What’s the mood of global supply chains? That sounds like a funny question, I know. We don’t typically think of supply chains as having a mood, but it might be appropriate after everything we’ve been through recently. As the months go by in 2023, we have witnessed a dramatic, atypical drop in global trade. We haven’t even experienced the seasonality we typically see. Winter melds into spring; spring melds into summer. The mood is steady and colorless. There isn’t any change. We’re not seeing the shifts in trade volumes and shifts we typically see through seasonal demand and supply.
In April 2023, Oxford Economics projected a 0.6% reduction in global trade this year, pointing out that many industries are struggling to overcome pandemic-era disruptions and shortages, consumer confidence levels are low, major economies are experiencing inflation, labor shortages led to higher shelf prices, and a shift from heavy reliance on Chinese manufacturing are all weighing heavily on this scenario.
Back-to-school, back-to-college, Halloween, and the gift-giving holidays toward the end of the year are just around the corner. Maximizing sales during the peak (or holiday) season is absolutely critical to meeting annual revenue goals in the retail and consumer industry. The season starts with an appetizer in July and August in some regions for back-to-school supplies, and the main entrée is served from October to December. Now is the time for supply chain leaders to check on every function in their supply chain to be sure they are ready for the peak season.
In this blog series, learn more about the new preparation strategies for your company to sail through with success.
Supply chain planning (SCP) is the process of anticipating market demand over time and determining the optimal use of assets and resources to make, move, and distribute supply to meet demand while minimizing costs and maximizing customer service. It answers the key questions that set the course for the entire supply chain – How much do we need to make? How many will we sell? Which products will sell? Where will each product sell? And how fast? And so on. Planning and inventory stocking levels are inextricably linked. From the demand and supply forecast, planners determine how much inventory to stock at points along the value chain and distribution centers, with some safety stock to absorb day-to-day variations. The system works relatively efficiently when forecast assumptions are known and variability is low. When shifts in demand and disruptions to supply are missed, inventory becomes a liability in the form of stockouts or excess inventory that ties up working capital.
How reliant are you on history repeating itself?
Traditional planning relies on historical sales data as the primary input to identify patterns and forecast demand over a given time horizon. Pre-pandemic, this was a reasonable assumption. Demand planners assumed supply is virtually unconstrained, that transportation is predictable, and that consumer behavior would repeat itself (after considering economic conditions, fashion trends, and so forth). Of course, the last three years have thrown everything into question. None of the last three peak seasons look anything like their predecessors. And the only guarantee in 2023 is that it will differ from any prior peak seasons.
In 2022, demand slowed dramatically, leaving retailers and manufacturers scrambling to find warehouse space to store incoming shipments. A year later, some companies have finally gotten their inventory levels to a manageable level, while others are still working to discount, donate, or destroy inventory at a tremendous hit to the bottom line.
The undercurrent of this—the turmoil of the last three years—is that most disruptions and variability originate from outside the enterprise. Unfortunately, traditional supply chain planning tools and processes rely on historical and internal data, making them susceptible to missing external risks to supply and demand.
Time for a paradigm shift
Albert Einstein is attributed with saying, “Insanity is doing the same thing over and over and expecting different results.” Whether he said it or not, the sentiment still holds a lot of truth. When planners strive to improve forecast accuracy by tuning forecast models or applying new algorithms against historical demand data, they are essentially doing the same thing and expecting better results. To stop from going insane this peak season, now is the time to recognize that your supply chain planning and inventory management processes might not be up to the task of dealing with the realities of 2023, not to mention whatever comes next year.
Before any flight, airplane pilots file plans in advance of departure. Much like a supply chain planner, they use domain knowledge and historical data to develop an optimal route from origin to destination. While in flight, they use the flight plan as a guide; however, they actively take in weather condition data, air-traffic information, and use radar to detect hazards and disruptions. Then they adjust their flight path to ensure a smooth and safe experience while delivering passengers to their destination on time. In the same way, supply chains need to use the long-term plan as a guide but actively detect shifts in demand and disruptions to supply early and make course corrections to maintain customer service levels and optimize working capital.
Navigating peak season 2023 and beyond
By now, you likely have your 3–6-month plan established for the second half of 2023. The question remains: Where did the plan get it wrong, and by how much? As we have all learned, uncertainty is the only certainty in today’s supply chain. You can shorten your planning cycles to react a little faster to changes. However, this is very resource intensive and yields minimal improvement.
Success during the peak season (really in any season) relies on consistent, short-term execution excellence. Like the airplane pilot, short-term execution excellence involves continually comparing the long-term plan to real-world market conditions. Planners should look at fresh daily forecasts at a granular level and make supply and inventory decisions to keep goods flowing on time and in full.
Without the right technology, a daily forecast and inventory balancing process can be overwhelming, if not practically infeasible. Technology can automate much of the process to collect and harmonize the data, apply advanced forecasting algorithms, and generate a daily demand forecast and inventory recommendations. There are two essential enabling capabilities needed to automate this process.
- First, identify data that drives or influences your demand. In other words, demand signals. Typically demand data includes ERP and point-of-sale (POS) data and can be extended to weather, social sentiment, pollen count, local demographics, etc. Connecting to these disparate data sources can be laborious, and each follows different data formats and protocols. E2open Demand Signal Management simplifies and automates the process of collecting, harmonizing, validating, and enriching any and all data relevant to your market.
- Second, demand sensing applications, like the pilot’s radar, help planners to see demand shifts in near real-time and understand the impact on the plan. E2open Demand Sensing uses proven machine learning (ML) algorithms to analyze real-time supply chain data and determine the influence of new demand signals. It automatically generates daily forecasts looking at the forecasted demand over lead time so planners can proactively adapt to changing market conditions.
No one knows how the next six months will unfold for this peak season. However, with demand signal data and machine learning insights from e2open supporting a focused execution process, supply chain planners can navigate the turbulence and maintain service levels, safeguard revenue, and improve working capital utilization.
To learn more about how to put planning with insights into practice, read Planning With Insight: Channel and Planning Functionality Combine for Success.
Do you have questions or wondering how to start? Let’s talk.
