-driven has more to do with analytics than with data management. If I understood correctly, by data-driven management you mean data-driven decision making.

I tried to read several times the post and I see you attempt to use the 5WH which translates to: Who are the actors? What do they want/need to achieve, what is the purpose? When do they need to act? Why do they need to achieve/act? Where do they need to act? How/by what means can they achieve that?

I saw this framework in several sources applied to strategies. E.g. how relates to data management; why, when, where and who to data governance, while the data strategy reflects the why. Conversely 5Wh can be applied also the steps of a process or strategy.

A lot from what you say makes sense, though the overall structure makes me question the content. Still, a valuable read.