I work at a place where data quality is not on anyone’s radar. We have a reporting team in our group so we do our best where we can, but combining any datasets with other groups (like marketing & sales) is next to impossible as each team is silo’d and do things their own way - think free-form text fields to tag content…
How can I politely and succinctly say the above? Also, anyone else in a similar boat?
Implementation of AI requires strong unified data governance and data hygiene to produce company wide strategic solutions. The current company posture instead is focused on tactical level data collection and analysis which does not lend itself to consumption in relevant possible cross-department opportunities.
And if you want to tank it without overtly tanking it.
“We will need to establish a review and governance board to establish standard data structures and reporting that can be used to drive the initiative.
It will need to be cross team and cross specialty so we should start by establishing a group to identify those people so we can proceed”
A year later and you’ll be lucky if they’ve even picked out who can be part of the review process let alone agree on some convention and adjusting their tooling and processes to make that work.
This is gold
Somebody give this guy a promotion.
I dunno. They forgot the hyphen between company and wide. 3/10.
Not three out of ten: forgetting a hyphen is unforgivable & puts it into negative territory. I would drop it by six points from there and give it 3/10.
We’re unable to leverage some of the latest advances in AI due to our Leadership’s abundance of caution and strategically allowable risk profile.
You can effectively shorten the second part to “due to the company’s allowable risk profile”
They’re not wanting to work better, they just want to be able to say they “use AI”.
Get them an estimate of how much it would be to give everyone Copilot for Business licenses and they will start talking about the business having other priorities.
We need shared definitions to tell meaningful stories with our data. And then use a company specific example like how a customer’s journey can not be understood with differing definition between marketing and sales. The marketing team can’t measure the quality of the leads they’re producing unless they can directly link a customer’s whole journey from acquisition to churn. Otherwise it’s just vanity metrics. But don’t be too harsh, vanity metrics are really common in business. A company needs strong data leadership to create a culture of using data to justify decisions to a culture of using data to inform decisions.
Definitely try to use examples to help them get a glimpse into the issue. I like to explain documentation errors by pointing out when what are supposed to be sequentially recorded timestamps are recorded out of order in my work’s database. Sometimes the data quality isn’t there.
“Each department in this company has developed their own way of doing things. Unfortunately, not every department is giving us information in a way that we can use it to our advantage. We need to get everyone across the company on the same standards so we don’t have any mixups. We can’t help you do your jobs better if we can’t process the information you give us.”
Our team does its best to maintain consistency within our own processes, but collaborating with other groups like marketing and sales can be challenging due to siloed operations. Each team follows different approaches to data management, often using free-form fields and inconsistent tagging methods, making it difficult to combine datasets effectively.
You pretty much already had it.
“sure thing boss”
Starts looking for new job
“yes sir”
Yeah sure
Having been in a situation in which management could not quite grasp the concept of “what you’re asking is literally impossible” the only answer I have to give is to leave and find someplace smarter to work.
Resign, then offer them consulting on it for $300/hour.
This is what AI is for. Why don’t you ask ChatGPT?
Our legacy systems have served us well. Unfortunately, the facts of being market leaders and first movers mean we’re not operationally equipped to leverage turnkey AI solutions. We will need significant buy-in from management in several stakeholder organizations, as well as significant time and resources for procurement (or development), implementation, and change management.
(optional depending on your GAF level) : With the right level-set and commitment, integrating our systems for AI could be transformative in the best ways.
www.goblin.tools is a godsend for this type of stuff.
Here’s what it put out using the “Formalizer” tool set to “More professional”:
Our leadership team primarily consists of individuals with extensive experience, but there appears to be a gap in understanding contemporary data practices. This challenge makes it difficult to fully leverage the potential of AI in our operations.
Have been using this the last 2 days and love it, thank you!
Hell yeah! Happy to help–it’s definitely a game changer for me and plenty of others. I wish you the best luck moving forward!
PS there is an app, and I think it’s $1. Worth throwing the dev something for their efforts imo!
It is actually easier to just get a different job with better leadership. You can say exactly what you wrote in your exit interview.
Well there’s a classic saying for this purpose: “Garbage in, garbage out”.
Removing the unecessary adjective “old” would be an obvious start.
But what is your audience and what do you hope to accomplish? Unless you really have an audience who is likely to accept that the people in leadership are lacking an important competence and the power to go around them to get something done, then I would assume that leadership is your audience. In which case the part that blames them is entirely unhelpful and you should stick to explaining the problem and needed changes.
