A fashionably late shift to improve speed-to-market times
For decades the garment industry has employed traditional demand planning techniques that have worked well with push production methods – where forecasting relies on a limited analysis of historical sales data and planning is often siloed across sales, finance, and product teams.
Assumptions made for long-range time horizons often trickle down to mid- and short-range plans without being validated by new data. These techniques originated when distribution channels were few and unchanging, and history was the best predictor of future demand.
But today, new developments in consumer behavior and expectations, high-velocity styles, demand shaping efforts, and omni-channel sales and distribution all mean that demand is fluid and dynamic. Effectively capturing, analyzing, and propagating demand data in real-time maximizes response time and enables a shift toward pull production. Modern planning should aim to shorten discovery to delivery times by using real-time demand data scrubbed of statistical outliers and propagated across the business.
Traditional demand planning techniques prove inadequate for near-term forecasting in today’s more complex environment due to:
Volatility: Changes in consumer behavior, preferences, and expectations
Today’s consumers expect instant gratification despite their growing appetite for unique, high-quality, and ethically-sourced products–items that traditionally require longer lead times. Disruptive, e-commerce natives are developing innovative customer experiences and brand identities, particularly those that point to brand authenticity, transparency, sustainability, and a passion for social justice. Meanwhile, traditional brand executives are scratching their heads at the complexities of optimizing their supply chains for faster response times.
Velocity: Abundant style adjustments and constant NPIs
With fashion as its backbone, the apparel industry is similarly fast-paced: constantly introducing new products as old styles lose their luster. Product lifecycles in apparel are around 8 months long. The consumer-driven need for product variety and velocity means successful brands see rapid SKU proliferation and a multitude of phase-ins and phase outs. Managing and forecasting a vast number of SKUs at the customer level is a key capability of any modern planning process.
Demand shaping promotion efforts influence
The relationship between promotions/demand and supply/promotions is bi-directional and parallel in nature. Promotions influence demand and supply can influence promotions. Demand shaping efforts like price adjustments or even dynamic pricing require tightly integrated planning processes.
Sales and marketing need to be able to quickly react to real-world circumstances that impact the supply of goods using cost and promotions as an incentive for consumers to buy more (or less) product so the demand is a better match for the available supply. Collaboration between demand, supply, sales, and marketing functions is a key driver in the reaction times between the value chain and the sales organization.
Variety: Disruptive omni-channel and e-commerce strategies
Brands who diversify sales channels to meet the growing variety of required customer experiences need an integrated platform to manage forecasts across the ecosystem. Syncing sales forecasts real-time into the demand and supply plans enables shorter production response times by ensuring the most up-to-date information is considered during decision-making.
Demand sensing for rapid replenishment
These increasing complexities are sparking innovative supply chain optimizations even within large global brands. Some employ new supply strategies like producing goods on Takt time, meaning the value chain produces exactly one finished good within the same time interval that one item is purchased by a consumer.
Syncing the entire, multi-dimensional value chain up with volatile consumer behavior requires advanced demand sensing abilities and a real-time union between your planning system and daily point-of-sale data. A planning platform needs to be able to ingest a large volume of data at a high frequency to enable early insight into potential new demand patterns.
By employing these strategies, along with the technology that can support agile planning processes, brands enable timely response to purchasing behaviors to keep merchandise stocked and off the end-of-season clearance racks for better profits. Technology-led supply chain optimization improves brands’ chances of surviving in the digital-first generation.