How to Optimise Fulfilment with Unified Data

Order fulfilment 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 organisations have multiple systems for order, warehouse, or transportation management that are barely integrated – frequently not at all. However, large organisations are often equipped to handle fulfilment in-house, leveraging their extensive resources and capabilities. An organisation 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 analyse masses of data in real time, you will struggle to deliver on-time, in-full and your reputation and revenue will be negatively impacted.

Optimising fulfilment 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 categorisations play a crucial role in determining the costs associated with shipping products that meet standard criteria in fulfilment centres. The fulfilment process is further complicated by ongoing shifts in customer expectations and demands and geopolitical and weather disruptions.

The key measurement of fulfilment is on-time in-full (OTIF) fulfilment, 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 fulfilment 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 fulfilment optimisation. Establishing standard benchmarks for services and innovations in fulfilment centres is crucial in this context. Fulfilment 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?” Fulfilment 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 fulfilment strategy can help businesses boost customer satisfaction (CSAT), reduce inefficiencies, and increase sales. By setting clear expectations and standards for fulfilment 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 analysing fulfilment operations can help identify areas for improvement and implement strategies to optimise these processes.

Effective fulfilment 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 fulfilment operations: in-house fulfilment or outsourcing fulfilment 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.

InterSystems surveyed 450 senior supply chain practitioners to examine key supply chain technology challenges, trends, and decision-making strategies across five key use cases: fulfilment optimisation; demand sensing and forecasting; supply chain orchestration; production planning optimisation; 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 Optimising Supply Chain Performance with Unified Data series, with a focus on optimising fulfilment. 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 fulfilment centres and the need for adaptive strategies to stay competitive in the evolving landscape.

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 fulfilment goals is impeded by several issues. When asked to name their top three challenges for fulfilment optimisation, 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, optimising fulfilment from the right location is more important than ever. Strategies for managing excess inventory and preventing overstocking are crucial to maintaining efficient operations.

The second challenge identified by respondents was the inadequacy of planning tools. This can lead to fulfilment 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 fulfilment 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%).

The final challenge associated with optimised fulfilment 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, geopolitical 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.

Respondents were asked to identify the data technology innovations they would most want to implement to achieve fulfilment optimisation. 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 harmonised and normalised 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 fulfilment.

AI and ML impact every stage of the order fulfilment 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 optimised fulfilment processes. Inventory management systems can ensure businesses are notified when stock levels are low, allowing timely replenishment and minimising the risk of stockouts.

InterSystems Supply Chain Orchestrator is a data platform that provides an AI-enabled connective tissue, ensuring real-time accurate data flows along all supply chain systems to transform order fulfilment rates. It provides four embedded technologies as a single capability: consistent trusted data that is harmonised and normalised from disparate sources; real-time data and analytics for on-demand, real-time analysis; intelligent processes for seamless interoperability; and business intelligence with actionable predictive and prescriptive insights, leveraging our ML and AI.

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

By increasing automation through Supply Chain Orchestrator, organisations accelerate decision-making, offer self-service access to analytics, and remove human errors. Organisations 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 fulfilment system is essential in managing order delivery and inventory, contributing to better operational efficiency.

Order accuracy and efficiency are critical aspects of fulfilment operations, as they directly impact a business’s ability to fulfil orders on time and in full. Effective order picking and shipping processes are essential for improving order accuracy and efficiency, reducing fulfilment 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 optimise fulfilment 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 fulfilment 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.

PALTAC is Japan’s largest wholesaler of over-the-counter drugs, cosmetics, and daily necessities. It has used the power of InterSystems technology to achieve landmark 99.999% OTIF, delivering 3.5 billion products annually. A reliable logistics network is crucial in achieving such high OTIF rates, ensuring efficient shipping and order processing. PALTAC's ability to efficiently manage the fulfilment of new products has been a key factor in maintaining their high OTIF rates.

Using InterSystems technology as a platform for digital transformation, PALTAC has improved its workforce efficiency as it routinely optimises fulfilment of orders for 50,000 items from 1,000 manufacturers in response to demand from 400 retailers operating 50,000 stores.

The platform supports an application which uses AI to automate allocation of personnel for in-store activities, increasing productivity, and on-shelf availability. Real-time data flows and advanced interoperability have driven more advanced use of robotics. The company is more agile and benefits from streamlined processes, higher revenue, and higher CSAT, all of which are underpinned by the trust customers place in their reliable fulfilment services.

These survey findings confirm that most organisations lack the necessary capabilities to optimise highly complex supply chains with interwoven dependencies. To be truly agile and competitive, organisations 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, organisations need a streamlined source of standardised, 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. InterSystems Supply Chain Orchestrator™ intelligent data platform eliminates the significant data challenges that organisations encounter on their path to optimised fulfilment and repeat purchases.

Read the full report here.