The Mainframe’s Renaissance – A Conversation with Allan Zander

 

Allan:  Thanks Reg. So I'm the CEO here at DataKinetics. The company has been around for a little bit and we're-it's pretty exciting what I am starting to see really happen in the mainframe space.  You know we are busier than we have been in a long time.  I'm very proud to say that we've had three record years of growth and we are about to start our fourth year.  A lot of that has to do with I think a little bit of a rebirth of the mainframe that I'm seeing from things like block chain to how people are using big data to how retailers are starting to do things, to personalize their journey with their customers to advance that we are seeing in health care. There's a lot that is really going on and there's a lot that the Fortune 500 is really starting to do to embrace the mainframe and make it play an even bigger role in the revenue-generating component of it that we've seen in the past.
 

Reg: Now you've hit on a couple of things that I think is really interesting because you know we as mainframers are different from other computer nerds if I may is that we are in that-we are about business.  You know I think a lot of other computer platforms are sort of about consumer electronics and stuff like that but the mainframe really does make the world, you know the business world run. I know you've been involved in that for quite awhile especially with cool products like tableBASE, which has really become a key part of big data right from the earliest days. Maybe if you could give us a sense of how that has all happened.
 

Allan:  I love the way you just talked about that.  That is something that we spent a lot of time talking about here but I think it is an easy thing for people to forget.  You know in the past 40 years that we've been around, we've seen a tremendous change in the way applications have evolved, and in some cases, we've even played a part in that.  You know things like big data and Cloud computing have been around for a long time and they've been around in different concepts within mainframe application programming and mainframe application architectures because that plays a big role in what I think you just said so elegantly.  Applications that are on the mainframe tend to be applications that create revenue for fundamental large Fortune 500 companies so you know by nature now, they tend to be complex.  They tend to be a little bit more evolved in what they are doing. They tend to have a little bit more associated with them so when you start talking about technologies like block chain, big data, or analytics and things like that, naturally, what is driving innovation in those areas is how do we increase our wallet share with our customers.  How do we become more competitive?  How do we use IUT as you know a competitive weapon to help us differentiate ourselves from the past?  We see that all the time.  I'm not bragging but that is probably why you know the #1 and the #2 in every major vertical that we have use our products.  They're the #1 and the #2 because of how they use IT and how they actually implement technologies like tableBASE or in memory acceleration or analytics or data replication to actually help them increase earnings, increase their value to their shareholders or ultimately increase revenue.  Naturally, they are embracing technologies like what we are seeing about now and it's such a fun time to actually be a mainframer.
 

Reg: Now I understand you play in a lot of different verticals.  You know as I think back to the verticals that really invented the mainframe whether you are talking government or military, academia, big business, banks and finance but one of the ones that has really become more and more important to the mainframe and I think it was always but we've become more aware of it and you referred to it is healthcare.  I understand that is something you guys make a particular contribution too.

Allan: Absolutely right.  You know a lot of the time that sometimes people forget about that is really big computing challenges is how you process different business rules as transactions in particular carry on and transactions is really where we tend to focus our space and what we do.   As you add more and more intelligence to a transaction or more different ways that you can actually compute a rule that will ultimately complete a transaction. Naturally, the complexity of that will rise and health care just happens to be a great example of that.  You know from how someone used to submit an expense that would ultimately be reimbursed in a health care facility 15 years ago is very different from ultimately what happens today. There are so many more rules.  There are so many more way that you can look at it. There are so many different data points that are touched along the way so yeah, as a matter of fact healthcare is one of our strongest verticals.  We play in there really well.  Because of that, we made some really good connections and I'm pretty proud to say two years ago, we actually launched a start up in the retail sector based on all the industry connections that we had and what we saw going.  That start up is getting a little bit off the ground.  We are actually incubating our second start up here at DataKinetics and it is going to have something to do with the healthcare space.  We're pretty excited about that.
 

Reg: Cool.  Now I think you referred to the term mainframe renaissance and of course you guy have again been there to see so much of the history of the mainframe. I understand you sort of have a vision for how that all fits into what is going to happen next in the mainframe.  Maybe if you could kind of draw a picture of that journey for us.
 

Allan: Yeah.  We really kind of see that transactional networks that we have are going to grow a lot in their sophistication.  That is going to happen on not only the front end of what we ultimately see going on where maybe you can actually start to add a few more analytics associated with things because ultimately if you want to do something with big data, you need to understand what are the questions you want to ask so you can actually attach that metadata that you need to your transactions to start to mine for that data intelligence that you need.  Start to look now if you are in the financial network, you are probably going to want to start to have ways where yeah, maybe your distributed world intersects and maybe pulls data from your mainframe side of the house that you have to make that more easily accessible and make those applications become more alive with what you have because maybe there will be a disruptive technology that is going to be coming down the field for you and it could be something like block chain for example. We don't want our customers to be scared when you start talking about all of these things.  You know that could be something like what I just described as seemingly huge or seemingly monumental but it's not.  The reason why is it's not is a lot of those concepts and a lot of those architectural approaches which you would need to solve those problems if you will have actually been around for a very long time and I can say that with a lot of confidence.  You know we have probably seen the most complex and the most business technical applications that are out there you know from things that you might see in the industry from insurance to finance to verticals to government to travel and tourism to you know  whatever it is.  Ultimately, it is our belief that some of the more cost conscious applications like how you process payroll for example or you know how you look at email or things like that, those applications aren't on the mainframe anymore. They are off on a system like a distributed system where you need to look at costs and you need to control costs from an operational point of view but when you start to look at it from a revenue perspective, we want to make it easier from our customers to not worry about how you integrate some of the complex code that they've had and that they have running that is so core to their business to make it more accessible for them to actually access the data that they need while taking into account the fact that since this is creating revenue that they can go to bed at night knowing full well that a company like DataKinetics has expertise, has capabilities here, has the tools, the products, you know the ecosystem and the customer contacts to pull things together to make great solutions happen because that is really what we are pretty passionate about here is making computing work at the best possible price at the best possible transactional loads so that your business grows and thrives.
 

Reg:  Excellent.  Well thank you very much Allan.  This has been most interesting.  Any you know brief closing thought just before we finish up this podcast?
 

Allan: Yeah, you know I'm-well one thing because you kind of tipped on it a little bit before. I really would kind of wish the world would stop at times thinking about the mainframe as a "legacy applications.”  It is really not legacy.  The fact that the mainframe has been around for a long time does not make it a legacy platform.  The fact that the mainframe has been around for a long time makes it a tried, true, trusted, reliable, scalable platform and if you are a business that has a high transactional volume for what you need, you've got the most flexibility, the best price performance for what you have and the best options available to you is a platform like that.  You know pick the best platform for the job that you have in mind and that is really where I think the mainframe comes into play.
 

Reg: Cool.  Well thank you very much Allan. This has been most interesting.
 

Allan: My pleasure Reg.  Thanks very much for calling.
 

Reg: You bet.