As a day job I still spend a lot of time each week — thinking about and consulting with others on “data”.

A typical discussion focuses on:

• what data the company has…
• who they provide or sell it to (or through)…
• to which market…
• for what purpose (or to address what problem)?

These questions can (and do) drive fascinating discussions.

Often though, the better “data” discussions are around other, somewhat broader, questions:

• what data does the customer share when they ask you for your data (inquiry data)…
• what data files do you “own” where key data element fill rates are less than 95% and why does/doesn’t that matter…
• in the space your data inhabits (NOT the space you inhabit) – what characteristics/similarities does the data you don’t have share (the missing pieces)…
• what would could you/should you learn about the missing pieces…
• what data would make your file “better” even though you can’t (yet) identify a customer that would immediately buy it?

Data is expensive to compile and time consuming to digest. And, data gathered from one type of source — used to solve one type of market problem — is inherently difficult to repurpose because of striking differences by market in the value of granularity. Nuance matters when it comes to data.

We’ve long used a saying “Ask a better question – get a better answer”. When talking about data let’s agree to ask each other better questions.

Cheers. DC