How Prioritization Helps Companies Define Value

How Prioritization Helps Companies Define Value

Accruing relevant data is great. But communicating these findings to executives, and demonstrating how this information creates company-wide value is where today’s data leaders need to shine. In this clip, Bill Schmarzo of Dell Technologies highlights how this process ideally works in the board room.

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Yeah, this prioritization matrix is by far. The most powerful management tool that I've I have ever used. And what it does, it measures on one ax axis value, which is great. It's a great conversation starter to get that whole, oh, how do you define value?

How do you measure value? And then it measures feasibility, implementation. And feasibility has a whole bunch of realms, right? Data quality, you know, you management, fortitude, budget, uh, tech, technology, debt and such, right? So once you have this thing framed, , you have to go through a process we talked about to identify those use cases to start with.

Well, what is the organization trying to accomplish? We talked about, you know, supply chain optimization. What are the use cases? Well, reducing obsolete and excessive inventory. Vendor quality of online delivery, right? So we have these use, these use cases come up. And then what's beautiful is you bring all the executives together, hopefully in the same room.

Cause I think it's great. And you take these post-it notes for use. and you have a debate. Oh yes.

An argument. I was gonna say each of, is it a debate or is it a fight? Yeah,

it's, see, it's a fight. They yell and they, they don't, they yell, but they get really agitated, but, well, you know, my use case, You have it, you have a way up there.

Well actually be honest with you. C is more valuable. And then you can have a chance when they, when they make the statement that C is more valuable, you can say, well, in what ways, how, what ways is it more valuable? And this, this conversation with executives allows you to. To th to, to further vet out the value components and how they measure value, as well as have a, a conversation about, whoa, is that really feasible?

Do you have the right skillset? Do you have the right level of, of data quality and data granularity? And at the end of this thing, you end up with having these use cases up here. And you say, okay, we're gonna start with B, but once B is done, we're gonna go with A. And then when A is done, we're gonna re huttle.

Because we have F over here at the edge, right? Maybe F is gonna march its way over here and become more viable as we start building out our data and analytics. So it's a great tool for making sure everybody has a voice, their voice is heard, and get alignment across the organization so everybody can see that, well, maybe my use cases in the first one, but I can see how A, B, and C is gonna make D more effective.

Yeah. And I know why you're doing this. So yeah, it's a, this is a great. Yeah,

I love it. And I often think about, um, so, so our X access or bottom part of the line is, um, how ready is the data or data complexity and qualities included in that? But you added something that I, I don't think I've thought of this before.

Management. Fortitude. Fortitude.

Because if they can't collaborate, if they can't share data, then all the economic value of data doesn't get realized, right? We don't, we don't exploit that unique data economic multiplier effect. So yeah, it's, it's a, it's a, so whenever we do these work, I always insisted I'm the person who stands next to the chart and drives the conversations with the customers.

It helps that I'm really tall and big, so if people listen to me and I can see over the group , but it, it gives me the license to challenge people to challenge. Say, tell me why that you think that's more valuable. Tell me why you think that's more feasible. Right. Give me details cuz I'm, I'm an outsider and I can ask that question cause I like to say them.

I say, I'm not here to make you. , I'm here to make you successful, so I'm gonna ask the hard questions. You may not like it, but you gotta hear 'em and you gotta answer 'em.