Structurizing Systems for Livestock Policy Evaluations

by Peter Hinrichs, FAL Braunschweig

Livestock-Environment-Interactions

Subject-Object-Relationships

Subsystems, Nesting and Aggregation

What´s a “System“ ? -General description

A system is a set of components (things or terms). This set may be seen as a compact part of the world because of the inter-relationships existing between the components.

System components usually differ from each other. Similar components may - and often should - be aggregated (to groups, herds etc.).

A system may - as a sub-system - be a component of a larger system.

Interrelations between livestock production and the environment

From the start, ELPEN‘s livestock systems are explicitly defined with two main components: The livestock production process as the kernel, and its (geographical, social etc.) environment.

It is obvious that the system “dairy herd in the high Alpes“ is different from a “dairy herd in the Netherlands“, e.g.

Most of the indicators in our list are elements of the interface between these main components.

LIVESTOCKPRODUCTION

Climate / Market / Policy Scenario

Effects on Society and Nature

Livestock / Environment - Model (Scheme)

VIRON-

MENT

EN-impacts

results

Interrelations kernel - environment (2)

In general, we discern two kinds of interactions between the kernel (livestock production) and its environment:- the influences of external (scenario) factors - climate, market, political regulations, e.g. - affecting the system kernel‘s development,- and the impacts of the kernel‘s resulting development on the natural, economic and social environment.

Policy evaluation calls for establishing a “Subject“

Since the policy evaluation aspect became a major feature of ELPEN, a further subdivision of the kernel in two components looks very useful: the holder (decision-making and acting subject) and the livestock (being the responding object).

This subject-object structure is widely used for technical, economic and politologicical questions and approaches.

OBJECT

Goals

Results

Climate / Market / Policy Scenario

Effects on Society and Nature

Success

Subject / Object - System (Scheme)

Plan Actions

SUBJECTVIRON-

MENT

EN-

Special features of the subject (1)

The “subject“ is the driving part of the system, the “object“ responds.

The actions are determined by - the subject‘s goals or targets,- its set of possible (feasible) actions - an assessment of the forecasted results of

these actions with respect to the goals.These are the main components of the

subject‘s plan.

Special features of the subject (2)

The goals, the set of feasible actions, and the assessment of the results are - as a rule - influenced by external (szenario) parameters.

When the actions have been done, the subject pays attention to special parts of the object‘s response, the “results“. If these (real) results differ from the projected ones, the subject revises its view of the system. It learns.

Affinity of the subject-object-structure to decision-makers

From all these features it follows that most micro economists as well as system engineers are familiar with the subject‘s features and preferably slip into its rôle - and not the object‘s.

The subject-object-structure especially reflects how technical, economic and political managers see their own rôle (and farmers, too, of course). They easily adapt this view and can easily use it as a basis of communication within their group.

LIVESTOCK

Goals

Results

Climate / Market / Policy Scenario

Effects on Society and Nature

Success

Farmer / Livestock - System (Scheme)

Plan Actions

FARMERVIRON-

MENT

EN-

Affinity of the subject-object-structure to scientists

Researchers in the natural sciences (astronomy, ecology, e. g.), however, usually work on systems, in which none of the sub-systems is supposed (or allowed) to take the part of a decision-making boss.

Even if they run a sharply controlled experiment, being a subject par excellence, they do not see themselves as a part of this or a wider system.

In some cases they better should.

More than one subject in a system - defining hierarchies (1)

A system may contain sub-systems, of which any may have a subject of its own.

Most frequently, a subject-object-kernel as a whole is defined as an object from the viewpoint of a superior subject.

To the sub-subject, the new subject‘s actions are just szenario parameters, influences from the environment, which have to be accepted as unchangeable.

More than one subject in a system - defining hierarchies (2)

In any actual system, only one subject should be valid at the time. Its objective function is the relevant one, if an evaluation or an optimization is required.

The subject should be unique, but it can be a group of stakeholders pursuing the same goals and acting under similar feasibility conditions.

The number and variability of the objects is not restricted.

Goals

Success

Plan Actions

OBJECTOBJECTS OG

P

S Results

A

Subject / Object- System 2nd Order (Scheme)

SUBJECTSUBJECT

Climate / Market / Policy Scenario

VIRON-

MENT

EN-

Effects on Society and Nature

Example: political regulations affecting the production process

The nesting of S-O-systems can be a useful tool.For instance, a politician trying to improve the

animals‘ welfare by issuing specific regulations, can be seen as a subject controlling both the farmer and his herd together as an object.

The farmer cannot modify the regulation. He only can modify the production process in order to fulfill the regulations and on the other hand make the best of it with respect to his own goals.

Goals

Success

Plan

ActionsFarmFarmFarmer

Live-stock

Goals

Plan

Success Results

Actions

Policy / Farmer / Livestock - System (Scheme)

Policy MakerPolicy Maker

Climate / Market / Policy Scenario

VIRON-

MENT

EN-

Effects on Society and Nature

Analytical and operational aspects of using S-O-systems (1)

Using nested S-O-systems for analytical purposes may look complicated at first glance.

But actually it is simple and easy to apply. The approach to apply is Dynamic

Programming (DP, Richard Bellman). It starts optimization with the smallest sub-system on the lowest level of the hierarchy, but for a wide range of possible influences from the superior subjects of the higher levels.

Analytical and operational aspects of using S-O-systems (2)

After this, the algorithm switches to the next higher level of the hierarchy, using the lower-level sub-system as the object, of which the response to whatever the “new“ subject may do has already been optimized and only need to be added to the actual results of this stage.

Thus, the system is enlarged level by level, but the evaluation time is almost constant for each stage.

Benefits of applying the S-O-system concept (1)

The specific rôle of actors is mapped explicitly with its main facets: goals/options, external and internal conditions, decision-making/controlling, evaluation of results, learning, plan revision.

Decision support systems are required by actors or their advisors. This concept will sell to them.

Any system kernel can be defined as the object of a superior system, any object can become a (sub-)system kernel with a subject of its own.

Benefits of applying the S-O-system concept (2)

So any user of the system can slip into the rôles of his superior or inferior counterparts and simulate their actions and/or reactions.

The system helps to distinguish between - given state, or scenario parameters,- decision, action, or control parameters, and- result parameters,as well as between projected (imagined) and real states, actions and results.

Benefits of applying the S-O-system concept (3)

The S-O-systems are flexible in complexity and size. They can be integrated in larger systems, and they can incorporate other systems, provided that these do not violate the rules of causality and transitivity.

The S-O-concept works well with the powerful Operations-Research tool of DP (R. Bellman‘s Dynamic Programming), its specific virtues will show up with stochastic and adaptive processes.

Benefits of applying the S-O-system concept (4)

Even if it is in no way used as an analytical tool, - it provides a convincing and easy-to-adapt pre-structurization of all decision problems,- it helps avoiding mis-interpretations and the improper or mistakable use of parameters.- and it will whet the end-users‘ appetite for the results of systems research.