In the world of demand planning, never before has the environment for retailers been so complicated. While many thought the pandemic to be a worst-case and likely short-lived scenario, we’re learning now that this was just the beginning.
Today, planning for future customer demand faces an onslaught of headwinds, from economic uncertainty that influences consumer behavior to rapid e-commerce growth and never-ending supply-chain disruptions that create inventory shortages. It’s a complicated situation compounded by the growing problem of customer returned merchandise. While retail sales growth has fallen back to pre-pandemic levels, the rate of returns has not, as e-commerce’s popularity remains historically high.
It’s quickly setting in as the new reality of retail. One in which consumers have opted to hang onto their lockdown online shopping habits, an automatic inheritance of yet more returns! For demand planners, it means a fraught path to giving the customer the right products in the right quantities at the right times.
Retail’s Returns Problem
An unstoppable force since the early days of eBay and Amazon in the 1990s, e-commerce has helped the overall retail industry sustain growth, even in the most difficult of times.
Prior to Covid-19, in 2019, retail growth stood at 3.5% for the year. The first year of Covid’s impact in 2020 saw that growth leap up to 7.6% and again to 14.4% in 2021. From there, we’ve seen it fall back, dropping to 7% in 2022 and then to 3.6% in 2023. The National Retail Federation also reports that the rate of returns in 2019 was at 8.1%, spiking to a high of 16.5% of sales in 2022, and falling back slightly to 14.5% in 2023. The problem is that since 2021 year over year growth has retracted by about 75% while the rate of returns has only declined by around 12% off of its pandemic high. This is a strong indicator that pandemic habits have staying power, and in fact, may likely be the new normal customer behavior.
The loss to businesses — $145M for every $1B in sales — makes it a no-brainer that returns should be a critical part of demand planning.
Customer Returns in Demand Planning
E-commerce’s Achilles' heel will always be customer returns. It’s to be expected considering the lack of personal touch and feel that shoppers miss out on at the time of purchase. Unsurprisingly, the most common reasons for returns tend to be due to the product’s fit, look, feel, and/or overall compatibility. For as much as we know about this natural predisposition for a higher rate of returns, there’s plenty that’s less obvious, especially when it comes to factoring returns into demand planning.
Customer returned merchandise can introduce a higher level of uncertainty when it comes to accurately forecasting future demand. Returns challenge the ability to plan for and replenish inventory effectively, introducing data discrepancies between real and forecasted demand. There are deep fluctuations seasonally for returns too, especially following peak shopping seasons. Failing to account for such variations can create inaccuracies in demand forecasts and inventory planning. Returns can also tie up working capital as the merchandise awaits processing; this reduces the liquidity ratio and limits the ability to invest in other areas of the business. On top of this, the reverse logistics process, coordinating transportation, sorting, inspection, and refurbishment of returned items is complicated and costly, not to mention time sensitive as returns will depreciate and/or fall out of trend.
The biggest challenge for demand planning and returns occurs within inventory management, where returned items can create more of an ebb and flow environment that makes it tricky to achieve accurate forecasts of future demand. This means that planning effective and consistent inventory replenishment can be challenged by the incoming pipeline of products being sent back by customers.
Poorly managed returns and demand forecasts that fail to effectively incorporate the future impact returns will have on inventory are a direct hit to customer satisfaction and loyalty. It can also lead to unanticipated business costs, such as warehousing and holding costs as these returns will have to be stored somewhere.
Leveraging Returns Data as Solution
Among the most important tools for creating accurate demand forecasts and plans lies within the data. Predictive analytics, which leverages statistics and machine learning to forecast demand based on historical data and trends, is the way of the future in demand planning, especially when it comes to factoring in the impact of returns.
Most brands and retailers undoubtedly have robust and voluminous data and trends regarding returns-related behaviors available to them. Being able to compile, process and interpret that data, is another story. While it can be costly, this is the single most important aspect of a good demand plan, one that effectively models what to expect from its customers once they receive their purchase, coupled with current market knowledge.
Collecting and analyzing data related to why an item was returned is a logical starting point for identifying trends that can then be incorporated into demand forecasts, predicting how returns might affect inventory levels, for example.
Predictive analytics, enabled by various software programs used throughout the industry, is especially useful for achieving a strong demand plan that evaluates this robust data set related to returns. These tools are capable of incorporating a much wider range of data sources and varying factors into the overall analysis. The more returns data that is captured and leveraged in this way, accounting for the reasons customers made the return in the first place and when improves modeling future returns trends.
Reverse Logistics & Customer-Centric Strategies
Having a reverse logistics partner that can integrate the data into the returns management process is invaluable. From determining the best lotting strategies to maximize recovery, to moving the item to the appropriate resale channel via qualified buyers, these partnerships not only help improve the impact of the data available, but they can streamline this process en masse and at the velocity that any given retailer needs.
This allows retailers and brands to more clearly see the reasons for returns and how they’re affecting overall inventory levels. It supercharges the ability to make informed decisions in regard to demand forecasting and inventory optimization, while retailers can more effectively reduce the impact returns will have on the overall business with a data-backed reverse logistics strategy that is geared towards recovering as much value out of returned goods as possible.
Another superpower that elevates the quality of the available data is the use of customer-centric strategies and, ultimately, segmentation. Placing the customer at the epicenter of the overall business operation, understanding their needs and terms of satisfaction, and fulfilling those needs and expectations quickly becomes the core of every function of the business. Each decision is reached through the customer filter. Naturally, long-term relationships and deeply loyal customers are born. On top of all of this, an operating mentality with the customer at the center creates a data-rich reality.
Segmenting customers, grouping them based on shared characteristics, behaviors, and preferences, allows retailers, for example, to tailor demand planning to certain segments based on the reasons for a return, the time of year, and a myriad of other data points. Targeted inventory strategies and pricing models that take into account the learned expectations of returns are truly the secret weapon no retailer should do without, especially as the scope of the returns problem is only expected to grow.
Without a reverse logistics partner, however, the benefits of these approaches are lessened by the ability to manage returns and exchanges effectively alone. Most retailers struggle to move returns through the system with the velocity necessary to capture as much value in the returned item as is possible. This is where reverse logistics partners become the linchpin, maximizing a retailer’s critical returns-related demand planning strategies for full effect, because the longer and more complicated the process, the more difficult it is for the business to recover lost revenue.
On top of this, we find ourselves at an important moment in time of growing consumer demand for returned merchandise. It means the opportunity to recover value is stronger than it's ever been. The world of demand planning and forecasting doesn’t have to be complicated by returned merchandise. By building operations around customers’ expectations and partnering with a reverse logistics expert who can help you leverage existing and new data, a future with a clearer picture of how returns impact the business from top to bottom is within reach.
