Advent of Business Architecture from a Process Perspective: Part 3

Lloyd Dugan:
All these things you're talking about, these are all aspects of self-knowledge. If you're going to plan a corporate strategy, if you're going to attempt to do a merger and acquisition pursuant to some kind of strategy, for example, you need to have your own self knowledge so you can compare it to someone else's. I think that that's what's missing is this perception. You talked about spending a lot of time pulling all this information together. If I have the self knowledge, then I'm not doing it. It's already there for me to use. There is an opportunity. I just I hope that more of it will be the case rather than the usual stuff for business architecture. Just speaking my mind on that one. I would just I would ask you, is in your own experience, are these actually happening? I know from my own I did spend one time in the prior life on a project to vet a potential M&A acquisition, and it was really hard to do because there was just no framework for comparison. We just had to create something out of whole cloth. So I ask you, is this something that's actually happening enough to give you confidence that it's the future or is it still something that people are struggling to embrace?

Jeffery Wallk:
Well, I think it's the future. The play on words that you put out there, which is the self knowledge, I think we need to take and shift that from self-knowledge to selfless knowledge. By that, I mean, we need to figure out how to get this knowledge into a digital means so that it can be leveraged and integrated. The real digital transformation is to move from the self contained knowledge that's embodied in all the different resources and systems and make that ubiquitous so that it's available, so that we have in any one moment in time, we understand what's really going on. That's one of the reasons that I shifted a lot of my focus from business architecture to what I call knowledge architecture and knowledge engineering in the last few years, because I believe that's the direction that we need to go in. I'm not abandoning the disciplines. I'm incorporating them into these knowledge frameworks because I think that's the only way we're going to be able to do that. Taking in one of your points earlier, if we're trying to do a merger and we're making decisions about key personnel or maybe a product, has anybody done a sensitivity analysis against the existing employees and or accounts that are part of the organization that's being acquired to understand how they might react if you with a change like that. If you don't know those things and you simply just make an assertion and you wholesale cut these things and you don't really know what value is being preserved and what's being cut out.

Interesing Links from Jeffery

Small Business Podcast:
https://www.youtube.com/channel/UCcLpn7bgkA9CRuLfK1qdu8A

Project mentioned in the transcript:
https://www.community1stproject.com/

Website:
https://www.enablingvalue.com

Jeffery Wallk:
Oftentimes mergers are not successful other than the fact that they've consolidated a market in that regard, because the laws allow for that level of consolidation without real value return, it's a problem. Unfortunately, there's a social penalty for mergers and acquisitions, which results in displacement of people. The same thing happens with technology. The promise of value and how we understand what is really being delivered versus what is desired is still a continuous gap that we can't measure very effectively. Measurement is a big problem with change. There isn't a good framework for doing it because it's hard. It's hard because there really isn't an ecosystem and a framing around all the various pieces. I think there is an opportunity for those organizations that are starting to move into these newer knowledge technologies and embracing to start to think about how they can start to coalesce these different disciplines, not replace them and not displace them, but really enables them, so that they can for the first time start to understand how they can work together and play off of each other. I'm hopeful that the organizations that are embracing these kinds of technologies are starting to realize it. They're typically doing knowledge, graphs and knowledge engineering on a very small scale. Some organizations are doing it on a specific aspect of their organization. But the future is very promising. It's really incumbent on all of these different disciplines to start thinking about how they can move their self repository of knowledge and disciplines and symbolics into this ecosystem of interactive and interoperable knowledge.

Lloyd Dugan:
So let me pause you there, because I think that first off, I'm going to say that you haven't copyrighted the term "Selfless Knowledge" by the end of the month, I'm going to claim it as my own for and that is a great term that's going to stick with me for a while.

Lloyd Dugan:
One of the primary artifacts out of business architecture tends to be the capability map. It's one of the things that people point to first. The value stream being the other one. Let's focus on the capability map. Capability map is really an easier thing for most people to get a handle around, especially because it works, because at least in my experience, because it's more about the what and it lends itself to a kind of functional decomposition view of the world or a functionally decomposed view of the world. And that's a lot easier than process modeling because that is a flow view of the world. That's a little harder for most people who are not familiar with process modeling to to wrap their heads around. What we have is with capability maps, again, what kind of statements, like account manager. That could be a top level capability. Then you could decompose that down to a couple of layers and get more differentiated, more specific. But the one thing it doesn't tell you exactly is how that works. So that "how" can be buried in the deeper layers of the business architecture as self-knowledge, that's intellectual property or corporate intellectual property. The capability is that selfless expression of that. Because there's nothing no, there's nothing intellectually proprietary about capability statements typically. So I offer that as an example of how we could see business architecture as a means to communicating selfless knowledge about oneself. You're sharing with the world. That's what the reference files are basically saying, everybody does the six things. We're not going to let you keep that specific, but everybody does these six or seven things.

Jeffery Wallk:
Look, it's not like we have to reinvent some of these things, they are already there. We know what they are. If there isn't a set of published capability maps for industries and organizations, they're simply going to continue to leverage the U.S. and use that. And maybe that's a good starting point. I think there are there are aspects of it that are useful. The challenge with a lot of the modeling is that maps are nothing more than simplistic renderings of models. But we have to be careful because if we're starting to move into the knowledge arena, then we have to be careful about the terms that people are using and not force people to use specific terms. We need to be able to support semantic dissonance and the individual perspectives. And I know that's something that we've talked about on many different calls with the guild and modeling team. I look at the opportunity to incorporate these kinds of maps and capabilities into a standardized framework. The framework isn't necessarily a meta model, but I think of it more as common sets of taxonomies and ontologies that any organization can leverage. Because that's where the knowledge is going. Part of this is a shift in the way people think about mapping versus modeling.

Jeffery Wallk:
With regard to the opportunity to create a more selfless body of knowledge. There are a lot of folks that have perspectives around how capabilities should be created and how they should be mapped. There is a certain perspective that they will use a top down derivative approach. The problem is depending on how many levels you go down, of course, each level you go down, there are going to be impacts that a change in one of those, let's say level two are level three capabilities are going to have on its peers and potentially on the layer above and the layer below. It's important to understand how those relationships should be mapped. Oftentimes they're just put into a simplistic relational approach or in a spreadsheet. In some cases, they'll they'll maybe go down a few different levels. But again, it's still very much of a componentized, top down perspective. I think of those things more around an organic presence with the relationships between each other. That's many-to-many. And it's hard to deal with that. So if someone is doing a capability map and they try to do a heatmap around that. Well, you need to understand how everything is performing and how to measure those and the interstitials between them. The relationships are the hard part. Some of us understand those things and we might call it out in the meeting. The average person isn't going to be able to embody all those relationships, understand them. So it lends itself to a knowledge graph much more than a relational structure. This is sort of the shift in mindset from columnar based thinking to conceptual thinking.

Lloyd Dugan:
So here's the shameless plug moment. Tell us about your own podcast.

Jeffery Wallk:
The podcast I've been doing for a while is really focusing on small business because I'm a small business owner. At the same time, I try to promote small businesses. So I started something called Ask the Experts as part of a series that I just interviewed different individuals and how successful business owners to share some of their knowledge. But I also do a lot of writing and blogging across the landscape. I'm heavily involved in work around some of the knowledge graph work that's undergoing right now and several different organizations trying to set standards for that. I also am doing a lot of work around digital twin planning and how that and trying to straddle between that knowledge graphs to figure out how best to align those and perhaps influenced the way we come up with reference models around digital twins as well.

Lloyd Dugan:
My question is this why have we not as a culture, as an organization, as a society, as a technology, informed and predicated society, move to seeing data from the semantic view? Why is it that we are still burdened by old school ways of seeing data that are by now over half a century old? And when you talk about knowledge graphs in particular, whether we call it the knowledge graph or a semantic graph or some other label we want to ascribe to it, it's certainly a different way of talking about information and data. But it's more useful. It's more accessible. It just has a higher utility over time. So why is it that we're still stuck in an old industrial way view of seeing data?

Jeffery Wallk:
Well, I think there are a number of factors. There's a social component to it and there is a commercial component to it. The social part is that change is hard. People are already inundated with the pace of change. It's fine to introduce semantic technologies. People are struggling with, what that even means because it becomes more abstract. While it's more abstract, it's also eminently more useful for answering hard questions. It's almost a paradox because we need it to help us answer the tough questions, yet we resist it because we're afraid we don't understand it and we understand how we try to answer tough questions today. But often hear the story of the boiling frog, which is just nothing more than a parable for human behavior. Really in many ways it defines a lot of the behavior we see in our society. We resist change until we have to deal with it. Typically, organizations and leaders are going to take a risk on shifting everything over to semantic technologies because they don't understand enough about it. They don't understand it's going to require a large investment. They don't know what the payback is. Until someone comes along and says we were able to create a new product. Define a new market and jettison a company two orders of magnitude larger than us from the market within three years. Now, when those kinds of things happen - from a smaller organization that understands how to leverage knowledge - you'll start to see people jump.

Jeffery Wallk:
There is a perception that there's trillions of dollars out there waiting for people to take advantage of knowledge and twins and so forth, and while that's true, you have to build a business case and a path forward for people to make those kinds of investments. Semantics and the technology are not the issue. They're really facing today the biggest issue of our time, which is the breakdown of trust. It's not a single point of truth kind of issues. Those are simple. What it's really about is the lack of trust that we're seeing across every facet of our society and in many areas of our industry and institutions. Semantics aren't going to save us from that. This is a basic human failure point that has been plaguing mankind from day one. The Internet has unleashed it, and people have learned how to exploit it. So the challenge right now is to rethink something maybe on the other side of the spectrum from semantic technologies. But where semantic technologies complete enormous role, which is in the realm of policy. That's another conversation, perhaps. But I think that. We're going to have to deal with this trust issue. There are some technologies that will help, but there are some fundamental things we need to change in terms of the way we control and manage human behavior. And it's not going to work if we're simply going to create more laws. That's a long winded way of saying there are a lot of different reasons why the semantic technologies have not taken off. Again, I think that there's there's several different elements to it.

Lloyd Dugan:
You certainly offer an interesting sociological perspective, which I agree would be a topic for further exploration on another podcast session. What I was really angling for was that when the relational theories in math that basically get the what we know today to be relational databases, and they've been around for decades now. But they experienced a lot of disruption because there was a flat way of seeing data which had to be junked in favor of this other way of seeing data. And I just I just am wondering if we're still working through that cycle now.

Jeffery Wallk:
Yeah, we are. So let me let me answer your question now that I understand a little bit clearer about what you're driving towards. I think there's a fear that if we embrace semantic technologies, perhaps people think we have to abandon all of our relational infrastructure and I don't think that's the case

Lloyd Dugan:
And I don't think anybody pushing it really, really tries to do that. But I agree with you that maybe the underlying theory that's at work. The bitter irony here is a massive chunk of the Internet or at least how we experience it, is driven by the technology that people just don't know that.

Jeffery Wallk:
Most of our systems are built on relational and they've served us well. Again, it's easy to understand relational. That's why spreadsheets are so popular. I don't know too many executives that work with abstract concepts. They're not going to work with models. They understand spreadsheets, rows, columns. It's intuitive. There's other stuff. It requires spatial reasoning. It's very different. We're not trained in these kinds of things. So it's a paradigm shift and it's a different way to think. When we go from the self based knowledge that and the way we organize our own stuff, we bring our own taxonomies and ontologies and that's how we understand our world. If I have to move it into a universe reality, I don't know how I'm going to understand that. So we still have to figure out how do we preserve my understanding of it, improve my understanding of it by applying semantics and take me along the journey. That's still part of what has to kind of evolve.

Lloyd Dugan:
It does. And I think it will just have to see how that unfolds over the next several years. But that was an excellent answer to the question. Thank you for the follow up.

Lloyd Dugan:
Thank you so much. We'll definitely have you back in the not too distant future, hopefully, to continue this good discussion, because we did a really good deep dive on half the questions. I'm sure we can do an equally deep dive on the other half of the questions with that. Bid you a good night.

Jeffery Wallk:
Thank you, Lloyd. Good good to talk to you again. And nice to be on the BPM Podcast. Anyway, I can help in the future. That sounds great. Appreciate the opportunity.

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Lloyd Dugan

Lloyd Dugan is a widely recognized thought leader in the development and use of leading modeling languages, methodologies, and tools, covering from the level of Enterprise Architecture (EA) and Business Architecture (BA) down through Business Process Management (BPM), Adaptive Case Management (ACM), and Service-Oriented Architecture (SOA). He specializes in the use of standard languages for describing business processes and services, particularly the Business Process Model & Notation (BPMN) from the Object Management Group (OMG). He developed and delivered BPMN training to staff from the Department of Defense (DoD) and many system integrators, presented on it at national and international conferences, and co-authored the seminal BPMN 2.0 Handbook (http://store.futstrat.com/servlet/Detail?no=85, chapter on “Making a BPMN 2.0 Model Executable) sponsored by the Workflow Management Coalition (WfMC, www.wfmc.org).