Four must-haves for a fashion & apparel supply chain planning solution
Fashion and apparel supply chains deal with a unique set of challenges that require differentiated planning processes and industry-tailored solutions. Product lines blend fast fashion with staple pieces, ever-changing international business regulations, and unpredictable consumer demand. To handle this, forerunners in the business need to design supply chains that are intelligent, unified, and responsive.
For these reasons, we want to highlight the capabilities that a supply chain planning tool needs to accommodate for the fashion industry:
- New product introductions – The problem with trying to forecast demand and adoption rates for new products is that there is no history to work with, at least no direct history. However, there may be similar products with comparable attributes and sufficient historical data to serve as a proxy. For example, a trendy black shirt with shoulder cut-outs might sell similarly to last year’s trendy black shirt with ruffle sleeves. Comparable forecasting is effective when combined with additional information for each new product, like seasonality, decay, launch time, life cycle, region, etc. A planner with domain expertise can select and test the likely demand factors that may affect the adoption of a new product and apply them to the forecast.
- Demand sensing for rapid replenishment – Take back mid-season replenishment. A real-time union between your planning system and daily point-of-sale data makes rapid replenishment possible. A platform that can ingest data at a high frequency enables early insight into potential new demand patterns. Responding timely to mid-cycle shifts in demand can keep your merchandise stocked, and off the end-of-season clearance racks for better profits.
- Multi-echelon inventory optimization – Global fashion supply chains are becoming increasingly complex with extensive omnichannel sales models including direct e-commerce, brick and mortar, as well as distributors and retailers. Sales and planning teams often work in silos, speaking various languages, and using different processes. Multi-echelon inventory optimization (MEIO) is crucial for omnichannel, because it balances inventories across the entire distribution network, taking into account the interdependencies between echelons. Organizations that go beyond single-echelon inventory optimization (IO) offer highly competitive service levels and see a reduction in (or elimination of) stockouts.
- A Unified S&OP model is crucial in the fashion and apparel industry, where the software should adapt to and guide an ever-maturing internal collaboration process, bring forth an intelligent analysis of historical data, and provide space for experts to incorporate their wisdom. Armed with the right solution, fashion companies can improve service levels, reduce inventory, avoid clearance racks, and reduce delivery time. They can keep inventories lean while maximizing sales.
For example, Vanguard Software proudly provides SCM solutions for a global leader in athletic footwear sales. The company required a solution that supports the input of critical insights from the Sales team about changes in the market like new customers, retailers, channels, trends, and products. Prior attempts at gathering data and analysis in a silo environment had resulted in lack of c-suite confidence in the forecasting and planning processes. The company needed a planning system that was flexible, unified, and supported a global rollout. Vanguard Predictive Planning was that system. Through network collaboration, advanced NPI techniques, and the consolidation of key insights from Sales, the executives have gained a single version of the truth and improved their overall confidence in business forecasting and planning.
About Vanguard Software
Vanguard Software introduced its first product for decision support analysis in 1995. Today, companies across every major industry and more than 60 countries rely on the Vanguard Predictive Planning platform. Vanguard Software is based in Cary, North Carolina.