Irene Lyakovetsky with SaugaTalks sat down with John Michelsen, the founder, and CPO of KristaSoft, to discuss how technology can understand people. Their conversation spanned various applications of automation, AI and technology analyzed trends to create intelligent projections about skills, careers, technologies, and the interaction of human beings with AI. Their engaging conversation was peppered with practical and relatable examples from the real world to help even beginners understand concepts like the Metaverse and automation. Here are some excerpts from their informative podcast.
We hear a lot from technical gurus that people have to get to know tech. Tech is the future. If you’re not in tech, you’re missing out, or another angle of how important it is that technology comes closer to people. We love intelligent automation that helps people. We hear a lot about automation trends for 2022. Let’s talk about what we knew before- this field is not new. But let’s also talk about shiny new technologies that propel us forward.
On The History of The Future
It’s a great time to be in the Intelligent Automation space. If you do playback over the last few years, the tech we’re using in most automation platforms is indistinguishable from the stuff we had 40 years ago. The approaches are largely record and replay of user interfaces or paint the screen, drag icons from a pallet, hit the button to generate the code. Well, we’ve been playing with that idea for a really long time. This is a watershed year, though Intelligent Automation is a very different animal. AI-led Intelligent Automation has a whole different organizing principle. And that idea is let’s have people and systems and AI collaborate to achieve outcomes. And that’s a very different model than painting the screen, hitting the button, and generating the code. It makes for a very interesting business case; it makes for a radically transformed organization. So, we’re really excited to be a part of it. And of course, that’s why the round of funding and that’s why the customer growth, we’ve had all kinds of good stuff.
On Solving the Consumption Problem
There is a problem in the Systemic Gap in Tech Delivery and Consumption. As CPO & Founder, why would one even enter this space? And what would the mission really be?
One of the most fundamental principles that we and IT have missed is this whole idea that we build stuff; it’s tough on the people we give it to. And as a response, we call them stupid or lazy. And that is not going to get us there. We are not going to deliver tech at the incredibly fast pace that we want to and continue to increase that pace, if users can’t easily consume what we’re delivering to them. So, we thought, since the industry is full of people trying to make people understand technology.
We need to make technology that understands people; if we solve that, we solve the consumption problem, and that means one can make updates daily, hourly, and no one needs a training class! We’ve had so many examples of you can’t change from system X to system Y, or you can’t add system X to my environment because I don’t understand it. I’ll need to be trained. I don’t understand the jargon. I don’t know when to use it versus other stuff. We just have to simplify this whole thing. We can make the iceberg technology, if we can keep it simple and small on the top of the iceberg, and we can have all of that tech underneath the water that no one has to worry about. That’s technology that understands people. So, we have a whole philosophy around this. It’s literally driving how we build our product and how we take it to market.
On Automation Connecting People
Automation is all about humans. When we talk about automation adoption, let’s see how it’s going to go into 2022, compared to last year. Or machines will be automating themselves with the help of AI. Then we’re going to watch them doing that for our benefit.
Not pushing as fast as we want it to, automation has been considered the way to do something without a human, and that was, we believe, a fundamental error. Businesses operate with people. And no, we don’t want human labor where a machine can do the job. And we don’t want humans making decisions that software can make. But automating a business is necessarily an integration of people, systems, and AI. It can be that you’re good at integrating systems, and you can build automation to do that. But if you’re no good at the other two, you’re not going to get there. So the trend that we like and why there’s so much demand for something like Krista, is that it’s not just about being able to stitch three systems together and make some automation among them occur.
It’s about taking people and systems, leveraging ML and NLP, and creating an outcome, which is a fantastic trend. We’ve got to move upstream in the value stream, so it’s great to save some redundant labor on data entry. That’s the classic early RPA use case, we find most customers are breaking out of that and saying, “Okay, where’s the higher value stuff? How do I interconnect people and systems in a much more meaningful way? Because then I can operate my business at machine speed, not at human speed with the queues and bottlenecks and waiting on emails, etc.” When the machine is more involved in that collaboration among people systems in AI, we get organizations that run at machine speed. And that’s the goal.
On Fixing or Simplifying Systems
Automating current processes the way your company is operating today will not propel you to digital transformation. Most automation practitioners miss this. Automating the existing way the business functions is not transforming that business at all. In fact, in many ways, we’re hard coding the way we currently do things, which makes change more difficult – the irony of all ironies. We want to empower someone to take six steps down to three. Give the machine more of the steps we want to make. We want to simplify. How often do you look at an organization and find the organization’s people and departments are essentially a reflection of the IT systems they use? There are six steps because there are six different systems involved, and we’ve taught six different people how to use those six, therefore the organization is stuck at six steps. That’s all nonsense. What we are trying to achieve is an outcome. And what is the most effective way to do that? Where machines do most of the work? And we have a whole philosophy on how that happens. Then you are transforming that business, and you’re making your people very powerful. And you’re making the machines very busy. And that’s the idea: Make the machine do the work.
How do you connect in the Metaverse?
This whole notion of Intelligent Automation making businesses function as a collaboration among people systems and AI is exactly what the Metaverse is. The Metaverse is a presentation of how we collaborate. You might do it very crudely with textual stuff in a chatbot. You might do it in a much richer way with pure voice in a fully realized metaverse. Or, you’re doing it as an avatar inside of a world where you’re interacting with tech that is AI-powered, and it’s able to interact with you in a much more human way. But that is the progression, and these are the steps involved. We can’t skip those middle steps of getting ourselves from what is right now, think about it this way. It’s so true in our industry that we either have collaboration tools, or we have integration automation tools, or we have AI kits. We need something that is equally all three that powers a Metaverse and that’s where Intelligent Automation takes us. And that’s where the work that we do is along that path.
How Will Customer Experiences Improve?
We have to improve the way people interact with a variety of things in our real world without the need to go to training. We need a common way to interact with technology. This is all about conversation. At the end of the day, we didn’t go to training class in order to talk to each other. And you and I can converse on a variety of topics. If you know the domain, and I know the domain, we’re going to have a great conversation, we’re going to achieve all of what we would want to, and that’s fantastic, right? Today’s applications and automation platforms are not conversational. And therefore, they use jargon and odd ways of doing things. They will put it this way. You don’t send your salespeople to sales training, of course, some do, most have to send them to CRM software training. But if the CRM software was as conversational as a human, there goes the training requirement, right? Like you and I talking about a sales effort you and I read, we would never think of, right? We don’t need training to go from one WhatsApp group to another group. We don’t need a training class to better understand the other group. It’s just not that way. Right?
So tech that understands people is conversational. And once we break that barrier, you know, humans can embrace tons of change, if it feels like more of the same conversation in a variety of topics is just more of the same. So we can continuously change the process, change the steps even change the rules. No one has to be pre-aware of that or read the playbook because the conversation just flows differently this time than it did the last. No one gets confused if the conversation flows differently from the last conversation. So this is our this is how humans embrace change through the notion of iterative or naturally evolving conversation. That’s how our systems need to work. That’s how AI-driven automation must work. And in fact, it’s how Metaverse has to work. We can’t pre-wire all of the ways humans will interact in Metaverse because they need to evolve how human conversation does. So long story short, conversation is the heart of this. And I don’t mean a chatbot or voice bot on a phone. I mean, literally, the composition of how we execute a process itself needs to be a conversation among people, systems, and AI.
On the New Generation Workforce
New generations starting their careers now live in a completely different reality. They are used to instantaneous feedback, so, if a job pushes them into the old industrial way of working like waterfall models, all this long-term planning and training and stuff we are going to lose them. We’re losing this young, bright generation. We need technology that understands people better than people.
Years ago, we were all talking about the consumerization of IT. But at some point, IT said, Hey, we’re not up for that. As a result, it just sort of died out. Well, the problem is, the consumers are still into it. And that, younger generation, they’re not tolerant of this stuff. It tech doesn’t understand how you work, if it’s not as simple to operate as a typical mobile app running on their, on their phone, it just won’t happen. It’s odd because we were raised in a generation, where we understood that this was complicated. We have to figure it out. We must read the manuals; we must go to class. It’s over our heads, and we’re just going to have to deal with it. There’s no such expectation in younger generations, and that really is the bar. And by the way, the answer is not to make them conform.
Our organizations operate at a huge disadvantage. After all, we were willing to deal with poor tech, right? Tech, that doesn’t understand us that we have to figure out how to understand makes things difficult. When we think about the vast numbers of businesses with large numbers of low-tech people who have to deal with high-tech IT nonsense, it gives me a headache. That has to stop. Because of the cost of changing employees, the cost of them moving from one part of the business to the other, all of those things, changing any of that stuff is such a large human labor effort. The way that the younger generations think is, that’s all nonsense. I’m not willing to do that. We meet that bar, and our organizations are actually better for it.
On Empathy
For these aforementioned skills, we will need so much more empathy than we have right now. So, humans will have to evolve to get us to a better place. But the good news is that we will not have to be essentially digging ditches with a spoon, which is what it feels like. So often we do in a business these days that we don’t even use decent tools, right? It’s frustrating when you think about how the Industrial Revolution reduced the amount of physical labor required to accomplish a significant amount. We’re in the computer industry, let’s face it, we’re still behind in terms of that type of evolution.
The number of people required to get a job done inside the business is still too high. So that number comes down. Machines do more of the work. The machine knows the steps, knows the rules, knows how to talk to everybody else about it, systems and people. And when that occurs, that part of our lives is much simpler. We have to now have more creative thinking, more insightful understanding, more empathy. A chief financial officer of a huge bank described this to me, and it was brilliant: he said, “My organization right now today spends 80% of its time doing things and 20% of its time thinking. Transformation for me is 80% of my people’s time thinking and 20% doing.” And that is a fantastic encapsulation of what machines are supposed to do for us, right? Not his goals, not half the people in his organization. His goal is to transform the activities they perform to more thinking and writing. He means empathy, creativity, planning, and finding new paths by thinking. Those are things we can do and add tremendous value. Let the machines do the rest.
On Human Evolution & AI
Evolutionarily, we were not created to read tons of volumes of text. We are not good at processing 5000 emails a day. We’re not good at it.
How can we improve?
The studies are all there. We can borrow an example from manufacturing: when a human does the same task 1000 times or 10,000 times, they get worse at the task. When a machine does that task, if you had our product with its insight and AI capabilities, it gets better at 1000. It gets even better at 10,000. We’re just doing the work that we should be giving the machine. We feel like, “Oh my goodness, 5000 emails, there’s just too much; there’s just too much we want to do with our lives that doesn’t have to do with reading so many emails.” When this is a real-world use case, we have customers who have vast numbers of documents, they could be contracts, it could be policies, it could be whatever, right. Regulations in government. We have people who are now deploying our software to read all of these documents.
Krista knows all of that content. Then, people just ask Krista a question. You don’t have to know those 1000s of pages. Whenever you need to know something from that knowledge base, Krista will answer the question. What an incredibly different world we live in, that instead of having to be so nervous about having to know everything about all of that content, we can just have a machine know all that stuff. And then ask what you need to know, whenever you need to know.
What skills are valuable today?
It’s anything in the creative realm. Planning is a big one, too. So people still, and hopefully always, will buy from people. The interfacing of people is incredibly important. There are a ton of skills that we still must have. The good news is we’ll never be doing the same thing a third or fourth time. We just won’t have to. We will do something once and say, “Hey”, I need my digital system to do that. I need my whatever, depending on the context, what kind of AI companion you have, and whether that’s a business context or personal. But in both of those, it will not be necessary for you to do the same thing the third time. The drive for humanity will be to increase its own evolution. In fact, it’s been it was a part of our thinking. And this is unfortunate, but it’s true. Moore’s curve, basically tells us that machines evolve at an incredibly fast pace and exponentially.
Humans evolved over eons. Well, how can those things work together? Well, that was part of what gave us the motivation, well, the machine has to do has to figure it out. Because people are going to take eons, machines can do it can figure it out much faster than people can. Our evolution has to start in increasing within our minds, our ability to be creative; we must think about a future. There’s so much capability in the technology, we have to think bigger about what we can do with technology. Our job is to figure out what machines can do better for us.
On Self-Serving IT
Business and IT will continue to merge. They will, and they have to. Let’s go back to the whole philosophy around what do we need to do to make this a completely different world in terms of Intelligent Automation? The consumption side, “technology understands people,” was one of the two constraints we had to solve the other one. The second challenge is that IT cannot keep up with the mouth of the business. It’s never going to. It’s unreasonable to think that I can program as fast as my business partners can ask me to do things- they can always ask faster than I can build. Even if I have ten times the number of people like can never keep up.
The nature of how we deliver IT services has got to separate. Here’s a silly analogy, but it works: when we got word processors into the business, it was WordPerfect, it was Microsoft Word and these guys, if you go back long enough guys, I used WordStar. Word processors were IT giving the business the ability to create their own documents and print them on their own printers.
Today, we have automation tools in IT, and we say, “hey, business, tell me all the things you want to automate.” I’ll write it all for you. That would be like saying, I’ve got word, you tell me the document, and I’ll write it in IT for you, and I’ll give it back to you. We would never do that. We have to self-serve our automation capabilities. Just like we self-serve, writing an email, writing a Word document, creating a spreadsheet.
Automating the steps and rules and processes and how we want outcomes design has got to be equally a self-service activity for the business person to do, not for IT. IT definitely owns all those systems of record, right. But that’s not what we’re talking about, here. We’re talking about the things that cross systems and people and AI, that needs to be self-service as a part of the business, just like writing a Word doc or creating a spreadsheet because, if it was signed up for doing all of that, we’d never get a Word doc done, would we? And, it’s no fault of IT at its best, it just cannot keep up. And, the change is required.
Every time you see something, every time IT gives a delivery of an app to its business partner, the business partner gives them 50 more things to do with that app, right? The same thing would be true the Word document, it’s not a different problem. It’s just that we solved it the wrong way. And, now the challenge was, IT didn’t have the technology to enable self-service for automation. We are reaching that point. So now it is time to empower self-service of automation. Then, the business can operate at its own speed.
On how change enables a better place and more free time
I think it’s natural to be nervous or concerned about change. That’s a fundamental human thing. That’s understandable. In most cases, those changes, and even tech changes, benefit everyone. Even though word processors phased out typewriters, or, typesetters were going away, and desktop publishing was coming in. Or, computers were coming in, and all of the people who do math for a living will be out of work. We could just keep going back in time and seeing this over and over again. But our world is actually all the better for it. All the better for it. We just have to recognize it’s an evolution toward a better place.
Future generations, they will have more free time. But I don’t call it free. I call it time to invent better. There are so many great examples of this. Just using GPS navigation software on my phone or in my car. When I was a kid, my dad took a week to plan our trip. He was drawing in a highlighter on a series of maps in order to get us across the country. And today, I would literally just say, “hey, Siri I want to drive to Orlando, Florida,” and I’m on my way. The amount of time that gives us adds days to our vacation. Just the ability to do that. In a business context, we want the same thing. We want outcomes tremendously faster. We want the machine to do more of the work make it we’re literally using GPS software that draws the highlight for us. Instead of dad spending several nights doing the highlights, and of course, if he gets it wrong, he is scratching that one and doing it differently.
An Optimistic End-Note
For this year we get higher level than task automation. We’re getting more and more to outcomes. We’re focused on the human aspect of what automations have to be. It’s not about separating people and systems. It’s actually when they collaborate that we get great business outcomes and where the more interesting value value proposition is.
“Where do we go beyond 2022?”
I’m a Star Trek geek. I want to be talking to the computer on Star Trek. I don’t want to be dealing with how many systems are behind it. I want to be able to say this is what my goal is and for the machine to figure it out. If there is something I need to hear, I want the machine to tell me. I don’t want to constantly check my emails or look at screens. That’s the world we need to be going to. We take a nice big step closer to that in 2022.
What is the Future of RPA?
Prev post
