The Senior Competitive Intelligence Analyst at Hitachi Vantara is an experienced hands-on director, manager and presales solutions engineer with over 30 years of experience in information technology, big data, department management, sales, large infrastructure & data center project management, network design & engineering, audio/visual system design, and security system implementation.
Welcome to this Studio NEXT podcast. I'm your host, Jeremy Brisiel, and we have a great conversation on tap today. Especially if you like competitive intelligence. I don't know how to not say that phrase that way. I know that I'm supposed to just say it as a normal way, but I can't say. Gentlemen, if you could, since I don't want to mess names up or titles, could you tell me who we're talking to today? Tell the audience.
Mark Farrant, Master Research Analyst, Global Competitive & Market Intelligence, Hitachi Vantara:
Okay. My name is Mark Farrant. I'm a Master Research Analyst with Competitive and Market Intelligence.
I know. I'm Chuck Kramer. I'm a Senior Competitive Intelligence Analyst for the data integration, big data and analytics space.
So, in case folks who are listening, you don't get it. We're talking to some really bright guys today about the overall landscape. Don't roll your eyes. This is an audio podcast. It's fantastic that you guys have a broad perspective on not just Hitachi, but on the industry and on trends and on the overwhelming way that things are tracking. So, I want to talk about those things.
I mean, in general, we tend to know more about the competitors' products than we do in some instances our own. But you know, as our primary customer is field sales, we have to give them the broad strokes of what our competition is doing. And some of our competitors have multiple products in multiple different stacks. So you know, what we faced, especially over the past 12 months, is we've been fighting NVMe. Our competitors have it and now they have NVMe over fabric and SCM. And if you don't know what those mean, then go out and look at them up. But with the Hitachi Virtual Storage Platform 5,000 series, with just NVMe , we've solved that particular issue. We have the fastest row in the world. Now when we go over fabric and with SCM, who knows what the future will hold.
Oh, that's great. You touched on so many of the great topics we want to dive down into before we get much further into it. For those that don't understand exactly what the competitive intelligence arm does or what you guys are doing, day to day, what's that look like?
Well, a lot of what we do is a somewhat reactive. So, our sales team, our field teams will have questions. Primarily, they'll be up against a specific competitor, with a specific use case and they need to know how to position our product. Because, to be honest, some of our competitors do things better than we do and we do things better than them in other ways.
What we need to do is understand, kind of what the use case is and provide those high-level understandings of, okay, this is what we do better, this is what our strong points are. This is positioning statements against what they may be saying about us and how to utilize our strong capabilities against some of their capabilities that may not measure up to what we're doing. Additionally, if there is a capability that they have working with our sales team to maybe reposition the conversation towards our strengths, and if the conversation with the customer can be a spent guiding them to be able to have that intelligent conversation. The ultimate goal, I think though, is to make our field teams more intelligent and when they're sitting in front of a customer to be able to talk about the market and the entire market and be that consultative type of a person with them. So that, when the customer has a question about, "How do you solve for this?" they sound like the subject matter expert, knowing full well what the competitive landscape looks like and being able to position what our capabilities are to the customer. So that the goal is for us to be able to get our products in and solve problems for Hitachi's customers.
Right. That all weaves together. You've touched on it already Mark, but let's dig down into it a little bit more. And you mentioned it Chuck, the competitive landscape. What does it look like? Where are we at right now? What do we see for Hitachi Vantara?
So, in the past, our customers have always perceived us as an engineering company. We've always brought product to market that has shown our engineering heritage. It may not be leading edge or bleeding edge, but when we have come to market and we are fully tested in those environments so that we can turn round so that somebody like Brian or Jonathan Martin can stand up and say, we can make these eight statements about our product. It is the fastest. It provides this extra type of capability, more storage support better, better, better, faster, more at the end of the day. Those are bold statements that are based on our engineering heritage. But more importantly — so that was just the VSP 5,000 series — more importantly, what was discussed in the Lumada Data Services. Now, that brings together lots of different product which we can sell, but to Chuck's point enables our sales teams to converse in a more strategic fashion with our customers. So that they're not just saying, okay, here's a box, we want to sell you the box, but rather understanding the customer's business. And then with things like Lumada Data Services, a data optimizer for Hadoop, edge manufacturing insights, those are all core to some of the fundamental aspects of Hitachi Vantara, Hitachi as a whole and especially with things like Hitachi consulting, where they bring that more consultative ability to the market. Again, solving business problems with a broad spectrum of technologies and capabilities.
You're talking about so many things there and many of the advantages that Hitachi brings across the board in so many ways, Chuck, the competitive landscape from your point of view, what does it look like for us? And then to follow up on Mark's thing, what does that shift from sort of box to strategy? How do you see that playing out?
Well, I use a slide when I do enablement to our sales teams and talk about the competitive landscape and it literally has logos of probably 500 different companies when we talk about the competitive landscape. And that depends on what you're doing in the area that I focus on: you know, data integration, analytics, big data — that environment. If you're integrating data loading data, you've got a set of 20 different competitors. I mean, there's actually, hundreds if you're talking about data preparation before you get to analytics and then the actual analytics, where that data is now insightful and people can make informed decisions and utilize that data, make it actionable.
We have a broad group of competitors because there are individuals that do each one of those steps along that data pipeline. Right. Now when we start bringing in some of the broader capabilities that we're talking about with the entire Lumada ecosystem that we're doing, you're now bringing in different vendors that may be in my realm, you know, the big data space weren't even considered to be a competitors. So, managing this, and one of the things Mark and I have been doing, we've been teamed up with our teams that are working on the project tapestry stuff, which we're going to announce here at NEXT is trying to define, okay, who are our key competitors? And that's very difficult to do when you're offering as many capabilities that we've got underneath this umbrella with Hitachi right now. So, it's quite an expansive and at times I don't, it is overwhelming to be able to say, okay, who's our competitor? Well, what are you trying to do? Well, we're trying to solve this problem for the customer. Okay, well in that case, your competitors might be these three entities or it might be this and a cloud based solution, and those kinds of things. And the next thing may be, okay, what are we doing? You know, well, we also have this use case. Okay, well hold on. And now that may be a different set of competitors that we have to put together. And then we have to create the positioning around, okay, why, us as a solution. So the good news is, and everything I've just described is what we're, bringing to market: this Lumada ecosystem and intelligent data operations that we're coming out with. Nobody's really doing everything that we're doing. So, as far as having a specific competitor that we can poke on the nose and say, this is our key competitor there: There really isn't one. We are coming out with some game- changing capabilities that it typically takes a solution to do. So, you need five or six different types of hardware, software, services, capabilities to be able to deliver what we're starting to deliver with some of the announcements, some of the capabilities in the Lumada suite.
It's what our competition in general terms can't do. So, to go back to Chuck's point, if I'm going up against a particular use case or a particular capability, in some instances we have to go back and say, who are you competing against? Because if you're going against competitor A or mentioning any names to preserve the innocence. A is tough though. Z is really bad because nobody understands what I'm saying at that point. If we have a competitor and it's going up against a data optimizer for dupes, say which we announced today, building that landscape document, those strategies, those silver bullets, the strengths, the vulnerabilities, and you know, the core things that sales guys are looking for or sales people are looking for. Sorry. That's generally the easy approach. Cause sometimes as Chuck alluded to, it's like, okay, I've got a hundred competitors in this one use case and then when we start branching out. A lot of what we're seeing, especially with Lumada Data services is the ability to strategically look at what we're doing and then go to market with a coherent story versus what all of our competition has to do. This is actually, okay well I'm going to have to do this for myself, third-party for something else, a partner for something else. What makes this really exciting and from my time in IT, which is expensive, is that we start bringing in both our partner communities and our service communities. So, this becomes an overall chic solution for ourselves. People who support Hitachi Vantara and also for our partners.
And that's, you started talking about that streamlining in that, which creates agility, which creates response time, which creates an ability to listen to customers in such a deeper way because you can respond more agilely. And for an organization of a certain size and age that isn't always the case. And that is exciting. That is exciting to see that transformation happen.
But the beauty about that though is that once we figured that secret sauce out, that which then becomes our Kung Fu is: Regardless of the customer, regardless of the industry that they working, the vertical they work in and also their size, we have scalable solutions to meet those needs. So, whether for a global 1000 customer or for a mom and pop operation in a local community, we still have those feature function capabilities because we've already figured the hard stuff out, which is getting all that stuff to work together in a more coherent manner.
That's remarkable in that way. And I, before we say goodbye as I could talk about this for a long, long, long, long time, as you can see both as well, but we lose the room in a little while. So we've got to get out of here. Oh no, that's not true. But I do want to talk before we say goodbye about data, it's always remarkable to have these conversations with a competitive marketing intelligence research, but also to the solutions that are all so data-driven that you talked about special sauce. But in a way drinking your own champagne is a fine way to get things done. It's also a good way to have a nice party. Chuck, data is a big part of the way to find the path to these solutions. How has that played out? How do you see it in the future being part of the strategy?
Well, as everyone's aware, data is not diminishing. Data is constantly growing. We have our watches that we're wearing, our phones, our other devices that are constantly generating data. And that's just from a consumer standpoint. Now, if we start talking about manufacturing, healthcare, all of the systems that are out there generating data and those edge devices, what we're going to be doing is aggregating all of these different data types. And you know, there's structured data, which is your standard spreadsheet data. Things that fit into nice columns and rows. Then there's a semi-structured data, which you can view as a tweet or some social media that has some structure. And then there's unstructured data like VI video. And where you're going to get the most value out of your data is when you have solutions that can gather that data at the edge with the capabilities we have with Hitachi. Take that data, blend it, normalize it and then be able to apply analytics to that, to get those actionable insights from that data. That's where the value comes in because everybody can gather data and you've heard the term, you get data lakes and you've got data swamps. I mean a couple of years ago it was like, gather all your data into one place. Now you've got it aggregated and you can go apply analytics to it and do all of this. Well, if you just throw all kinds of stuff into this, this data lake, it becomes a swamp because you don't necessarily know. You've got to have governance, you've got to have rules. You've got to have different capabilities around that and some of the AI technologies that we've come up with to be able to take that data, curate that data, prepare it for analytics before you land it into a data lake. So, now when you apply your analytics to it or pull specific aspects of that data out, you can truly derive insights from it because the data is ready to be analyzed. And you can now, if you're in a retail environment or whatever, you can monetize that data. If you're utilizing it for healthcare, you can now apply that to research and save lives because you've got all this wealth of data and now you're able to actually utilize it in a way that's meaningful to derive those insights.
Do things more efficiently, speak time to market for new products, build new, better understandings, right? That, then tie into some of our other initiatives around, you know, social innovation and what the digital business means. So, for us, who all began guys who thrived on spinning disk, or spinning rust as it's referred to occasionally, it's a totally different way of thinking. And strategically that's much more interesting, especially when we start looking at the benefit that we derive from providing these types of solutions to our customers. But, also looking at what social impact can be as well. I mean even if it's things like public safety, some of the more esoteric things that we get involved in that we can't actually talk about, that's all next-generation stuff. Cause that's another one of our outputs: It's inputs into strategically developing what's happening in the next three and five, seven years.
It's totally true.
So, at the end of the day it's like what benefit can we provide the customer: It's going to be where we sell product, but it's got to be products, services, capabilities, solutions that make sense for their business. Because again, driving intelligent insight from their data makes them more agile and also makes our day-to-day lives much more interesting 'cause we're having to think about things in a completely different way. That's where we're seeing in the competitive intelligence perspective, this blending of capabilities. You know, Chuck doing the analytic side, me understanding the hardware, some of the strategic stuff.
One final point as we move into Lumada Data Services, we see that it's that amalgamation of capabilities that basically could be the grand future for Hitachi Vantara.
Well, I think the future is in very good hands. You guys have shared a lot of the insights, to see where the future is laid out, to go from box to strategy, in a very short way. Chuck and Mark, thanks for being with us. It was a great conversation. I look forward to wrapping it up again and having another conversation just like this, but even with more interesting and fascinating data and insights in 2020.
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