Utility value of management tools Advanced Herd Management Anders - - PowerPoint PPT Presentation

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Utility value of management tools Advanced Herd Management Anders - - PowerPoint PPT Presentation

Aug 25, 2023 212 likes •571 views

Utility value of management tools Advanced Herd Management Anders Ringgaard Kristensen What kind of tools? Complex systems Not just single pieces of information Management information systems Bedriftslsningen

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Utility value of management tools

Advanced Herd Management Anders Ringgaard Kristensen

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What kind of tools?

Complex systems

Not just single ”pieces of information”

Management information systems

”Bedriftsløsningen” ”E-kontrol”

Monitoring tools

FarmWatch

Decision support tools

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Why do we want to evaluate?

Farmers who consider to buy a system would like to know the expected benefit Developers who wish to sell a system would like to be able to demonstrate the benefit Only very little research has been done in this field

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Basic problems

Value of single ”pieces of information” is difficult to assess. Secondary effects

Positive: Increased focus Negative: Decreased focus in other areas

The farmer perhaps doesn’t use the system in an

  • ptimal way.

Interactions production system/farmer/tool No control (what would have happened without the tool?)

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Methods (Verstegen et al. 1995)

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Methods (Verstegen et al. 1995)

Normative approaches

Decision theoretical approaches

Decision tree analysis Baysian Information Economics Control Theory

Decision analytical approaches

Simulation Linear and dynamic programming

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Methods (Verstegen et al. 1995)

Normative approaches

Decision theoretical approaches

Decision tree analysis Baysian Information Economics Control Theory

Decision analytical approaches

Simulation Linear and dynamic programming

Not value

  • f tools
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Methods (Verstegen et al. 1995)

Normative approaches

Decision theoretical approaches

Decision tree analysis Baysian Information Economics Control Theory

Decision analytical approaches

Simulation Linear and dynamic programming

Not value

  • f tools

Examples

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Dynamic programming

1 333 1 299 1 327 1 304 ” , DKK/(1000 kg milk) 38 59 35 50 Annual replacement % 3b 3a 2 1 9 319 9 544 9 150 9 236 Net ret., DKK/cow/year 101.3 96.4 102.7 100.0 Number of cows 25 21 28 25 Average week of replac. 6 991 7 350 6 896 7 082 Milk yield, kg/cow/year Policy

Kristensen & Thysen (1991)

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Dynamic programming

Validity

What would the farmer do without the tool? Would he/she follow the recommandations? Are the registrations correct? External validity:

Model versus real world The tool tests itself Bias for optimal policy

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Simulation (Markov chain)

Jalvingh et al. (1992)

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Simulation (Markov chain)

Validity

What would the farmer do without the tool? Would he/she follow the recommandations? Are the registrations correct? External validity:

Model versus real world The tool tests itself Bias for optimal policy

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Simulation (Monte Carlo)

Jørgensen & Kristensen (1995)

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Simulation (Monte Carlo)

Validity

What would the farmer do without the tool? Would he/she follow the recommandations? Are the registrations correct? External validity:

Model versus real world The tool does not tests itself No bias for optimal policy

The preferred normative approach

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Empirical (”positive”) approaches

Verstegen et al. (1995):

Experimental designs

Field experiments Experimental Economics

Quasi-experimental designs Nonexperimental designs

Use of data from herds

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Classification of designs

PO PP TS No control NPO NPP NTS Nonequivalent Control (N) TPO TPP TTS True control (N) Posttest

  • nly (PO)

Pretest- posttest (PP) Time series (TS)

Verstegen et al. (1995)

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Designs

No control:

Only farms using the tool are included in the study

Nonequivalent control (quasi-experimental design):

A control group is included in the study afterwards As equal as possible to the farms using the tool

True control (experiment in the usual sense)

Farms are randomly divided into two groups

One group is told to use the tool The other group is not allowed to use it

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Classification of designs

PO PP TS No control NPO NPP NTS Nonequivalent Control (N) TPO TPP TTS True control (N) Posttest

  • nly (PO)

Pretest- posttest (PP) Time series (TS)

Verstegen et al. (1995)

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PO: Posttest only

Not serious!

Result Time

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Classification of designs

PO PP TS No control NPO NPP NTS Nonequivalent Control (N) TPO TPP TTS True control (N) Posttest

  • nly (PO)

Pretest- posttest (PP) Time series (TS)

Verstegen et al. (1995)

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NPO/TPO: Posttest only

Manipulation

Confounding between farmer type, production system and use of tool Result Time } Effect

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Classification of designs

PO PP TS No control NPO NPP NTS Nonequivalent Control (N) TPO TPP TTS True control (N) Posttest

  • nly (PO)

Pretest- posttest (PP) Time series (TS)

Verstegen et al. (1995)

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PP: Pretest and posttest

Manipulation

Perhaps a general trend: All farms may have improved as those being investigated Confounding between general development and effect of tool

Result Time } Effect

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Classification of designs

PO PP TS No control NPO NPP NTS Nonequivalent Control (N) TPO TPP TTS True control (N) Posttest

  • nly (PO)

Pretest- posttest (PP) Time series (TS)

Verstegen et al. (1995)

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NPP: Pretest and posttest

Correction for

General trend Confounding with farmer type (partially, no randomization)

Result Time } Effect

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Classification of designs

PO PP TS No control NPO NPP NTS Nonequivalent Control (N) TPO TPP TTS True control (N) Posttest

  • nly (PO)

Pretest- posttest (PP) Time series (TS)

Verstegen et al. (1995)

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TPP: Pretest and posttest

Correction for

General trend Confounding with farmer type (randomization)

Result Time } Effect

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Classification of designs

PO PP TS No control NPO NPP NTS Nonequivalent Control (N) TPO TPP TTS True control (N) Posttest

  • nly (PO)

Pretest- posttest (PP) Time series (TS)

Verstegen et al. (1995)

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TS: Time series, no control

Confounding with farmer type Development over time

Value in the beginning versus full value

Result Time

} Effect

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Classification of designs

PO PP TS No control NPO NPP NTS Nonequivalent Control (N) TPO TPP TTS True control (N) Posttest

  • nly (PO)

Pretest- posttest (PP) Time series (TS)

Verstegen et al. (1995)

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NTS: Time series, control

Development over time

Value in the beginning versus full value

No confounding with farmer type

Result Time

}

Effect: b - a

a b

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Classification of designs

PO PP TS No control NPO NPP NTS Nonequivalent Control (N) TPO TPP TTS True control (N) Posttest

  • nly (PO)

Pretest- posttest (PP) Time series (TS)

Verstegen et al. (1995)

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TTS: Time series, true control

Development over time

Value in the beginning versus full value

No confounding with farmer type

Result Time

}Effect

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Example: NTS

Value of a management information system for sow herds

Response: Piglets/sow/year Nonequivalent control Time series