The Exchanges

Q has funded memory-centric infrastructure companies at every level of the Berkeley data analytics deck, the badass deck. And Mike Matchett, senior analyst at Tanasia Group, which covers everything related to big data, compute, and storage. Okay, so that's the intros. To kick things off, I just have to ask, why should we care about storage? I feel like it's a dark underbelly of computing that no one really cares about.

A Look, I mean, while storage may be the underbelly, without storage, computers wouldn't work, and so, uh, it's one of the most important, you know, compute, networking, and storage are the three fundamental elements of what makes the entire internet work and makes cloud computing work, and without storage, you wouldn't have databases, and without databases, you wouldn't have big data, you wouldn't have analytics, you wouldn't have anything, because Information needs to be stored and it needs to be retrieved. So storage is hugely, hugely important. And, you know, it, the interesting thing is I think we're in a very transformative period of time here where storage is undergoing a, a bit of a renaissance, and I think it's going to transform how computing and applications work in the not too distant future.

AI assessment note: “without storage, computers wouldn't work, and so, uh, it's one of the most important”

Q What is data? That's a very existential question.

A Well, up until right now, compute data has largely been input by some human being typing on a keyboard or a database recovering a record. That's the input of a human asking the computer something that data largely has been put in there through human fingers and through some human interaction. Fast forward to right now, let's just talk about a self-driving car that has sensors. Those sensors are now, uh, inputting data that's the world around us, and so there's completely new types of data. So what is data now far exceeds the human input data. We are now collecting the world's information via sensors, and all of that needs to be processed now. And stored. It will be literally orders of magnitude and in the exact mathematical sense, orders of magnitude, more data that needs to be stored in process. So that's sort of, that's sort of .1 on what's happening. Secondly, the mobile supply chain is influencing the data center and influencing the cost curves in the data center for storage. You take a mobile phone and you take the components of that mobile phone and put it in the data center. You have a A very inexpensive storage substrate that is far less expensive than the enterprise systems that we saw in the past, and so the cost curves come way down. We will have much more in-memory data, systems that literally live in real memory, and the notion of disk drives and tape drives and ev…

AI assessment note: “So what is data now far exceeds the human input data.”

Q I've heard both of you say like, then you need to have, you still need a Salesforce. So, but do you really?

A It's sort of a head fake when, you know, the best products, the products with this unbelievably great product market fit from day zero with freemium start to take off. And the assumption is like, oh, well, look at here. We don't need a sales organization. Let's just go hire more engineers and the market will just continue to uptake. But what we see is over time, that curve starts to flatten out because the number of users and kind of the virality starts to slow up and the value that one can get out of the revenue value that one gets out of that from an organizational standpoint can never be realized in the same way as when you have a sales organization actually selling and educating the organization on the benefits of this.

AI assessment note: “that curve starts to flatten out”

Q I've heard both of you say like, then you need to have, you still need a Salesforce. So, but do you really?

A It's sort of a head fake when, you know, the best products, the products with this unbelievably great product market fit from day zero with freemium start to take off. And the assumption is like, oh, well, look at here. We don't need a sales organization. Let's just go hire more engineers and the market will just continue to uptake. But what we see is over time, that curve starts to flatten out because the number of users and kind of the virality starts to slow up and the value that one can get out of the revenue value that one gets out of that from an organizational standpoint can never be realized in the same way as when you have a sales organization actually selling and educating the organization on the benefits of this.

AI assessment note: “can never be realized in the same way as when you have a sales organization”

Q That was actually my next question, which is, to kind of close this out then, how does this change all the knowledge we have about how, how to do product management? That we've all learned through these traditional companies.

A It heightens the importance of really putting a go-to-market plan in place early on, because the natural tendency, we have been conditioned to listen to our customer, and I can tell you what a customer says when you release open source is make it easier and more functional, and I will adopt it. So let's say we now take that back to our developers, and they say, great, we're going to add, Let's take all of these features that we thought we'd go charge for and throw it into open source because that's going to increase adoption. But the defeating point there is that, well, there's no revenue anymore because the customer has taken all this stuff and it works great and they're using it everywhere, but we don't have anything else to sell. And so having a real awareness on that, and I'm not saying don't listen to customers, but I think we have to be very, very careful in terms of that. Fluidity between open source and the revenue opportunities for the company and to make sure we always understand the trade-off between adding another feature into open source versus the monetization and go to market plan that we established when we started out. And so I think it becomes important very early on where in the past it didn't really matter that much. You can kind of figure out features as you go and customers would tell us and all that stuff. And now you have to be a lot clearer and a lot mo…

AI assessment note: “It heightens the importance of really putting a go-to-market plan in place early on”

Q developers all with their different pet I mean, yes, there's a period before they coalesce around a popular single to one or two tools where they're just trying out a bunch of different stuff. And at least before you had a direct arc to go to central IT department and say, I'm going to sell you this. And that was that. So how then do you now sell to developers?

A You know, any, any time users have more choice and more flexibility, it benefits everyone. And there was a time where IT would go make a decision and Many of us have heard or have used the word shelfware many times where IT would buy something and no one would use this stuff because it was some slick sales guy who sold to some golfing partner who happened to be running the IT department. And that's how the, that's how the software got deployed. And then it got rolled out and no one would use it. Here we have the democratization of applications of developer tools through open source, through SAS that I believe Really moves the needle in terms of innovation and the best products are the ones that win. Now that doesn't mean that that's the end of the sales cycle. That's the start. Really the whole indoctrination of open source and SaaS as a starting point is a marketing vehicle to build a pipeline for an organization. And then in order for that to be sold into the, it's sort of the upside down approach. You start from the bottom. And then you sell to the top. In the old days it was sell to the top and then proliferate down. Here, the real users start with it, and then there are typically enterprise wide licenses and all of that. So you use the open source SaaS tools and services as a marketing and pipeline development, and also a way to influence innovation in your company, and th…

AI assessment note: “You start from the bottom. And then you sell to the top.”

Q How do you navigate that though when you have multiple budgets and multiple decision makers inside the enterprise, different groups or departments have different problems or itches that you're scratching, and how do you sort of up level it so that you're selling into getting the big bucks and not just sort of the incremental budget?

A I mean, I would say it all depends again on this, you know, product market sales strategy. A lot of companies that start with bottoms up only go after an individual user. And then they get enough use on individual users and propagation from the bottoms up. I call that self-serve. So there's no complexity there. There's no, you know, multiple buying centers or whatever. So it's not a foregone conclusion that you just, that that, you know, is the way to go. Now, after enough people are using the product, then you can come in with tops down and say, Hey, did you know, like everyone in your organization is already using the product? You ought to have a corporate-wide license so we can private support and all of that. So that would be an example of bottoms up and then coming in on tops down. Many other products, though, are designed to be tops down as a starting point because it may go across departments, it may be more complicated, there's security needs, whatever, where a bottoms up design just doesn't work, right? Um, in which case then you probably need to start with a More traditional, I'll say a direct sales organization. It could be an inside sales organization or direct calling in and actually getting the customer. I mean, complex sales often requires multiple buyers, multiple parts of the organization to come together. And that's a skill set that, you know, a, a, a well-hon…

AI assessment note: “You ought to have a corporate-wide license so we can private support and all of that.”

Q How do you navigate that though when you have multiple budgets and multiple decision makers inside the enterprise, different groups or departments have different problems or itches that you're scratching, and how do you sort of up level it so that you're selling into getting the big bucks and not just sort of the incremental budget?

A I mean, I would say it all depends again on this, you know, product market sales strategy. A lot of companies that start with bottoms up only go after an individual user. And then they get enough use on individual users and propagation from the bottoms up. I call that self-serve. So there's no complexity there. There's no, you know, multiple buying centers or whatever. So it's not a foregone conclusion that you just, that that, you know, is the way to go. Now, after enough people are using the product, then you can come in with tops down and say, Hey, did you know, like everyone in your organization is already using the product? You ought to have a corporate-wide license so we can private support and all of that. So that would be an example of bottoms up and then coming in on tops down. Many other products, though, are designed to be tops down as a starting point because it may go across departments, it may be more complicated, there's security needs, whatever, where a bottoms up design just doesn't work, right? Um, in which case then you probably need to start with a More traditional, I'll say a direct sales organization. It could be an inside sales organization or direct calling in and actually getting the customer. I mean, complex sales often requires multiple buyers, multiple parts of the organization to come together. And that's a skill set that, you know, a, a, a well-hon…

AI assessment note: “come in with tops down and say, Hey, did you know, like everyone in your organization”

Q What is data? That's a very existential question.

A Well, up until right now, compute data has largely been input by some human being typing on a keyboard or a database recovering a record. That's the input of a human asking the computer something that data largely has been put in there through human fingers and through some human interaction. Fast forward to right now, let's just talk about a self-driving car that has sensors. Those sensors are now, uh, inputting data that's the world around us, and so there's completely new types of data. So what is data now far exceeds the human input data. We are now collecting the world's information via sensors, and all of that needs to be processed now. And stored. It will be literally orders of magnitude and in the exact mathematical sense, orders of magnitude, more data that needs to be stored in process. So that's sort of, that's sort of .1 on what's happening. Secondly, the mobile supply chain is influencing the data center and influencing the cost curves in the data center for storage. You take a mobile phone and you take the components of that mobile phone and put it in the data center. You have a A very inexpensive storage substrate that is far less expensive than the enterprise systems that we saw in the past, and so the cost curves come way down. We will have much more in-memory data, systems that literally live in real memory, and the notion of disk drives and tape drives and ev…

AI assessment note: “We are now collecting the world's information via sensors”

Q Right. So you're saying the value is defined by the customers. Do you guys have any thoughts on how to define the value? That sort of loosey goosey vague thing of you want to make sure you're selling value.

A You know, there's a couple of things which I've used in companies that I've run is If you look at competitive products, what are they, what's the chart, you know, how much do those cost? There's an overall stack of technology, and if you're providing a certain solution, what is that stack in general? How do people, how, how have they budgeted for that? And then I always like, um, this concept of charge more than you think in there, and you can always discount back to make sure that you're not really leaving Value on the table. I didn't say money. I said value on the table, which I think is very important. You know, the thing that is also I learned along the way is customers actually like to spend money for value. It's not a problem. We all do, right? Even as consumers, it's not a problem. And to come in with the low cost, like if your value is, you know, we're lower cost or whatever, that tends to be as soft as not Standing up for the value that you're actually producing, and if you have the proper go-to-market, you have the proper product, and you have the proper positioning, then you can, you can basically get the maximum dollars that customers are willing to pay, and everyone feels like it's a very fair transaction, that the value being delivered to the customer is very reflective of the price that they pay.

AI assessment note: “If you look at competitive products, what are they... how have they budgeted for that?”

Q Right. So you're saying the value is defined by the customers. Do you guys have any thoughts on how to define the value? That sort of loosey goosey vague thing of you want to make sure you're selling value.

A You know, there's a couple of things which I've used in companies that I've run is If you look at competitive products, what are they, what's the chart, you know, how much do those cost? There's an overall stack of technology, and if you're providing a certain solution, what is that stack in general? How do people, how, how have they budgeted for that? And then I always like, um, this concept of charge more than you think in there, and you can always discount back to make sure that you're not really leaving Value on the table. I didn't say money. I said value on the table, which I think is very important. You know, the thing that is also I learned along the way is customers actually like to spend money for value. It's not a problem. We all do, right? Even as consumers, it's not a problem. And to come in with the low cost, like if your value is, you know, we're lower cost or whatever, that tends to be as soft as not Standing up for the value that you're actually producing, and if you have the proper go-to-market, you have the proper product, and you have the proper positioning, then you can, you can basically get the maximum dollars that customers are willing to pay, and everyone feels like it's a very fair transaction, that the value being delivered to the customer is very reflective of the price that they pay.

AI assessment note: “If you look at competitive products, what are they, what's the chart, you know”