Phil Fersht [00:24]
Thank you, Mark. Avinash, great to see you again. So let’s start by talking about process intelligence. Why is it such a topical area at the moment? Why should people care?
Avinash Misra [00:38]
First of all, a pleasure to be with you again, on a relatively cooler day in Dallas, Texas today — it’s been 100-plus throughout. To your question on why people should care, I think what is happening today is that there’s an increasing realization that the inputs we’re making into making things better, from an operational perspective and from a transformation perspective, are not giving the results that they’re supposed to. And there’s the realization that there is work that we are doing in silos, and there are inputs that we are giving to those silos — automation is a good example. But there’s a realization that we must understand the end-to-end and use that knowledge to be able to optimize, to be able to transform these business processes. So the word process intelligence, in some sense, is a proxy for this end-to-end understanding, this holistic understanding of the way an organization works. Now, hidden in all of this is also, in some sense, the cause and effect. For a long time now, the arguments for these kinds of things have been all around efficiency. However, there’s now a greater realization that it’s not just the efficiency but the effectiveness of these processes, of the work that an organization does. And so companies such as ourselves — and we believe that we are at the forefront of this process intelligence revolution — are trying to find the most non-intrusive, the fastest ways to rapidly understand work as it happens at the edge of work, where humans and digital systems come together. That’s one part: understanding that. And then, secondly, being able to link that to outcomes — being able to understand, based on what’s happening or what we did, how it actually worked out by way of outcomes. So that is the overall realm of process intelligence, and the world is moving more and more towards this cause-effect understanding, and we use the word process intelligence for it.
Phil Fersht [02:44]
OK. And we’ve seen this evolution of task mining and process mining and process discovery, and now process intelligence, which my analysts keep telling me is the coming together of mining and discovery. But what is it exactly? If you had to explain it to your mom and dad, or to someone down in a wine bar, what is it?
Avinash Misra [03:10]
At the heart of it, it is observation of human-digital interactions — and not just their actions but also the context in which those actions are taking place. That context comes from where in the process that action is, where a human is inserting themselves, and on what application. Context also comes from what’s the data on those applications in the moment, and before and after, and all of this data put together tells us truly, from an end-to-end perspective, how work actually happened. Now, humans are reliably unreliable in repeating back to someone else how something happened, so observation is the only way to get rid of the bias that exists in people’s minds and in organizations — because organizations tend to do things that feel right, or tend to act on things that feel right. So how do you remove all of this? The act of observation clarifies, and repeated observation over a large set clarifies further. So I would say that ours is a technology that brings together all of the interactions that humans have with digital systems, the context and the data at the point of interaction, and uses that to build out the totality of work that an organization does. That’s the first part. The second part is that if you have a digital twin, it is still not complete of what I just described. It is not complete because you’re still not linking it to the effects of this work that you’ve done. And so the digital twin, or the most advanced process intelligence framework, would also take into account what these actions end up meaning — let’s say, to cost, to effectiveness, to customer satisfaction, to many of these things that organizations want to control. And the loop-back of this entire thing put together is what I call process intelligence.
Phil Fersht [05:08]
So we’re connecting people, data, and processes to drive enterprise transformation.
Avinash Misra [05:15]
Indeed, and that’s a smarter way of saying that. But I still want to add outcomes to this. I think there’s far less attention being paid to outcomes. We’re focusing on the efficiency argument and not the effectiveness argument. Once you add the effectiveness argument to this equation, then the loop gets complete.
Phil Fersht [05:34]
OK. So what’s the link between… We came through 10 years of RPA — we’ve got our 10th anniversary of RPA coming up in a couple of months — and the evolution from fixing stuff that needed fixing to this much more advanced thinking around discovering, linking, and connecting humans and digital. What is the link between RPA and process intelligence, and where do you see this going next?
Avinash Misra [06:02]
I think the link… in fact, if I look back on the founding of Skan, and many of the companies in a similar light — all of us… I have a big background in RPA. In fact, I used to work for a very large BPM player, and my co-founder and I were in charge of many of those RPA initiatives there. And all the failures we had on the RPA side, or the challenges we had on the RPA side, we ultimately attributed to not knowing enough about the nuances, permutations, and exceptions in the work that was happening, and not having an end-to-end understanding of work. Most of our RPA efforts, and even to some extent even today, are focused on silos, on the task. So while you might optimize that task, you still are left with many such tasks put together which are still unoptimized. Your entire output is then premised on your weakest link in that chain of tasks. So one of the things that I think is the evolution that is happening is to move from — and in some sense you’ve already spoken about this in your Horizon 2, with the OneOffice idea — moving from this task orientation to the end-to-end understanding of business processes, and the work that they do and the outcomes that they generate. So I think that’s the evolution that is happening. And in fact, I’ll be the first one to say that it was RPA that shone up, in a cold, harsh light of immediacy, the problem — which is that we truly do not understand end-to-end work; let alone understanding the end-to-end work, we still don’t understand the tasks as well. So as a result, companies such as ourselves were born to first understand the task, and then we began to realize very quickly that if you understand the task and you understand end-to-end, then there’s greater benefit beyond automation. It goes more towards the operational, and how people are running those things. So that insight is valuable to automation, but even more valuable to an operational leader, to a transformational leader who’s looking at work end-to-end and at the outcomes they’re producing through those processes.
Phil Fersht [08:16]
Are you seeing a much stronger involvement from the CTO and the CIO in automations and process intelligence now, within the clients that you talk to?
Avinash Misra [08:27]
Yes, we are. At the same time, I also believe that, at least in our customer base, we have a very strong relationship between the CTO/CIO and the line-of-business owners, and we’ve seen the best outcomes come together when both those stakeholders are involved. At the same time, I think increasingly now the CIOs and CTOs are much better informed than they were about two years ago on the notion of understanding work, on the notion of mapping work, and on their choices around process intelligence and so on and so forth. I remember two years ago, people used to say, you observe screens to do what? To now saying, well, how is this different from other approaches — you can observe the screen, but can you also connect it to back-end data, and so on and so forth? And our technology has also evolved, by the way. We are at the sweet spot in the intersection of taking the best of what back-end data says without actually going into back-end data, by looking at data on the screen and so on. So there is, I would say, an evolution that is happening in our space as well.
Phil Fersht [09:36]
Absolutely. And I think the involvement of the CTO in particular is very strong, because, A, they’re excited about automations and doing things better, and B, they know how to start projects, get them done, and finish projects. And I think that was the big struggle pre-pandemic, where a lot of lines-of-business leaders tried to drive a lot of these process initiatives, and they tended to hit a lot of brick walls, a lot of politics. And if you didn’t have IT on board and building out an industrialized platform at scale, things tended to fail. So I do feel the involvement of IT with the business is where these things are starting to take shape. So tell me a bit about your company, Skan. You’ve raised some money, you’ve made some noise in the market. There’s obviously been a bit of a crash in the tech market as well. Where are you in your evolution, and what do you think is going to happen in this whole process tech industry?
Avinash Misra [10:35]
I think, first of all, evolution is continuous, and in some sense, when markets crash, it gives companies the time — especially the people who have a strong thesis — and the customers the time to really sit down and look at the problem with a certain pause and a certain amount of focus. So I think what’s happening now to all the venture-led companies is that they are now fundamentally looking at their space in a much deeper way, and that gives us a lot of focus on saying, OK, what’s the market, where are we going, and so on — as opposed to a very, very hyper-growth market where all you’re chasing is logos and revenue. So that, number one, gives us the pause. Number two, as you said, there’s maturity that is happening — technology is getting involved, business is getting involved, and new use cases are emerging. And even as I speak, Phil, it surprises even us, who think about this day in, day out, how customers, when given the same data about how their work is happening, how the business process is running, how the end-to-end process looks, correlate it back to the kind of problems that historically they’ve always wanted to solve but did not have an answer for. Now, these problems go beyond just, hey, I want to automate. These problems go into the efficiency, the efficacy, the outcome orientation of what these processes were producing. So the root-cause analysis, the cause-effect thing, is becoming stronger. So our industry ultimately will not be about process intelligence; it will be the coming together of the process intelligence that we call process intelligence today and the decisions that are made on it, or the outcomes that are produced from it. So the trajectory is clearly towards a set of work that humans do and a set of outcomes that the organization produces. Can you have a feedback loop and mechanism on all of this through the same acts of observation and continuous monitoring of both the work and its output? That’s where I see the whole thing going. And in fact, I don’t need to tell you — if you look back at your own thesis, which I was going through earlier, on Horizon 2 and Horizon 3, ultimately it’s the same thing. Whether we look at connectedness within the enterprise or outside the enterprise, it’s about outcomes and looping those outcomes back into the work that the organization is doing.
Phil Fersht [13:00]
Interesting. So as you look at companies investing in these mega-platforms like ServiceNow, Mega, Azura, these types of businesses, how do you see Skan fitting into the corporate tech jigsaw as we look out over the next couple of years?
Avinash Misra [13:21]
First of all, to the investment by the interventionist companies — everyone has a certain kind of intervention, maybe a workflow kind, maybe an automation kind of intervention — discovery is very important to them. However, discovery is also important in other ways. So any investment that goes in by an interventionist company is focused on that intervention. However, there is always a space for the more secular and independent analysis of work that is end-to-end, that does not have a specific agenda for a specific integration. That intervention may be a bot, the intervention may be putting a new orchestration in place, and so on. So I firmly believe that there is a strong space for the most secular process intelligence framework that, beyond all the imperatives of what I want to do, gives you a complete and unbiased picture of what should be done — not just that, but if it is done, then how do things evolve, and what are the intended and unintended consequences of the way work is happening in the organization. So telemetry is a given. Telemetry is bound to come to our industry. It has already come to much of human endeavor. The BPM world needs telemetry, and secular telemetry at that.
Phil Fersht [14:29]
Excellent. Well, so how did you end up doing this yourself, Avinash? You’ve been an honored figure in services and tech for a long time. How did you end up building a platform like this, and is this something that you’d recommend others do?
Avinash Misra [15:02]
No, no. Of course, everyone should do what they feel most passionate about, so I won’t recommend anyone do anything other than what they like and the problem that they face themselves. And like all… some things appear true in hindsight; as you’re doing it, they don’t, but when you look back, you say they’re absolutely true. When people say that to be able to solve a problem you should have lived through the problem — and to your question as to how I came to do this: Manish Garg, my co-founder, and myself… Manish was also my co-founder for the last 20 years; the last company was also co-founded with him. So both of us actually lived through the problem. And in honesty, when our last company was acquired by Genpact, we did not have a clue what we were going to do next. But such is the conspiracy of the universe that you end up solving hairy problems of automation, re-engineering, and transformation, and you begin to see that not just in those circumstances but in general in the industry there is opacity — opacity of work. And technology is already there to remove that opacity. How do you bring that technology to bear in a manner so that, A, the opacity is removed, and B, the removal of the opacity leads to certain outcomes — outcomes that organizations are looking for? And again, serendipity is that when you think of this idea, at the same time you find a customer, and then the customer says, if you build it, you buy it — then you go to an investor and say, well, the customer is saying this, so you get to raise some money. So I can’t overstate the influence of serendipity and good luck in being able to find both initial customers as well as people who will fund this venture.
Phil Fersht [16:54]
I love it. Serendipity indeed. Well, I think you’ll be gracing us with your presence at the HFS Summit next month, so hopefully we’ll have you on stage and meeting with many of our clients and friends as well. Avinash, I look forward to seeing you again, and thanks for your time today.
Avinash Misra [17:11]
Phil, I cannot tell you how thankful the world is for folks such as yourselves who are now creating, moving beyond the online and coming back to the real world. So forget about being on stage — just being in the presence of a lot of warm bodies and seeing you all in three dimensions is rewarding enough. So I’m looking forward to it. Indeed, it’s been three long years and it’s coming back. I can’t wait myself. Perfect.
