Product returns have catastrophic impacts on retailers. Reverse the trend with this identification and corrective workflow.
Prevention Begins With Production
Sara Kim highlights the production and sourcing decisions that manifest into product returns and what retailers can do ...
Sara Kim highlights the production and sourcing decisions that manifest into product returns and what retailers can do to avoid them.
Tell me if you have heard these before.
- You have a particular style where sales have exceeded expectations at the start of the season. To fulfill the demand, you reach out to your vendor to negotiate a rushed production run.
- You need to reduce the costs of an existing carryover style, so you work with your vendors to cost engineer for next season. Some costs can be reduced by buying in bigger bulk, but you need to find other ways to reduce the cost: removing some stitching, using a different fabric, buttons, elastics, or zippers. You feel good that you didn't change the design aesthetics, not even an inch, but you know that decision has been made in other cuts.
- You've been asked to consolidate your vendors. While it's been difficult, your best vendors agreed to produce products that were, until recently, made by vendors you no longer work with.
- You're taking one of your core items and transitioning to a new, more sustainable fabric. This new fabric has passed all testing, so everyone is excited about this change's impact on your company's environmental footprint.
These are typical stories for retailers, but not without a heavy lift. Sourcing departments, designers, and merchants work tirelessly with their vendors to make it happen. Yet despite everyone's best intentions, the trade-offs from these actions can lead to mistakes which lead to returns.
After years of working in product development and production, both for retailers and vendors, I understand retailers' struggles and what vendors do to meet retailers' needs. I've seen, managed, and mitigated many issues and know what can arise. Starting with the ones above:
- The Rush Re-Order: Vendors have to plan and plan their production runs across several factories months ahead of time. So when they receive a re-order with a shortened lead time, the factory that manufactured the original order may no longer have capacity. Hence, vendors may subcontract or split production between multiple factories, but this can lead to variations in the final product.
- Cost Cuts: Pennies add up. Retailers must find ways to remove costs and waste from their production. But changing a button, a zipper, fabric weight, or stitching could produce substandard quality, which isn't noticed except after the customer wears or washes it.
- Vendor Consolidation: While you may be consolidating with a vendor you love; they might not be proven in the new merchandise category you want them to develop.
- New Fabrics: Anytime you start using new fabrics, there is a chance something could go wrong, such as discomfort, durability problems, and even skin irritation for customers.
I mention these points not to suggest they are bad practices or to insinuate that they will invariably result in adverse outcomes. I tell them to emphasize where and why breakdowns happen, which can increase product returns.
What can be done? How do you identify the damaging side effects from fabric, color, sewing, or other quality issues to avoid them in the future?
To gain the necessary insights for better production and sourcing, artificial intelligence (AI) can play a vital role. AI-powered analytics and data processing can identify patterns and trends that are not immediately apparent, enabling proactive measures to be taken.
For instance, AI can analyze year-over-year (YOY) vendor performance to identify any consistent issues or improvements. Retailers can add this information to their vendor scorecard, highlighting areas where additional support or intervention may be needed.
Furthermore, AI can dissect the performance of each category, style, and product produced by each vendor, allowing companies to identify specific areas of concern. By examining the data, businesses can pinpoint product vulnerabilities, such as particular styles, designs, or materials that are more prone to be returned.
AI can verify the reasons for returns attributed to specific vendors. Retailers can identify patterns and common issues associated with particular vendors, enabling targeted actions to address the root causes. Was the product returned due to the fabric or quality of the merchandise? Or was the return entirely out of the control of the vendors' actions?
Returns prevention begins with production, as addressing production-related issues is crucial to minimizing product returns and associated costs. By determining the root causes of these issues and leveraging AI-powered insights, companies can proactively prevent returns, enhance customer satisfaction, and improve their bottom line.