Feeding innovation – Update on the feed innovation toolkit and where we are with FEAST and Techfit

Feeding innovation – Update on the feed innovation toolkit and where we

are with FEAST and Techfit Alan Duncan

Feeding Innovation - Stocktaking workshop on a Feed Innovation Toolkit for Livestock in the tropics

Dak Lak, Vietnam, 22-24 September 2014

Feed interventions often don’t work – why?

Silos

Scientists work alone in their plots

The extra NPN in the straw will provide better microbial growth

which will improve digestibility as well as intake….

Extensionists and farmers speak apart

All that extra work for a handful of

straw. What if that chemical kills my

cow?

Extensionists and farmers speak apart

The extra NPN in the straw will provide better microbial growth

which will improve digestibility as well as intake….

Extensionists and farmers speak apart

All that extra work for a handful of

straw. What if that chemical kills my

cow?

The extra NPN in the straw will provide better microbial growth

which will improve digestibility as well as intake….

Land

Labour

Knowledge

Cash Inputs

Animals need a lot of support

Feed interventions often do not work – why?

• Failure to place feed in broader livelihood context

• Lack of farmer design and ownership

• Neglect of how interventions fit the context: land, labour, cash, knowledge etc

FEAST

Techfit

FEAST

The problem

Feed assessment

• Conventionally focuses on: – The feeds

– Their nutritive value

– Ways of improving nutritive value

• FEAST broadens assessment: – Is livestock an important livelihood strategy?

– How important are feed problems relative to other problems?

– What about labour, input availability, credit, seasonality, markets for products etc.?

How does FEAST work?

• Overview of farming system and livestock feed aspect

• Milk marketing, veterinary services

• Major problems for livestock production

1. Farmer centred diagnosis

• Quantitative information on crop-livestock production, feed availability, feeding rations

• Qualitative information - perception on feed quality

2. Individual farmer survey

• Enter data in FEAST template

• Based on result develop ideas for intervention

3. Data analysis and developing interventions

Farmer centred diagnosis

• General description of farming system e.g. – farm labour availability – annual rainfall pattern – types of animals raised by households

• General description of livestock production e.g. – types of animals raised – purpose of raising these animals (e.g. draught,

income, fattening, calf production) – general animal husbandry (including; management,

veterinary services and reproduction). – ease of access to credit and inputs

• Problem identification and potential solutions

Quantitative questionnaire

• Quantitative information on livestock production e.g. – Animals – livestock inventory – Crops - yields and areas to derive crop residue availability – Cultivated forages – yields and areas – Collected fodder: proportion of diet – Purchased feed – Grazing: proportion of diet – Contributors to household income – Production.

• Milk production • Sale of livestock

– Seasonality. • Feed supply: overall seasonal availability • What is fed in different months?

Sample output

32%

22%

20%

14%

6%

6%

Contribution of livelihood activities to household income (as a percentage)

Agriculture

Livestock

Remmitance

Labour

Others

Business

More sample output

Crop residues5%

Cultivated fodder

25%

Grazing30%

Naturally occurring and

collected33%

Purchased7%

DM content of total diet

Final output

• Feast report with some ideas for key problems and solutions

• Better links and understanding between farmers, research and development staff

www.ilri.org/feast

Techfit

The problem

What is your main problem

Extensionist talks to farmers

What is your main problem

Feed

Farmer responds

What feed technologies

have you got?

Extensionist approaches scientist

What feed technologies

have you got? Planted forage

Urea treated straw Bypass protein

Scientist offers what he has

What feed technologies

have you got? Planted forage

Urea treated straw Bypass protein

OK, let’s try those

Extensionist takes what’s offered

A solution

Techfit

• A discussion support tool for prioritizing feed technologies

Key context attributes

Land

Labour

Credit

Input

Knowledge

Key technology attributes

Land

Labour

Credit

Input

Knowledge

The core concept

Key context attributes

Land

Labour

Credit

Input

Knowledge

Key technology attributes

Land

Labour

Credit

Input

Knowledge

x = Score

Matching context to technology

Technology filter

Scope for

improve

ment of

attribute

s

Context

relevanc

e (score 1-

6; low-

high))

Impact

potential

(score 1-

6; low-

high)

Total

score

(context

X impact)

Requ

Score 1-3

(1 for

more;

3 for

less)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

more;

3 for

less)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Score 1-5

(1 for

less and

5 for

more)

Urea treatment

of straw2 3 6 3 2 2 2 2 0

Supplement with

UMMB2 5 10 3 3 3 2 1 1 1 1 3 1 2 22

By-pass protein

feed1 3 3 3 3 1 1 3 0

Feed

conservation

(surplus)

(HAY)

4 3 12 3 3 2 2 3 3 3 3 3 3 1 41

etc

etc

III.

TECHNOLOGY

FILTER

(Technology

options to

address

quantity,

quality,

seasonality

issues)

Pre-select the obvious

(5-6) based

on context relevance

and impact potential

Score the pre-selected technologies based on the requirement, availability and scope for

improvement of five technology attributes

Attribute 1:

Land

Attribute 2:

Labour

Attribute 3:

Cash /credit

Attribute 4:

Input delivery

Attribute 5:

Knowledge

/skill

Total

Score

Technology filter

Scope for

improve

ment of

attribute

s

Context

relevanc

e (score 1-

6; low-

high))

Impact

potential

(score 1-

6; low-

high)

Total

score

(context

X impact)

Requ

Score 1-3

(1 for

more;

3 for

less)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

more;

3 for

less)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Score 1-5

(1 for

less and

5 for

more)

Urea treatment

of straw2 3 6 3 2 2 2 2 0

Supplement with

UMMB2 5 10 3 3 3 2 1 1 1 1 3 1 2 22

By-pass protein

feed1 3 3 3 3 1 1 3 0

Feed

conservation

(surplus)

(HAY)

4 3 12 3 3 2 2 3 3 3 3 3 3 1 41

etc

etc

III.

TECHNOLOGY

FILTER

(Technology

options to

address

quantity,

quality,

seasonality

issues)

Pre-select the obvious

(5-6) based

on context relevance

and impact potential

Score the pre-selected technologies based on the requirement, availability and scope for

improvement of five technology attributes

Attribute 1:

Land

Attribute 2:

Labour

Attribute 3:

Cash /credit

Attribute 4:

Input delivery

Attribute 5:

Knowledge

/skill

Total

Score

Technology filter

Scope for

improve

ment of

attribute

s

Context

relevanc

e (score 1-

6; low-

high))

Impact

potential

(score 1-

6; low-

high)

Total

score

(context

X impact)

Requ

Score 1-3

(1 for

more;

3 for

less)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

more;

3 for

less)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Score 1-5

(1 for

less and

5 for

more)

Urea treatment

of straw2 3 6 3 2 2 2 2 0

Supplement with

UMMB2 5 10 3 3 3 2 1 1 1 1 3 1 2 22

By-pass protein

feed1 3 3 3 3 1 1 3 0

Feed

conservation

(surplus)

(HAY)

4 3 12 3 3 2 2 3 3 3 3 3 3 1 41

etc

etc

III.

TECHNOLOGY

FILTER

(Technology

options to

address

quantity,

quality,

seasonality

issues)

Pre-select the obvious

(5-6) based

on context relevance

and impact potential

Score the pre-selected technologies based on the requirement, availability and scope for

improvement of five technology attributes

Attribute 1:

Land

Attribute 2:

Labour

Attribute 3:

Cash /credit

Attribute 4:

Input delivery

Attribute 5:

Knowledge

/skill

Total

Score

Technology filter

Scope for

improve

ment of

attribute

s

Context

relevanc

e (score 1-

6; low-

high))

Impact

potential

(score 1-

6; low-

high)

Total

score

(context

X impact)

Requ

Score 1-3

(1 for

more;

3 for

less)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

more;

3 for

less)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Requ

Score 1-3

(1 for

high;

3 for low)

Avail

Score 1-3

(1 for

less;

3 for

more)

Score 1-5

(1 for

less and

5 for

more)

Urea treatment

of straw2 3 6 3 2 2 2 2 0

Supplement with

UMMB2 5 10 3 3 3 2 1 1 1 1 3 1 2 22

By-pass protein

feed1 3 3 3 3 1 1 3 0

Feed

conservation

(surplus)

(HAY)

4 3 12 3 3 2 2 3 3 3 3 3 3 1 41

etc

etc

III.

TECHNOLOGY

FILTER

(Technology

options to

address

quantity,

quality,

seasonality

issues)

Pre-select the obvious

(5-6) based

on context relevance

and impact potential

Score the pre-selected technologies based on the requirement, availability and scope for

improvement of five technology attributes

Attribute 1:

Land

Attribute 2:

Labour

Attribute 3:

Cash /credit

Attribute 4:

Input delivery

Attribute 5:

Knowledge

/skill

Total

Score

Current Techfit filters

• Core Feed issue (Quantity/Quality/Seasonality)

• Core commodity (Cattle fattening, dairy etc)

• Farming system (pastoral, agro-pastoral, mixed, landless)

• Core context attributes (land, labour, cash, inputs, knowledge, water)

• Impact (only interventions are scored, not context)

Cost-benefit assessment

• What does the technology cost?

– Inputs, labour, land etc?

• What does the technology deliver?

– Enhanced milk yield, improved reproductive performance, better growth etc

• Does it make sense?

Final output

• Ideas for some promising feed interventions that might work

• Better understanding of why the usual suspects often don’t work.

FEAST evolution

Originally developed at cross-country workshop in Hyderabad, 2009

Historical refinements

• Luke York – worked on original Excel sheet

• Ephraim Getahun/Addis Mulugeta – produced macro-driven version

• Arindam Samaddar – developed problems and solutions approach

• Ben Lukuyu – extensive field testing and training

• Peter Ballantyne – popularizing and shepherding the evolution

New initiatives

• FEAST Aggregator

– Allows individual FEAST excel sheets to be imported

– Aggregated data from many FEAST assessments can be downloaded

– Will provide global database of FEAST data

New initiatives

• FEAST Learning Materials

– Training presentations

– Video clips

– Instructions for hosting FEAST training

– Enhanced manuals

Participants in the ILRI-ICRISAT FEAST and Techfit training workshop 27-30 Nov 2013

Also trainings in Addis, Botswana …..

Ethiopia, 90

Kenya, 34

India, 29

United States, 22

France, 11

Tanzania, 11Uganda, 11Nigeria, 9Bangladesh, 8Pakistan, 8

Germany, 7Indonesia, 7

Netherlands, 7Rwanda, 7

United Kingdom, 7

Zambia, 7

Other, 155

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NGO

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Downloads by month

Techfit evolution

Steps

• Two pager from Steve Staal

• Dehra Dun workshop – Sept 2011

– Introduced general concept and developed preliminary tool

• Addis Ababa workshop – Mar 2013

– Refined technology list

• Addis Ababa workshop – May 2013

– Detailed scoring of technologies

Dehra Dun workshop – Sept 2011

• Introduced general concept

• Group work to come up with Context Attributes – 20 plus

• Preliminary list of technologies

• Some experimentation with scoring methods

Addis Ababa workshop - Mar 2013

Addis Ababa workshop - Mar 2013

• In groups we covered: – cost-benefit analysis approaches

– the 'pre-filters‘

– the 'scope for impact' measure

– the technology/interventions scoring

– the 'context' scoring

– approach/instrument

– what to improve in the tool - design, functionality ...

• Some significant developments were: – more filters

– the tool helps to prioritize interventions, not just technologies

– CBA needs to be piloted to discover how to really use it

– the intervention list was extended and refined

– TechFit and FEAST can be adapted to better fit each other

Addis Ababa Techfit Development Meeting - May 2013

Addis Ababa workshop - May 2013

• Areas worked on included: – Adoptability component

– Finalising the intervention expert scoring

– Initial template for intervention 'factsheets' (or decision-sheets)

– Ideas to adapt FEAST to generate context scores for Techfit

– CBA approach

– TechFit Manual

Actions from Addis Ababa - May 2013

Task Responsible Status Overall coordination, budgets etc

Alan, Peter Thorne, Michael Blummel

Ongoing

Generate updated overall process/flow diagram

Alan Done. May also need description of overall scope/boundaries

Modify FEAST tool to generate 'context score of attributes and filters' for Techfit

Alan, Ben, Jane, Brigitte Done by Ben in April 2014

Update FEAST materials online

Done as part of Iddo's training material work

Test 'new' FEAST with techfit Not yet finalized - Gregory Sikumba

Create online FEAST aggregator

Beta version online - Addis Mulugeta

FEAST ‘user meeting’ Brigitte Partly this meeting

Finalise an 'adoptability' protocol and process description/checklist

Peter T, Brigitte, Biruk ???

Task Responsible Status

Devise/Finalise/Test a ‘rapid’ easy to use CBA approach/tool

Isabelle, Padma Partly done - Padmakumar. Still needs some work

Set up some CBA pilots (a few interventions, across species/filters, easy/not easy)

Nicholas, Barbara, Isabelle, ...

Not done

Finalise the expert scoring of interventions

Werner, Alan, Adugna, Harinder, others

Completed - July 2013 Werner, Adugna others

Capture reasoning, document scoring process, finalise all row and column descriptions

Partly done - Werner

Sensitivity analysis and Testing Eduardo, Jane Poole Some preliminary thoughts - Eduardo

Develop a manual Padma, Adugna, Keith Not done … fact sheets

Devise next generation tool design

PeterT, Alan, Padma, Nils Partly done - Nils, Padma

Techfit testing in different projects and locations

Ethiopia, Tanzania, India - Padma, Jane, Gregory/Ben

Actions from Addis Ababa - May 2013

New initiatives

• Techfit score sheets - Werner

– A score sheet for each intervention giving basic details of what is involved

– Draws on Techfit scores to help users to see where the intervention might work

New initiatives

• Techfit scoring – Nils

– Finding a way of combining scores to come up with a more useful and realistic prioritized list

New initiatives

• Ration balancing methods

– Various least-cost feed formulation programmes are around

– Smallholder farmers are often too small scale to justify the costs of a tailored approach

– link to FEAST and Techfit?

– Use FEAST to cluster farmers to reduce cost per farmer and allow general recommendations

New initiatives

• FEAST and Techfit report inventory

Links

• http://techfit.wikispaces.com

• http://feed-tool.wikispaces.com

• www.ilri.org/feast

• www.ilri.org/feastaggregator

• http://fodderadoption.wordpress.com

The presentation has a Creative Commons license. You are free to re-use or distribute this work, provided credit is given to ILRI.

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