The Women in Leather Craft Report

Women participate in leather craft through a wide range of roles: artisan production, stitching, finishing, footwear and handbag making, factory employment, home-based work, microenterprise, training and leadership. Yet the statistical picture is fragmented. Some datasets count artisans, others measure trainees or factory workers, and relatively few follow women from technical skill through income, ownership and decision-making.

This report brings those layers together. It uses direct leather-sector evidence where available and broader craft or industrial evidence where it helps explain the surrounding ecosystem. The central distinction is between presence and economic agency. A high female workforce share can coexist with weak access to formal employment, finance, higher-value technical roles or leadership. Conversely, a small targeted program can be significant when it connects skills directly to enterprise creation or decision-making.

The evidence is therefore organized around a practical sequence: participation, skills, employment, livelihoods, enterprise, market access and leadership. The goal is to show where women are visible in leather craft, where the evidence is strongest, and which metrics are needed to understand whether craft participation becomes durable economic opportunity.

Executive Women in Leather Craft Benchmarks

The numbers defining participation, skills and economic opportunity

Women’s participation in leather craft is best understood as a pathway rather than a single workforce percentage. The evidence spans artisans, handloom and handicraft beneficiaries, leather-industry employees, trainees, micro and small enterprises, leadership roles and wider industrial participation. These populations are not interchangeable, but together they show where women enter the craft economy and where measurement needs to become more precise. India provides the broadest artisan context: women account for 64% of the national artisan population and 71% of the handloom weaver population in the selected benchmark. Those shares establish the scale of women’s involvement in craft, while leather-specific evidence from Ethiopia, Bangladesh, South Africa and India shows how participation changes when the lens narrows to the leather value chain.

The strongest direct training signal comes from Bangladesh. Nearly 12,000 people were trained through a leather-sector centre of excellence, 95% of newly trained people were reported as employed, and women represented 70% of the employed trainees. Applied to the rounded training total, that combination implies approximately 7,980 women among employed trainees. The figure is a derived estimate rather than a reported headcount, but it is useful because it connects training volume, employment conversion and female participation in one pathway.

Ethiopia adds a different layer. A 192-person LISEC gender-analysis sample included 134 women, equivalent to 69.79%. Women represented 70% of targeted leather-value-chain MSME members, 70 female employees completed leadership and assertiveness training, and women held 60% of department leadership roles at a partner enterprise. These measures show why an effective benchmark must separate presence in the workforce from access to enterprise networks and decision-making positions.

The executive picture is therefore mixed in a productive way. Some datasets show high participation, others show training-to-employment conversion, and others expose the difference between production work and leadership. A credible women-in-leather-craft benchmark should keep these measures separate before combining them into an overall assessment. High participation is important, but durable inclusion also depends on skills, paid work, income stability, ownership, market access, finance, formalization and leadership.

 

Figure 1. Selected benchmarks show strong female participation in several craft and leather-specific populations, but the populations and years differ.

 

Why Women’s Leather Craft Requires a System-Based Benchmark

Participation is only the first measurement layer

Leather craft sits across several business models at once. A woman may work from home on stitching or decorative finishing, contribute to a family workshop, receive piece-rate work from an intermediary, hold a formal position in a leather-products factory, participate in a cooperative, run a microenterprise, or manage a department in a larger organization. A single employment statistic cannot describe all of those arrangements. The same is true of training: completion demonstrates access to skills, but it does not automatically show whether work became regular, whether earnings improved, or whether the trainee moved into higher-value tasks.

The dataset therefore separates direct leather evidence from wider craft context. This distinction matters especially in India, where the 64% women-artisan share and 71% women-weaver share describe national craft populations rather than leather workers alone. State beneficiary counts are valuable for understanding the size and geography of the artisan ecosystem, but applying national female shares to state totals produces estimates, not reported state-level sex counts. That difference should remain visible whenever the figures are used.

 

Women in the Global Craft Workforce

Establishing the wider artisan context

The broader craft economy provides the labor and skills context in which leather craft operates. In India, women make up 64% of the national artisan population in the selected benchmark, while women account for 71% of the handloom weaver population. These are not leather-only shares, yet they show that women are structurally important to craft production rather than a small specialist segment. The implication for leather programs is practical: recruitment, training design, equipment access and market development need to account for a workforce in which women may already be deeply embedded in traditional and household production systems.

State-level beneficiary figures illustrate the scale and uneven distribution of craft support. Over the five years to July 2025, Andhra Pradesh recorded 85,201 handloom-scheme beneficiaries and 17,597 handicraft-scheme artisan beneficiaries. Assam recorded 46,120 weaver beneficiaries and 21,163 artisan beneficiaries, while Arunachal Pradesh recorded 1,356 and 2,500 respectively. The values are program-beneficiary counts rather than total workforce populations, but they demonstrate how sharply the scale of organized support differs between locations.

India: Women in the Artisan and Handicraft Economy

Scale, state variation and support infrastructure

India offers the deepest contextual layer in the dataset because national female participation shares can be read alongside state beneficiary counts and multi-year public support. The national benchmark places women at 64% of the artisan population and 71% of handloom weavers. Those percentages suggest that any craft-sector policy or market program that ignores women would overlook a majority of the population in these categories. For leather craft, the figures are best treated as a participation backdrop rather than a direct estimate of women leather workers.

Program scale varies markedly by state. Andhra Pradesh’s selected five-year totals reach 85,201 weaver beneficiaries and 17,597 artisan beneficiaries, while Assam records 46,120 weavers and 21,163 artisans. Arunachal Pradesh is much smaller in absolute volume, with 1,356 weavers and 2,500 artisans. The composition also differs: Andhra Pradesh’s beneficiary pool is dominated by weavers, while Arunachal Pradesh has more artisan than weaver beneficiaries. These differences matter because leather-craft opportunities depend on the local structure of skills, clusters and existing support institutions rather than on national averages alone.

Funding provides another view of the support environment. Selected handloom and handicraft scheme funding was INR 392.98 crore in 2020-21, rose to INR 651.86 crore in 2021-22, then moved to INR 428.60 crore in 2022-23, INR 465.85 crore in 2023-24 and INR 486.35 crore in 2024-25. The series shows substantial annual variation rather than a smooth upward line. For women artisans, the relevant question is not simply how much funding exists but how much reaches technical training, tools, market access, finance and enterprise support in forms that can be tracked by sex and craft type.

The country also provides a large enterprise context. By February 2026, 30,742,621 women-led enterprises were registered through Udyam Registration and Udyam Assist in the selected national benchmark. This is a cross-sector figure, not a leather-only count, but it demonstrates the scale of the formalization pipeline available to women-owned micro and small businesses. Credit-guarantee coverage for women-led MSE loans was reported at 90%, compared with a 75% general benchmark, alongside a 10% guarantee-fee relaxation. For leather artisans moving from household production to registered enterprise, those mechanisms illustrate the type of enabling environment that can matter after technical skills are established.

 

Leather Craft Skills and Training

Training is the first major conversion point between participation and economic opportunity. Leather work combines manual craft with production discipline: cutting, skiving, stitching, edge finishing, pattern preparation, assembly, quality control, machine operation, footwear construction and handbag production can each require different skill levels. Business capability adds another layer because an artisan who can make a strong product may still need costing, inventory, customer service, digital selling and financial management to build a sustainable enterprise.

Bangladesh provides the largest direct training signal in the dataset. Nearly 12,000 people were trained in the leather sector through a centre-of-excellence model. The reported employment rate among newly trained people was 95%, and women represented 70% of employed trainees. Those figures matter together. A training count alone measures program reach; the employment rate measures conversion; the female share shows whether women participated in the resulting labor-market outcome. Using the rounded totals, approximately 11,400 trainees would be employed and about 7,980 of those employed trainees would be women.

Ethiopia provides a more targeted leadership-oriented example, with 70 female employees completing leadership and assertiveness training under LISEC. South Africa adds a smaller craft-enterprise intervention: 15 women participated in a five-day leather and footwear skills program in Durban focused on handbag production, sewing and business skills. The small cohort should not be compared directly with Bangladesh’s industrial-scale training numbers, but it illustrates a different model in which technical making and enterprise capability are developed together.

Figure 2. Bangladesh connects training volume with employment conversion and women’s share among employed trainees.

 

Bangladesh: From Leather Training to Employment

A direct training-to-work case

Bangladesh’s leather training evidence is valuable because it connects three stages that are often reported separately. The program trained close to 12,000 people, reported a 95% employment rate among newly trained participants, and reported that women represented 70% of employed trainees. The sequence turns a simple training statistic into an employment pathway. If the rounded training count is used as a base, a 95% conversion implies about 11,400 employed trainees; applying the 70% female share gives an estimated 7,980 women among those employed trainees.

The derived headcount should be treated as an approximation because the source training total itself is rounded. Its analytical value is nevertheless strong: it shows the scale that can emerge when training is linked to employer demand. For women, the 70% share indicates that leather-sector training can connect to paid work at meaningful scale when recruitment, curriculum and placement systems align.

Ethiopia: Gender Inclusion in the Leather Industry

Participation, MSMEs and leadership

Ethiopia provides the most multidimensional direct leather-gender evidence in the dataset. A LISEC gender-analysis sample covered 192 employees, including 134 women. Women therefore represented 69.79% of the sample. That figure is important as a participation signal, but the program evidence goes further by measuring leadership development, enterprise participation and organizational decision-making.

Women accounted for 70% of targeted leather-value-chain MSME members, while 70 female employees completed leadership and assertiveness training. At the Addis Ababa Abattoir Enterprise, women held 60% of department leadership roles in the reported partner outcome. Together, these statistics form a more complete inclusion picture than a workforce share alone: women appear in the employee sample, in targeted enterprise membership, in leadership development and in departmental leadership.

The LISEC intervention area also extended within a 100-kilometer radius around the Modjo leather hub, emphasizing the geographic dimension of value-chain development. Leather industries operate through clusters of tanneries, manufacturers, service providers, suppliers and small enterprises, so women’s access can depend on transport, location and the concentration of opportunities around industrial hubs.

The analytical lesson is that gender inclusion becomes more meaningful when indicators are connected. A high female share in an employee sample is stronger evidence when accompanied by training and leadership outcomes. Similarly, women’s participation in MSMEs becomes more informative when the program can show whether enterprises gain customers, finance, equipment and stable orders. Ethiopia’s evidence provides a useful model for building a scorecard that follows women across multiple points of the leather value chain.

 

Figure 3. Ethiopia’s selected leather evidence spans participation, enterprise membership and leadership rather than one workforce measure.

 

From Workshop Worker to Entrepreneur

Women’s economic position can change substantially as leather moves from material to finished product. Production begins with material preparation and component work, then moves through pattern making, cutting, stitching, decoration, assembly, finishing and quality control before reaching wholesale, retail or direct-to-consumer channels. Each stage carries a different combination of skill, capital, equipment and market power. A worker who performs a specialized production task may have deep craft knowledge without controlling pricing or customer relationships, while an enterprise owner may capture more value but also carry inventory, finance and sales risk.

This is why workforce statistics need occupational detail. A headline female share can conceal concentration in specific functions. The same 70% participation rate has a different economic meaning if women are predominantly trainees, machine operators, home-based stitchers, MSME owners or department leaders. Role-level data makes it possible to identify where women are entering the value chain and where advancement slows.

 

Home-Based Work and the Hidden Female Craft Economy

Why conventional employment counts can miss production

Craft production does not always happen inside registered factories. Leather stitching, decorative work, small-goods assembly, repair and finishing can be organized through households, family workshops or subcontracting relationships. These arrangements can provide flexibility and lower entry costs, but they are harder to capture in conventional employment statistics. A woman may contribute economically to a leather product without appearing on a factory payroll or enterprise register.

The measurement challenge is particularly important when piece-rate work is involved. Hours may vary with orders, income may fluctuate by season, and payment may be recorded at household rather than individual level. Family enterprises can also blur the boundary between paid work and unpaid contribution. Without worker-level records, a high volume of production can coexist with limited visibility into who performed the work and how much income they received.

 

Earnings, Livelihoods and Economic Independence

Participation tells us whether women are present; earnings tell us whether participation produces economic return. The current evidence is stronger on workforce, training and enterprise access than on standardized leather-craft earnings. That gap is itself important. Programs can report impressive enrollment or employment figures while leaving unanswered questions about wages, hours, piece rates, income regularity and progression.

The Bangladesh training evidence demonstrates why conversion metrics are powerful: 95% employment after training and a 70% female share among employed trainees provide a bridge between skills and paid work. The next step is to measure wage quality and progression. Ethiopia’s MSME and leadership evidence similarly shows participation beyond basic employment, but longer-term enterprise revenue and earnings data would strengthen the livelihood picture.

Economic independence should therefore be treated as a measurable outcome rather than an assumed benefit of craft participation. A women-in-leather dashboard should report median earnings, hours, wage progression, enterprise margin, repeat-order rate and income volatility alongside workforce shares. That would make it possible to distinguish a sector that simply uses women’s labor from one that creates durable economic opportunity.

Women-Owned Craft Enterprises and MSMEs

Ownership, finance and commercial capability

Enterprise ownership changes the relationship between craft skill and economic control. An employee sells labor to an organization; an entrepreneur makes decisions about products, pricing, investment, customers and growth. In leather craft, micro and small enterprises can operate from a household, shared workshop, market stall, production cluster or digital storefront. Their constraints can include machinery, working capital, raw-material purchasing, design development, compliance and access to consistent buyers.

Ethiopia’s selected leather evidence reports women as 70% of targeted leather-value-chain MSME members, providing a direct indicator of female enterprise participation. India offers a much broader cross-sector enterprise environment: 30,742,621 women-led enterprises were registered through Udyam Registration and Udyam Assist by February 2026. The figure should not be interpreted as leather enterprises, but it shows the scale of women’s formal business participation in a market where artisan enterprises can potentially register and access support.

Finance mechanisms also matter. The selected Indian benchmark reports 90% credit-guarantee coverage for women-led MSE loans compared with 75% general coverage, plus a 10% guarantee-fee relaxation for women-led MSEs. These measures address risk and transaction cost rather than craft skill itself. For a leather artisan, however, finance can determine whether she can purchase a sewing machine, cutting equipment, inventory or packaging and whether she can accept larger orders without cash-flow stress.

Enterprise success should be measured through more than registration. Useful indicators include active trading status, revenue, margin, employee count, repeat customers, financing received, equipment investment and direct-market share. Registration is a gateway; commercial durability is the outcome.

Figure 4. Enterprise registration and finance benchmarks show the wider enabling environment available to women-led businesses in India.

 

Leadership and Decision-Making

Leadership is one of the clearest ways to distinguish participation from influence. Women may form a large share of production workers while remaining less visible in supervisory, technical-management or enterprise decision-making positions. That gap affects who controls schedules, investment, training priorities, quality systems, hiring and promotion.

The Ethiopia evidence provides a direct positive signal: women held 60% of department leadership roles at the Addis Ababa Abattoir Enterprise in the reported LISEC partner outcome. In the same program context, 70 female employees completed leadership and assertiveness training. The relationship between those figures should not be treated as a simple cause-and-effect claim, but together they demonstrate why leadership development deserves its own measurement category.

Leadership also affects the visibility of women’s needs inside organizations. Decision-makers influence equipment design, working-time arrangements, safety, training access and promotion systems. Measuring women in leadership is therefore not a symbolic add-on to employment statistics; it is part of understanding how the economic system is governed.

 

Cooperatives, Collective Organization and Market Power

Collective organization can change the economics of small-scale craft. Individual artisans often buy materials in small quantities, negotiate with intermediaries from a weak position and have limited capacity to fill large orders. Cooperatives, producer groups and shared-service organizations can pool purchasing, equipment, training, quality control and market access. For women, these structures can also reduce the isolation of home-based production and create routes into formal programs.

The strongest dataset evidence is not a universal cooperative count, so collective organization should be measured directly rather than assumed. Useful indicators include women’s membership, leadership roles, order volume handled collectively, shared equipment use, average selling price, training completion and access to finance. The distinction between membership and decision-making remains important: a group can have many women members while leadership remains concentrated elsewhere.

Rural Women and Leather Craft Livelihoods

Craft livelihoods are closely connected to place. Rural and peri-urban women may combine production with agriculture, household responsibilities or other informal work, making flexible craft activity economically important even when it is not full-time employment. Leather goods can offer a pathway from local skills to higher-value markets when design, quality and market access are strong.

India’s state beneficiary data illustrates how different the support landscape can be. Andhra Pradesh, Assam and Arunachal Pradesh show sharply different scales and compositions of weaver and artisan beneficiaries. These counts do not identify leather workers, but they demonstrate why regional planning matters. A training model designed for a dense production cluster may not suit a dispersed rural artisan population, and a digital-market intervention may require different infrastructure from a factory-placement program.

The geographic dimension also appears in Ethiopia, where the selected LISEC intervention area extends within a 100-kilometer radius around the Modjo leather hub. Cluster-based development can concentrate employers, suppliers and technical services, but distance can still shape who can participate. Measuring travel time, transport cost, home-based work and access to shared facilities can therefore improve the gender analysis of regional leather programs.

Figure 5. Selected state beneficiary counts illustrate the different scale and composition of craft-support ecosystems.

 

Country-Level Women in Leather Craft Signals

The country evidence is most useful when it is treated as complementary rather than forced into a single ranking. India provides scale in the wider artisan economy and a direct leather-industry benchmark reporting women as 30% of employment in leather product manufacturing in the selected historical source. Bangladesh provides a training-to-employment pathway. Ethiopia provides employee, MSME, leadership and training indicators. South Africa provides a targeted women’s leather and footwear skills intervention. Pakistan provides leather-sector employment scale alongside wider female industrial participation constraints.

India’s leather industry was reported at around 2.5 million total employment in the selected historical benchmark, with women accounting for 30% of employment in leather product manufacturing. The age of the source means it should be treated as historical context rather than a current workforce estimate. It remains useful because it provides a direct gender share for leather product manufacturing, something that broader artisan datasets cannot supply.

Pakistan’s selected leather evidence records an estimated 500,000 direct jobs in 2010 and about 400,000 after factory closures in 2013. Registered leather-product establishments in 2013 included 108 establishments and 12,958 workers in Punjab, and 30 establishments with 3,937 workers in Sindh. A later overview reports the leather industry contributing 4% of GDP. These figures describe sector scale rather than women’s leather employment specifically. Wider 2026 industrial gender indicators show female labor-force participation around 25%, male participation around 80%, fewer than 15% of working women in formal employment, and women at 3.6% of employment in major industrial sectors. Those broader figures help explain why sex-disaggregated leather data would be especially valuable.

Regional Africa evidence adds a programmatic signal: approximately 10 women entrepreneurs received direct support under a gender-development component, against a target of 150 employment opportunities for women that was not fully achieved. The gap between support delivered and target ambition is a reminder that targets should remain visible beside outcomes. Country comparison should therefore identify what each dataset measures, the year and population involved, and the missing indicators needed for a complete picture.

 

Figure 6. Pakistan’s leather employment figures describe sector scale; sex-disaggregated leather employment remains a separate measurement need.

 

Traditional Skill Preservation and Women Artisans

Leather craft carries knowledge that is difficult to reduce to a machine setting: hand stitching, edge finishing, pattern judgment, material selection, decorative techniques and repair skills often develop through repeated practice and apprenticeship. Women’s participation in the wider artisan economy means they can play an important role in maintaining and transmitting such knowledge, particularly in household and community production systems.

Preservation, however, is strongest when skills remain economically viable. Younger workers are more likely to invest time in learning a craft when it can provide income, status and progression. Training programs therefore need to balance heritage techniques with contemporary requirements such as consistent sizing, quality control, costing, digital presentation and customer service. The objective is not to freeze craft in a historical form but to preserve valuable skills while allowing products and business models to evolve.

The Indian national benchmark showing women as 64% of artisans reinforces the importance of this connection. It does not identify leather artisans specifically, but it demonstrates that women are central to the wider population from which craft knowledge is transmitted. A preservation scorecard could track apprentice numbers, age distribution, training completion, income from traditional products, product innovation and the share of trained artisans who remain economically active after one or two years.

Barriers Facing Women in Leather Craft

Where participation can weaken along the economic pathway

The available statistics point to several measurement gaps that correspond to common barriers. Training may be visible while wage progression is not. Enterprise membership may be recorded while financing and revenue remain unknown. Workforce shares may be available without occupational detail. These gaps matter because barriers often appear between stages rather than at the initial point of entry.

Pakistan’s wider industrial indicators illustrate the scale of one structural challenge. Female labor-force participation is approximately 25% compared with about 80% for men, fewer than 15% of working women are in formal employment, and women represent 3.6% of employment in major industrial sectors in the selected 2026 evidence. These are economy-wide or industrial-context statistics rather than leather-specific measures, but they show why formalization and industrial access deserve attention when evaluating women’s leather opportunities.

Finance is another potential constraint. India’s higher credit-guarantee coverage for women-led MSEs—90% compared with a 75% general benchmark—shows how policy can be structured to reduce financing barriers. Access still needs to be measured at the user level: eligibility does not prove that a leather artisan received credit, purchased equipment or expanded production.

A barrier-to-metric approach makes the analysis actionable. Skills barriers can be tracked through enrollment and completion; employment barriers through placement and retention; pay barriers through wages and piece rates; enterprise barriers through registration, finance and active trading; market barriers through direct sales and repeat orders; and leadership barriers through supervisory and management shares. The objective is to identify where women disappear from the pathway and then measure whether interventions close that gap.

 

Digital Commerce and Direct-to-Consumer Opportunity

Shortening the distance between maker and buyer

Digital commerce can alter the traditional craft value chain by allowing an artisan or small enterprise to reach customers without relying entirely on multiple layers of intermediaries. For leather goods, product photography, customization, storytelling and direct communication can support premium positioning, while digital payments and order management can make small-batch production easier to organize.

The opportunity should not be romanticized. Digital selling requires reliable connectivity, product consistency, packaging, fulfillment, customer service and working capital. Platform fees and advertising costs can also reduce margins. A women-owned leather enterprise may therefore gain market access while taking on new commercial tasks that were previously handled by wholesalers or retailers.

Building the Women in Leather Craft Benchmark Index

A practical benchmark can convert the report’s evidence into eight weighted pillars. Workforce participation receives 16% because presence is the foundation of inclusion. Skills and technical training receive 15%, reflecting the importance of capability in a sector that combines craft and production discipline. Employment conversion and stability receive 15% because training only becomes economically meaningful when it leads to durable work. Income and livelihood outcomes receive another 15%, ensuring that a high headcount cannot substitute for adequate economic return.

Enterprise ownership and MSME participation receive 12% because ownership changes control over pricing, investment and growth. Leadership and decision-making receive 10%, capturing progression into supervisory and management roles. Market and finance access receive 10%, reflecting the importance of buyers, working capital and equipment. Formalization, protection and data transparency receive 7%. The final pillar has the smallest weight but should still act as a confidence control: an impressive score should be treated cautiously when worker status, pay, role or source population is poorly documented.

The index should keep sub-scores visible. A program with strong participation and training but weak earnings should not be described in the same way as one that also produces stable income and leadership progression. Similarly, a women-led enterprise initiative with strong ownership but limited market access requires a different response from a factory-employment program with weak promotion rates.

The purpose of the index is therefore diagnostic rather than promotional. It organizes evidence around the stages that determine whether women can enter, earn, advance, own and lead. Scores should be accompanied by the underlying metrics so that a single total never hides the mechanism producing the result.

Figure 7. The benchmark gives the largest combined weight to participation, skills, employment and income while keeping ownership, leadership and enabling conditions visible.

 

90-Day Women in Leather Craft Measurement Plan

Days 1 to 30 should establish the workforce and enterprise baseline. Record sex-disaggregated headcounts, age bands where appropriate, job role, work location, employment type, home-based or workshop status, training history, working hours and production function. For enterprises, record ownership, registration, employee count, primary products, equipment and sales channels. This phase should also identify which statistics are reported directly and which are estimates or derived values.

Days 31 to 60 should measure economic outcomes. For employees, capture wages, piece rates, hours, attendance, retention and movement between tasks. For artisans and business owners, capture sales, direct costs, margin, order frequency, inventory, finance received and equipment investment. Training programs should connect completion records to placement and active-work status rather than reporting participation alone.

Days 61 to 90 should measure advancement. Track promotion, supervisory responsibility, leadership training, enterprise registration, new customers, direct sales, repeat orders and financing outcomes. Where women work from home, record whether order volume and individual income can be distinguished from household totals. Where programs target MSMEs, verify whether enterprises are actively trading and whether support changed revenue, productivity or market reach.

The 90-day objective is not to produce a perfect long-term impact evaluation. It is to build a disciplined baseline that separates participation from economic quality. Once the system is operating, the same measures can be repeated quarterly or annually to show whether women are moving toward more stable, higher-value and more influential positions in the leather craft economy.

 

 

Metrics Leather Brands, Workshops and Development Programs Should Track

Workforce metrics should begin with female share but immediately add role and status. Track women by production function, technical role, supervisory level, contract type and work location. Record retention and turnover so that a high recruitment rate is not mistaken for stable participation. Home-based and subcontracted workers should be included where they contribute to production.

Skills metrics should include enrollment, completion, competency assessment, certification and movement into technical tasks. Bangladesh’s 95% employment rate after leather training demonstrates the value of linking skills to work. Programs should go further by tracking placement quality, wage level and retention at six or twelve months.

Economic metrics should include wages, piece rates, hours, monthly earnings, enterprise revenue, gross margin, order regularity and financing. Advancement metrics should cover team leaders, supervisors, department heads, cooperative officers, women-owned enterprises and women with direct customer relationships. Ethiopia’s 60% women share of department leadership roles shows the type of organizational indicator that can complement workforce data.

Finally, data-quality metrics should identify source year, population, directness to leather and whether a number is reported or derived. The distinction is essential when broad craft statistics are used to frame leather-specific analysis. A dashboard becomes more credible when it makes uncertainty visible instead of compressing every number into a single undifferentiated total.

 

How Women’s Outcomes Change by Business Model

A home-based artisan may gain flexibility and low overhead but have weak statistical visibility, irregular orders and limited bargaining power. An independent workshop can provide greater control over production and pricing while requiring capital, equipment and customer acquisition. A cooperative can pool machinery, purchasing and market access but needs governance systems that ensure women members also participate in decision-making.

Factory employment offers a different trade-off. Formal systems can provide regular schedules, standardized training and clearer progression routes, yet workers may specialize in narrow tasks and have less control over products or customers. The Bangladesh training-to-employment evidence is particularly relevant to this model because it shows how skills programs can connect workers to industry demand. Leadership data then becomes important for showing whether women move beyond entry-level production.

MSME ownership creates the possibility of greater value capture but also shifts commercial risk to the owner. Ethiopia’s 70% women share among targeted leather-value-chain MSME members demonstrates strong female presence in an enterprise-oriented intervention. Access to finance, machinery and markets determines whether that presence becomes business growth.

Direct-to-consumer brands sit closest to the customer relationship. They can combine design, storytelling and craft with higher margins, but they also require marketing, logistics and customer service. No business model is automatically superior for every woman. The benchmark should instead measure whether each model provides fair economic return, sustainable workload, skill development, market access and a realistic path to greater control.

 

 

The Women in Leather Craft Report FAQ

Are women a significant part of the craft workforce?

 In the selected Indian national benchmark, women account for 64% of the artisan population and 71% of handloom weavers. These are wider craft statistics rather than leather-only shares, but they establish that women are central to the artisan economy. Direct leather evidence also shows substantial female participation in selected programs, including 69.79% of Ethiopia’s LISEC gender-analysis sample and 70% of employed trainees in the Bangladesh leather training case.

Which countries provide the strongest leather-specific gender signals?

Bangladesh provides a large training and employment case; Ethiopia provides employee, MSME, leadership and training measures; India provides a historical direct leather-product employment share alongside a much larger artisan context; South Africa provides a targeted women’s leather and footwear skills program; and regional African evidence includes women-entrepreneur support and an employment target.

Does training improve women’s employment prospects?

The Bangladesh case reports a 95% employment rate among newly trained people and women as 70% of employed trainees, showing strong conversion in that program. It should not be generalized automatically to every training model. Retention, wages and progression are needed to judge long-term quality.

Why is informal work important?

Leather craft can be performed in homes and family workshops or through subcontracting. These workers may not appear in formal payroll statistics even when their production is economically significant. Measurement should therefore include work location, payment method and individual earnings.

Are women represented in leadership?

 The selected Ethiopia partner outcome reports women holding 60% of department leadership roles, and 70 female employees completed leadership and assertiveness training. Broader leadership representation across the global leather sector cannot be inferred from that single case, which is why comparable role-level data is needed.

Why are women-owned MSMEs important?

Ownership gives women greater control over products, pricing, investment and customer relationships. Ethiopia reports women as 70% of targeted leather-value-chain MSME members, while India’s wider enterprise system reports more than 30.7 million registered women-led enterprises across sectors.

What should leather brands measure?

At minimum: women’s workforce share, occupational role, employment status, wages or piece rates, training completion, retention, supervisory progression, enterprise ownership, direct-market access and leadership. These measures should be reported with year, geography and population so that unlike datasets are not treated as equivalent.

How should regional statistics be interpreted?

 Country and program figures often measure different populations and years. They should be used to illuminate different parts of the pathway rather than to create a simplistic ranking. Direct leather statistics deserve priority for leather-specific claims, while broader craft and industrial data should be labeled as context.

Final Takeaway

The Women in Leather Craft Report shows why female participation must be measured across the complete economic journey. India’s wider craft benchmarks place women at 64% of the artisan population and 71% of handloom weavers, demonstrating the scale of women’s role in the craft ecosystem. Direct leather evidence then shows how that participation can translate into specific pathways: Bangladesh reports nearly 12,000 trainees, a 95% employment rate and women as 70% of employed trainees; Ethiopia’s LISEC sample is 69.79% women, women represent 70% of targeted leather-value-chain MSME members, 70 women completed leadership and assertiveness training, and women hold 60% of department leadership roles in a reported partner outcome.

The evidence also exposes what still needs to be measured. Headcounts and training totals are stronger when connected to wages, retention, occupational progression and enterprise performance. Ownership statistics are stronger when connected to revenue, margin, finance and direct customers. Leadership shares are stronger when tracked across multiple organizations and over time. Informal and home-based work requires special attention because conventional employment records can miss economically significant production.

Country evidence should remain contextual. India, Bangladesh, Ethiopia, South Africa, Pakistan and regional African programs illuminate different parts of the value chain and use different populations, periods and methodologies. The most credible analysis preserves those differences rather than manufacturing a single global percentage.

The central benchmark is therefore simple: women’s contribution to leather craft should be measured from skills and production through employment, income, enterprise, market access and leadership. A sector can have many women workers without giving women equal economic control. The strongest outcome is not participation alone, but the ability to enter the craft, earn reliably, build capability, access markets, own enterprises and participate in the decisions that shape the industry.