The off-season in the fashion industry is characterised by low productivity, lean output, and strained revenue. But with the right strategy, manufacturers can make the most out of slumps in between seasons.

Manufacturers may optimise production through lean manufacturing, a smaller and scalable workforce, and operating on a small budget by smartly allocating spend on fixed and variable costs during this period. This could help apparel manufacturers maintain a healthy cash flow and reasonable revenues even in times of demand slump, and transform the fashion market to introduce year-round productivity.

This blog explores strategies and roadmaps across a number of areas that could  allow garment manufacturers to navigate seasonal slumps more efficiently.

1. Understanding Seasonal Demand Fluctuations

• Seasonal Trends

From catwalks to retailers, the fashion year is divided into four seasons – Spring/Summer, Pre-Fall, Autumn/Winter, and Resort. Manufacturers also take their production cues from this calendar, (especially Spring/Summer and Autumn/Winter). Manufacturing hubs are busiest in the run-up to these seasons.

The off-season periods of fashion usually occur after each season or post-holidays like Christmas and New Year. These periods are characterised by subdued demand, in response to which manufacturers experience lean periods of activity. 

• Factors Influencing Demand

Seasons in fashion mirror changes in the weather – while Spring/Summer collections are produced using lighter fabrics like cotton and linen, the production for Autumn/Winter requires the use of wool, tweed, fleece, leather, and more. Similarly, the demand for festive wear rises during the holiday season. In fact, the holiday season also coincides with increased purchasing power (thanks to bonuses and planned savings for major festivals like Christmas and Diwali).  

• Impact on Operations

Manufacturing takes a back seat during the off-season. Production is scaled down – or completely shut down – to manufacture smaller batches and avoid overproduction and surplus inventory. Manufacturers may also limit production to selective pieces that remain in demand around the year, instead of manufacturing trendy items. Inventory management is critical in between seasons as overstocked goods might not sell, driving up costs of storage, insurance, spoilage, and obsolescence of design.

The workforce is likewise scaled down. Factory owners often introduce layoffs, reduced working hours, or furloughs to slash labour costs. But this comes with a downside – they risk losing skilled workers who are difficult to replace. When demand picks up again, it becomes challenging to rehire these workers who may have found jobs elsewhere; and it is expensive to recruit and train new staff. 

Cash flow management often becomes a challenge during seasonal slumps. As sales volumes decline, manufacturers may experience liquidity crunches that make it challenging to cover fixed costs like rent, utilities, machinery depreciation, and salaries for admin and management staff. In fact, in case of unusually low demand, manufacturers may even struggle to cover operational expenses like the cost of fabric, labour wages, and shipping.

To deal with cash flow constraints, manufacturers may be required to take on loans and delay payments to suppliers and vendors. As a result, they may expose themselves to higher expenses in interests payable and financial risks, and damage their relationships with other supply chain actors.

2. Data-Driven Demand Forecasting

• Importance of Accurate Forecasting

Seasonal slumps are a reality that manufacturers reckon with every year. However, there is no tried-and-tested playbook to prepare them for it. There are many reasons for this – fashion seasons are now changing along with changing climate; seasonal changes can be exacerbated by geopolitical shocks; or there may be unforeseen changes in the supply of raw materials due to variations in agricultural outputs like cotton, linen, jute, wool, or bamboo.

Data-driven demand forecasting, derived from recent or even real-time data, can help manufacturers better manage operations and absorb uncertainties along the supply chain. This has applications in better inventory management, production planning, waste reduction, financial planning, revenue forecasting, workforce management, delivery scheduling, and overall risk mitigation.

• Forecasting Techniques

Manufacturers may use several data-driven techniques and data models for demand forecasting like:

1. ARIMA: 

The AutoRegressive Integrated Moving Average (ARIMA) can model time series data to capture trends and seasonal patterns that have persisted over time. For example, sales data for the past five years can be used to forecast demand for the upcoming seasons. It can account for repeating seasonal patterns, ensuring that inventory is available when demand is expected to peak.

2. Holt-Winters exponential smoothing:

This is a simple model that can be easily understood and implemented. It helps predict future values based on past trends which is crucial for apparel companies where fashion trends  influence demand.  It smooths out short-term fluctuations, focusing on the underlying trend, which aids in long-term planning and strategy. It also continuously updates the level, trend, and seasonal components as new data becomes available, ensuring that forecasts remain accurate and up-to-date.

3. Random forest

Random forest can model complex, non-linear relationships between promotions, holidays, weather, and economic conditions data points to forecast demand. This helps with better inventory management, reducing the risk of overstocking or stockouts, and best allocation of stock across different warehouses and stores. 

• Implementing Forecasting Tools

The adoption of forecasting tools in apparel manufacturing workflows is easier said than done. Factory owners should put in place a comprehensive strategy to ensure seamless integration of forecasting tools. Here’s a roadmap they can follow:

1.  Assess objectives: Examine their needs and objectives such as improving inventory management, reducing stockouts, optimising production schedules, or enhancing supply chain efficiency. Manufacturers may establish key performance indicators (KPIs) like success of the integration, such as forecast accuracy, inventory turnover, and customer satisfaction levels.

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2. Software selection: Evaluate software options to compare features, scalability, ease of use, integration capabilities, and cost.  Ensure the software is tailored for the apparel industry, supporting seasonality, trends, and the specific challenges of fashion demand forecasting. 

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3. Implementation: Configure the software according to the company's requirements, setting up parameters for forecasting models, time horizons, and update frequencies. Customise the software to include specific business rules, segmentation (by product line or region), and seasonal adjustments.

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4. Training and onboarding: Conduct comprehensive training sessions for staff to ensure they are proficient in using the software. Provide detailed documentation and user manuals to support ongoing usage and troubleshooting.

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5. Integration with existing systems: Utilise APIs to integrate the forecasting software with existing ERP, SCM, and MES systems for real-time data flow and automation. Ensure regular data synchronisation between systems to keep forecasts up-to-date.

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6. Process alignment:  Align demand forecasting processes with existing business workflows, ensuring seamless handoffs between forecasting, planning, procurement, and production teams and automate routine tasks such as data updates, report generation, and alert notifications to improve efficiency.

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7. Testing & improvement: Gather feedback from users and stakeholders to refine the model and adjust parameters as needed. Continuously monitor the performance of the forecasting software using the established KPIs. Regularly update the forecasting models based on new data and changing market conditions to maintain accuracy.

3. Inventory Management Strategies

• Just-in-Time Inventory

Just-in-time (JIT) inventory allows manufacturers to secure supply of raw materials with production on an as-needed basis. This strategy enables a direct supplier-to-production line approach, and cuts out the need for storage. Manufacturers need not pay holding costs for raw materials, significantly saving on operational expenses during periods of low demand and, likely, low revenues.

JIT inventory is extremely compatible with the conditions of a seasonal slump - it helps manufacturers produce on-demand, avoid overstocking, and limit the batch sizes. Not only this, but JIT inventory management also quickens the production turnaround time by eliminating the long durations for which raw materials are held in warehousing and instead focusing on the production processes themselves.

• Stock Optimisation

Apart from JIT, manufacturers may utilise several other techniques to optimise their stock levels to avoid overproduction such as:

1. Economic order quantity: The economic order quantity production scheduling model was developed by Ford W. Harris in 1913. It uses a formula to determine the best optimal quantity of inputs a manufacturer should purchase to minimise holding costs while meeting demand.

The EOQ formula tells the manufacturer the ideal number of input materials they must order, and can be modified to arrive at varying production levels. However, this model isn’t ideal for garment manufacturers in today's uncertain times as it assumes that consumer demand, the reordering costs, and holding will remain constant. 

2. Newsvendor model: The newsvendor model, on the other hand, is more suited to industries like fashion where demand is seasonal and the selling period is predetermined. It takes into account demand uncertainty, a single selling period, costs of underage and overage, and the ideal point of demand distribution. The method allows clothing manufacturers to account for risks while placing orders, thereby optimising storage costs. 

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• Inventory Reduction Tactics

Manufacturers may employ several tactics to keep inventory from tumbling into excess. While sales, discounts, and other promotional tactics can help free up inventory, it requires a more structured approach. They may consider making both long- and short-term changes across these areas:

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1. End-to-end visibility: Create a data centre for all stakeholders along the supply chain with insights drawn from a variety of planning software like ERP, MES, and supply chain management tools. This would allow for transparency into supply, inventory, warehousing, and more so that staff can make fact-based interventions when required.

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2. Segmented optimisation: Identify items that should be sold at a markdown, liquidated, or packed away. These decisions should be made based on the seasonal relevance of the items; the cost of liquidation or packaway; as well as the level of markdown required to boost sales. 

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3. Warehouse optimisation: Examine warehousing and logistics to better plan purchases and avoid transitional blockages. Manufacturers may even consider doing an audit of their inventory for inaccuracies,tweak the frequency of inventory cycle counts, and revise standard operating procedures for accuracy.

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4. Flexible Production Planning

• Adjusting Production Schedules

Manufacturers must devise a more flexible and scalable production strategy during the off-season to respond better to changes in demand.  

1. Resource allocation: Allocate resources based on the skill levels of workers, the capacities of the equipment and machinery capabilities. Divide tasks and schedule production based on these factors to reduce idle time and remove any bottlenecks.

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2. Flexible work hours: Instead of employing workers full-time, on a rigid schedule, consider opening part-time positions during seasonal slumps. This would improve morale, rein in labour spend, and bring scalability and flexibility into production

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• Modular Manufacturing

Modular manufacturing is an excellent technique to introduce flexibility into the apparel manufacturing process. As opposed to the unit production system line, this method divides workers into teams of seven or 10. These workers are cross-trained in all areas of manufacturing and use a range of machinery to complete several tasks in the production process instead of being assigned to a single task. 

1. Greater adaptability: This method allows each module to reconfigure and organise to produce various styles based on demand changes.

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2. Scalability: Modular production allows manufacturers to produce in smaller batches more proficiently during times of reduced demand.

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• Outsourcing and On-Demand Production

Manufacturers may consider outsourcing components of the manufacturing process to expert producers. These could include pattern-making, cutting, stitching, sewing and quality control. This helps manufacturers free up their capacities for their core competencies to focus on their key strengths. 

Instead of pushing large batches of garments on the market based on seasonal forecasts, manufacturers may follow an approach wherein they respond to actual demand. They may procure raw materials and ensure that production is only done in response to tangible demand. On-demand production supports agility in garment production, shortens turnaround cycles that can help reduce demand uncertainty; and requires a lower capital investment. 

5. Cost Control Measures

• Budgeting for Low Demand

A budget designed for a low demand period should cover the following:

1. Fixed costs: These costs, like rent, utilities, lease payments, and salaries of essential staff, will be incurred regardless of demand. Manufacturers must negotiate with vendors and landlords to get discounts and flexible payment terms. They must earmark a portion of the budget to a reserve fund to tide over unexpected downturns.

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2. Variable costs: Variable costs like warehousing and logistics can be controlled by employing lean inventory practices. Moreover, manufacturers can make bulk purchases of raw materials and inputs during high-demand periods to get reduced costs during the off-season.

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3. Workforce management: The workforce can be scaled down during periods of low demand by allowing them to work on a part-time basis and offer voluntary time off to reduce spending on wages. Cross-training can equip workers to handle multiple roles at the same time and allow for flexibility. 

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4. Tech-led efficiency improvements:  Treat spend on technology solutions as an investment that can improve efficiency irrespective of  demand levels and reduce long-term costs.

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• Reducing Operational Costs

Manufacturers can reduce their operational costs without compromising on the quality of the output by using a number of tactics like:

1. Energy and water savings:  Implement water recycling systems in processes like dyeing and finishing to reduce water usage and costs. 
2. Process improvements: Invest in automated machinery for tasks such as cutting, sewing, and finishing to increase precision and reduce labour costs.
3. Small-batch production: Employ a limited workforce to produce small batches in periods of lean demand.
4. Design for manufacturability: Design products that are easier and cheaper to manufacture without compromising quality.
5. Standardised components: Use standardised components and materials across different products to streamline production and reduce costs.
6. 5S methodology: Implement the 5S methodology (Sort, Set in order, Shine, Standardise, Sustain) to organise the workplace for efficiency and effectiveness.
7. Value stream mapping: Analyse each step of the manufacturing process to identify and eliminate waste.

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• Financial Planning

Ensuring financial stability in times of seasonal slumps is as challenging as it is crucial. Manufacturers must pay attention to: 

• Managing operational costs
• Scaling down production
• Conduct regular cash flow projections
• Improve receivables management, payables management, and credit management
• Continuously monitor and adjust cash flows. 

6. Leveraging Technology for Efficiency

• Automation and AI

The use of artificial intelligence (AI) and automation can help manufacturers bring efficiency into production during seasonal slumps in a number of ways:

1. The use of robot process automation (RPA) to automate fabric spreading, stacking, and sorting can reduce reliance on expensive labour. Automated cutting and sewing machines can handle repetitive tasks with high precision and speed, while minimising errors.

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2. Automated inspection systems using cameras and sensors can detect defects and inconsistencies in fabrics and finished products, ensuring higher quality and reducing rework. Continuous monitoring of production lines through automated systems can help identify issues early, reducing downtime and waste.

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• Digital Twins

Digital twin technology creates virtual replicas of physical production processes, allowing for simulation, analysis, and optimization of various scenarios. It can replicate the entire apparel manufacturing process, from initial design to final production. It simulates various production scenarios like changes in production volume, machine downtime, or material shortages. By inputting various parameters and constraints, manufacturers can analyse the impact of these scenarios on production efficiency, lead times, and costs.

• IoT and Smart Manufacturing

IoT devices equipped with sensors can be installed on machinery, equipment, and other assets throughout the manufacturing facility. These sensors collect real-time data on machine performance, energy consumption, temperature, humidity, and other relevant metrics. This data can be processed and analysed using advanced analytics tools.

7. Sustainability and Ethical Practices

Sustainability is linked to quality. High-quality garments have a longer lifecycle, which reduces consumers’ need to purchase more. In the long run, this results in limiting consumption, and therefore production. Reducing apparel production is necessary for manufacturers and retailers to make good on their sustainability commitments. 

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Periods of demand slump give manufacturers respite from the pressures of short production cycles. Factories have the short-lived luxury of slow production during these periods which helps manufacture higher-quality and durable products using more sustainable practices.  

Garment production during demand slumps can also help manufacturers engage in ethical labour practices. The workforce need not work faster or longer to fulfil orders as the batch sizes tend to be smaller during this period. They may benefit from flexible work hours, part-time employment, and voluntary vacation time.

8. Long-Term Strategic Planning

• Scenario Planning

Scenario planning is a strategic process that envisions various future scenarios that could impact the business. This approach helps manufacturers anticipate potential changes and uncertainties, allowing them to make informed decisions and create flexible strategies.

Manufacturers must identify market trends, tech advances, regulatory changes, and shifts in supply chain dynamics to create a variety of scenarios – baseline, optimistic, pessimistic, and alternative – that could take place in the future. They must then analyse the impact of each scenario, and develop strategic responses to each.  

• Diversification Strategies

Manufacturers may be in a seasonal slump, but the reality of the fashion industry is that seasons are changing today. There is a need to produce evergreen products that can be worn around the year, but there is also a need to diversify to different markets and across products. Such a strategy would allow manufacturers to remain in business beyond their usual productive months. 

For example, in addition to lightweight summer clothing, manufacturers can also produce winter wear, accessories, or even non-seasonal items like activewear or loungewear. This ensures that there's demand for their products throughout the year, in various geographical regions, reducing the dependency on any one particular season.

Conclusion

Apparel manufacturing is an extremely competitive industry during its traditional seasons. To stand out and make a bid for a larger piece of the pie, manufacturers may look to increase their productivity during the off-season. 

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Manufacturers must craft an all-encompassing strategy that includes demand-driven forecasting, inventory management, production planning, cost control, the use of technology, and sustainable practices to navigate seasonal slumps in a way that delivers the optimum output and increases revenues. In a shrinking world and the changing nature of demand, off-season productivity may very well be the next frontier for apparel manufacturers to conquer.

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