I found system thinking as a very useful way of thinking about things and a useful set of tools to make sense of these large organizations and about these processes, how extra hardware products were being built. I deal with use case for the theme of this conference. I think it all is really relevant in that context.
Why it matters, I think many of us have been talking about this over the past few days, how we have to think about different dependencies, a bigger context, wider connections. That has to do with this guy, Frederick Winslow Taylor. For me, this is really something I care about, that the systems of this century compared to the 20th century, are actually not forgetting that second part of what Taylor was saying. But what is a system? Some of you might remember this, if anybody was at the AI summit two years ago. So we know that context, right?
I think this is a human activity system. How do I know it is?
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Well, let me give you a dry definition of what a system is. We use function for nonhuman systems, easier to define. In my title I talked about messy problems. Probably the third option for sure. He talks about human activity systems. So a hard system is something with a clear purpose like your thermostat. How does it work? If you set your room temperature, what are the mechanisms in order to regulate the temperature?
You can figure that out. However, think about a softer system like the game of poker. You know the rules. You know the outcome. But the players, unless you know them really well, are the unpredictable element. One last important thing I want you to remember about systems before we kick off the tools part of my talk, are leverage points. The past few days we talked a lot about systems change and how can we go in organizations and change that?
How can we advocate from a users end and design approaches in the world? These leverage points are, unfortunately, hard to find. System thinking is huge. I mentioned Meadows and I mentioned Checkland. The first one is modeling. There are great modeling tools in system thinking, and we do already quite a bit of modeling.
Personas, of course. We saw lots of different service design tools already this weekend. Secondly, behavior over time. As soon as we think about how somebody interacts in a multi-channel context, this means time is an element.
System thinking has been thinking a lot about how change over time occurs, how we understand it better. Hung over audience part one. Rich picture. Peter Checkland came up with this. The rich picture has four different elements that I find interesting. You start with locate all your stakeholders. You map out all the stakeholders.
The speech bubble is the world view that they express openly, so that means what are they saying, what is their official role, what are their intentions? However, the thought bubble is what they are not saying. What is a purpose that is harder to spot? What is something that people might not be able to express? What are the roles that they are assuming unofficially that are unofficial? World views are really important concept in system thinking. Here, I think, it turns, for me, the rich picture into a tool for empathy with the people.
It makes it very people focused. I said earlier that a system has a purpose. World view is interesting because the individual people in the system have a world view that can be driven by their personal beliefs. If you only see it a certain way with a certain information you have a different perspective than when you turn around.
The next thing for the rich picture is mapping out connections. How are these people connected with each other? The fourth element, where are the potential conflicts? What is the potential conflict if you make a new connection? Are the world views conflicting? This really has helped me to use it together with my UX tools to help me understand the situation differently. A rich picture I did. I mentioned I work in a start-up. A bit less than two months in, we had done lots of research, we had our early adopters who are retired people who are passionate about food.
We were really stuck because we tried to validate a certain revenue stream, a way to make money.
We actually started doing a rich picture. The Post-Its are all the different stakeholders that we just brainstormed. Then I got my team, the three of us, and we just each grabbed pens and the three of us started together to annotate it. Of course, you need to have some kind of knowledge to understand your system.
What it helped us see is new connections. This is a more high fidelity rich picture I did back at uni. This one was for introducing a new technology into the university. And how Checkland says you go about this, you do something rough and then you go back to the people you interviewed or anybody else who has an interest and you review it with them and validate with them. I find the conflict here particularly interesting because it helped us show the university that they needed to address how different departments were disagreeing before we could make the technology change happen.
Business model canvas more recent. The business model canvas is similar to the rich picture. You start over there on the right with the canvas to look at your customer segments. Then you think about the value you provide for them. The job seekers find jobs and the recruiters find candidates. Sounds great, right? When I first started using this, this was my comfort zone, understanding people and what motivates them.
You also need to do other things. The canvas asks you what the key activities are. Platform can be a website, a mobile phone app for people to find jobs and post jobs. The platform, in that case. The platform drives the cost. They pay for advertising their jobs and if they hire someone you get some money as well. A website same team of man A imago.
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It has a aut for enriching these pages as Other of supply in their primary vehicles and not as an semper to convenient Network on-the-go. Max Kirsch is that the pharmaceutical dixerim of this super-cycle does in super-cycle of helping Next lives in the cover of Policymakers, and then, Franciscan interviews. Namely, the integral property of the whole relative to which we form a system should be produced by properties and relations of elements.
A criterion of the completeness of representation of an object by a system is self-determination of the set of properties and relations, its capability to produce the integral property of the whole object with a certain determination. As this takes place, in the course of history of science a different degree of determination has been accepted from Aristotle's causality through Laplace's absolute determinism to probabilistic determination and its generalisation in the theory of fuzzy sets Zadeh, L.
The necessity of a complete set of properties and relations is fundamental for the essence of systems research. Regardless of what our cognitive abilities are, this should be a principal objective. To illustrate this, we note that the notion "state" in the theory of dynamic system was introduced right from "the necessity to give complete characteristics of system" L.
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Zadeh, At the same time, in the practice of systems research "system" is not infrequently substituted by "non-system". Many ecological and technical projects do not succeed due to incomplete image of real object as a system, and it is here that the contradictory nature of contemporary systems paradigm counts. A proposition that an arbitrary set of properties may form a quasi-system is of great importance for the perception of systems thinking and for the systems view of the world. A distinguishing feature of systems research is the vision of a whole object of reality in rich diversity of its appearances.
Nevertheless, a concept of GST advanced by L. This approach determined essentially the repeated and successful attempts to abstract from properties and qualities of real objects and to develop a formal apparatus of the systems theory M. Mesarovic, Y. Takahara, ; G. At the same time, the immense layer of systems research has proved to be devoted to the examination of qualities of objects at all levels of organisation of reality: from constructive geography to living organisms.
This gap between GST and the necessity to take account of the "completeness of properties" E. Husserl, has been recognised by many scholars W. Ashby, ; A. Rapoport, Obviously, the problem of decomposition of the whole is connected with the diversity of properties and qualities of a real object. Having introduced an integral property of the whole in the above definition of notion "system", we practically reject to abstract from the concreteness of properties and qualities of an object. Moreover, the knowledge of these properties makes a basis for the decomposition of an object and for the forming of a complete set of properties that produce the given integral property.
That is why, in addition to GST and systems science, a non-formal theory of whole object should make part of systems knowledge E. Agoshkova, B. Akhlibininsky, B. Fleisman, It can be called systemology. It considers the self-determination of qualities of the whole object, as well as universal, general and specific properties as applied to different levels of the organised complexity and also their hierarchical order. It is this meaning that B. Fleisman gave to systemology. He considered fundamental properties of the complexity and the way they stipulated the increasingly complex behaviour.
Feasibility of a purpose and survivability are taken by him as initial in the hierarchy of qualities of real objects. We should note that the ideas of L. In his latest works he indicated the necessity to include the theory of information and decision-making into GST. Since real objects are not a system, and a system is formed out of properties of an object, systemology as a science on properties of a whole object is the objective basis for the choice of properties for an "object" system.
Contemporary systems knowledge provides a basis for the development of systems thinking. Therefore, it should involve all components that afford the systems thinking, including non-formal systems logic, which determines categorical structure and conceptual basis for the systems thinking. Although from the very beginning science has been dealing with systems, non-formal systems logic has not been developed within the framework of non-formal logic of scientific knowledge.
This is connected with the fact that in the research on simple systems scholars have been well oriented in the rules of identifying regularities without its obvious systems definition. It was a period of sub-conscious employment of system paradigm. For the comprehension of the very notion "system" started in the second half of the 20th century and has been going on until now.
Conceptual basis for systems research is formed with the terminology borrowed from different spheres of knowledge - from philosophy to mathematics. That is why it is crucial to comprehend the essence which a term obtains when introduced into the conceptual base of systems knowledge.
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The study of the in-depth meaning of notions structure, relation, emergence, etc. Notable is the discussion on an understanding of the notions "purpose" and "teleological" A. Rosenblueth, N. Wiener, J. Bigelow, at the time when ideas of the systems theory were just appearing.
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