Elasticity is a measure of the responsiveness change in the demand of the quantity and its supplied to change in any of its determinants.

Feature Extraction refers to the process of selecting & transforming raw data into a set of representative features that capture the data.

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For a long time, I've been using maps of industries, businesses and systems to determine gameplay, management, learning of economic forces and how to manipulate markets. The map has two axis - one of value chain (which represents a recursive set of needs from user needs to supplier needs) and the other of evolution. See figure 1. Figure 1 - a map of HS2 The first maps I produced were in 2005 and at that time whilst I suspected and had examples of a pattern for evolution (from the genesis of an act to commodity provision) , I actually had no way of describing why it occurred. At that time, I was familiar with concepts such as Everett Roger's diffusion curves (adoption over time) but they provided no consistent pattern for change - the diffusion curve of one instance of an activity is not the same as the diffusion curve of another if measured on identical axis. Furthermore an act didn't evolve in a continuous path but instead involved many diffusing instances of more evolved forms e.g. take an activity A then we would see the diffusion of A[1] lead to diffusion of A[2] lead to diffusion of A[3] with each instance being more evolved than the prior. See figure 2. Figure 2 - Different diffusion curves for maturing instances of the same activity The solution to the problem occurred during a chance set of conversations in which I noticed that whilst people could agree whether something was a commodity when it came to products and something novel (i.e. the genesis of an act) then disagreements abounded. This led me back to the Stacey Matrix (see figure 3, this version is a simplified diagram created by Brenda Zimmerman). Figure 3 - The Stacey Matrix The Stacey Matrix is useful in discussion of how groups agree and what peaked my interest was the use of a certainty axis. This coincided with something Everett Rogers had said that activities evolve through multiple waves of ever improving and more mature examples. A key part of evolution seemed to have something to do with certainty. Hence in 2006 and 2007, I spent a great deal of time trying to determine a measure for certainty for an act. It was by looking in detail at publications of journals and papers on activities that I noted how they changed with time. In examining a core set of activities and 9,221 related articles, I was able to categorise the articles into four main types - see figure 4. Figure 4 - type of articles I then developed a measure of certainty that used the volume of articles of type II and type III produced relative to the total volume of articles when that activity is commonly described as a commodity. I used that reference point (when the activity was commonly described as a commodity) to examine how ubiquitous the act was and then compared past market adoption and publications against this measure. The result was the common pattern shown in figure 5. Figure 5 - Ubiquity vs Certainty Now, when examining each of the types of the publication used to manufacture the graph - it became clear that each type of publication was related to a stage of evolution. See figure 6. Figure 6 - Types of publication and relationship to evolutionary stage By overlaying the types onto the ubiquity and certainty curve and extrapolating the ends (i.e. when something is novel we have very little information on it), I was able to finally produce in 2007 the evolution curve (see figure 7 below) which demonstrated the pattern which I had used in mapping (see figure 1 at the top). It was shortly after this, I was able to demonstrate the reason why the pattern occurred was simply the interplay between supply and demand competition. . Figure 7 - the evolution curve. I then gave a series of talks on this in late 2007 and early 2008 using the curve to explain the impacts of cloud, 3D printing and highlighting some other common economic patterns e.g. how organisations evolve, how you can exploit ecosystems to manage the future etc. However, as backward as this process sounds it's actually quite normal for a pattern to be 'noticed' and found useful well before any evidence or model demonstrates whether that pattern might exist or is entirely false. In my case mapping was based upon a pattern I noticed (pre 2004), that had proved itself useful (post 2005) and this was well before I had any solid model behind it (2007). It doesn't mean the pattern is right, just that I've yet to find a better one. I'm sure I'll find some examples which break the model at some point in time - though after 7 years, I'm still looking. Added 27th July 2014 I was asked recently what is unique about the evolution axis? Well, since I discovered and demonstrated the pattern then I'm likely to be biased. However, that said :- 1) There is data behind it (thousands of data points) and examples of the pattern are commonplace. However, I haven't published the details of the technique for categorising publications because I'm still using it (for weak signals). Which means, YOU should not trust it. As far as you should be concerned then this evolution curve is only opinion. If you find the pattern useful then use it until something better comes along. The curve has been published in both peer reviewed academic papers and books as a "useful" model. 2) There is consistency in both axis i.e. we're not talking adoption curves where the time axis can vary according to the activity in question. 3) There is causation and not just correlation i.e. what drives the patterns is competition (both supply and demand) 4) It is weakly predictable and I have run predictability tests on this (in particular with the formation of new organisations). Predictability is the single biggest issue with the evolution curve. In order to create it then I had to remove time but of course, by removing time then it is no longer predictable over it. This is the one bit which makes me feel very uncomfortable with the curve and hence reluctant to publish a book on the subject. Though I find it useful, this is at best a weak hypothesis and I'm still looking for a better way to test / falsify. 5) It is useful or at least it appears to be highly useful as part of the overall map (see figure 1). Added 2nd Sept 2014 Though I've covered this several times over many years, it's worth reiterating that evolution doesn't just apply to activities but also practices, data and knowledge. Each of these classes of things evolve through the same mechanism (driven by supply and demand competition) with changing properties as noted in figure 6 above. To make it extra clear, I've spelt out those classes in figure 8 and the relationship with the evolution curve (see figure 9) Figure 8 - Different Classes (activities, practice, data and knowledge) evolve through the same property changes. Figure 9 - each of those classes, evolve through the same mechanism. This is why, when we map an environment we can also map - practices, data and types of scientific knowledge along with activities. However, as a guide, the bottom axis of a map I tend to describe activities (genesis, custom built, product and commodity) simply because I don't find Type 1 to 4 as meaningful.

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The RAPID framework is a tool used to help businesses make important decisions. The RAPID framework was developed by global consultancy firm Bain & Company, which noted that "high-quality decision-making and strong performance go hand in hand.” ElementDescriptionConcept OverviewThe RAPID Framework is a decision-making and responsibility assignment model used to clarify roles and responsibilities in...

The Theory of Computation in computer science explores the efficiency of problem-solving on a computational model through algorithmic processes.

A research paradigm, or set of common beliefs about research, should be a key facet of any research project. However, despite its importance, there is a paucity of general understanding in the medical sciences education community regarding what a research paradigm consists of and how to best construct one. With the move within medical sciences education towards greater methodological rigor, it is now more important than ever for all educators to understand simply how to better approach their research via paradigms. In this monograph, a simplified approach to selecting an appropriate research paradigm is outlined. Suggestions are based on broad literature, medical education sources, and the author’s own experiences in solidifying and communicating their research paradigms. By assisting in detailing the philosophical underpinnings of individuals research approaches, this guide aims to help all researchers improve the rigor of their projects and improve upon overall understanding in research communication.

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A heuristic in psychology is a mental shortcut or rule of thumb that simplifies decision-making and problem-solving. Heuristics often speed up the process of finding a satisfactory solution, but they can also lead to cognitive biases.

A cognitive bias is a systematic error in thinking that affects the decisions and judgments that people make. Some of… by trasteandolinux

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VRIO Framework is one such business analysis framework tool used to analyse the internal resources and capabilities of the firm

A map has an anchor. In chess, it's the board. In geographical maps it's the compass. In a Wardley map, it's the user need (of course, I'm assuming you've actually described the user journey and know what those needs are). A map has position (relative to the anchor) and the ability to show movement. In Chess, it's the position of pieces on the board and where they can move to. In geographical maps, it's the position relative to compass setting (northwest of here or in more advanced forms, GPS) and the features that enable or hinder movement (a cliff, a road). In a Wardley map, position is shown through a chain of needs and how visible the component is to the user (the anchor) whilst movement is shown through evolution. There are many types of pieces on a map. In Chess, well that's obvious. In geographical maps these are landmarks or troops (in combat). In a Wardley map, you have many different types of activities, practices, data and knowledge. All of these types in a Wardley map are evolving and co-evolving. The x-axis is just short-hand for evolution and I chose activity as the most useful description. But all of these types evolve through different stages (I to IV) over ubiquity and certainty. This is driven by competition and causes common characteristic changes. Unfortunately, to see evolution then you have to abolish time and measure over ubiquity vs certainty. This is not adoption vs time (a diffusion curve) which measures diffusion. Diffusion and Evolution are not the same thing but they are related (i.e. evolution consists of many diffusion curves). Because we have no crystal ball (i.e. you can't measure evolution over time and predict the future accurately) then you have to deal with the certainty axis and that things start of as uncertain. In practice this means you can only accurately map where something WAS once it has become a commodity. To estimate where something IS then you have to use weak signals or discussion between a group familiar with the field. Evolution just shows you the path, the future still remains an uncertainty barrier we can't peak through but we can approximate. The cheat sheet (more accurately, my cheat sheet) is based upon weak signals for each stage (I to IV) and is broadly applicable across all types (some of the characteristics are specific to a type but it's a good enough approximation). Once you have a map of your landscape, you can start to learn about common climatic patterns, use it to apply universal doctrine such as removing duplication and bias, use it to communicate and challenge assumptions, use it for context specific gameplay (i.e. strategy) and learning of such, use it to link strategy to operations, use it determine flow, use it for organisation ... in fact, you can do an awful lot with a map. Four final notes. 1. The only people who can map an industry are those that work in that industry. You have to learn to map and play the game for yourself. By all means you can use consultants to advise on different forms of gameplay (assuming they know any context specific forms) but the only person who can map your environment is ... YOU. 2. No map is "right", it's an approximation and open for challenge. The beauty of drawing a map is that it can be challenged easily. The key to mapping is don't try and create the perfect map but quickly draw the environment and share with others. With practice, you should be able to map a business in a few hours. NB. This means YOU, not someone else. 3. Mapping itself is not "right". These are Babylonian clay tablets for business. Someone will make a better way of mapping. All models are wrong, some are however "useful". Trying to determine strategy or operate a company without understanding your landscape is something that I don't find to be useful. 4. The Wardley Mapping technique is creative commons share alike, it has been for almost a decade. I found it useful, so I gave it away in the hope that others would.

A current list of tools for Wardley Mapping is maintained over at LearnWardleyMapping.com. This post has two main sections: A semi-serious reflection on the problem space of tools for mapping, and …