What I’ve noticed for years is that across many many leadership teams is a complete lack of ability to articulate a story from the data. Often the leader states what the important metric is and everyone just barfs up other data that jives with that key metric. In short, the decisions that are made are based on data that was curated by the IQ of the leader and not what is actually valuable. When questioned, ego was quickly involved and by the next reorg that person that questioned was gone, by their choice or not.
In multiple companies another LT altitude frustration is the lack of effort to bring new leaders along regarding the way the LT looks and thinks about data in relation to business success. It’s like an unspoken religion that a new person has to intuit by reading the tea leaves. A dashboard that looks like an impending disaster in one company
may read as strong headwinds in another. And the distinction between the two seems to be based on a religion I am simply not part of and operates like the first rule of Fight Club.
Jonah, I can't tell you how much this resonates with me. I spent last week working on a presentation where I highlighted this exact issue. These leadership roles all require strong data literacy, but it's entirely possible that two data literate people can reasonably interpret data in different ways, given their different context. It seems like the approach commonly taken is to just assume data literate people are / stay aligned, and that doesn't always (or even often) pan out.
A past leader of mine often said, "If something is important, it needs to be someone's job." Aligning leaderships' mental model around data is IMPORTANT: It shapes how the business is run. So whose job should it be? I'd argue a senior data leader -- but the org needs to see that role as a peer, and not an order taker, and that's rare to find in my experience.
Early into my career as a data scientist (in an embedded role), a colleague of mine was astute enough to call out our quarterly business reviews as extremely valuable. At the time I was intelligent enough to see her point and agree with her, but not wise enough to act on much (being in an embedded model does not offer much help either). Fast forward to now and I sincerely miss these meetings. Our company stopped having our quarterly business reviews in mid-2022.
I really appreciate how you have articulated the benefits of these meetings for analytics leaders and resources alike, and what opportunities businesses who do not have them are missing out on. If you're in an analytics role and have the opportunity to join such meetings, do yourself, and your business, a favor and be present at them.
Thanks for the comment! It's great to hear your perspective on this.
I can definitely relate to the challenges you faced getting involved with the embedded model. In many companies, the path of least resistance is often for DS teams (and individual Data Scientists) is to settle into a task taker role, rather than a decision maker one. Just because metrics reviews are useful for DS, doesn't mean we always get a seat at the table.
One of the reasons I wrote this one was in support of my past self, who has struggled with getting a seat at that table in some circumstances. Hopefully future me -- and others! -- will have a better argument in their favor going forward.
Your deep understanding of business dynamics helps articulate the value of these meetings - plus help other data analysts push toward data-driven action. Great article.
What I’ve noticed for years is that across many many leadership teams is a complete lack of ability to articulate a story from the data. Often the leader states what the important metric is and everyone just barfs up other data that jives with that key metric. In short, the decisions that are made are based on data that was curated by the IQ of the leader and not what is actually valuable. When questioned, ego was quickly involved and by the next reorg that person that questioned was gone, by their choice or not.
In multiple companies another LT altitude frustration is the lack of effort to bring new leaders along regarding the way the LT looks and thinks about data in relation to business success. It’s like an unspoken religion that a new person has to intuit by reading the tea leaves. A dashboard that looks like an impending disaster in one company
may read as strong headwinds in another. And the distinction between the two seems to be based on a religion I am simply not part of and operates like the first rule of Fight Club.
Jonah, I can't tell you how much this resonates with me. I spent last week working on a presentation where I highlighted this exact issue. These leadership roles all require strong data literacy, but it's entirely possible that two data literate people can reasonably interpret data in different ways, given their different context. It seems like the approach commonly taken is to just assume data literate people are / stay aligned, and that doesn't always (or even often) pan out.
A past leader of mine often said, "If something is important, it needs to be someone's job." Aligning leaderships' mental model around data is IMPORTANT: It shapes how the business is run. So whose job should it be? I'd argue a senior data leader -- but the org needs to see that role as a peer, and not an order taker, and that's rare to find in my experience.
Early into my career as a data scientist (in an embedded role), a colleague of mine was astute enough to call out our quarterly business reviews as extremely valuable. At the time I was intelligent enough to see her point and agree with her, but not wise enough to act on much (being in an embedded model does not offer much help either). Fast forward to now and I sincerely miss these meetings. Our company stopped having our quarterly business reviews in mid-2022.
I really appreciate how you have articulated the benefits of these meetings for analytics leaders and resources alike, and what opportunities businesses who do not have them are missing out on. If you're in an analytics role and have the opportunity to join such meetings, do yourself, and your business, a favor and be present at them.
Thanks for the comment! It's great to hear your perspective on this.
I can definitely relate to the challenges you faced getting involved with the embedded model. In many companies, the path of least resistance is often for DS teams (and individual Data Scientists) is to settle into a task taker role, rather than a decision maker one. Just because metrics reviews are useful for DS, doesn't mean we always get a seat at the table.
One of the reasons I wrote this one was in support of my past self, who has struggled with getting a seat at that table in some circumstances. Hopefully future me -- and others! -- will have a better argument in their favor going forward.
Your deep understanding of business dynamics helps articulate the value of these meetings - plus help other data analysts push toward data-driven action. Great article.