Order fulfillment is the complete process from when an order is placed until the shipment is delivered. Accurately fulfilling thousands of orders for millions of items is extremely challenging. Many large organizations have multiple systems for order, warehouse, or transportation management that are barely integrated – frequently not at all. However, large organizations are often equipped to handle fulfillment in-house, leveraging their extensive resources and capabilities. An organization with tens of thousands of different products may have to move them across many modes of transportation, IT systems, and third-party logistics partners, all adding to complexity, as well as loss of visibility and control.

Sudden and significant changes in demand, especially in consumer markets, stack up more challenges, requiring order revision and reallocation. If your systems are disjointed and you lack the ability to analyze masses of data in real time, you will struggle to deliver on-time, in-full and your reputation and revenue will be negatively impacted.

Optimizing fulfillment requires a series of steps to get a shipment from its source to the end customer. These steps include sourcing and receiving inventory, storing inventory, order processing, picking and packing an order, shipping the order, and returns management. Standard sizes and categorizations play a crucial role in determining the costs associated with shipping products that meet standard criteria in fulfillment centers. The fulfillment process is further complicated by ongoing shifts in customer expectations and demands and geo-political and weather disruptions.

Introduction to OTIF Fulfillment

The key measurement of fulfillment is on-time in-full (OTIF) fulfillment, which is calculated as a percentage of orders that are delivered on the requested delivery date and in the quantity requested by the customer. The formula for OTIF is:

Measuring a supply chain against OTIF metrics is a key strategy that helps decision makers attach a tangible value to the success of their fulfillment and allows them to determine key strategies. Factors like planning tools, inventory management, demand patterns, and innovations in technology contribute to the success or failure of fulfillment optimization. Establishing standard benchmarks for services and innovations in fulfillment centers is crucial in this context. Fulfillment costs can significantly impact profit margins, making it crucial for businesses to understand these financial implications and how they influence consumer spend.

The question then becomes “what is a good OTIF score to shoot for?” Fulfillment success, and the associated OTIF score, will vary by industry, region, and other assorted factors, but generally speaking, an OTIF score is considered good if it falls between 80% and 90%. Many companies aim for 95% or higher, which can be a daunting task. For suppliers, the penalties associated with missing OTIF goals can be significant. For example, Walmart’s OTIF program mandates that suppliers should meet the 90% on-time and 95% in-full goals to avoid penalties. Walmart fines suppliers 3% of the cost of goods sold (COGS) for orders that fail to meet on-time and in-full delivery requirements.

A good fulfillment strategy can help businesses boost customer satisfaction (CSAT), reduce inefficiencies, and increase sales. By setting clear expectations and standards for fulfillment operations, including OTIF rates, shipping times, and inventory levels, businesses can ensure that they meet customer demands and maintain high levels of satisfaction. Regularly monitoring and analyzing fulfillment operations can help identify areas for improvement and implement strategies to optimize these processes.

Effective fulfillment requires a well-designed system, efficient logistics, and a reliable supplier network to ensure timely and accurate delivery of products. Companies have two options to consider for fulfillment operations: in-house fulfillment or outsourcing fulfillment to a third-party logistics (3PL) provider. While outsourcing to a 3PL is a common strategy, new technologies and approaches now exist to achieve higher OTIF rates in house.

Warehouse Fulfillment Complexities and Inefficiencies

InterSystems surveyed 450 senior supply chain practitioners to examine key supply chain technology challenges, trends, and decision-making strategies across five key use cases: fulfillment optimization; demand sensing and forecasting; supply chain orchestration; production planning optimization; and environmental, social, and governance (ESG). These respondents came from 13 countries and 12 industries, representing decision-makers across project management, fleet management, sales & marketing, HR, and finance.

This blog is Part 1 in our Optimizing Supply Chain Performance with Unified Data series, with a focus on optimizing fulfillment. Effective inventory management strategies are crucial for businesses looking to expand their operations and improve delivery efficiency, particularly when scaling to multiple warehouse locations. Looking to the future, businesses should prepare for trends such as the growth of micro fulfillment centers and the need for adaptive strategies to stay competitive in the evolving landscape.

Ability to Meet Fulfillment Goals

According to the survey, only a mere 1% of respondents achieve 80% or higher for their OTIF metrics, with the average percentage of OTIF being a mediocre 62.21%. The ability to meet fulfillment goals is impeded by several issues. When asked to name their top three challenges for fulfillment optimization, respondents cited the high volumes and complexities of SKUs (59%), inadequacies of existing planning tools (51%), and volatile demand (42%). Considering that the majority of respondents are using manual processes, legacy systems, or multiple solutions from different vendors to integrate and prepare disparate data, this makes sense.

SKU complexity generally refers to the challenges and inefficiencies associated with keeping a large number of SKUs within a store, warehouse, or factory. This includes picking the correct items from inventory, packing them appropriately, and ensuring their timely delivery to customers. Managing too many SKUs leads to higher inventory carrying costs and general inefficiencies. On top of that, the lifecycle of a SKU is getting shorter, especially as more businesses turn to e-commerce for direct-to-consumer selling. A SKU is designed, received, and pushed to the market, but often it is not available six months later, making replenishment nearly non-existent. Without re-stocks, optimizing fulfillment from the right location is more important than ever. Strategies for managing excess inventory and preventing overstocking are crucial to maintaining efficient operations.

Inadequacy of Planning Tools

The second challenge identified by respondents was the inadequacy of planning tools. This can lead to fulfillment failure from the standpoint of missed deadlines, increased costs, or poor customer satisfaction. Timely information is critical, as data older than a few days can lead to costly supply chain disruptions. Perhaps not surprisingly, the industries that reported they would see the biggest improvement in fulfillment rates if able to ingest real-time data and provide actionable insights to business users were automotive and aeronautics (55%), FMCG (44%), and manufacturing/CPG (43%).

Demand Volatility

The final challenge associated with optimized fulfillment is demand volatility. Demand volatility is the sudden and unpredictable variation in customer demand for products or services over a specific time. The root causes are not always easy to identify, but they can be attributed to changing customer expectations and demands, changing promotions, or a shift in market dynamics such as external weather events, geo-political instability, and shipping disruptions like the Francis Scott Key Bridge collapse or the blockage of the Suez Canal. These changes make it harder for companies to forecast demand in both the near and long term and can lead to further supply chain disruptions. Effective returns management is also crucial in handling the unpredictable nature of demand, ensuring that returned products are inspected, restocked, or disposed of efficiently. Tracking how much inventory is held and assessing inventory age are essential to making informed decisions about restocking and mitigating risks such as stockouts and overstocking.

Fulfillment Strategies

Respondents were asked to identify the data technology innovations they would most want to implement to achieve fulfillment optimization. The top response was the use of artificial intelligence (AI) and machine learning (ML) (46%), which outpaced predictive and prescriptive analytics (37%), the use of a decision intelligence platform within supply chain (37%), real-time harmonized and normalized data from multiple sources internal and external (37%), and streamlined integration of different solutions (37%).

These technologies can be directly integrated with existing systems, allowing businesses to automate workflows and reduce errors in managing inventory and order fulfillment.

AI and ML impact every stage of the order fulfillment process, with a specific emphasis on forecasting, inventory management, order processing and picking, and last mile deliveries. For improved OTIF, AI and ML help companies make smarter decisions faster, improve turnaround times, and simplify manual processes in the warehouse. The real desire for survey respondents is to improve upon current systems and processes to make better sense of their data, enabling optimized fulfillment processes. Inventory management systems can ensure businesses are notified when stock levels are low, allowing timely replenishment and minimizing the risk of stockouts.

Actionable insights drive significant efficiencies in every area, increasing automation and significantly boosting productivity. Supply Chain Orchestrator provides the infrastructure needed to optimize raw materials handling from point-of-supply to end consumption. Organizations can integrate transportation, warehouse management systems, and advanced robotics. Packaging plays a crucial role in the fulfillment process, ensuring items are carefully packaged for safe transport.

By increasing automation through Supply Chain Orchestrator, organizations accelerate decision-making, offer self-service access to analytics, and remove human errors. Organizations are ready to implement AI and ML-driven prediction and productivity gains. They achieve rapid adaptation to any changes in demand, logistics disruptions, or business priorities, leading to increased CSAT and higher revenue. An efficient fulfillment system is essential in managing order delivery and inventory, contributing to better operational efficiency.

Order Accuracy and Efficiency

Order accuracy and efficiency are critical aspects of fulfillment operations, as they directly impact a business’s ability to fulfill orders on time and in full. Effective order picking and shipping processes are essential for improving order accuracy and efficiency, reducing fulfillment costs, and enhancing the overall customer experience.

By implementing efficient logistics and shipping strategies to ship orders, businesses can reduce shipping times, improve their OTIF rates, and increase CSAT. Regular monitoring and analysis of picking and shipping processes are vital for identifying areas for improvement and implementing strategies to optimize fulfillment operations.

Technology plays a significant role in improving order accuracy and efficiency. Automated packaging and shipping systems can help businesses streamline their operations, reduce errors, and lower fulfillment costs. By leveraging these technologies, businesses can ensure that their customers receive their orders accurately and on time, leading to higher levels of satisfaction and loyalty. But technology plays an even bigger role in data unification and management, especially when it comes to integrating new technology with existing applications.

Final Thought on Fulfillment and Repeat Purchases

These survey findings confirm that most organizations lack the necessary capabilities to optimize highly complex supply chains with interwoven dependencies. To be truly agile and competitive, organizations must be capable of extracting critical insights in near real-time. But as things stand, this remains a significant challenge when so many businesses lack end-to-end visibility, or rely on manual data analysis and ad hoc assemblages of different solutions.

In the face of constant change, disruption, and opportunity, organizations need a streamlined source of standardized, clean, meaningful, and reliable data that is available to business users. Maintaining proper stock levels is crucial to ensure product availability and prevent issues like stockouts or overstocking. An intelligent data platform eliminates the significant data challenges that organizations encounter on their path to optimized fulfillment and repeat purchases.

Read the full report here.

Chris Cunnane is the Supply Chain Product Marketing Manager at InterSystems. In this role, he is responsible for developing and executing marketing strategy and content for the InterSystems supply chain technology suite. Chris has 20+ years of supply chain expertise, leading the supply chain practice at ARC Advisory Group, as well as holding various sales, marketing, and operations roles in the wholesale, retail, and automotive parts markets. He holds a BA in Communications from Stonehill College and an MA in Global Marketing Communications from Emerson College.

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