Hello and welcome to Episode 3 of the first season of the "Your DataOps Advantage" podcast series by Hitachi Vantara! In this episode, podcast host Bill Schmarzo (our CTO of IoT & Analytics) meets again with Renée Lahti (our CIO) and Jonathan Martin (our CMO) as they react to the previous day's Digital Envisioning Workshop, the importance of knocking down organizational silos, data quality versus data action, and the importance of pragmatism. Plug those wireless headphones in folks—it's time to unlearn something!
CTO, IoT and Analytics, Hitachi Vantara
Bill Schmarzo is regarded as one of the top Digital Transformation influencers on Big Data and Data Science. His career spans over 30 years in data warehousing, BI and advanced analytics. As the current CTO, Analytics and IoT for Hitachi Vantara, "The Dean of Big Data" guides the company's technology strategy and drives "co-creation" efforts with select customers to leverage IoT and analytics to power digital transformation.
Chief information officer, Hitachi Vantara
Renée Lahti develops and implements information technology (IT) initiatives that align with Hitachi Vantara's mission. She leads the transformation of the Hitachi Vantara IT group from a conventional organization with many operational silos to a dynamic, agile team that efficiently focuses on business outcomes. Today, the IT group is an organization of cross-functional teams that include business and IT functions to work together using iterative, agile sprints.
Chief marketing officer, Hitachi Vantara
Jonathan Martin is responsible for the global strategy and execution of all aspects of Hitachi Vantara's marketing efforts. Self-described as a career CMO, Jonathan's passion is to drive a progressive approach to B2B marketing at the intersection of metrics and magic where creativity and data work together.
Hello. Welcome to the Hitachi Vantara DataOps Advantage podcast. My name is Bill Schmarzo, I'm the Chief Technology Officer of IoT and analytics here at Hitachi Vantara.
The DataOps Advantage podcast series is going to track the trials and tribulations of different organizations, of different sizes across different industries as they wrestle with how do you get value from your data. What we're going to do is we're going to talk to these organizations about how they're leveraging DataOps to uncover value in their data and help them to figure out how to drive return on their data investments.
Welcome to episode three of our DataOps Advantage podcast series. This is an exciting day for us. This is the day after we have actually held the workshop. We survived! Everybody's here, no lives were lost in the process. And let me just start off by asking a question, but go with you first. Renée, what'd you think about the process?
Renée Lahti, Chief Information Officer, Hitachi Vantara
Process was great. We had a cross functional team of I think almost 50 people, on the phone and in the room and lots of strong thoughts and opinions, but everyone spoke their mind and I thought it was a really great cross functional company event to say this is the value of our data as a group.
Good. Jonathan, what do you think it was?
Jonathan Martin, Chief Marketing Office, Hitachi Vantara
It was awesome. It was a really, really great experience to be part of. I'm so super excited to be able to connect, get going with this activity.
Bill: So during the workshop we have lots of different rules we use to kind of govern the workshop, right? Be courteous, be respectful of the conversation. All ideas are worthy of consideration, which by the way doesn't mean all idea ideas are good, right? But give everybody a chance to have a voice to be able to speak out. We also talked about the importance and the power of disagreeing, but committing. Being very important that we walk out of there aligned. One of the other things we ask is be willing to unlearn. No, don't always unlearn things. But was there anything about the workshop or anything that happened yesterday that forced you to pause and think and maybe relearn something?
Yeah, there is a cross functional team, HR, sales, finance, marketing, IT and they all had an opinion. And my unlearning was to listen for example, to the training and education representative speak and the passionate data that he wanted that wasn't necessarily training related. You put people in buckets, even we do as executives or in silos. And it was kind of unlearn what you think you know, even from the team that was there in the room, they all were inspired. And it was an interesting, story to hear that person say, this is a day I want, cause I think it'd be really valuable for you, marketing department.
So the one thing for me that strikes me about these workshops and it kind of builds on this, we bring together very diverse set of people and there's one chart that we create, that shows, everybody's inputs. We, interview everybody, everybody has ideas and themes. We capture those ideas. And then we, look for common subsidiaries, we aggregate them up in the use cases. So we took approximately a hundred different ideas and they aggregate it into about 11 different use cases. And I think what the epiphany moment is at these workshops, and you could see this yesterday, is when people from different functions, different parts of the organization all realize they're trying to solve the same problem.
Bill: That there is, if you start knocking down the silos, all of a sudden you can start driving much closer collaboration. And the more people who have different perspectives on the same problems, the richer the answers are going to be.
And I think the other thing that I noticed when this, this slide went up yesterday, was that people, everyone first of all look for themselves. So it's a process like am I part of the process? Did my feedback get through? So everyone looks for where they are. And then the second thing they do is they look at what everybody else did. So they tried to decode the net, the names on the top of ethic. I think that they were looking at them like, what does that, what did that person think? What did that person think and look at like, are there clusters? Does that, I would expect that person to think the same way. I think. Did they, from the interviews? Yeah. So I thought that was a kind of really fascinating moment of, of people just kind of wanting to be included and wanting to see, see their work kind of on the board.
Yeah. There was that, that, that epiphany moment and they all realize, wow, we're all fighting for the same thing. We may not need me come at it from different perspectives, but we're really all on the same page. Right. And, and if we can give people a common mission, common vision, a common language and a process, then you can drive phenomenal results from a collaboration perspective. The one thing that yesterday that kept coming up time and time again, there was a very much a challenge between data quality concerns and doing something. You could see the, the IT people in the room really saying the data's not ready. We don't have it. All of it there. In fact, even some of the data scientist people were kind of raising red flags. But you also could see the people who were, I would say more on the business side saying, Hey, we've got to do something. How did that strike you?
Yeah, for sure. Like, I think I learned more about data engineering yesterday than I've learned in the my previous life. I think people, people naturally rat hole too. Like, Hey, like we'd love to do this, but we can't because of dot, dot, dot, dot, dot. And I think getting to a point in the conversation where, you know, let's focus on, on the criteria we're trying to use to make decisions, let's be ambitious. We know going into this, there are going to be things that trip us up. There are going to be things that are difficult if the things become so difficult in the timeframe that we're working on, we just need to descope the project a little bit and say, you know what, we're not gonna do it for all the data that we have or we're not gonna do it for all of the geographies or all the theatres. Maybe we're going to do it for one theatre, one segment or one industry. Um, so I think we have the opportunity as we go through the process to continue to kind of rescope the project a little bit. But I was glad that we didn't allow ourselves to get tripped up on the, we can't do this because dot, dot, dot, dot. Because there's going to be many, many more of those ahead of us. Exactly. Yup.
Yeah. So again, you talked about the IT group, you know, oh, the data's not good. We can't get it all. We can't load it in. And I think the, the mantra is this, just is it just good enough? you know, and descope it, take it smaller, but just good enough data. That doesn't mean crappy data slipshod work, but just get something in there and start digging into it. You don't know what you don't know until you get in and start looking at the data. No matter how imperfect it is.
Yeah, and I, and I think what happens is there is so much data out there that when you try to fix it all, make it all perfect, you end up getting none of it fixed. So the fact that we were able to focus in on one or two use cases and identify the, the most important data associated with that, I would hope it tells the it organization, let's double down on these data sources. Ignore the rest for now. Let's focus on these. And given the use case we're going after, let's, let's not let perfection get in the way of progress. Perfection is like either black or white, and all the interesting stuff is the colours in between.
That's right. And again, I mean, I'll confess the sin as an executive, I'm always the one that saying our data's crap. So, you know, parts of it are, but that doesn't mean don't use it. I think you called my puddle muddy.
In the wholistic world of Hitachi Vantara, our data could be better. It's true for everybody, but yeah, and that's not a unique thing. And what I realized is by saying that people worry that, oh my gosh, then we got to make it perfect before we use it. And that's not the right answer.
One of the things about the workshop, it's really key for success is that we've spent enough time with the executives, you guys, um, to really understand what are the criteria, the five, four, six different points that are in the most important things you're trying to achieve and then use that as a vehicle for helping us to make this trade off decision. Tell us what went through your head yesterday as we were trying to make decisions and how you used, cause I saw you use this very effectively, to really move the team back towards a goal that was really more pragmatic.
Yeah. Like a lot of the time but I don't think just to get to size yesterday, but as a, as an executive you're constantly for, I constantly find myself having to, you know, get the team to take a hard look in the mirror, take a step, step back from the detail and look at the bigger picture.
And we certainly witnessed that yesterday multiple times where people begin to rat hole or get into the detail of the use case and how it's going to be great and change the world. I'm done, done, done, done. But does it really match up to the criteria that we're trying to use for selection? And just, you know, I think a lot of time on our role was like pulling people out a little bit and saying hey like that's a really great use case. Like, I certainly really want to do it, but is it going to be the one that we select correctly based on the criteria we're trying to use? And so, so the, the key learning for me on that one was spending the time on making sure that the selection criteria are absolutely the right selection criteria because they are the things that ultimately gonna determine the outcome.
That's, that's part of having that common language. Yeah. Sorry, we all speak in the same language. No, we're trying to achieve.
So we had the fight, I mean we had it handwritten on a, on a butcher paper in the front and one of us would say, so how does this one relate or support number five? Yep. And then there was a little bit of silence in the room and I think then they like had to step in and go, okay, this right. It's a really cool idea. But these were the five things we said were most important for this workshop. Doesn't support it.
And the fascinating thing is when we, as we're going around the room and we're kind of sticking post-its on boards and this sort of thing, as soon as those criteria were off behind us, somewhere in the other side of the room, everyone just kind of forgot about them again. So you bring them over and sticks them in front of people and is this the criteria we're trying to use, so that's right.
We learned a lot. I mean, we ran, typically it's a four hour workshop. We did it in two hours and we ran through it pretty fast and a number of ideas we got. It always impresses me how sometimes your best ideas come from the person who's most quiet in the room and getting people that say…
That'd be the data scientists, right? Yeah.
There you'd also in the back of, they're very good. They're very, very quiet. Yeah. They argued about those random forest versus SVM methodology. Quit it guys quit it. Okay. Was there anything about that process of, of the ideation part of things came out that that either surprised you or made you happy, made you confident in the organization?
Yeah. It's like the, the thing I loved is, so we, we end up with, we do the a hundred interviews, we get it down to this, what was it, like 11 niche use cases. Yep. And obviously everyone had not seen, in the room, had not seen all the use cases. And it's one of those things where, you know, diverse groups just come up with better conclusions. And people were seeing these use cases for the first time and bringing like their raft of experience to that use case. And it was like just, you know, it's like this is why diversity is important. This is why, you know, getting group groups from different parts of the world and functions together, thinking about something just ends up with a better result. So it was great to watch that. Like in action.
We had a quiet, I think it was the second row, third row, second, second, second rows quiet. But yeah. And at some point they spoke up towards the end and there was two or three just amazing ideas. They'd kind of digested it. And then they came up with a, that was basically unstructured survey data from our visitors centre. Right? And so we could use that. We could all of a sudden the energy and the juice has got flowing with the, again, diversity always brings the best answers.
That that was the moment for me when I, when I, you know, I always watched these things for what does my kind of epiphany learning moment is when we started talking about the insight center. And how much did we have there and how we could use that data. It's like, wow, that's a great use case, right? Yeah. And it may not be the, we go after first. In fact it wasn't right. But what it shows us is there's a, we can, after we've picked our first use case, we can put together a roadmap that shows how the first use case and what we're doing there from a data analytics perspective can help make our second use case easier and faster. We can accelerate time to value. We can de-risked projects. And literally I started attacking each of these 11 use cases almost one at a time.
Yeah. And we, we would never have got those insights if we'd said, hey, this is a marketing project. Yep. Or a marketing it project. Let's just get marketing and IT people together in a room. By bringing like all of those disparate functions to bring like their experience you just end up with a better, more comprehensive kind of result.
We talked in the first episode about culture, about how important it is to have a culture where people are willing to share ideas, feel comfortable to speak out, but eventually at the end commit. What does it say about our culture here that we had that kind of exercise yesterday with that kind of great participation?
I'm still pretty new here, but what one of the things I do love about working here is if you, you set the bar, like people rally and people jump in and people are not afraid to, you know, get, get wet and start swimming even if they don't know where that the surface is. And I think, again, that was that, that kind of culture, that mentality kind of throwing out like people like, hey, we're going to go do something new. We've not done it before, but we are, you know, we were in an environment safe enough that we can throw things out. And I think that's a lot of that was down to your leadership and the tone we set at the start of the meeting, It's like, you know, and know all ideas are valid. Not all ideas are valuable, but you know, jump in and get wet and, you know, contribute.
So I've been here a little over three years and the thing that I say a lot is, uh, we have the hearts of lions here. We will charge a hill. If you get the everyone in the room with that same common goal, no matter what it is. And that was what showed up yesterday in the workshop. That's, you know, it is not a marketing IT project. Everyone knew the value of this data for our customers, make our customers happier. All of the things that came up, um, was in, in the support of Hitachi Vantara. So it was really cool.
Yeah. And it was a very, you know, you, you look at, look at at our, the behaviours we want to exhibit around like fighting spirit and harmony and we did both of those things yesterday. Okay.
Well there's Hitachi Vantara has a very unique aspect and respect to the customer, very heavily focused on customer success. And that comes through yesterday where people are really focused on how do we collaborate to help people be more successful. That's, that's why it's fun to work here. It's really great. Let me ask you a unusual question, challenging one. So yesterday.. was once upon a time.. yeah.., I'll put my Cinnabons on. And um, how, how do we as an organization scale that kind of innovation, how do we scale that kind of innovative thinking? So we, we just don't ideate, but we actually also act. What are the challenges we face as a corporation that I'm sure our customers face as well. Once you start going down this road, once you start taking this kind of, this digital value enablement approach where you're really bringing in a collaborative environment, you're really getting the best ideas out of everybody. You're leveraging design thinking techniques to do this. How are we gonna accelerate? How are we going to scale this across the organization?
So, so I think, I think for me like people in general, people want to come to do work to work and like do a better job and work more efficiently and that sort of thing. And so so finding a project like this where they can see, see new ideas and they can collaborate and they don't have, have to figure out for themselves what kind of a passenger on the train, but they're like learning the new experience, learning the new way, working learning the these new thoughts and ideas and then taking that into the second project. And the third product is the bowling pin kind of kind of thing. You start to start with one and from one, come to two and from to two come to four and from four, comes whatever's after four…so you know, we, we've I think the same kind of wave that went through organizations four, five, six years ago with, with agile, it was like, hey, we used to, used to work in a, in a waterfall mode and then there's a new way of working. It's called Agile and you run out on one project and people like Moen complain about, it's like more meetings and it's more difficult and I don't like this and it's too much accountability and blah blah. And then after three or four weeks people are like, oh actually I'm like more informed about what's going on in the project. I have a voice. I understand, I understand a lot more about what people are doing. Um, and so I think, you know, organizations are here for you and for these new ideas. So I'm super excited about this project, but I think I'm even more excited to see what those kind of number two, number four kind of bowling pins end up looking like.
Yeah, so I think from an IT perspective, how do you connect the dots of a company's objectives all the way down to every last employee in your organization that does tech, right? That's hard to connect the dots. We just went through a workshop yesterday. The DV workshop and framework not only has eight initiative we aligned behind, we have a roadmap, it's actually an operational roadmap. We're going to churn it from projects into this is how we run the business. IT was in that room understanding the value of our data, how we run our businesses at Hitachi Vantara. So I think that's a really empowering thing when people can all connect to what we do as a company. And I think this is a, again, it's, it's, it's DataOps, it's now the data operations world that we're all moving into. It's really exciting.
DataOps is very much like data science is very much founded and excels in an environment around collaboration. Because what's going to happen, and we're going to see this in the project, I know what's gonna happen in the next couple of months. We're going to go sideways, we're going to run the data problems. We didn't know we were gonna have. We're gonna run into data science problems. We didn't know we're gonna have, we're gonna run into problems now. It's real easy to run away and start pointing fingers and then we'll go nowhere. Or we can leverage that collaboration we started building yesterday to really amass a team to address that, to shrink the scope of what we have to or to morph the scope a bit. I mean, we're going to hit inevitable. Our customers see this all the time and sometimes you're not prepared as management, as leaders for when things go sideways. How do I support the team? What are your thoughts about over the next couple of months as we go towards next, trying to deliver something? What do, what are the kinds of things that you are personally going to be able to bring to the team to help us through those tight moments?
So collaboration, going sideways. I think part of it is us just showing up. So that's key. Reminding them again to that butcher paper or a fact was just carry that butcher paper with us to every meeting right there. Okay, everyone remember this? Um, I think is a good point. And then the second one is just people need to know that we have their backs. It's, we're going to fail fast. We're going to do a whole lot of learnings. We're going to go sideways. The data's not going to be the best. We're going to re-scope. It's all okay. It's like permission to play and be empowered as that cross functional leadership team.
I have nothing more to add. Success is rarely a straight line.
That's right. Success is rarely a straight line.
One of the most powerful things that's happening in digital transformation is a realization that the economies of learning are more powerful than economies of scale. That an organization they can learn and share and refine and reuse is going to grow faster, will accelerate time to value. On the second, third and fourth use case, we'll de-risk projects and we will find those moments, but it's going to take strong leadership to stand up there and say, hey, we're going to go sideways. We're here to support you. If we've got to tweak it a bit, it's okay if we fail on certain things, it's okay as well as long as we learn. Well thank you very much. This has been the end of episode three. We finished the workshop. It was, it was great. It was a lot of fun. I learned a lot in the process. I always do. It's great to see teams of people, well actually individuals come together as teams to just start to create a term I like to call organizational improvisation, which is the ability for teams to quickly move around a problem to drive together to achieve an objective. So Jonathan and Renée, thank you very much for your time. I'm very eager as we keep on this journey. I'm sure our customers are going to be very eager to hear what we've learned, what's the good, the bad and the ugly. Yes, and stay tuned. We have more to come.
I hope you enjoyed this podcast and you certainly want to come back to the next one as we talk again to more organizations about how they're leveraging DataOps to drive value out of their data. If you want to learn more about Hitachi Vantara, track us on Twitter at @HitachiVantara, or if you want to follow me, follow me at @Schmarzo. I'm the only one on Twitter. Thanks for your time. Until next time, cheers.
Enable Policy-Based Migration of Data With NAS System Software
Read this datasheet to see how network attached storage (NAS) system software, included with Hitachi Virtual Storage Platform N series (VSP N series) and Hitachi NAS Platform (HNAS) systems, provides advanced cloud integration and intelligent tiering.
Note: Since you opted to receive updates about solutions and news from us, you will receive an email shortly where you need to confirm your data via clicking on the link. Only after positive confirmation you are registered with us.
If you are already subscribed with us you will not receive any email from us where you need to confirm your data.
"LblCustomField1": "What solution area are you wanting to discuss?",
"ApplicationModern": "Application Modernization",
"InfrastructureModern": "Infrastructure Modernization",
"DataModern": "Data Modernization",
"GlobalOption": "如果您在下方选择“是”，则表示您同意通过电子邮件接收有关 Hitachi Vantara 产品和服务的商业通讯。",
"EmailError": "Must be valid email.",
"RequiredFieldError": "This field is required."