Paul Omerod believes that biological systems, social systems and economic systems are related in many ways – especially with respect to their rates of survivals and extinctions. What do all these have in common? They are predominantly causative systems that are able to adapt and change their composition over time as their environments change. They evolve. Whether evolution, involution or revolution, all these systems adapt in different manners to their environments.
DEFINITION, LOGIC AND EXAMPLES
A causal resource is a composite that purposely causes selected primal substances (matter, energy, information, or space) to change from a less useful form (input) to a more useful form (output) as determined by its internal structure.
- Purpose driven: Causal resources are purpose-driven. A block of concrete that changes a spectrum of visible light to infrared cannot be termed as a causal resource since it does not cause the change on purpose. However, an electric light bulb is a causal resource in that it was designed or bought purposely for lighting by converting electrical energy from the main supply to light energy.
All institutions are purpose-driven. Corporations most especially may not have any other purpose other than to maximize shareholders’ wealth. Under such scenarios, the component parts of the organizations must function to deliver on such a purpose.
(Simple purposes to complex purposes)
- Selective: Causal resources are selective. Causal resources, in interacting with their environment choose the inputs to change. The central nervous system of a human, a typical causal resource, does work only with the limited electrical activity of the neurons.
- Internal Structure: The distinctive feature of causal resources is their internal structure, composed predominantly of agents, depositories and channels. Agents are the components that act on the input primal substances to cause change; depositories hold the primal substances while the channels provide the route for the primal substances to flow through the internal structure. The digestive system of a mammal is a typical example of the functioning of an internal structure. Food is taken into the mouth (acting as a depository), chewed and churned using teeth, tongue and the walls of the mouth (the agents), and sent to the stomach (another depository) via the esophagus (a channel).
Examples of Informational Resources include: Strategy, Software, Methodologies, Processes, Human Brain, Clocks, and Computers.
BASES OF VALUE
The value of an informational resource is based on output relevance, intelligent scope, signaling rate, memory size, memory exchange rate, memory decay, computational frequency, aggregate count and gates count.
- Output Relevance: This is the extent to which the output information from the informational resource is significant to the perspective of the intended user.
The financial information system of a business is an informational resource intended to provide information on the financial performance of the organization to its stakeholders, potential and actual. The main output of this system, financial statement, has a track record of not being entirely relevant to its intended users.
In finance, it is very evident that the financial accounting information provided by corporations is not sufficient guide to decision makers in making better decisions within their respective roles. As such, decision makers rely more on other sources of information to supplement for these lapses. Management relies more on the corporation’s management accounting information system which thus far has proven to be more effective than traditional financial accounting information. Investors on the other hand rely more on the information they can have from multiple analysts in order to have a better picture of the firm’s viability and thus their investment decisions. We thus conclude that in decision making for both managers and investors, historical financial performance presented in the conventional financial statements is irrelevant to both managers and investors.
A classical example is the sponsored links presented by Google whenever a search is made on its popular search engine. The client will click on a link provided the preliminary information indicates some clarity and relevance to his perspective.
In business accounting, profitability, liquidity and other financial performance ratios are considered as paramount by investors because they believe these provide the most relevant information as to the sustainability of the business.
- Intelligent Scope: This is the range of inputs (material, informational, spatial) the causal resource is capable of intelligently changing.
This is just like the concept of bandwidth for radio devices. For instance, an FM receiver is capable of reception within the range of 88 - 108 MHz. There are other radio receivers that can receive beyond the FM bandwidth – AM, SW1, SW2 etc.
For humans, our eyes, ears, skin, tongue, and nostrils enable us to intelligently interact with visible light, audible sound, heat and cold, smell and taste. As such, we say we have a broad intelligent scope. However, there are other categories that our natural senses can never sense. We have been able to extend our intelligent scope through technology: X-ray, Infrared, Radar, UV etc.
For businesses, the traditional intelligent scope was limited to financial perspective. The invention of the Balanced Scorecard expanded the scope to include customer perspective, internal perspective as well as learning and growth perspective.
Like humans, computers have very broad intelligent scope. However, their very basic nature is limited to the binary states fields: electric and magnetic.
- Depository volume: This is the maximum unit of primal substances the internal structure can hold per unit time.
In computers, the holding capacity has been divided into two types, permanent storage (hard disk, DVD, memory sticks etc) and the volatile storage (RAM and Page file). Another interesting thing with computers is the fact that the bit is the smallest unit of information storage as such capacities can be measured and compared easily.
In humans, our current knowledge has not been able to decipher how information is being stored, whether in bits as in computers or some unknown quantity.
- Internal Volume: This is the number of categories that can be stored in the internal structure of a causal resource.
Every causal resource has an internal volume. The essence of the internal volume is to establish, make available and preserve the internal structure as well as store the categories (input, work in progress and output) the causal resource is working on.
In an organization which to a great extent is a causal resource, the internal volume for information (memory) is beyond the physical memory contained in the information system. It includes the memory of the workers about processes, process memory, strategic memory, culture, standards, rules of thumbs and a host of other tacit and explicit information stored in everything within the organization.
In humans, the internal volume for information (memory) includes the memory of the central nervous system, sensory subsystem and motor subsystem. For organisms that do not have a central nervous system, the memory is at the level of the sensory and motor subsystems.
- Bottleneck: This is the maximum units of inputs within the intelligent scope that the causal resource is capable of working with per unit time.
Most organizations have very low informational bottlenecks. There is so much information at the disposal of organizations; however, very few people have the necessary talent and skills to this information beyond signals to be processed.
- Internal Exchange Rate: This is the number of categories that can be exchanged to and fro the storage points per unit time.
Internal Exchange Rate determines how well the internal structure functions.
In businesses, the internal exchange rate varies from person to person, process to process or technology to technology.
In computers and other physical informational resources, the internal exchange rate is defined by the memory operations per second.
- Internal Volume Decay: This is the number of categories that will be ejected or disintegrated from the internal volume naturally, without interference after a period of time.
Memory Decay is critical in the functioning of the informational resource. In situations where the memory losses information within a very short time, then the K Set of the informational resource becomes very dynamic and it is very difficult to keep track and hence make matching and translations of the U Set with the K Set. The K Set then becomes uncertain within a very short time, thus creating uncertainty and infiniteness in a system that is supposed to be finite and certain.
However, memory decay is very necessary; otherwise, the informational resource may never be able to adapt to environmental changes.
There are thus two opposing concepts embedded within memory decay that must be optimized based on the perspective of the informational resource.
In humans, the brain optimizes this by making use of more than one memory type: sensory memory, working memory and long-term memory. From this, adults have the possibility of becoming too biased by their experiences, while children have the highest and best potentials for learning.
This could be one of the major constraints in creating systems that compare to human intelligence. There is no doubt that computers can perform many tasks faster than men, however, they still need a great deal of human intervention to define their K Set. This, I believe, is the main limiting factor.
- Activity Frequency: This is the maximum number of relevant activities that can be done by the agents per unit time.
The key here is on the word relevant. Irrespective of the number of activities that can be done per unit time, how much of all that is relevant? It is not about data analysis, as in analyzing everything that we think is worthy of analysis. The issue is with respect to the number of computations that are significant in transforming the output towards the desired perspective.
I believe the best designs of informational systems with respect to computational frequency are found in biological systems. Taking the DNA for instance, it is evident that from the very beginning of life for an organism, it does just the necessary computations that are needed for every stage of development for the organism.
Computer systems on the other hand do not have that kind of computational frequency, thus the high levels of complexity involved just to do simple tasks, like retrieving information from a memory.
Organizations, most especially government agencies have a knack for being unnecessarily burdensome.
Computers have helped so much in the way work gets done in organizations based on their oversized computational frequencies.
- Aggregate Count: This is the minimum number of inputs that must be integrated to provide a relevant output. Aggregate count ranges from one (01) to infinity.
Most computer chips have a signal aggregation of eight for them to provide either numerical or text-based characters.
Nerves could have higher measures of signal aggregation. I believe this is one of the reasons there is an average of about ten thousand (10,000) neurons connected to one another.
- Gates Count: This is the minimum number of computations that must be done on an input for it to yield to a relevant output.
