8 Predictions and Innovative Trends in Logistics and Supply Chains for 2021


8 predictions and innovative trends in logistics and supply chains for 2021

The aftermath of the pandemic, with its technological and economic adjustments, and the shift to a new normal, will drive operational processes in in-plant and e-commerce logistics and supply chains into a more agile form.

77% of organizations recognize the need for change, and are accelerating investments in supply chain sustainability over the next three years

In 2020, supply chains experienced the biggest disruption since WWII. The COVID-19 pandemic has highlighted weak spots in material flows and a lack of resilience in global supply chains. The emergency situation confronted the logistics industry and supply chains with a new set of issues and challenges, which could have been prevented through timely access to accurate data and the implementation of more elastic operational processes.

Recent supply chain disruptions and shutdowns in logistics flows foreshadow more extensive changes to come in the global supply chain model. The transition to features and operating principles of digital supply network will be accelerated in order to adapt strategies ensuring business and operational continuity and sustainability even in the face of unprecedented events and emergencies.



68% of organizations said the current crisis has forced them to adapt their business models to be more flexible and agile, while up to 62% of companies cited increasing supply chain flexibility in the post-COVID-19 period as a priority

One of the most important findings since the outbreak of the pandemic has been that too much emphasis has been placed on streamlining logistics flows and accelerating "Just in Time" deliveries at the expense of their resilience to disruptions. Therefore, the challenge for the near future in the logistics industry will be to ensure the performance of lean supply deliveries without compromising its flexibility and continued operability.

One way to achieve supply chain flexibility is through more accurate sales planning and delivery projections. Businesses that want to better anticipate potential sudden changes on markets and be prepared for the rising volatility in customer orders should focus on solutions of predictive analytics.

Proper implementation of predictive analytics requires access to relevant data. The right data ensures that sales planning and scheduling take into account the strategic and operational objectives of the business. The outputs of the predictive analytics also serve as timely alerts and notifications for employees about expected shifts (or disruptions). On the basis of this information, authorized personnel can adequately and speedily respond to changing priorities, and operationally intervene to assure smooth deliveries.


62% firms say they have limited supply chain visibility

Insufficient supply chain visibility has been frequently identified as a shortcoming in supply chain management during the pandemic. Businesses are not yet using their data to their full potential for making quick and informed decisions. Incorrect or missing data reduces the visibility of material flows, and means that material transfer and order movement cannot be adequately monitored. This significantly limits the flexibility of logistics operations and their ability to adapt to market changes.

The lack of data and the low supply chain visibility can be caused by:

  • manual demand planning,
  • inflexible ERP systems,
  • WMS systems with significantly limited functionality in terms of monitoring, data analysis and overall performance.

The result is not only an inaccurate and outdated overview of the current state of inventory and what is happening in material flows, but also inefficient and slow supply delivery processes. However, enlarging data collection and analysis can contribute to:

  • enhancing the visibility of logistics operations,
  • more detailed status information on material flows,
  • more accurate capturing of relevant transfers and movements of material and components in real time,
  • gaining access to different demand patterns that can be used for efficient inventory and order fulfillment planning.

In order for companies and distribution center operators to multiply the added value of data analytics in inventory and warehouse management, they should process data from diverse sources such as sales forecasts, POS terminals and others. The interconnection of data sources should lead to the integration, collaboration and synchronization of data and logistics processes, including the breaking down of data silos between the shop floor, the warehouse, in-plant logistics and material flows from suppliers.

Advanced data analytics is part of the innovative concept of "Demand-Driven Adaptive Enterprise", which was created in response to the growing volatility of global supply chains. The demand-driven adaptive enterprise represents a management and operational model focused on the flow of relevant information and materials while taking into account the operational, tactical and strategic scope of the enterprise. the model has three key components:

  • a demand-driven operating model,
  • demand-driven sales and operations planning,
  • adaptive sales and operations planning.

In order for an enterprise to shift towards adaptive operating models, it must begin the transformation with a demand-driven logistics, which includes:

  • increasing data clarity and unambiguity in the company's material flows and supply chains achieving a so-called single version of the truth,
  • demand-driven manufacturing planning and scheduling,
  • long-term demand and capacity planning,
  • coordinated management of materials and resources in logistics flows,
  • automated replenishment of stocks,
  • inter-departmental data integration to maintain inbound inventories up-to-date,
  • real-time tracking of material transfers,
  • data analysis with the intention of identifying deviations, downtimes, and errors in material flows,
  • predictive analytics to increase throughput in logistics flows,
  • automation of sales planning and scheduling.


56% of clientele fail to become returning customers if the seller does not have an omnichannel strategy implemented

E-commerce businesses and online retailers became the winners of 2020, as they continued to grow despite the fact that a significant portion of the economy slowed down. The combination of a variety of online and offline sales processes, i.e. the omnichannel strategy, is already becoming a necessary standard. Logistics procedures, supply chain management, and the overall process of order fulfillment must also appropriately adapt to omnichannel sales principles.

The interconnection of the physical and digital environments in omnichannel logistics provides a substantial part of the answer to the question of how to correctly ensure adequately flexible, sustainable, and serviceable logistics which have the required performance level. The fast and flawless operation of e-commerce logistics is no longer possible without:

  • an immediate overview of inventory balance and availability,
  • real-time monitoring of material flows,
  • qualified projection of expected demands and sales,
  • expanding customer-centric services.

From the point of view of strengthening the strategy of business sustainability and continuity even in cases of unexpected circumstances, such as a pandemic, it is necessary to be able to serve several sales channels simultaneously.

A comprehensive and integrated solution of intelligent logistics has already become a prerequisite for the successful transformation of the warehouse, and the adaptation of inventory management and warehouse logistics, to the model of multiple sales channels. Furthermore, businesses can no longer function effectively and efficiently with an advanced WMS system that allows them to optimize the processing of larger volumes of diverse orders, shorten picking cycles, and maximize the efficiency of order fulfillment processes.

In fact, a new generation of WMS systems is emerging to satisfy the ever-increasing requirements for performance and quality in inventory and warehouse management processes, the scaling of warehouse automation, and the demand for extended customer-centric logistics functionality. This is the Warehouse Execution System (WES). The ascent of WES systems is partly fueled by the growing demands of omnichannel distribution and logistics for more integrated solutions. Omnichannel logistics is a long-term investment and innovation.


Travel time (i.e. pickers walking around the warehouse) can account for up to 50% of the total picking time

The growing volumes of customer orders, the increasing turnover of goods, the expanding variability of sizes and types of items in warehouses, as well as the integration of other services and operations into order-picking processes, such as:

  • completion of customer orders,
  • packing and repackaging of items,
  • express dispatching of priority orders.

These already require an intelligent warehouse with an automated process management system.  As the trend of omnichannel logistics develops, and services aimed at fulfilling individual customer preferences expand, the concept of the lean warehouse is becoming a key feature in inventory and warehouse management.  

The concept of lean inventory management and warehousing primarily focuses on eliminating three side effects:

  • waste,
  • variability,
  • inflexibility.

This can lead to improvements in the areas of:

  • optimizing operating costs,
  • improving the quality of processes,
  • expanding customer service levels.

The methodology of lean warehouse management specifically includes:

  • elimination of unnecessary traveling in the warehouse (or distribution center),
  • reduction of tedious searches for ordered items,
  • prevention of downtime, unnecessary operations, and activities lacking added value,
  • elimination of picking errors,
  • removal of damaged or expired items from available stocks.

The management of e-commerce logistics and retail inventories must be adapted to ever-changing consumer behavior and fluid market conditions. This is one of the reasons why warehouse and distribution center operators need to adopt agile logistics management

For the same reasons, too, the development of warehouse intelligence goes hand in hand with streamlining inventory management (or order management in the case of e-commerce and online retail industry).

  • Dynamic warehousing procedures,
  • automated and demand-driven stock replenishment,
  • and hybrid picking strategies,

are being employed to promote both trends of warehouse intelligence and streamlined inventory management. A similar set of functionalities is used to increase the efficiency of an omnichannel warehouse (or distribution center), while the basic requirement for both scenarios is a powerful warehouse operating system and the right management infrastructure, which modern WES systems usually contain.


74% of firms use 4 or 5 different transportation modes each among their supply chain

The expansion of IoT in logistics, connecting an increasing number of devices and data sources, has allowed businesses to perform detailed data collection and analysis, and thus operate with more advanced analytics. Meanwhile, this data is key to the transition to a demand-driven logistics, to the further scaling of digital logistics management solutions and their integration with other segments of the supply chain and enterprise (e.g. shop floors, assembly lines, etc.).

Real-time data processing contributes to more flexible planning, which enables companies to reduce their reaction time in order to cope with market fluctuations. The scaling of IoT in logistics operations and the integration of other segments of material flows (warehouses, cross-docks, in-house flows, external logistics, subsidization of stocks on the shop floor) in the upstream and downstream contribute to augmenting agility and responsivity through the employment of dynamic strategies and methods.

Cyber-physical management platforms and technologies, such as digital twins, make it possible to diversify the procedures for planning, inventory managing, and order picking. An intelligent management system often uses artificial intelligence algorithms to evaluate the suitability of available procedures to maximally reduce downtime and efficiently allocate available resources with respect to ongoing jobs and tasks, leading to the further optimization of operating costs.

This approach is part of a more widespread shift in logistics and supply chain management. Modern management systems and smart industry solutions have decentralized management, which achieves extended adaptability in identifying the most appropriate logistics strategies for fulfilling business goals.

The intelligent warehouse management system - Warehouse Execution System - can combine several different picking methods based on available key data and expected sales projections. Such an approach is more appropriate for picking, packing, and dispatching a variety of different volumes, orders, and items, than relying on just one method. It allows operators better lead times in handling, moving and delivering orders.

Current WES systems can simultaneously manage cluster picking for retail orders, while deploying zone picking for wholesale orders, due to the recurring type of goods. At the same time, dynamic slotting of incoming goods can take place. The system can automatically calculate which items may become fast-moving based on actual trends and sales, and therefore assign them slotting positions as close as possible to the packaging and dispatch point.

With the availability of accurate data and a combination of appropriately selected strategies, the warehouse will increase its performance, while the processes will remain flexible enough to enable the business to respond immediately to changes in consumer behavior and adapt its logistics operations in a timely manner.


By the end of 2021, 90% of all manufacturing supply chains will have invested in the technology and business processes necessary for true resiliency, resulting in productivity improvements of 5%

Ever more companies are looking to transition to a demand-driven supply chain model, with a holistic approach to digital transformation, and the intelligent automation of logistics. This requires a close relationship between logistics and manufacturing based on data integration and the collaboration of processes.

The interconnection and coordination of material flow and warehouse management (WMS) with shop floors is becoming increasingly common. This is not only done to ensure the timely and accurate material delivery for manufacturing workplaces and assembly lines (line-feeding), but also in the interest of component preparation, the transfer of semi-finished products between individual workplaces on the shop floor, and the transportation of finished products to the warehouse for shipment (Milk Run 4.0).

More and more manufacturing firms are adapting the dynamic synchronization of material flows, not only for in-plant (manufacturing) logistics, but also in the supply chain, in order to increase overall productivity. The synchronization of manufacturing processes and material deliveries is partly covered by

  • sequential planning,
  • JIT/JIS supply,
  • or overall JIT operational strategy.

The integration of the data from the logistics and manufacturing processes, together with real-time monitoring of movements in material flows, will enable businesses to migrate to demand-driven planning while contributing to a partial expansion of process flexibility. This will allow companies to work centrally with data, and continuously plan, analyze, and accelerate qualified decision-making based on accurate and timely information.

The next step in increasing business efficiency is the direct connection between logistics management and manufacturing operations. Such integration enables dynamic synchronization and customization of management strategies in different parts of the supply chain simultaneously. In addition to streamlining material flows and accurate deliveries through following the Just in Time strategy, dynamic synchronization increases the agility of both the logistics and manufacturing processes.

The seamless coordination of logistics and manufacturing is achieved mainly through a combination of dynamic methods and elastic strategies in various parts of the material flow, and also thanks to the automatic adjustment of processes to market demands and customer requirements and preferences. Moreover, dynamic strategies lead to more efficient management of available resources, which results in the optimization of warehouse and inventory operating costs.


70% of supply chain leaders plan to invest in the circular economy

Eco-logistics initiatives and concepts of the environmental sustainability of the supply chain will continue to grow in importance. Digital technologies are already being used to reduce the carbon footprint by trimming journeys and promoting more efficient routing in in-plant logistics. Furthermore, "green" practices in warehousing and inventory management are becoming more and more common, in particular:

  • deploying electrical handling and transport equipment (forklift trucks, AGV, tugger trains, etc.),
  • employing intelligent slotting strategies,
  • installing lighting systems with motion sensors and timers,
  • using natural light on shop floors and in warehouses,
  • utilizing natural ventilation systems and strategies,
  • giving priority to solar power in the warehouse,
  • digitalizing administrative and financial processes in order to reduce the use of paper.

However, omnichannel logistics herald another significant development in sustainability. As part of the expansion of services and the growing focus on customer needs, warehouse operators and retailers are aiming to make returning goods as effortless and smooth as purchasing them. This makes reverse flows an important part of omnichannel logistics and distribution.

To ensure the efficient management of complaints and returns, the functionality of standard WMS systems needs to be extended to include reverse logistics processes. This is especially important in modern retailing where the ability to return goods easily for free and is becoming a significant competitive advantage.

Logistics thus serves not only to deliver orders to customers, but also to ensure the return of goods back to the warehouse. The return process is not exclusively reserved for unwanted purchases but also relates to products at the end of their lives. The two-way logistics concept helps close the product lifecycle loop, so an old product can be returned to a seller or a manufacturer, who can then proceed to refurbish it, recycle it, or dispose of it in an eco-friendly manner.

This approach is heralding a transition from a linear economy to a circular economy, in which reverse logistics plays a critical role. Linear supply chains will be gradually transformed into circular supply chains.

Some of the world's leading brands have already started such initiatives. For example some brands allow customers to return old and worn shoes, and the material is re-used to produce a new pair. Furthermore, we can expect this form of sustainability to shift soon from a position of corporate social responsibility to a business condition mandated by law.


By 2024, 60% of manufacturers will participate in distributed supply chain networks to reduce the risk of an unplanned disruption in their value chain

The consequences of the pandemic outbreak, such as the deceleration of globalization and the increase in regionalization, will also have an impact on the future structure of supply chains. Digital technologies have already begun to transform the design and management of supply chains, as the new tech is able to manage processes and operations in supply chains through a decentralized management model.

This means that the traditional linear supply chain model will adapt to copy the concept of distributed management. This means that the traditional linear supply chain model will copy the concept of a distributed management and lead to the alteration of the supply chain model.  This will result in the following changes:

  • shortened delivery times,
  • accelerated responses to changes in customer requirements,
  • the hyper-personalization of handled and delivered materials, components, and goods,
  • the adaptation of the principles and models of omnichannel sales to the B2B environment,
  • the transformation of business processes to fit the concept of a networked enterprise,
  • sustainability,
  • a shift to a demand-driven supply chain,
  • the implementation of artificial intelligence and machine learning technologies in order to automate the planning and management processes of material flows,
  • the transition to a circular economy.

The implementation and management of the supply network of micro-chains and cyber-chains will necessitate the following:

  • extended master data management across individual segments of the supply network,
  • B2B process integration between suppliers, subcontractors and manufacturers within a common digital inter-enterprise ecosystem,
  • the synchronization and coordination of processes between various business partners,
  • flexible cloud services and applications,
  • digital twins for the autonomous management of operations and intercompany process management,
  • the so-called control towers (applications or platforms providing a panoramic view across material flows and supply chains focused on solving specific business tasks), which not only monitor but also manage processes in real time based on available in-plant and business data. These will be able to anticipate events in the supply network, issue early alerts and correct maladjusted processes. The more technologically advanced control towers will use digital twins for greater automation of process control and ultimately, autonomization.

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