How We Helped a Tirupur Apparel Manufacturer Unlock Margin and Cash

A mid-sized apparel manufacturer in Tirupur (“the Company”) engaged The Meridian. after two difficult years of margin compression, rising input costs, and worsening payment delays from export buyers. Revenues had grown to roughly ₹180–200 crore, but cash was constantly tight and profits did not reflect the effort leadership and teams were putting in.

The mandate was clear: improve EBIT margin by 300–400 bps, ease working-capital stress by shortening the cash conversion cycle, and build a credible, numbers-backed story to support a targeted capex program in automation and energy efficiency—without disrupting core customer relationships or product quality.

1. Client Context and Mandate

The Company produced knitted garments for a mix of export buyers and leading Indian brands. The plant ran multiple stitching and finishing lines, prided itself on reliability, and had long-standing relationships with key customers and suppliers. Yet lead times were volatile, quality issues surfaced periodically on complex styles, and the owners were increasingly involved in daily firefighting.

In the kickoff session with the owner, CFO, and functional heads, we aligned on three primary objectives: lift EBIT margin by at least 3 percentage points over 18–24 months, improve the cash conversion cycle by 20 days, and translate operational improvements into a bankable business case for fresh capex funding.

2. Diagnostic: From Symptoms to Root Causes

The engagement began with a structured diagnostic combining market research, data analysis, and on-ground interviews. The aim was to move quickly from anecdote (“costs are increasing”, “buyers are squeezing us”) to a precise view of where value was leaking and what truly drove profitability in this business.

2.1 Building the Fact Base

Over 4–5 weeks, we worked with the client team to assemble and standardise the data required for deep analysis:

• Collected 24 months of financial statements (P&L, balance sheet, cash flow) and aligned them to a consistent reporting structure.
• Obtained raw material purchase and consumption data for yarn, dyes, trims, and packaging, including price, supplier, and usage by style where available.
• Compiled machine utilisation, downtime, and defect logs across key stitching and finishing lines.
• Validated HR cost, overtime, and headcount data by department and shift, highlighting hotspots of chronic overtime.
• Cross-checked energy bills and boiler logs for the past six months to link steam and power usage to production levels.

All information was cleaned and standardised into an Excel model, becoming a single source of truth that tied operational drivers (utilisation, defects, energy, labour) to financial outcomes (EBIT, working capital, cash flow).

2.2 Interviews and Issue Log

Alongside the data work, we conducted structured interviews to capture the lived reality on the ground:

• Owner and CFO: financial pressures, banking covenants, seasonal cash crunch patterns, and informal credit practices with buyers and suppliers.
• Production head: bottleneck machines, changeover practices, frequent reasons for downtime, and typical drivers of urgent rework.
• Procurement manager: supplier mix, contract vs spot purchasing, and leverage in negotiating terms.
• Sales and client servicing: receivable delays, quality claims, chargebacks, and how pricing decisions were taken under deadline pressure.

Insights from these conversations were logged in an issue database and later triangulated with data, helping separate perception from fact.

2.3 Key Analytical Insights

With a reliable dataset in place, we ran a series of focused analyses:

• Material cost trend and variance: tracked material cost percentage by buyer, style, and order type, revealing that a few marquee customers were actually margin-dilutive once claims and air shipments were considered.
• OEE and downtime: computed overall equipment effectiveness and showed that effective utilisation on key lines was closer to 60–65%, not the 80%+ assumed by management.
• Working capital bridge: analysed receivables, payables, and inventory days, highlighting that two large buyers alone accounted for a disproportionate share of locked cash due to extended credit terms and slow collections.
• Margin bridge vs industry: decomposed the EBIT gap into material yield losses, labour productivity shortfalls, energy inefficiencies, and SG&A overhead.
• Defect and rejection impact: quantified rework, scrap, and claims, showing that quality issues were eroding approximately 1.2–1.5 percentage points of margin.

These findings were consolidated into a clear diagnostic deck and tested with management to ensure they reflected ground truth, not just model outputs.

2.4 Root Causes, Not Just Symptoms

We created a root-cause tree for the three central problems: depressed EBIT, stressed cash flow, and unreliable delivery on complex orders. Each branch of the tree was linked to specific data elements and qualitative evidence.

• Line balancing and micro-downtime issues causing hidden capacity loss and overtime.
• Poor segregation of complex “development” orders from standard production, leading to frequent changeovers and quality problems.
• Unstructured credit decisions extending terms to large buyers with weak payment discipline.
• Energy wastage from sub-optimal boiler loading, compressed-air leaks, and lack of monitoring at the line or process level.

A management workshop was then used to validate these root causes, align on their estimated rupee impact, and create ownership for solving them.

3. Solution Design: From Ideas to a Sequenced Program

With clarity on root causes, the focus shifted to solutions. The key was to generate ambitious yet realistic options, quantify their impact, and phase them to match the company’s execution capacity.

3.1 Brainstorming and Cost–Benefit Analysis

In cross-functional working sessions, we brainstormed interventions across operations, commercial policies, and enabling capabilities:

• Structured line balancing and standardised changeover procedures on key stitching lines.
• Clear segregation of development orders from volume production, with dedicated capacity and governance.
• Improved defect tagging, line-level quality checkpoints, and root-cause reviews.
• Supplier consolidation and framework agreements for better terms and price stability.
• Deployment of a basic production planning and scheduling tool.
• Targeted capex in automation and energy-efficiency upgrades with measurable payback.

For each initiative, we estimated one-time costs, annual impact, and implementation difficulty. This enabled a rational prioritisation into quick wins, medium-term process changes, and strategic moves.

3.2 Implementation Roadmap and Charters

To move from ideas to execution, we translated selected initiatives into formal charters:

• Each charter specified the problem statement, target KPI, scope, owner, sponsor, and cross-functional team.
• Milestones, timelines, and decision gates were defined upfront.
• Risks and dependencies were documented, including required changes in behaviour or incentives.

These charters fed into a consolidated 18‑month roadmap with a clear governance cadence: monthly project reviews led by functional owners and quarterly steering reviews with the promoters.

4. Financial Model and Funding Story

The owners wanted modernization to translate into a stronger position with lenders and potential investors. We therefore built a full 3‑statement financial model and used it to articulate a rigorous funding story.

4.1 3‑Statement Model and Scenarios

The model linked operational improvements directly to financial outcomes:

• Baseline performance was reconstructed for six months using detailed management accounts.
• A 12‑month forecast was built with explicit assumptions for OEE uplift, defect reduction, and energy efficiency.
• Working-capital metrics (DSO, DPO, inventory turns) were integrated, allowing us to simulate improvements in the cash conversion cycle.
• Planned automation and energy capex was added, with depreciation, interest, and maintenance reflected in the forecasts.

On top of this base, we modelled conservative, base, and upside scenarios to show the range of possible EBIT and cash outcomes.

4.2 Margin and Return Analysis

To evaluate investment quality, we:

• Modelled EBIT margin improvement under each scenario, clearly attributing gains to specific initiatives.
• Ran IRR and NPV calculations for each major capex component (automation, energy upgrades, critical equipment replacements).
• Performed sensitivity tests on volumes, pricing, and working-capital assumptions to show resilience under stress.

This work demonstrated that the planned capex program had a payback comfortably under three years in the base case, with attractive upside if operational initiatives delivered ahead of plan.

4.3 Investor and Lender Materials

To support discussions with lenders and potential investors, we prepared:

• A roadmap deck visually linking operational initiatives to EBITDA uplift, cash release, and risk reduction.
• A concise, two-page funding note translating plant-level changes into ROI, payback, and risk-mitigation language.
• An investor deck with scenario charts, sensitivity analysis, and a simple risk register with mitigations.
• Rehearsal sessions with the management team to refine messaging, anticipate questions, and build confidence in presenting the numbers.

By the end of this phase, the Company had a coherent narrative: where the money was going, what would change operationally, and how that would show up in the P&L and cash flow.

5. Implementation: Turning Plans into Daily Practice

Over the next 9–12 months, we worked alongside the client team to implement the roadmap, with clear focus on line-level changes, working-capital discipline, and governance.

5.1 Operational and Energy Initiatives

On the shop floor, the following changes were rolled out:

• Daily and weekly performance huddles using simple dashboards for output, downtime, and defects by line.
• Revised line balancing and standardised changeover protocols, piloted on select lines and then scaled.
• Improved defect tagging and root-cause reviews at the line level, with shared accountability between production and quality.
• Implementation of targeted automation on high-variance operations, coupled with operator training.
• Energy upgrades, including compressor optimisation, better boiler loading, and systematic leak detection, tracked via energy cost per garment.

5.2 Commercial and Working-Capital Actions

On the commercial and financial side, discipline and transparency were strengthened:

• A formal credit policy segmented buyers by risk and margin, requiring explicit approval for exceptions.
• A weekly collections rhythm was introduced, assigning clear accountability for follow-ups and overdue accounts.
• Pricing for structurally unprofitable combinations of SKU and customer was revisited; in select cases, volumes were carefully reduced or mix was adjusted.
• Purchase planning and supplier negotiations were aligned with the new production plan, improving both material availability and payment terms.

5.3 Governance, Tracking, and Learning

Governance ensured that progress was visible and reversible slippage was quickly caught:

• Monthly review meetings tracked initiative status, KPIs, and realized financial impact.
• A monthly performance pack connected operational KPIs to P&L, working-capital, and cash metrics.
• The financial model was updated with actuals, enabling before–after comparisons and recalibration of assumptions.
• Lessons learned were documented and translated into updated SOPs, training modules, and next-wave improvement ideas.

The engagement formally closed with a final presentation to management and promoters and a structured repository of models, dashboards, decks, and process documentation handed over to the client.

6. Outcomes: Impact After 18–24 Months

While exact numbers are confidential, the realised impact for this engagement fell within the ranges below, consistent with what a well-executed program can achieve in a mid-sized Tirupur apparel manufacturer:

Perhaps the most important shift was behavioural: the owners and second-line leadership moved from managing primarily by instinct and crisis to running the business with a shared, data-backed view. Modernization became a continuous capability rather than a one-time project.

7. What This Means for Similar Businesses

For apparel and textile manufacturers in hubs like Tirupur, this case illustrates a repeatable pattern: start with a rigorous diagnostic, link plant reality to financials, design a sequenced roadmap, and ensure every initiative is backed by a clear cost–benefit view. The goal is not to become a “tech company”, but to build a modern operating system around the strengths that already exist.

When owners treat modernization as a strategic capability—rather than an IT expense—they create businesses that are more resilient to demand shocks, more attractive to lenders and investors, and better positioned for generational transition.