WEBVTT - Transforming organizations using data

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<v Speaker 1>Seven two. Let's walk the talks extremely countrywide on the

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<v Speaker 1>Prime Media plus app. Chapman is past five. Good morning,

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<v Speaker 1>welcome to the second half of the Early Breakfast Show.

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<v Speaker 1>And we're looking at transforming organizations using data. So you

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<v Speaker 1>might have heard about the conversation or the conversational trope

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<v Speaker 1>digital transformation. What does it really mean for organizations and

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<v Speaker 1>how can it be leveraged. We're talking to asang Amehana,

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<v Speaker 1>who's a business improvement specialist. No he didn't hear me

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<v Speaker 1>hit correctly, because we will be talking to Asan to

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<v Speaker 1>explain the real foundations behind it. She's a business improvement specialist.

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<v Speaker 1>So what's digital transformation? Often sparking a rush to adopt

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<v Speaker 1>new system but as business improvement specialist asang A Mayan explains,

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<v Speaker 1>the real foundation lies in understanding and optimizing data and processes. First,

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<v Speaker 1>we will look at how organizations can build sustainable digital

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<v Speaker 1>futures while still putting people at the heart of the transformation. Asana,

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<v Speaker 1>thank you for joining us this morning, and how are

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<v Speaker 1>you doing good, good good things inrighting me? So many

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<v Speaker 1>organizations jump straight to adopting new digital systems. Why is

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<v Speaker 1>starting with data and process optimization? Crucial. So if you

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<v Speaker 1>can explain this in the most simplest of ways. You know,

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<v Speaker 1>we often get told if you're talking to your grandmother

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<v Speaker 1>or like a child, how would you explain what digital

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<v Speaker 1>transformation is and how important it is to businesses?

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<v Speaker 2>Okay, So to explain it to the most simplest way

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<v Speaker 2>I can think of, digital transformation is basically a way

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<v Speaker 2>in which we improve the manner in which you operate

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<v Speaker 2>using digital software. Right, And why it's important to start

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<v Speaker 2>with the process is that, in fact, if you get

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<v Speaker 2>the process right, you'll actually start to experience efficiency before

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<v Speaker 2>you've even put the systems in. And it's commonly said

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<v Speaker 2>that if you start to put in systems before you

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<v Speaker 2>improve the process, you also risk the chance of multiplying

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<v Speaker 2>the inefficiencies that sit within the process.

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<v Speaker 1>Okay, so we're taking it a step back to say

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<v Speaker 1>systems before we actually talk about processes. Is there some

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<v Speaker 1>strategic reasoning behind why you'd want to look at the

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<v Speaker 1>systems first? Process first? Okay, process first, full systems.

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<v Speaker 2>And due to past experiences, my default is not to

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<v Speaker 2>jump into a system solution system solution, right, And I'll

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<v Speaker 2>give you an example. I'd worked for a company that

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<v Speaker 2>wanted to develop all of its offices based on one

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<v Speaker 2>key indicator is that they wanted to reach one industry

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<v Speaker 2>KPI and there was KPIs in place. Processes were, you know,

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<v Speaker 2>in place for us to start redeveloping. However, I went

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<v Speaker 2>to look at the data and the information that informed that.

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<v Speaker 2>I looked at what is it that needs to be

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<v Speaker 2>done in order to achieve this KPI and the result

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<v Speaker 2>was that we found that we could improve or reach

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<v Speaker 2>this industry industry target by simply changing the face of

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<v Speaker 2>the company, painting maintenance, cutting trees, putting the product in front.

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<v Speaker 2>And it had also had requirements to improve safety, so

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<v Speaker 2>pedestrian walkways, painting signage, and also using the existing budget

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<v Speaker 2>for marketing to put up particular branding in particular places.

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<v Speaker 2>And that was essentially where it kicked everything off in

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<v Speaker 2>that we're able to achieve this without touching KPEX.

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<v Speaker 1>Just can you break down that k PIX Well, what

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<v Speaker 1>does that mean?

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<v Speaker 2>So KPEX is using capital to improve something. So digital

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<v Speaker 2>transformation requires heavy capital investment, right, and by just looking

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<v Speaker 2>at the existing environment we found what you have already

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<v Speaker 2>and looking at actually what the client wants. You can

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<v Speaker 2>achieve that.

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<v Speaker 1>By just how do you define the gap between data

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<v Speaker 1>collection and meaningful in amation and how can organizations bridge it?

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<v Speaker 1>I often talk about data dums with collecting it and

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<v Speaker 1>then we're leaving it. But it's not speaking to each other,

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<v Speaker 1>it's not intelligible.

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<v Speaker 2>Data is a substance and must we build information and

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<v Speaker 2>decisions are made, okay through good information? Right? So when

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<v Speaker 2>companies want to use a process where they collect data

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<v Speaker 2>first and see what the insights say and then kind

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<v Speaker 2>of figure what to do next, I think that's backwards.

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<v Speaker 1>Okay.

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<v Speaker 2>The aim is to collect to first understand what we're

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<v Speaker 2>trying to achieve, right, so what is the outcome? Then

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<v Speaker 2>what is the information we need to be able to

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<v Speaker 2>make those decisions? And then we collect the data that's

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<v Speaker 2>relevant to making that decision. So you get data dumbs

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<v Speaker 2>because let's collect data because we can. Let's then make

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<v Speaker 2>sense of it and then see where it drives where

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<v Speaker 2>it drives us, so it should be the other era

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<v Speaker 2>out So.

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<v Speaker 1>What's that step of you understand to interpret the brief

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<v Speaker 1>and what you want to achieve, and then you said

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<v Speaker 1>you information and research and before you go into data

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<v Speaker 1>the actual data collection, what's that step before?

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<v Speaker 2>So the step is first know what you're trying to answer. Okay,

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<v Speaker 2>what decision are you trying to make? Then what information

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<v Speaker 2>do I need to be able to make that decision?

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<v Speaker 2>And then collect the data to be able to make

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<v Speaker 2>that framework.

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<v Speaker 1>Yes, all right? And the common mistakes businesses make regarding

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<v Speaker 1>data management and you know a lot of so we

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<v Speaker 1>need data driven decisions, as you say, but what are

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<v Speaker 1>some of the mistakes businesses make regarding data management?

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<v Speaker 2>It's collecting too much data with that purpose, so we've

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<v Speaker 2>touched on that. This results in the data in the

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<v Speaker 2>data dams and there are no insights in that right.

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<v Speaker 2>And then it's also confusing systems for solutions, so a

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<v Speaker 2>real focus should be on the workflow and clarity, not

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<v Speaker 2>just the technology, right. And then it's also forgetting data

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<v Speaker 2>must be trusted and used by people. And then I

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<v Speaker 2>think a big one for me, it's the poor data capturing.

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<v Speaker 2>So usually there's no standard set beforehand, and the time

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<v Speaker 2>taken to do that would would save so much in

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<v Speaker 2>terms of askating to the information that we want so people,

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<v Speaker 2>For example, when you're working with Excel Excel sheets entering

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<v Speaker 2>January the forward and jan jan and twenty twenty four

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<v Speaker 2>oh one and one twenty twenty four, and then you

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<v Speaker 2>multiply all those inconsistencies.

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<v Speaker 1>Through like rows of data human errors.

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<v Speaker 2>Exactly, or you're multiplied by the number of entries that

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<v Speaker 2>you're putting in. You spend more time cleaning the data.

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<v Speaker 2>So that's exactly so that it can give information.

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<v Speaker 1>Gotcha. So just giving someone a spreadsheet really doesn't help

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<v Speaker 1>to give those data driven insights. We hear a lot about,

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<v Speaker 1>you know, data driven insight, but what does that look like?

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<v Speaker 1>Who uses data driven insights and why is it so important?

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<v Speaker 2>So data driven insights are essentially used by leaders to

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<v Speaker 2>make decisions, but the people who collect that data are

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<v Speaker 2>the users of the processes, right, So the then is

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<v Speaker 2>to collect the data in a clean manner so that

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<v Speaker 2>it can be quickly analyzed. So it's that analyzing part

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<v Speaker 2>that gives the information and the insights in order to

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<v Speaker 2>make that decision.

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<v Speaker 1>And there's people involved here. So how do you balance

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<v Speaker 1>the technical human elements to create sustainable improvements? Because you've

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<v Speaker 1>got a data capture, as you've mentioned, can we use

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<v Speaker 1>that as an example.

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<v Speaker 2>I don't lead with technology. Technology I feel is the

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<v Speaker 2>last step, So I often say that it's it's optimizing

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<v Speaker 2>the process that you currently have before you then transform.

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<v Speaker 2>So if you can be sure that you've optimized what

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<v Speaker 2>you have by optimizing, it means it's cleaning up the process,

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<v Speaker 2>taking out the non value ads you'll often hear of that,

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<v Speaker 2>and making sure that it's the value that you're trying

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<v Speaker 2>to get out of the process that you maximize.

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<v Speaker 1>Sure, you don't want to tell someone that their workstream

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<v Speaker 1>or task is a not value add but there's a

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<v Speaker 1>way in which change management is key. What advice would

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<v Speaker 1>you give organizations about asking the right questionestion before collecting

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<v Speaker 1>data and even pushing back to say I need a

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<v Speaker 1>bit more context so this has value.

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<v Speaker 2>Okay, I'm going to go back to that link.

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<v Speaker 1>Its right.

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<v Speaker 2>There's an example of the Boeing seven three seven right

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<v Speaker 2>that there was an initiative to improve systems and they

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<v Speaker 2>improved systems without the people involved, and the people are

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<v Speaker 2>the pilots that actually end up using the system. And

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<v Speaker 2>what happened there is that two Boeings crashed, and that

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<v Speaker 2>was a devastating outcome because there was so much surety

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<v Speaker 2>in that we fixed the system and the technology worked,

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<v Speaker 2>but because you didn't train the pilots. The pilots weren't

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<v Speaker 2>able to use. So the technology fixing the technology without

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<v Speaker 2>the people, it's quite dangerous.

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<v Speaker 1>So it also sounds like AI almost People say AI

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<v Speaker 1>is going to replace us, and I think it's there's

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<v Speaker 1>certain elements where it has existed, but we can go

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<v Speaker 1>towards automation. So how all this kind of thinking impact

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<v Speaker 1>workers and listeners alike? Here? And in terms of just

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<v Speaker 1>as a partying shot, if you've just joined us, we're

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<v Speaker 1>wrapping up a conversation regarding transforming organizations using data with

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<v Speaker 1>Asanga Malos a business improvement specially, so practically speaking for

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<v Speaker 1>listeners out there as a takeout that is not just consultative,

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<v Speaker 1>what would you say is an impactful workers and listeners

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<v Speaker 1>alike can get from digital transformation?

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<v Speaker 2>And I'm going to start it for from my perspective.

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<v Speaker 2>For me, data removes bias and subjectivity, right, I have

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<v Speaker 2>the confidence to sit in any table. And I think

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<v Speaker 2>this also goes way back to being young and black

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<v Speaker 2>in a male dominated space. There's there's bias from outside

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<v Speaker 2>because they're judging your age, maybe they judging your gender

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<v Speaker 2>or your race. But there's also your personal insecurities However,

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<v Speaker 2>when I put something upfront and it's data editions, I'm

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<v Speaker 2>sure that there's a saying that you must know, don't

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<v Speaker 2>don't trust me, trust the data. It takes away that

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<v Speaker 2>it gives you that confidence and there's also credibility. So

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<v Speaker 2>that's that's where it's important for me, and that's where

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<v Speaker 2>I can sit in a confidence position. But I think

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<v Speaker 2>for workers it your voice doesn't get lost in rank

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<v Speaker 2>or personality. And I think for leaders, data helps you

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<v Speaker 2>lead with clarity and not instinct, right so as leaders

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<v Speaker 2>as so, I also want to say data shouldn't be

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<v Speaker 2>used to justify one's decision, but it should be used

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<v Speaker 2>to direct it.

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<v Speaker 1>As indeed, you know, there's the theory side of things

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<v Speaker 1>and then there's a practical experience. But it's a pleasure

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<v Speaker 1>talking to you this morning a sang Aman as a

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<v Speaker 1>business improvement specialist. We've been talking transforming organizations using data.

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<v Speaker 1>Sang I thank you so much for your time this

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<v Speaker 1>morning and all the best for the future.

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<v Speaker 2>Thank you.