1. Gender in Dairy value chain in Bangladesh
SDVC Project
CARE Bangladesh
4-Nov’2011
Presented by:
Kakuly Tanvin
Toufique Ahmed

2. SDVC Gender Distribution- At a glance
Participants Total Number Women Avg. monthly income
(W #) participants
Participants 36400 (29745) 82% $13.27 (milk sales)
Producer Groups (Excluding pilot) 1162 (524) 45%
Farmer Leader 3425 (2443) 71%
Milk Collector 308 (28) 9% $8 ($36)
Livestock Health Worker 201 (45) 22% $81 ($246)
Input Shop (ISC 3,CAS 28) 150 (31) 21% ISC = 3($129),
CAS =28($ 30)
No of Savings group 568 82%
Total Savings $70444 82%
Independent cow ownership 217 (27) 12.4%

3. Targeting achievement
Producer Gender % Collector Gender %
Percentile distribution of participant by Percentile distribution of trained
Gender (Yr: 1-4) Collector by Gender (Yr: 1-4)
(Except Pilot)
Men Men
18% 91%
Women
82%
Women
9%
FL Gender % LHW Gender %
Percentile distribution of trained Farmer Percentile distribution of trained LHW by
Leader by Gender (Yr: 1-4) Gender (Yr: 1-4)
Men Men
29% 78%
Women Women
71% 22%

4. Objective of SDVC-GAAP initiative
• To explore and examine sustainable impacts on
women and men’s asset acquisition, ownership,
• Explore related impacts on household and
community gender dynamics of the Dairy Value
Chain project.

5. Project Methodology
Qualitative Analysis Includes
• Focused group discussion (FGD)
• Life History Analysis
• Women Barrier Checklist
• Use Daily time use tool
Quantitative analysis Includes
• Questionnaire interview
• Participatory Performance Tracking (PPT)
• Staff progress report

6. Activities Completed
 Analyzed existing data to ascertain knowledge gaps about gender
and assets
 Qualitative research tool has been developed and field tested.
 14 focus group discussions facilitated covering around 250 SDVC
producers.
 18 semi structured interview done with individual participants.
 2 separate gender related learning sessions was designed and
implemented for the producers.
 Women barrier checklist has been prepared of the value chain
actors and supporters. Different techniques to address those
barriers are also documented for further use.
 Analysis done on daily HH role distribution
 Common variables in baseline and monitoring surveys were
identified to analyze emerging trends.
 SDVC M&E linked MIS data with GIS data to demonstrate
performance status geographically.

7. Qualitative Findings
with Quantitative Figure

8. Qualitative Assessment Findings
Focused Area Key Findings
Asset ownership  Women can buy or own cattle, poultry & gold more easily
pattern & dairy
income mgt.
 Cent percent can manage milk sales income
 12.4% Women have individual cow ownership
 Women who owns cattle can take decisions on expenditure
more easily.
Dairy Management  Workload increased but family members are sharing the
and gender roles workload
Access to input,  Women now have easy access to training, credit & savings
capacity & Mkt.
 Have access to input and output market.
Normative attitude  Women still face difficulties buying big assets
and women barriers
 Inherit the lowest quality land and get the lowest share
Project impact  Significant progress is seen in intangible assets
 Around 25% of participants reported an increase in cow
ownership
 Women’s opinions are getting more preference in HH and
community level
 2.3% increase is seen in womens’ individual cow ownership

9. SDVC groups' performance score (PPT) by groups’ gender
Selection Year (1+2+3)
(Aug'2011)
74 73
72
72 71
70
68
66 66
64
62
60
Women only Mixed Men only Total
PPT SCORE OUT OF 100

10. Producers' FM Knowledge changed from starting month by gender
(Knowledge : Knowledge score out of 10)
Selection Year (1+2+3)
Base Sep'2011 % change
7.0
6.4
4.3 4.4
47% 58%
Female Male
Starting month Definition: This means when M&E started collected GPF data collection after training from SDVC.
FM : Farm management

11. % of SDVC groups engaged in savings by groups' gender markup
Selection Year (1+2+3)
(as of Sept'2011)
77%
66%
60% 60%
Women only groups Mixed groups Men only groups Total

12. Average of total savings amount (US$) by groups' gender markup
Selection Year (1+2+3)
(as of Sept'2011)
128
123 124
50
Women only Mixed Men only Total

13. % of savings group used savings money by groups' gender
markup
Selection Year (1+2+3)
(Sept'2011)
59%
54% 56%
17%
Women only Mixed Men only Total

15. The effects of learning group gender
composition on HH income
Households that have female farm leaders and groups that are all women have significantly
higher total HH income from dairy. F(13)=1108.9, p<.0001. . This relationship has been
modeled using a linear mixed-effects model which controls for phase, year, size of herd,
and includes random effects for learning group.
6.7
Log of Total predicted monthly HH
6.6
6.5
6.4
income from Dairy
6.3
6.2
6.1
6
5.9
5.8
5.7
5.6
Female Farm Male Farm Women Only Mixed Learning Men Only
Leader Leader Learning Group Group Learning Group
Expected Income depending on gender of FL Expected Income depending on gender mix of group

16. Relationship between women owning cattle
and women’s total knowledge score
There is a significant relationship between the gender of who owns the cattle and women’s
knowledge
score. The Pearson correlation is .241, p<.01. And the one-way ANOVA F=486.74, p<.001

17. Relationship between women owning cattle and decisions to
sell cattle
There is a significant relationship between the gender of who owns the cattle and who
makes the decision to sell cattle. The Pearson correlation is .46, p<.01. Cramer’s V (.464),
p<.0001.
Who Decides About Selling Cattle?
80%
73%
70%
60% 56%
50%
40%
30% 26%
20% 15%
12%
10%
2%
0%
Self Husband Jointly
HH Where Women Own Cattle HH Where Women Don't Own Cattle

18. Relationship between women owning cattle and
permission to attend group and distance meetings
There is a significant relationship between women owning cattle and needing permission to attend
both group meetings and distant meetings. The Pearson correlation for attending group meetings
is .65, p<.01. Chi-square (4) = 7031, p<.0001. The Pearson correlation for attending distant meetings
is .68, p<.001, Chi-square (4) = 7095, p<.0001.
100%
90%
90%
80% 77%
70%
60%
50% 48%
40% 34%
30%
20%
10%
0%
Need Permission to attend Group Meeting Need Permission to Attend a Distant Meeting
HH Where Women Own Cattle HH Where Women Don't Own Cattle

19. LHW income status by gender

20. Challenge faced
• Research on gender issue is very sensitive in the rural context.
Participants didn't always want to provide the exact answer.
• Baseline variables are not sufficiently gender focused to
measure the women progress,
• There was not a specific project milestone on gender asset
changes.

21. What would have done differently
• Strong platform of solidarity in the community.
• Introduce successful women farmer leaders, LHW, Collector and
entrepreneurs as model for others
• Being reflective on women barriers in the field and address those
accordingly
• Take positive discrimination for women (e.g. No training fees )
• Introduce Daily Time Use tool & Work with family member for
motivating and reducing the work load of Women
• Awareness campaign on milk consumption
• Ensure access of Women to Input & Output market
T

22. Next Action
• Continue Focused group discussion.
• Continue gender based learning session for the producers
• Conduct stakeholder workshop on WE issues
• Life history analysis and women barrier checklist
• Design Final evaluation with the gender related questions to track the
progress.
• Take assistance from IFPRI/ILRI to analyze project M&E data regarding
gender asset.

23. Video of Kallyani-FL cum feed seller

24. Thank You…