IFPRI, NEW DELHI

Impact of Capacity Building Under NAIP

6-7 June 2014

NASC Complex, New Delhi

Outline

• Background and Objectives

• Typology and Profiling

– Budget and Scope; Participating Institutions; Spread of Trainees by SMDs, Themes and Sub-themes; Trainees Profile; Destination Mapping and Top

Mentors /Facilitators

• Impact Assessment

– International Training - Attitudinal Changes; Benefits in terms of publications, technology, IPRs, Proposals, New Projects etc.;

– Cost and Benefits – Some case studies

– National Training – Some reflections

– Leadership Management Program – Utility and follow-up

• Conditions for Success of Capacity Building Programmes

• Suggestions and Way Forward

2

Background, Objectives and Framework

3

Background

• ICAR continuous to invest in capacity building (CBPs)

in frontier areas

• CBPs in deficit/frontier areas of contemporary

relevance and anticipated future

• Some flagship programmes:

Summer & Winter schools (SWSs))

Centre of Advanced Faculty Training (CAFTs)

Externally Aided Projects (like AHRD, NATP, NAIP, etc.)

11th Plan - ICAR sponsored 588 SWSs and CAFTs benefitting about 11000 scientists and faculty of NARS

Capacity Building Program under NAIP

• NAIP (launched 2006) - Contributes to the sustainable

transformation of agricultural research system

• NAIP has 4 components; and a part of first component

focuses on human resource development

• Overall objective of CBP was to enhance technical

capacity of NARS:

Predetermined 27 frontier areas of agricultural sciences in

advanced labs all across the world

Key objectives of the study

• Describe typology of CBP, trace input allocation, investments and outputs of thematic and research skills developed

• Document costs, benefits, productivity and efficiency gains of CBP

• Undertake a few case studies to assess potential of technological innovation as a result of CBP

• Document evidence of collaborative research programs and networks developed as a result of CBPs

• Document conditions for success of CBP and the way forward

Framework for Impact assessment

7

STEP 1: BENEFICIARIES OF THE PROGRAMS

Direct beneficiaries Indirect beneficiaries

STEP 2: OUTPUTS FROM THE

TRAINING PROGRAMS

STEP 3: OUTCOMES FROM

THE TRAINING PROGRAMS

8

Survey Group Sample Responses

Received

1. International Training

participants

337 178

2. Control Group (non-trained

scientists)

500 164

3. Heads of the

institutes/universities

90 12

4. National Training participants 600 30

Framework for Impact assessment contd..

Typology of Capacity Building Program

9

Highlights – Budget and Scope

10

91.33crores

L&CB

487

Trainees

7.86 Lacs

per Trainee

23

Countries

122

Institutions

6

Core Themes

27

Sub-Themes

38.26 crores (42%)

International Training

94%12 weeks Training

6%2-3 Weeks

Training

Distribution of Training Duration

Basic Sciences

Processing Technology

Biosecurity

Climate Change

Informatics

Social Science and Policy

11

122

Total Institutes

75%

ICAR Inst.

25%

SAUs

7%

Trainees From IARI

19%

Trainees

81%

Trainees

Top SAUs Participated3% UAS, Raichur

3% TN Vet and AS University, Chennai

2% PAU, Ludhiana

2% CSK , Palampur

Participating Institutions

Spread of Trainees by Subject Matter Divisions

12

Social-Sc

Engg

NRM

Fish

Animal-Sc

Crop-Sc

Hort

6%

8%

10%

14%

19%

20%

23%

SMD Horticulture Biggest Gainer followed by Crop Sciences

Trainees Profile: Designation (%) and Age / Experience (years)

13

Scientists / Asst. Prof.

24

Sr. Scientists / Assoc. Prof.

63

Principal Scientists /

Prof. 13

Age - 41 Exp. - 13

Senior Scientists a Major Lot

Age - 36 Exp. - 8

Age - 46 Exp. - 19

Female, 19%

Male, 81%

Female, 19%

Male, 81%

Female, 22%

Male, 78%

14

Gender of Trainees

All Trainees

ICAR SAUs

USA + Canada (70 + 3)

UK+ EU (8+9)

AU+NZ (4)

SEA (4)

EU – UK, Germany, France, Italy, Sweden, DenmarkSEA – Singapore, Malaysia, Thailand, PhilippinesOthers – Syria, Peru , Columbia, Mexico, Chile

Destination Mapping : Distribution of Trainees (%) : Countries & Institutions

16

Basic Sciences 48

Processing Technology

18

Biosecurity 10

Climate Change 8

Informatics 8

Social Science and Policy

8

Distribution of Trainees (%) by Core Theme Areas

17

Marker Asst. Selection 19

Carbon Trading 7

Bioinformatics 5

Nutraceuticals 5

Allele Mining 5

Biomolecules 5IPR 5

Fermentation Tech 4

Nanotech 4

Sensor Based Apps 4

Other Sub-Theme Areas

37

Distribution of Trainees (%) by Sub-Theme Areas

18

Our Top Mentors /Facilitators

Impact Assessment

–Trainees’ Perception

19

Trainees’ Perception about training program

20

•Training objectives met (92%)

•Training very comprehensive (82%)

• Training content directly relevant to area of work (82%)

Impact on skill development - research, communication and linkage & network

Research/ Technical

• Inspired new research ideas (94%)

• Learnt, which is immediately applied to current work 80%)

Presentation/Writing

• Improved presentation/writing skills (65%)

Linkage & network

•Develop linkages at universities/ institutes visited (33%)

Impact on attitudinal change

Motivational Change

• More motivated to do their job (83%)

Confidence Building

• More confident in their position (86%)

Expectations at work place

• Increased expectations from trainee, at work (85%).

Impact on Trainees’ level-productivity, efficiency and effectiveness

23

Efficiency

• More efficient at work (86%)

Productivity

• Increase in productivity (86%)

Effectiveness

• Increase ineffectiveness of trainees in their current organisation (86%)

24

Impact Assessment

– Trainees’ level

Indicators of benefits/outcomes of CBPs in terms of output index in pre and post training period

Note:-Technologies developed are defined application of techniques for improving productivity through

developing new varieties/breed. Possible technologies are:- prototype, genetic/stock, variety/breed, product,

vaccine, diagnostic kit, process, methodology/technique.

100 100 100 100 100 100 100 100 100

162

136 135 133

117113

109 107 107

0

20

40

60

80

100

120

140

160

180

ProjectProposals

submitted tonon-ICAR

Journalarticles

accepted forpublication

Patentssubmitted

ProjectProposalssubmitted

Journalarticles

accepted forpublication asa first author

ProjectProposals

submitted toICAR

Technologiesdeveloped as

a CO-PI

Technologiesdeveloped as

a PI

Technologiesdeveloped asa PI & CO-PI

Index pre training Index post training

Outputs Post-training incremental gains in output(%)

Journal articles • Bio-security/conservation (50%)

• Informatics (77%)

• Processing technology (45%)

• Basic Sciences (34%)

Technologies developed • Bio -security/conservation (6%)

• Processing technology (15%)

• Basic Sciences (4%)

Patent submitted • Processing technology (5%)

• Basic sciences(12%)

Project proposals submitted • Basic Sciences (13%)

• Informatics (33%)

Message: Biosecurity/conservation, Basic sciences, Processing

Technology & Informatics have gained more

Theme-wise benefits: publications, project proposals, technological innovations & patents submitted……….cont….

Outputs Post –training incrementalgains in output (%)

Journal articles • USA (32%)

• Others (48%)

Technologies developed

• Others (7%)

• USA (9%)

Patent submitted • Netherlands (100%)

• USA (75%)

Project proposals submitted

• Netherlands (50%)

• USA (23%)

Message: Training-location – Trainees trained at USAhave gained more with respect to outputs

Training Location –wise analysis of benefits: publications, project

proposals, technological innovations & patents submitted……….contd.

Outputs Post-training incremental gains in output(%)

Journal articles • Horticulture (68%)

• Fisheries (12%)

• NRM (33%)

Technologies developed

• Crop Sciences (24%)

• Horticulture (33%)

• NRM (32%)

• Fisheries (24%)

• Animal Sciences (5%)

Patent Submitted • Agricultural Engineering (30%)

Project Proposals submitted• Crop Sciences(68%)

• Horticulture (2%)

Message: Horticulture, Crop Sciences and NRM

Management have more gains with respect to outputs

Division analysis of benefits: publications, organizing events, project proposals, technological innovations & patents submitted……….contd.

Outputs Post –training incrementalgains in output(%)

Journal articles • Scientist/Assistant professor (51%)

• Senior scientist/Associate professor (26%)

Technologies developed

• Scientist/Assistant professor (32%)

• Senior scientist/Associate professor (56%)

Patent submitted • Senior Scientist/Assistant professor (80%)

• Principal scientist/professor (22%)

Project Proposalssubmitted

• Senior scientist/Associate professor (10%)

• Principal scientist/professor (23%)

• Senior scientist/Associate Professor have gained more with respect to journal articles accepted forpublication, followed by technologies developed, patent and project proposal submitted.

• Principal scientist/Professor have gained more with respect to patent and project proposalssubmitted.

Designation –wise analysis of benefits: publications, project

proposals, technological innovations & patents submitted……….contd.

Outputs Post –training incremental

gains in output(%)

Journal articles • 12 weeks (41%)

Technologiesdeveloped

• <12 weeks (15%)

Patent submitted • 12 weeks(42%)

Project proposals submitted

• 12 weeks(24%)

Message: Duration- Trainees underwent training for 12weeks (3 months) had more gains with respect to outputs.

Duration –wise analysis of benefits: publications, project proposals, technological innovations & patents submitted……….contd.

Outputs Post- training incremental

gains in output(%)

Journal articles • 35-40years (43%)

Technologies developed • <35 years(52%)

• 35-40 years(31%)

Patent submitted • 40-45 years(91%)

Project Proposals submitted • 40-45years(46%)

Message:

• Trainees with age of < 35 years and 35-40 years had gained with respect to

journal articles accepted for publication and technologies developed.

• Those of >40 years had gained more with respect to patents and project

proposals submitted.

Age-wise analysis of benefits: publications, project proposals, technological innovations & patents submitted……….contd.

System Wide/Institutional Impact

32

33

Impact of training at institution –

level – impact more in SAU

• Immediate application of training skills in

current work area

• High impact on presentation/writing skills

• High impact on networking / linkage

skills to enhance research

34

Impact of training at institution –

level -impact more in ICAR

• More number of trainees submittingjournal articles for publication

• Application of techniques learnt at trainingin developing new project proposals

• More joint publications with supervisors

35

Connections leading to Collaborations

Message:

• Developed connections

resulting in a collaborative

projects (55%)

Message

• Trainees initiated

communication resulting in a

collaborative project (47%)

• Organisations initiated

communication resulting in a

collaborative project (8%)

Professional recognition - Awards and promotions received post-training

Message:-

• Awards received

(27%)

• Institutional award

(17%)

• National award(7%)

• State-level award

(3%)

Message:-

• Promotions (35%)

Journal impact factor rating pre and post training (NAAS Rating)

Message:

Post training, the average capacity the scientists of publishing in high rated journals had increased. The figure indicates that

scientists had published papers in journal articles with rating 1-4.9 but post-training, they had been able to published more in

journal articles with rating 5-10.9.

0

0.2

0.4

0.6

0.8

1

1.2

11-11.9 12-12.9 14-14.9

Number of

papers published

pre-training

Number of paper

published post-

training

0

5

10

15

20

25

30

1-1.9 2-2.9 3-3.9 4-4.9 5-5.9 6-6.9 7-7.9 8-8.9 9-9.9 10-10.9 11-11.9 12-12.9 13-13.9 14-14.9

Percentage of papers published by the scientists in the respective journal impact factor category before training

Percentage of papers published by the scientists in the respective journal impact factor category after training

Benefit and Cost – Some Case Studies

38

Framework

7

Frontier Science Areas

11

Scientists

Marker Assisted

Selection

Fermentation

Tech

Nanotechnology

Genome RC

Carbon Trading

Nutraceuticals

Allele Mining

Science

Conventional Technology(Control)

New Technique Learnt

(Treatment)

Multiple Gains from New

Technology

Time

Convenience

Precision

Efficiency

Probability

Economy

Productivity

Profitability

Profitability

40

Theme

(number of scientist)

Conventional

Technology

New technology / Tool

Learnt

Product Application Average

B-C Ratio

Marker Assisted

Selection (123)

Phenotypic

Selection

Marker Assisted

Selection

HY Cattle Cattle

Improvement

11.35

PB - 1121 MAS (Disease

Resistant)

Disease

Resistant PB

Rice

Improvement

9.32

PB - 1121 MAS (Salt Tolerance) Salt Tolerant PB Rice

Improvement

9.31

Nanotechnology

(19)

Biochar Nano-patterning Nano-biochar Fertilizer

Economy

1.95

Photo

degradable

polymer

Bio-based polymer Biobased

polymeric films

Packaging 1.13

Conventional

nano-fibre

Nano-fibre (electro-

spinning technique)

Cellulose

nanofibre

Water/air filters 1.25

Fermentation

technology (15)

Conventional

Nisin

production

Improved Nisin

production

Nisin (biological

preservative)

Bio-

preservative

1.40

Bio-ethanol Improved Bio-ethanol Cellulosic

ethanol

Bio-ethanol 1.15

Benefit- Cost Ratio – Case Studies (1)

Figures in brackets indicate number of trainees.Note: Details worked out after discussion with the concerned/selected trained scientist/s. B-C ratios estimated with needed assumptions, being further checked and subjected to sensitivity analysis

41

Theme

(number of scientist)

Conventional

Technology

New technology /

Tool Learnt

Product Application Average

B-C Ratio

Carbon Trading /

Sequestration

(19)

IPCC Tire – I IPCC Tire – II and III Carbon Credits Carbon Trading 1.85

IPCC Tire – I IPCC Tire – II (GC –

for estimation of

GHGs)

GHG reduction

factors

GHGs

accounting /

inventory

2.52

Genome Resource

Conservation (13)

Genetic analysis

(w.o

automation)

Automation in

Genetic Analysis

(automation)

All economic

traits

Crop/ Animal

Improvement

3.88

Genome Resource

Conservation (Hort.)

Conventional

Breeding

DNA Marker Analysis Hybrid Crop

Improvement

1.009

Nutraceutical

(Fisheries)

(20)

Chemo-therapy

/ anti-biotics

Nutraceutical Nutraceuticals

Fish

Shrimp / Fish

Feed

1.17

Allele Mining

(14)

SSH cDNA library Microarray Identification of

special Genes

Shrimp / Fish

Feed

25 times

cost

efficient

Benefit- Cost Ratio - Case Studies (2)

Figures in brackets indicate number of trainees.Note: Details worked out after discussion with the concerned/selected trained scientist/s. B-C ratios estimated with needed assumptions, being further checked and subjected to sensitivity analysis

Thank you all

Dr. A. R. Rao, IASRI

Dr. Mukesh Kumar Rana, NBPGR

Dr. Manish Srivastava, IARI

Dr. (Ms.) Anju Arora, IARI

Dr. (Ms.) Sunita Singh, IARI

Dr. (Ms.) Sangeetha Lenka, IISS

Dr. M. S. Sekar, CIBA

Dr. Ambasankar, CIBA

Dr. Sachin Dey, NDRI

Dr. Sandip Gangil, CIAE

Dr. Vigneswaran, N., CIRCOT

Dr. A.K. Singh, IARI

Dr. Vij, NBAGR 42

National Trainings-Impact Assessment

43

44

National Training – Benefit Streams

18% change in journal articles accepted for publication and accepted as

a first author

30% change in journal articles accepted for publication in subject area

trained

OutputsAverage output

pre-trainingAverage output post-

training% change in

output

Journal articles accepted for publication 0.6 1.65 18

Journal articles accepted for publication as a first author 0.25 0.7 18

Journal articles accepted for publication in subject area trained 0.05 0.2 30

Annual reports/conference proceedings published as a first editor 0.3 0.35 2

45

Research/ Technical Skills

• Training objectives were met (100%)

• Training inspired new research ideas (85%)

• Training was complete and comprehensive(74%)

• More efficient at work (75%)

Presentation/Writing Skills

• Improved presentation/writing skills (65%)

Linkage & network skills

• Develop connections & linkages (55%)

Analysis of Skills - research, communication and linkage & network

Leadership Management Program – Reflections

Leadership Management Program – Outputs and Outcomes

Skills developed/improved

• Decision making skills• Management skills• Communication skills

• Useful in problem solving

• Better understanding of leadership process

• Developing a leadership plan for long-term perspective with effective utilization of institute resourcesFollow-up Actions

• Skills to be used for better research management process• Training modules developed for grassroots level workers and

stakeholders• Efficiency improved in managing programs• Collaborations developed

OUTPUTS

OUTCOMES

Response from Directors and Mentor/Facilitators

48

Response - Directors/Heads of the ICAR institutes & VCs of SAUs.

Research/Technical skills improved

• Analytical skills improved

• Improvement in formulating better project proposals

• Technical capacity improved (through new techniques learned)

Soft skills development

• Peer interaction improved

• Motivation improved• Communication skills

improved• Confidence to conduct

quality research• Special skills to do

demand driven research

Linkages developed

• International contacts developed

• Interactions with global knowledge resource

OUTCOMES

IMPACT

New Projects Initiated

Publishing reports

Help in current projects

Long-run projects planned to maintain

relations with global institutions

International Trainings

50

Director’s Evaluation of Impact of National Training

Broadened knowledge base and

forged linkages outside NARS system

Many externally projects are being

obtained

Establishing linkage with

private sector facilitated

Some examples of inter institutional

collaborations during CBP

51

Example 1

Example 2

• IARI • CSRI• ICAR• NRC on Seed Spices • CIAH • CSKHPKV • IIHR

MICHIGAN STATE UNIVERSITY

ICAR INSTITUTES

Conditions for Success and Way forward(based on our study findings and suggestions

from mentors/facilitators)

54

Selection criteria:

• Age- designation-education profile of trainee

“Young age- middle level- doctoral degree” combination more

potential for technology development

“Senior” level more suited for developing project proposals;

patents

• Gender balance

• Balancing ICAR and SAU scientists

• Pre training exposure to research

• Pre training publication

• Preference to proposals with innovative research ideas

• Preference to proposals that have better potential for

long-run collaborative research

Selection criteria, contd. ….

Selection criteria, contd. ….

• Preference to applicants who have identified a

faculty with similar research interests abroad

and initiated some contacts

• Preference to applicants who have their own

data/ samples to work on to ensure

accountability and ownership on output

57

Training design:

• Prioritize areas and themes for training

• Dovetail training duration to training purpose

Skill development – shortest duration

Updating expertise – medium duration (max. 12 weeks)

Frontier research – longest duration (min. 6 months)

• Orientation of trainees to acclimatize to foreign country conditions

Training design, contd. …..:

• Focus on quality and depth of training content

• More publications and project proposals during training

• Rewards for on-training publications

• Research project designed for long term collaborations between trainee and mentor (both at individual and institutional levels)

• Involvement with superiors in designing the training

Follow-ups/ monitoring:

• Post training follow-ups/ monitoring

Follow up on accomplishments using base line data

Faculty mentor travel back to monitor and assess progress

Mandatory output in terms of joint publications/continued research collaborations

Annual event for fostering networking among trainees on return to share experiences , assist is research and teaching

Post training multidisciplinary workshops.

Trained resource can be used for international / national

training in specific areas.

Creating central facility – investment intensive equipment –

Nanotech, MAS – to promote use of modern science

Attach trained resource to the industry for scaling up –

provide venture capital

Invest in periodic up-gradation of the skills of the trainees

61

Follow-ups/ monitoring , contd. ….

Implementation : • Flexible rules, regulations and policies

• Adequate physical space and facilities, infrastructure

including ICT

• Supportive leadership

• Encouragement from seniors and leaders

• Financial resources

Collaborative multidisciplinary research grants for long-runcollaborative research

Seed grants for short run collaborative research.

Financial supports to trainees during training like, bench fee, travelfunds etc.

62

Inventory :

• Generate discipline wise inventory

Resource persons (experts/mentors/facilitators/ trained scientists)

Training manuals

Suggestions and recommendations for future lines of work

• Inventory should be in the public domain – upload on ICAR website

63

Thank you

64