We provide pricing and promotions solutions for clients across several industry verticals and each one of them has their own unique challenges or circumstances that must be addressed.  The Softlines retail space is no exception with managers needing to account for things like long lead times, short seasons, unpredictable demand, and the possibility for volatility.

Smart teams augment their experience and judgement with data analytics that can help them maximize sell-through, maintain margins, and more accurately forecast demand.  They manage to blend the art of producing items that correspond with certain trends with the science needed to ensure that they allocate their capital in products that can generate the greatest return. Specifically they need to focus their efforts such that they accomplish the following four key imperatives.

1. Selling a larger percentage of goods at full margin through maintaining more of the right items at full price longer into the season.
2. Identifying and promoting the slow-moving or over-inventoried items earlier in the season, and identifying items that can be promoted to stimulate demand.
3. Improving the timing of markdowns for remaining markdowns.
4. Tailoring forecasting, promotion and markdown tactics at a more granular level to achieve better targeted and overall performance.

Successfully and consistently accomplishing those four things is a tall order and means that you’ve addressed things like modeling demand by style, accounting for demand transference, addressing seasonality, and effectively communicating insights and forecasts across the entire supply chain. There are a lot of moving pieces to address with a very tight time frame to executive which makes this such a compelling challenge to address.  Over the next few months Clear Demand will be sharing how some customers have used our solution to address the challenges unique to softlines.  We hope that these posts will be a useful guide for you as you look to improve your execution within your merchandising or pricing team.