E30 Dr. Marco Motta - Drama from data: Where stats, insight and influence converge

“In fact, there’s nothing normal. Everything is what we make of it to a certain extent.”

Dr. Marco Motta

In this episode, you’ll hear about:

Data storytelling: How to present data in a means to create shared understanding across an organisation and use narrative techniques to make it personable, digestible and immersive

Mitigating data literacy: Establishing an evidence-driven culture by bridging the data literacy gap in an organisation and increasing the capacity for informed decision-making

The responsibility of data stewardship: Delegating roles for data management and ensuring privacy, confidentiality and integrity is maintained when utilising data

Data visualisation: Why the visualisation of data can completely change how it’s received & top dataviz strategies for ensuring it achieves the purpose you’re after

The power of philosophy and critical thinking: Why its valuable to deploy philosophical techniques into consulting and data analysis to ensure decisions are rooted and strategically considered

Key Links

Heidegger: https://plato.stanford.edu/entries/heidegger/

Phenomenology: https://plato.stanford.edu/entries/phenomenology/

Arnold Hauser: https://arthistorians.info/hausera/

Sapiens book: https://www.amazon.com.au/Sapiens-Humankind-Yuval-Noah-Harari/

Transport of Main Roads: https://www.tmr.qld.gov.au/

Hamlet’s Mill: https://www.goodreads.com/en/book/show/1439

Translink: https://translink.com.au/

About our guest

Dr Marco Motta (https://www.linkedin.com/in/mottamarco01) is the Managing Director of Motta Consulting, a boutique organisation that specialises in data analysis and visualisation.

He has a strong track-record transforming the performance reporting culture of large organisations, using data storytelling to craft business stories that break silos and support good decisions. He marries this with a doctorate in philosophy from the University of Queensland and uses his background in critical thinking to help organisations and clients identify, define, break-down and solve complex business challenges.

About our host

Our host, Chris Hudson (https://www.linkedin.com/in/chris-hudson-7464254/), is a Teacher, Experience Designer and Founder of business transformation coaching & consultancy Company Road (www.companyroad.co)

Chris considers himself incredibly fortunate to have worked with some of the world’s most ambitious and successful companies, including Google, Mercedes-Benz, Accenture (Fjord) and Dulux, to name a small few. He continues to teach with Academy Xi in Innovation, CX, Product Management, Design Thinking and Service Design and mentors many business leaders internationally. 

For weekly updates and to hear about the latest episodes, please subscribe to The Company Road Podcast at https://companyroad.co/podcast/

Transcript

[00:00:07] Chris Hudson: Hello again. It's that time of the week where we dive into another set of influence drivers and some practical advice for all of you intrapreneurs out there. And this week we're going to go deeper into the area of data or data as it's called over here in Australia. 

And after six and a half years, I still can't bring myself to say it that way, but anyway, we're going to be talking data science analytics, data visualization and what makes it really an incredible superpower if you use it correctly and allow me to introduce my next highly qualified guest, who's going to lift the hood on data today, Dr. Marco Motta. So welcome Marco.

[00:00:37] Dr. Marco Motta: Thanks, Chris.

[00:00:38] Chris Hudson: Marco, you're a leader in reporting automation. You've got a mighty amount of experience in data analysis and visualization. A doctorate in philosophy as well from the University of Queensland. And you use your background in critical thinking to help organizations really identify, define, break down, solve complex business challenges.

 And you've done high profile data analysis. You're a bit of a whiz when it comes to visualization, market analysis. You've done org wide methodologies to measure customer experience in a suite of interactive dashboards to monitor performance of almost 5 billion of yearly investment. There's a whole load of stuff I want to get into today.

So thank you very much for joining. And I'll start with a simple question, which is really around your background in data, but also your background in philosophy and how those two worlds really meet. So what is the intersection? How did that come about? 

[00:01:24] Dr. Marco Motta: Thank you so much for the opportunity, by the way, and I really appreciate being on your podcast. The intersect just comes from the fact that I ultimately started my career as an academic. When I finished uni, I decided to keep going with my PhD in philosophy and wrote a long dissertation on relatively obscure complex topic in philosophy and as part of that, that was what I wanted to do.

As life gets on had a child, couldn't really find anything that was really working in terms of like, in academia. And so I decided to, like a friend came around, a friend from philosophy came around and say, hey come and join TransLink. It's a public transport agency here in Queensland to write correspondence.

And basically I started there in the mail room. It's my origin story. Started in a mail room of TransLink and eventually started to see that I enjoyed reporting on stuff and figuring out where are the letters that were overdue and what was happening, automating some of those reporting tasks.

And slowly I basically developed this other skill that I had no idea I was interested in which was reporting data analytics and building up my tool sets and my skills and soon however, I realized that, the two things do come together in a certain way, or at least they come together in the way that I approach it, because on the one hand, philosophy is all about trying to break down problems and figure out, how do you approach a problem to find the right solution, or at least to find a range of solutions?

And often there isn't, so to speak, a right solution. There are lots of solutions that are wrong, but there's also lots of solutions that are right. And so being open to that, to thinking critically through the information. And that's kind of where data kind of kicks in for me in the sense, a lot of the time, the big challenge is to find what is the evidence that's relevant here.

Often times, we make decisions and value judgments based on evidence. But sometimes those evidence turn out to be way more kind of flawed than we think they are. I think that happens in pretty much everyday life. We need to go and get a vaccination for COVID. And we're like, yeah sure.

We'll all be good corporate citizens. But in reality, like, there are some levels of complications in some of the data that is collected. And, to a certain extent that is almost philosophical. It kind of comes to the point where it's like, there's a certain amount of certainty, but there's never like 100 percent certainty.

And That's what I like about data. And that's what also I think I brought to data in terms of the way that I approach it. And we can probably talk about this a little bit more later, but I think there is a traditional interpretation of how data is used, which is data is this objective thing that this almost scientific thing, and we could talk about why science also isn't 100 percent objective, but there's this thing where it's like basically provide certainty.

And in reality, there's such an amount of subjectivity and biases and the ability to pick different things on data that is really just like, yeah, there is no objective data. A lot of it is subjective. A lot of it is determined by who looks at the data, who interprets it.

And so, I think this, I bring that to the conversation as a new way of looking at data, a way to like, look at data from the lens of how can we use data to influence people in the- influence organizations, influence decisions in the right way or in the way that we think is the most truthful way that we can construct at the time and, tomorrow, then we might find out that we were totally wrong.

And that is okay as well.

[00:04:40] Chris Hudson: You're the second person that I've spoken to in a little while who has a philosophy degree. The other one I went to uni with as well and he was always very into magic and he became a professional magician and he's on the circuit doing shows in Vegas, various other places, but totally different.

I think there's an element of magic in obviously what you have to do with data. I think, it comes from a, I suppose an understanding of the world that you're seeing and the observation that that you then need to apply to what's in front of you. How do you think, can we prove that a philosophy degree is useful in that sense?

Is it helping you unpick and unpack certain scenarios? What is there in plain sight at you thinking about that through a deeper lens than perhaps other people do you feel?

[00:05:20] Dr. Marco Motta: Again, I don't know if I think about it more deeply, I think. I definitely tend not to accept the current definition of things at face value. That's something that I think it's important to the way I approach things. It doesn't mean that the definition of things is wrong.

In fact, in my doctoral thesis, the author that I looked at has got basically has this idea apart from a lot of other ideas. One of them is that we live most of the time in a in what he calls like the, in German, the das man, like the one gives us like it's the way that we are normally, we're kind of all understand each other more or less.

We live in this kind of, he calls it inauthentic way of living. It doesn't mean it's bad. It just means that we're not really going deep because we don't have time to go deep in fact. A lot of the way that our brain works it's designed not to go deep because you and again, I love talking about this stuff in terms of like evolutionarily as well.

It's like evolutionarily it makes sense not to necessarily go deep into a problem, especially when you have a lion in front of you that wants to eat you. You're not there to kind of analyze what's going on. You actually need to react quickly. And so from our brains perspective, it makes sense that a lot of the time we basically rely on other people's experience and other people's judgments and the hearsay of, what you told me, what another person told me to make quick judgments.

But, there's another dimension to that, which is what this author that I studied, Heidegger, calls the authentic. In itself it's really about going, it's when you go deep to try and understand how all of this is grounded, where are the flaws, what are the issues, how do we believe what we believe?

And in a lot of cases, the deeper you go, the more you figure out that a lot of this is beyond what we can understand. The grounding of this kind of comes from somewhere else. That is, we can intuit, but we can't necessarily know as such. And so there's from that point of view, I think it's not about necessarily thinking more deeply than others most of the time, but it's about trying to think deeply about some important things sometimes so that you can unlock something new in there.

[00:07:24] Chris Hudson: I mean, sometimes there's maybe a word that pops out there because within the world of work, when you and I are consulting, it just feels like the time and the place for that type of conversation isn't always presenting itself, I want to say, and that's maybe the understatement of the year, but it feels like we we would want to go deeper into a lot of things, but we don't always have the luxury of time.

So how do you navigate some of that? 

[00:07:45] Dr. Marco Motta: I do find the consulting is interesting from that point of view. And I think you talk about intrapreneur. I think at some point in my career, I was an intrapreneur, or at least, and I think I ultimately made the jump to entrapreneur proper. I think consulting is interesting because in the good consulting jobs, you're kind of presented the opportunity to go a bit deeper on something as opposed to, having to run an organization and often you get called when there's a problem, you get called when there's like, we've got to fix this. And so there is a good opportunity to go deep into some problems which is really cool because ultimately with data, often you can unlock some things that the people that in front of you have been staring at all along, but they couldn't quite see it because they were enthralled in their own normal understanding or normal kind of operation.

And so they disregarded some of the signs that would have told them exactly what was going on. I do love consulting for that. Even though sometimes, you're not afforded, sometimes you can only bring people to the point that they can be brought and again, sounds like it's autology, but it's like, you can't force some, it's almost like a, if you go to the psychologist or the therapist, they can really only bring you to a certain point of understanding or of kind of epiphany or revelation, but you kind of need to get there yourself as well. Otherwise it's like, otherwise it's almost so shocking that you're you would completely shut down. And often I think I've made the mistake in different organizations where I lay it all out for them.

And they're like, oh the first reaction is like, oh that's not us. You've got it wrong. There's the denial that often doesn't then allow you to continue to do more work and to help them, which is ultimately the point of all of that.

[00:09:26] Chris Hudson: Yeah, I mean that denial is interesting isn't it? I mean that's a reaction that you sometimes get but you don't 

[00:09:32] Dr. Marco Motta: I love it because it's very predictable. 

[00:09:33] Chris Hudson: is that something you've tuned in more so over, over the years? Is it something that you've refined? What was sort of driving the reaction that you felt you got in those situations and, you know, what happened? 

[00:09:43] Dr. Marco Motta: I talk about the five stages of grief of data visualization. Like I've done a couple of funny posts about that, but it's not really funny because it's like, I think it's just the human reaction to anything that we don't like. And so, there's or anything, any change. And so I think to a certain extent, a dashboard is not the same as losing a loved one, but to a certain extent, there is a point to be made about when I present a mirror of your organization, there's a certain amount of like, it's almost like seeing that for the first time.

It's like, hearing your voice for the first time when you record yourself, it's like that feeling is like, that's not quite my voice. That's not how I sound inside my echo chamber. And I think that's basically the point. I've often found that when presenting visualizations and dashboards often what I try to do is I try to tell a story about that organization. And in telling that story, sometimes I find that the first reaction is like, oh, the numbers are wrong. And in reality, then you go check all the numbers. And most of the time, by all means, I'm not always right, but most of the time they're correct.

It's just that they have never seen those numbers quite in that light. And so again the first reaction is that denial and then they try to find a way to like get out of it so it's like oh, can we maybe not report that number?

Maybe we can change it to this other number. Like can we not report profit per head because it makes us look bad. Can we report profit in total because it makes us look like slightly better. Ultimately you get to the point where hopefully, the mature organizations accept that the problem is better than not seeing the problem because it allows them to act and change and get better.

 That's where I like to bring any organization, but also where I'd like to bring myself, where I like to bring any person that I talk to is like, let's try and see what the problems are with me, with us, and how we can all get better, how we can all improve this world to a certain extent.

[00:11:33] Chris Hudson: I mean, there's definitely a lot of pressure and it feels like within organizations that, there just needs to be quantified measures much more so than ever before. The trust is still there, but people want to see, the evidence that it's going to deliver on something or that, there's positive ROI and metrics.

And now, they were quite limited really, if you even rewind 5 years or so 10 years, The metrics are pretty set, you were looking at sales and you were looking at, you were looking at revenue and profitability and, you know, margin, but now the kind of explosion of, technology and its application and its usage has meant that, increasing number of data sets have become available.

 But to the point where they can be more easily accessed and drawn upon really in terms of sources of truth, but also played back to leadership teams to boards and the the level of granularity brings with it some level of responsibility. You're thinking about stewardship really, when it comes to data, what numbers am I going to lift out and report on?

And so I'm just wondering, within the context of that, it's been a lot of change. But who do you think is best placed to manage the data across organizations when it, in effect it's become everyone's responsibility.

[00:12:43] Dr. Marco Motta: I find that at this point at least the organizations that I've talked to, that I've worked with there's still a lot of work to do internally in getting that data up to the point where it's refreshed at the right rate.

So each organization has a big role to play, which makes it, how it is when it's everyone's responsibilities. Also, no one's responsibilities like the minimum common denominator, unfortunately but there's also, there's opportunities for smart organizations to, to leverage that. I was talking about it on on the weekend because I saw an art or actually maybe this week because I saw an article about how like in November, they released some figures for September economy like in terms of how economic growth of Australia like the surprising thing again is to see that, you're releasing September figures, October.

quarter two, figures in almost, end of quarter three. And this is nothing shocking to me because I've seen that play out in government a lot of the time and it's not for lack of trying internally, it's often because some of these things do require an amount of investment in automation that is just hasn't been there.

And so I guess from that point of view the stewardship falls on anyone that has that data. In a lot of cases, it does fall on government departments that do have a lot of interesting data that people would like to access to make important decisions like, do we hold interest rates or do we push them up?

And I think the RBA in November could have had those figures. And could have had them in October. And those figures probably would have- because the economy has actually shrunk, it would have actually probably caused a different decision and that decision has a real impact on people and mortgages and all of that.

It has an impact on the economy. Maybe we've gone a little bit too far now, again, if you don't have the right information at your fingertip, then it is hard to make decisions. Those decisions are often made on a certain level of gut feel on a certain level of almost like manipulating people's opinion as opposed to actually make a decision on real facts.

And again, nobody can fault the RBA if they didn't have that data. But the point is, why wasn't that data available? And often the answer is enough investment in data automation and reporting automation and collecting data at the right time rather than collecting it later and automating pipelines across government departments often.

[00:15:01] Chris Hudson: Yeah, it's interesting, isn't it? Because, obviously it depends on what you collect and who gets to see that but in terms of the story that then unfolds. Say there's good and bad, there's obviously like this duality of what data presents sometimes. And sometimes it's kind of painting a picture, a rosy picture, in other cases it's not so rosy.

And the way in which you position that, because a statistic is usually wrapped into a sentence or an insight statement or something. It feels like there's still quite a lot of room for maneuverability in how that number is being presented essentially. So it is a responsibility and I'm thinking about data literacy from that point of view of actually understanding what the number is and the implication is of you using it but also in omitting certain things.

So, is your argument not just black and white and balanced, but is it more black than white or vice versa? Some people have the ability to kind of craft that story and ensure because they want to, that it's a fair representation of what the scenario is. But in other cases it's definitely thrown one way without the counter story being presented.

So why do some people do that?

[00:16:04] Dr. Marco Motta: There's so much in what you said just now, like, I think, and there's so much that I've been thinking about, like I think the data literacy problem is an Australian problem, but it's a world problem. I think we, and again, I think that ties back into philosophy. I think philosophy is not really it's not something that is taught in kind of Anglo Saxon schools from my understanding, either in Anglo American schools.

It is more so in Europe, but even then I think it's kind of like decreasing in importance, and part of why I say that is because I think we're coming to it like we're as a society again, maybe it's a general statement, but we're becoming a little bit less mature about how we see things is like we're being drawn, whether it's through, social media or whatever.

It's whatever the reason at the moment we're drawn to the extremes and part of being drawn to the extremes is to become like to stop seeing that there is truth on both sides. And the truth is not a matter of who is right and who is wrong, but it's a matter of ultimately, looking for truth.

And so from that point of view, I think, it's really concerning that to a certain extent people can't understand that data can be not always black and white again back to that point. Data has a factual element to it, but it also has an interpretive element.

And I think it's not that the factual element doesn't exist or at least I don't think that everything is interpretation as such, but there is a play. And again, that comes from my philosophical views from Heidegger and his teacher who basically the idea is that there's no kind of subject and object duality.

There's actually like a, there's a plane called, it's a phenomenal logical plane that their philosophy is called phenomenology, basically where everything. It's like where things appear because of the intersect between this, us looking at something and the something being looked at and being something to look at.

And so ultimately, when we talk about data, there's no hard facts as such, but there's an intersect between me looking at the fact and the fact kind of looking back at me and what we see is that phenomenon. In that phenomenon, I am part of that phenomenon and you're part of that phenomenon.

And so saying that there's, even science that I think a lot of people that are not literate in science believe that science is a, there's often the duality, science, religion, it's like, religion is just like fairy tales and science is real facts. In fact, science is a type of fairy tale.

It's a type of narrative around how we look at the facts and those facts are actually the tenet of science, or at least, some philosophy of science believes that any scientific theory needs to be or can be at any time discredited and another theory can come in. And so the point is, yes, science is true, but it's true only to the point that it can be proven wrong at some point in the future by new evidence.

And so if the scientific theory cannot be proven wrong, at any point, then it's actually no longer scientific theory, in fact, is religion. And so, because religion can't be proven wrong by facts because it's not based in, what we call facts and realities. And so I think it's based on other things, it's based on a different set of facts and objects that can't be proven scientifically.

And so that's kind of the point, when you take science to be true, no matter what, when you take anything to be true no matter what, you're actually stepping into that religious territory. And then it's like, when you take data as like, we took during COVID, COVID was a big kind of shift for data analysis and data visualization, because people started to look at charts, all of a sudden there were charts and graphs everywhere and it was great, but at the same time, again, it was just like it's great for us, at least, it's kind of like a way for people to kind of be introduced to do data visualizations without even knowing about it.

But the point that happened during COVID again is that people took those numbers to be 100 percent accurate or totally inaccurate as opposed to questioning, okay, we have the number of cases now and some people did to be fair that we had the number of cases now, but is that important now or is a more important number of people in ICU?

And so see how the same set of data, it's like the same set of facts, the people that are sick of COVID all of a sudden can take different shapes, depending on how you look at it. And so being data literate and having again, going back to the organizations and the different people that are in the organization, supporting data literacy in your organization is only going to strengthen that aspect of, being able to look at things in different ways, ultimately innovation, ultimately change, ultimately the ability to to take the right decisions based on the balance of facts, not based on an immutable dogma that you've got to do this or that.

I think that's the key. And I think that's the key of using data in the right way.

[00:20:50] Chris Hudson: Because it feels like you're passing on the information, and I think, in a lot of organizations, a lot of corporates, there'll be established reporting practices where the framework's there already, and you're meeting every quarter to report the same numbers, so the degree to which you can interpret it or question it or maybe run things differently is somewhat stifled, but I think what we're saying is that there needs to be a broader awareness and a broader literacy. What are some of the steps that leaders or intrapreneurs or organizations could set up to ensure that would be happening?

[00:21:20] Dr. Marco Motta: So I think this is something that I've done in the past in different organizations. This is something that I've done at transporter main roads in particular. The starting point is really to create. To create an artifact that we can all kind of huddle around. That for us was the when we- I took this report that was called the Queensland transport snapshot, which ultimately was to report on the benefit realization of infrastructure.

It sounds relatively boring. We kind of spun it in a way that we were reporting on a lot of different metrics across transport fields, but across the whole variety of transport fields from safety to traffic to public transport to walking and cycling, all that sort of stuff.

And so having something that you can look at and you can look at together creates a shared understanding of where we're at, creates what I would call a shared narrative of where, of how your organization is working. And what things are going well and what things aren't going well.

And so to me, that's the first step being able to report and have a shared understanding of data and figures that are important to your organization. And my surprise is always, even with the biggest organizations that I go and work with, my surprise is always to see that some of that stuff is just not done.

Like some of that stuff is still done in Excel, is not automated. If they have a report it's done by, one person in a corner and it gets read by three people in reality, like the first step to change the culture of your organization towards a more data driven, evidence driven culture is to be able to, broadcast some of these key metrics and have people criticize them as well, you might think that I'm just thinking of an example that doesn't get me too much in trouble. But look, I think, it's no secret that some organizations measure, like, public transport organizations measure their patronage, like how many people are actually on the bus in trips.

So trips are useful because they can be broken down, especially if you've got a multimodal transport network with buses and trains and, ferries or whatnot. It does give you an opportunity to say how many people are on the ferry and how many people are on the bus, but trips can also be manipulated in a way that if you want to double your patronage overnight, you can actually just split all the buses in two. You make like all the buses become two trips, the same trip is like a truncated and then you get, you got to change bus and go to another, to the next one that will ultimately look like your patronage has increased 100%.

But in reality, it's a bad outcome for the customer. And so yeah. In a lot of cases, it's great that people have the chance to talk to the pros and cons of a metric and how to also then think about how to avoid that situation. So if you're seeing that people are just truncating services, you're like hey we can also measure this in journeys.

And if the journeys are the same, but the trips have doubled, then we haven't really done that much. That's just one example of how you can get an opportunity for people once you publish that metric to criticize it and to look at how to use it in the right way and to avoid bad outcomes.

[00:24:22] Chris Hudson: Sorry I was still trying to get my head around trips and journeys and what the difference is, but 

[00:24:26] Dr. Marco Motta: Oh, sorry. So basically, like, a trip is just, if you're, if you do a trip on the bus, it's like

from A to B. If you do a journey, you can potentially, your final destination could be work. But you might have to stop and interchange from the train to the bus. And that's two trips.

Ultimately, I always bring it back to the purpose. Like, what's your purpose? Your purpose is not to go to the interchange. Your purpose is to get to work. And so journey to me is more important than trips. Although trips has a part to play in the way that we understand which part of the system is working and how much, but measuring patronage in trips can have its issues. Especially when things aren't functioning as normal. And that's something that COVID taught us that when things aren't functioning normally, all of a sudden, all our metrics and all our data is it just gives us weird results. And we're like, Oh, that's not reporting the right thing anymore 

[00:25:16] Chris Hudson: Now that's interesting. And it also depends from what I'm hearing a lot of language and how language is used consistently because people can get very panicky about this in the way that presentations put together, but it is incredibly important, obviously, to relay narratives and data and reporting things in the same way.

And we just gave the example of trips and journeys, but actually, more broadly than that, I think there's a bigger point there in that, just the description around data that exists in the narrative that exists isn't always delivered in the same way. So take your numbers, house them in something that's kind of consistently- 

[00:25:47] Dr. Marco Motta: Language is key 

[00:25:49] Chris Hudson: Yeah, it's key, isn't it?

[00:25:50] Dr. Marco Motta: Narratives is key. And to that point, the first step is to create an artifact where we can all kind of huddle around. The next step is from that artifact to kind of all have a go at understanding it and creating that shared narrative. I think one of the biggest challenges that I see in organizations is where there are, whether those shared narratives that don't exist, whether you can, you walk into an organization and you're, that they're in trouble immediately because everyone's kind of talking in almost like talking a different language. I'm sure you've seen examples of that. And I think it's clear that there's a there's an interesting kind of example from the world of art and has history. There's this painting from the case of Lescaut in France, I think, or close to Spain.

They're the first kind of paintings ever recorded of the caveman and if you haven't seen them like they're basically like this large animals and there's all this kind of little stick figures kind of throwing sticks at it. And Arnold Hauser, who's a very important art historian from last century, was talking about this idea that those paintings aren't a representation of reality.

 As it is, they actually create a reality that doesn't exist yet, but that the people want to kind of bring into existence, almost like magic. The idea is that the painting kind of brings about a reality that doesn't exist yet, but it already exists in the painting.

And so by extension, it's already existing for all the tribe, and now all the tribe can kind of rally behind that objective that is now being created and go and kill the beast so they can have a great lunch and a great meal that will get them through the winter. So I think the whole idea of that is, is pretty powerful in the sense we often think again, I think, modern understanding, we often think about facts and narratives as in stories are made up. Facts are real. Stories are fantasies in people's minds, and facts are realities that we can touch with our hands and all of that sort of thing. There's so many examples of things that we think are totally real that are just a figment of our imagination.

And I think one of the again, without kind of wanting to hammer too much on this point, but the point of narrative is really important to me at this point. I'm thinking about it a lot. And another book that I love is Sapiens by Yuval Noah Harari. 

He talks about a lot of stuff, but one of the stuff that really stuck with me is that he thinks that human superpower compared to animals is not that we can talk, it's not that we can, to an extent, it's not that we are more intelligent. The main point is that we can create these shared narratives that can allow us to have groups of a very much increased size compared to what you can do without those narratives.

When you think about animals, there's a few exceptions, but most animals will have groups of, 30 and 50 and realistically, like in prehistory humans also have tribes of that size, but all of a sudden they, they started to be able to, like, control larger and larger number of like groups

The way that, Harari argues that is done is through making up these ideas like a nation, an empire, the economy, money. I think today the economy makes, kind of makes that point better. Because it's money doesn't exist. Like money has no real existence, apart from the fact that I wanna exchange something with you.

Like if all of a sudden we all decided that money had no value, money would have no value. At this point, our global group that encompasses the whole of humanity lives and dies by money. Like by that idea that it doesn't have a factual basis. People die for money. People live because they have money that they can exchange for something else. it's crazy. And so, like, thinking about that sort of stuff, makes you realize how important that shared narrative is in an organization. If you have that shared narrative, you got someone that's carrying through that shared narrative.

And, you think about all the successful organizations, like Apple, like those guys, they have Google, they have important narratives at the bottom of their like, organize the information for the whole world or think different, all that sort of stuff. They're not just like a phrase or a slogan, they're ultimately like a narrative that everyone shares about who we are and who the organization is and how we can achieve something in the world through that.

[00:30:15] Chris Hudson: There's a part to that which is around the influence of the narrative which I think to be successful, certainly in my experience, I do a lot in the area of human centered design and we're thinking about how to design businesses, products and services around people and what they need.

And that's both your customers, but also the people within an organization that it's your culture and your fabric and your DNA as an organization. I think to tie together some of the different things that we've talked about today, I think there's a need to really involve people in the understanding, but also in the crafting of that message and the crafting of that narrative so that it's at least aligned upon and it's agreed and it's powerful and people agree then that it can be taken forward and used either for a longer period of time or in other applications, that's essentially what your employee value proposition or your brand strategy or any of those manifestations will do for you.

But it does rely on you doing it with other people. I think at the heart of this point is really that, if you're the data professor, and you've got access to the data points, you can put that into a presentation that can go forward. But unless something is done with that, and then taken forward, but done, almost within a co created environment nobody else will take ownership of that unless you involve them in some way. So I think as the intrapreneur, it feels like you're having to bring that conversation together and facilitate some of that agreement. But also that evangelism then out to the rest of the business. Do you think that's a fair point?

[00:31:39] Dr. Marco Motta: Oh, absolutely. I think there's, silos of people that are really good with data and people that are really savvy in the organization's kind of operations. And one of the things that we were quite successful doing in Transport of Main Roads, and we repeated that in other organizations, is that situation that opportunity.

We used to do it through just simple workshops that where we talked about the dashboards that we created. It's like it's an opportunity to talk about together, like to bring together people that understand what the data is saying and people that understand what the business is doing. Like how the business actually works. In a lot of cases, things like the data can tell you only so much.

Like I always say, I can only tell you how fast you're going, I can't tell you if you're going in the right direction. It's a point that I believe in the sense, while I can imagine what the right direction would be, I am not necessarily the most qualified person to tell you that.

We used to have a metric for how many trucks used to run on certain roads annual average daily traffic of trucks of different sizes and often it was like, we were never sure whether it was like, is it a good thing that we've got more trucks?

Is it a bad thing? And it's sometimes it's a good thing in terms of economic development, but sometimes it actually means, so there was a year where basically because of the drought, a lot of the cattle feed was not available locally and had to be imported from other countries. And so there's a lot of trucks going from the port into inland.

And that wasn't, that was actually worse for the economy because we now had to import all this feed to feed the cattle as opposed to like, use the local one. And so, as an analyst, it's impossible for me to know that level of nuance of a business. And I think the more analysts can embrace that and talk to the right people in their organization to get an understanding of what the data actually means, the more dashboards are going to be used, the more data will be regarded not just as a hat on, but as a critical part of doing good business.

 I think that's it's critical to bring the two sides together and to not work in isolation as an analyst.

[00:33:42] Chris Hudson: Yeah, I mean, there's definitely a leap from raw data into pretty much observation and we've talked a little bit about subjectivity and objectivity. Some of these things have been helped by observation is it's like an interpretation but then inside is almost looking for patterns.

And then bridging from insight into opportunities or even recommendations. I mean, these are several steps that you have to kind of string together to make the data story sound compelling in one way or another. So what advice, if anything, would you give in some of those areas? I know that you love a bit of data visualization yourself.

But for clarity and impact and storytelling and influence really, what are some of the magic things that you can do with data to make that possible?

[00:34:24] Dr. Marco Motta: There's lots of fun stuff that you can do with data. Particularly like just using visualizations to unlock the information behind data, again, often data is not like it's hard to look at a spreadsheet and understand what's going on.

So again, the steps of manipulating it to make it tell a story are very important because again, the human brain can only process that much information at a given time. And if you want to bring a number of things together. You do have to use data visualization and you got to use techniques to do that.

I recently taught a course on data visualization storytelling, and that's a lot of the courses about how you use colors, how you use the space on your dashboard, how you guide the reader, the user of the dashboard through your narrative by positioning things in the right spot.

And so being an expert data visualizer really helps because it helps you, it's not just about putting some data on a piece of paper. It is about guiding your user through the information that you think is relevant, but at the same time, then checking in back with the user, with the people in the organization to see whether that actually makes sense or whether they think there's a different story that should be told or should be highlighted more. And that's again, that's a process for anyone that's interested in improving their maturity around using data to make decisions. Like I said, sort out your pipelines, build your dashboards, do the technical stuff but the next step that comes straight after that is to get everyone involved. Get people involved in the data, even the people that are not familiar with it.

And a good analyst should be able to do that, to bring everyone together to the party and collaborate on, what do we do from here? So what? Now that we know this information, what are the next steps? And it's not about jumping to solutions, but it is about recognizing that data is only useful if you do something with it.

[00:36:15] Chris Hudson: Yeah, you raise an important point there. I think that a lot of data is sort of, in the way that it's presented and it feels a little bit half baked. You're getting to see the stats without the so what and you know the why and the direction for where you think it might be going.

So you don't want to lead everybody. But actually, if you're just presenting a slide with the statistics on that, it's really relying on your audience to then think about what they're going to do with that information. And if you're sitting in a boardroom or in a team meeting, and that's happening, then You might get a discussion going, there might be three or four loud voices, there might be a bit of disagreement, this and that, it's a bit like being a barrister and you're in court, you don't want to lead the witness, but you need to kind of present a bit of a story around it so that people know what to do with that information.

 A little bit of hand holding, I want to say. So, in- we've talked about art, we've talked about philosophy, science, literature a little bit. In literature. there are certain narrative structures that seem to work where you have pretty much a sizzling start and there's something punchy up front, things get unpacked. There's that fish shape kind of narrative analogy that sometimes use so you have a very pointy start it then expands it comes back together at the end and then there's a big crescendo towards the end as well with a fishtail. Is that something similar to what you would use to talk about data storytelling, what would be your advice with data storytelling?

[00:37:31] Dr. Marco Motta: It's often not as exciting as a real story. But there's a lot to be said for again using stories as a device to bring a better understanding of the facts. I think that's something that many people do. I think if there's a again referring to back to books, there's other amazing books.

The book that I love is called Hamlet's meal by an Italian and a German scholar that talk about this idea that stories that we used in the past to codify very complex mathematical actually very complex astronomical calculations about how certain stars were moving due to a interesting phenomenal perception, procession of equinoxes. So it's like there's stories kind of help us in a number of ways, but like you say, you know, now, and when I talk about that, storytelling is basically, that idea that if you create a shared narrative, but also if you create a shared emotion about it, about data, which sounds crazy, but in reality, that's what we're doing. We're creating an emotion about how you see something. Is it good? Is it bad? Is it an issue? When you think about it, like the story that there's never a story, like it's very hard to make a, to write a short story or a movie or like where there is no kind of bad character or nothing bad happens, something bad always has to happen for the story to move along.

And so there's always an element of that discomfort in any story that we're telling. That's kind of part of the narrative. And if you don't find that discomfort, you kind of end up with a really boring story that nobody remembers. It is about finding the balance to a certain extent.

It's not just about looking for bad stuff, but it is about finding what the problems are and how they talk to the story of your organization like it's crazy how much like I've since I've kind of started to think more closely about storytelling. It's crazy how much of like the identity of nations is, shaped around stories and narratives like, the ANZAC story or the the whole the way that the Americans see themselves is like, the story of liberation and freedom. Like we don't see ourselves that way. You know what I mean? It's like, that's their story. We have another story. And it's quite interesting how that story and our story produce different effects in the real world.

 Yes, it's a story, but the way that they behave reflects that story and the way that they understand themselves and they understand their actions reflect that story. So, to a certain extent, just to make generalizations, an American might be more interested in those values of freedom of speech and like being in, I guess we absorbing a lot of that through media, but in Australia, you might be more interested in that those values of self-giving and being more kind of like open to that idea of self-sacrifice for the good of others to a certain extent. And I think, that guides our actions that's a way. And so like from that point of view, literature and data and science and philosophy all kind of come together and the way that we talk to each other all come together to form how we do things because it's really about how you get to do something that's relevant, that's important, that has meaning. And so that is why storytelling is important, not so much as just, as telling a story in itself.

But in so far as that story, that shared narrative will finally prompt us to do something that is meaningful. That is to an extent beyond what we think we could have done before kind of brings us to the other side. It gives us the opportunity to think, actually, I don't have to stay here.

It's like that coming of age story. I don't have to be here. Yeah, I don't have to be this. I can be that and so in an organization that can be quite powerful. And I think in general, in the world, that's really powerful. That's why stories are important.

That's why basing them on a certain amount of truth is important as well, because we want to achieve the right thing, not just, achieve something that's meaningful and real and good for everyone. 

[00:41:26] Chris Hudson: Yeah, I mean, it has to align to a sense of purpose and fulfillment. Well, I mean, a nation or a country is one level. It's a very macro level, but at a micro level, you're thinking about, how do I relate to the content that I consume, on a day to day basis?

What's your conversation that I'm having? Something that you say to somebody? You're trying to find relatability in a lot of what you do. There can be broader guiding principles, commonwealth or jurisdiction or a constitution. There can be bigger things in play. 

[00:41:53] Dr. Marco Motta: So that that's the point. You've got to find something in common to be able to communicate. Even language, at a basic level, if we speak two different languages, it's very hard to

communicate,

But we can still do it through sign 

language, because maybe there's something deeper that we share.

But if we share nothing, it would be very hard for us to communicate with an alien that had a totally different understanding of reality or time than us, we would still need to find something in common to be able to communicate and in a lot of cases, we rely on the fact that those commonalities exist.

Without house having to do anything because we're educated into them and, raised into some of those things and all of a sudden, like, and I found that as a person coming to a different country, when I was 19, I came to Australia from Italy and it's like some stuff is jarring because all of a sudden your way of approaching something doesn't reflect the way that other people approach it. And so it's like, who is right? All of a sudden you kind of, it's almost like you step out of the dream and you realize that it's not all normal. And in fact, there's nothing normal. Everything is what we make of it to a certain extent.

[00:42:58] Chris Hudson: I think about that alien analogy a little bit too, because you find yourself doing something, say it's playing, I don't know, a game of tiddlywinks with the kids, or I was at a local agricultural show the other week, and and there was a bit of a dog parade type thing going on, and people were running their dogs around, and they're very nicely groomed, and they're bouncing around with these dogs.

 And I thought if aliens just turned up one day and saw us doing this, they'd be thinking what on earth are you doing? Pardon the pun, but it's kind of what is going on here? It's the fact that you've made a procession out of, humans and animals doing this thing and people are going to judge it and somebody's going to win.

It's just a construct. Nobody understands what's happening unless you're in that. So I think part of the point of all saying all of that is that part of what you have to do with data and, all the things that we've been talking about is actually build in a way to create empathy.

So if you're presenting your data to a room of people that have no idea what you're going to say and no idea what you do and about who you are and what you stand for and the values that you represent, what are some of the things that you can do to kind of bridge the gap? What's worked in your experience in that respect?

 Let's put it like this if you want to get there and if you want that shared understanding, if you want people to really understand your data, you have to put in the work. And so sometimes when you're presenting to a room full of people that doesn't understand fully where you're coming from, you have to, for lack of a better word, you do have to dumb it down to the point where, you're telling brush strokes, but you're not telling the full picture and sometimes that can be frustrating, but I also find that it's a way to draw people in. So I love talking about these things a little bit in general, but I also love to get really deep into the details.

[00:44:33] Dr. Marco Motta: And so when you're talking to an audience, just to kind of give them an idea, and that's why to a certain extent, CEOs and other people do that in those kind of hold like, large meetings where they talk about stuff in general, and I feel everyone in those situations often everyone feels like they, he or she is saying something interesting, but also they always find that is not fully relatable to them because it's like kind of a bit surface level.

And so I think, you've got to do that sometimes, but most of the time, the best strategies that I found is to, you've got to bring the organization on for the journey, and so you've got to accept that at the beginning, we will have to be surface level, and that's okay, but slowly, we want to improve, we want to provide more and more information, we want to make that data more available, we want to talk about it more, we want to provide opportunities to talk about it and discuss it.

We want to ultimately support the organization going deeper and deeper into their data, have that data available for them to use, have those discussions internally happen can we make it happen all the time? Not, but if you put the work in that, then there is a big uplift in, in so far as organizations start to find that they don't just have to rely on gut feel to make decisions that may turn out to be wrong.

They can go and find some additional information quickly. They have to justify or at least to find a way to support what they're trying to do. There's lots of arguments about, we're trying to justify what we already want to do. I don't necessarily espouse them. I think for some people it happens.

 I find that I'm happy to change my mind. Maybe again, it comes from philosophy. Very happy to change my mind if I can find enough information to make me change my mind about something. And so I think organizations that can get to that point, they can stop looking at, just at their individual kind of self interest and can work together to the common good of the organization or their customers, they tend to be more successful in that journey. Yeah, it takes a lot of courage because, nobody wants to see, their job endangered or their livelihood disappearing. I think in a lot of cases also stands to, it's also about creating a culture where you feel like you, other people have got your back and you can say something and you can raise an issue and you can say, hey my job is not achieving what it's supposed to do. And that doesn't mean that you get, kicked out of the organization that doesn't mean that you lose your privileges or you lose your livelihood.

You know what I mean? It's about creating that safe again, sounds corny, but it's a safe space to be able to criticize and say stuff and do stuff and be wrong and move on.

[00:47:11] Chris Hudson: Yeah, amazing. I mean, such an interesting chat. And I think, if we've highlighted anything is that the data is incredibly powerful. Obviously, it's everywhere as we establish big data is once people talked about that, it's everywhere. Bigger than life. It feels like it's there to establish understanding obviously, set direction, set narratives, set story.

But also as an enabler, and a connector really around how shared points of view come together and it creates not only a discussion point, but a way of aligning people around a certain truth, which people hold dear, you need that to be able to feel comfortable in your work.

I think listeners will really enjoy the chat we've had today. I've really appreciate the time, Marco. But I just want to say a massive thank you to you and I'd love it if you want to tell anyone about your business and where they might find you if they've got a question, philosophical, but Marco can cover data, art, science, philosophy, music, anything really.

So yeah, how would people get in touch with you if they wanted to?

[00:48:05] Dr. Marco Motta: So, we've got a website which is mottaconsulting.com.au. My consulting business that I'm the managing director of. On there, you'll find a lot of links, including my phone number, my email. So lots of ways to get in touch with me in terms of where I tend to spend a lot of time talking about this kind of stuff, LinkedIn is my favorite place. So if you look me up on LinkedIn you will find me. But yeah, LinkedIn is my home. I love for people to get in touch with me, whatever questions I always find that conversations lead to other conversations. And I love talking to people about these things. And I love to have a chance to listen to what people have to say and to different opinions because that it's really enriching and it helps me to stop my echo chamber, which is quite always very easy to find yourself in and find yourself challenged to, to be able to grow. So yeah always interested to talk to people and listen. I think, a lot of what we do is in reporting automation and data, that data capability uplifting and digital transformation.

So always interested in talking to people if they've got problems in those areas because I feel like that there we can help.

[00:49:09] Chris Hudson: Yeah, perfect. All right, we'll leave it there. Thanks so much, Marco. I appreciate your time.

[00:49:12] Dr. Marco Motta: Thank you so much Chris.

[00:49:12] Chris Hudson: Okay, so that's it for this episode. If you're hearing this message, you've listened all the way to the end. So thank you very much. We hope you enjoyed the show. We'd love to hear your feedback. So please leave us a review and share this episode with your friends, team members, leaders if you think it'll make a difference.

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