Tuesday, August 18, 2009





The first step in Soft Systems Methodology ( SSM ) is to formulate the Root Definition of the System you are studying, analysing, designing, evaluating or even quality assuring [inspecting].


A Root Definition is a structured description of a system. It is a clear statement of activities which take place (or might take place) in the organisation being studied.

A properly structured root definition comprises three elements [what, how, why] and is of the form: A System to do X, by (means of) Y, in order to achieve Z.

XWhat the System does
Y How it does it
Z Why it is being done

The 'what' is the immediate aim of the system,
The 'how' is the means of achieving that aim,
The 'why' is the longer term aim of the purposeful activity.

CATWOE analysis helps in proper formulation of a Root Definition.

CATWOE is a mnemonic which helps identify and categorize all stakeholders [people, processes, environment, entities] of the System being analysed for formulating the Root Definition.



To elaborate a bit:

C: The ‘customers of the system’ , clients or System Beneficiaries. In this context ‘customers’ means those who are on the receiving end of whatever it is that the system does. Is it clear from your definition of “C” as to who are the beneficiaries of the system?

A: The ‘actors’, meaning those who would actually carry out the activities envisaged in the notional system being defined. Actors transform inputs into outputs.

T: The ‘transformation process’. What does the system do to the inputs to convert them into the outputs?

W: Weltanschauung - The ‘world view’ that lies behind the Root Definition; the perspective from which the Root Definition if formulated. Putting the system into its wider context can highlight the consequences of the overall system. For example the system may be in place to assist in making the world environmentally safer, and the consequences of system failure could be significant pollution.

O: The ‘owner(s)’ – The person(s) who has commissioned the system and who has sufficient formal power over the system to stop it existing if they so wished (though they won’t usually want to do this).

E: The ‘environmental constraints’. These include things such as ethical limits, regulations, financial constraints, resource limitations, limits set by terms of reference, and so on.


CATWOE Analysis yields a more elaborate all encompassing Root Definition of the form:

A System owned by O to do W by A by means of T given the constraints of E in order to achieve X for C.

[A briefer version – a T system in which A do W for C]

Here is a CATWOE Model of a hypothetical Higher Education System [a University or College:

C – Students
A – Teachers
T – School Pass Outs are transformed into Graduates [Degree Holders]
W – Graduation [a Degree] is a means of assurance to potential employers that the Graduate [Degree Holder] possesses a specified standard of proficiency and skills in the domain of qualification.
O – The University or College Governing Body or Top Management
E – The Prescribed Educational, Academic Quality, Assessment and Accreditation Standards and Requirements.

Now this CATWOE Analysis may yield a Root Definition that this particular Higher Education Institution is a university owned system to award degrees to students (X) who successfully qualify assessment (Y) in accordance with prescribed standards in order to certify assurance (Z) to potential employers that the students possess the requisite proficiency, capabilities and skills.

Is this Root Definition okay or is there something amiss?

Suppose we define Potential Employers [or Industry] as CUSTOMERS [C] and include students as ACTORS [A] along with teachers – won’t we then get a more apt Root Definition and consequently realise a better Educational System in keeping with current needs and ground reality?

It is vital to accord apt attention to optimizing the System Root Definition for the System under consideration for best results and in this the CATWOE Model is very helpful.


At a recent alumni meet of a prestigious Engineering College I asked a few recently passed out alumni [who were working for a leading IT company for just over a year] as to how much of what was taught in his four year Engineering Degree Course in his college was useful in his work.

They said: “Less than 5% (five percent)” – which means that his employer had to invest heavily [almost 95%] in his training and the rest he had to learn on the job.

Maybe the educational institution needs to introspect and have a relook at its CATWOE Model and reformulate its ROOT DEFINITION and restructure its curriculum and revitalize its pedagogic methodology to meet the challenges of current needs and envisage seamless integration of fresh BE and B. Tech. Engineering Graduates into the industry.

A Systemic Approach to education incorporating increased partnership and congruence between the industry and universities is the sine qua non of optimal human resource development in science and technology.

The disconnect between the industry and educational system must be bridged.





Human Errors in Decision Making





“The man who insists upon seeing with perfect clearness before he decides, never decides” …Frederic Amiel

Decision-making is so pervasive that everyone, professionally or personally, is involved with making a variety of decisions.

In today’s fast-moving world, the timing of a decision is of paramount importance in many decision-making situations. In real life even the “perfect” decision may not be optimal if it is made too late.

Information is a vital resource in decision-making.

One of the most important characteristics of successful managers is the ability to make the correct decision when confronted with imperfect or insufficient information (i.e.) Decision-making under conditions of uncertainty.

In the context of decision-processing, two realms or domains of uncertainty are:

1. Information-Input Uncertainty which creates the need for hypothesis generation and evaluation;

2. Consequence-of-Action Uncertainty which creates the need for option generation and evaluation.


A Decision Taxonomy: The Stimulus – Hypothesis – Options – Response (SHOR) paradigm, formulated by Wohl, is useful in such decision situations.

The SHOR paradigm represents a qualitative, descriptive model as distinct from a quantitative, predictive model, and comprises the following primary decision-making task elements:

S: Stimulus Input Data Processing

H: Hypothesis Generation, Hypothesis Evaluation, Information Processing [What is?]

O: Option Generation, Option Evaluation, Decision-Making [What if?]

R: Response Output Action

The SHOR paradigm is basically an extension of the classical Stimulus – Response (SR) Paradigm of behaviourist psychology.

The SHOR paradigm provides explicitly for the necessity to deal with information input uncertainty and consequence-of-action uncertainty, and helps us understand some of the peculiar human factors that affect the quality of the decision-making and answering questions such as:

What makes some decision-makers perform better than others, especially in placing high-value assets at risk ?

What are the sources and dimensions of “poor” performance?


Based on the SHOR Model, human errors in decision-making appear to lie in four domains:

(S) Stimulus: “I didn’t know…”

(H) Hypothesis: “I didn’t understand…”

(O) Options: “I didn’t consider…”

(R) Response: “I didn’t act…”

Stimulus based errors of the type “I didn’t know…” result from lack or inadequacy of information, the true inability to obtain information.

“I didn’t understand…” is the fundamental result of information input uncertainty, while “I didn’t consider…” is the product of consequence-of-action uncertainty.

It is possible to have accessed all significant information, to have developed the correct hypothesis and to have selected the best option and yet fail to take appropriate action.

The two possible reasons for the “I didn’t act…” type of response error are:

1. Paralysis: This is a complete failure to act, the pathological “observation of an inevitable course” without intervention. It is caused by an over-riding emotional struggle in which some internal factor is being placed in conflict with the course of action selected by the decision-maker. The final scene in the evergreen classic film The Bridge on the River Kwai (1957) exemplifies such a situation.

2. Misjudgement: The decision-maker correctly decides what to do but errs in either or both of the two dimensions – how [the specifics of the action] or when [the timing of the action].

Prediction of the critical consequences of inaction may be of some help in dealing with paralysis whilst the ability to perform sensitivity analyses may assist in alleviating misjudgement.

Any Decision-Maker [and designers of decision aids] must address the four cardinal errors in decision-making epitomized by the SHOR paradigm:

“I didn’t know…”

“I didn’t understand…”

“I didn’t consider…”

“I didn’t act…”


In the context of decision-making in uncertainty, the conflict theory paradigm developed by Janis and Mann may be apt.

This paradigm postulates five patterns of coping behaviour which tends to occur in such situations:

1. Unconflicted Adherence in which the uncertain, or risk, information is ignored and the decision-maker complacently decides to continue whatever he has been doing.

2. Unconflicted Change to a new course of action, where the decision-maker uncritically adopts whichever new course of action is most salient, obvious or strongly recommended.

3. Defensive Avoidance in which the decision-maker evades conflict by procrastinating, shifting responsibility to someone else, or constructing wishful rationalisations and remaining selectively inattentive to corrective information.

4. Hypervigilance wherein the decision-maker searches frantically for a way out of the dilemma and impulsively seizes upon a hastily contrived solution that seems to promise immediate relief, overlooking the full range of consequences of his choice because of emotional excitement, repetitive thinking and cognitive constriction. In its most extreme form hypervigilance is referred to as “panic”.

5. Concerned Vigilance in which the decision-maker optimally processes pertinent information and generates and evaluates hypotheses and options before selecting a response as characterised by the SHOR paradigm.

In many real-life situations a decision-maker cannot always keep waiting until the entire information-input and consequence-of-action conditions are known a priori with certainty. In most cases there is no such thing as “perfect” certainty.

If a single most important characteristic is crucial to a decision-maker in any field, it is the ability to make optimal decisions in conditions of uncertainty.

Qualitative descriptive models like the SHOR paradigm may prove useful in such situations.

To quote Frederic Amiel once again: “The man who insists upon seeing with perfect clearness before he decides, never decides”.


Copyright © Vikram Karve 2009
Vikram Karve has asserted his right under the Copyright, Designs and Patents Act 1988 to be identified as the author of this work.