Supplier Collaboration Value

With cost cutting still very much at the top of the business agenda, companies across the world have already started creating improvement plans to tackle operational expenses, writes Simon Thompson (pictured), VP Northern Europe at JAGGAER.

Businesses are focusing on driving value through supplier partnership and are prioritising visibility of stock and procurement strategies optimisation. In fact, one typical business area that is usually seen as no more than a cost centre is procurement and, more specifically, the supply chain. As a result, savvy businesses are reassessing their approach to supplier relationship management, enacting measures that amount to a complete paradigm shift to transform this function in a value centre that can create long-term value as well as reduce costs.

Traditional cost-cutting strategies, that prioritise short-term savings and negotiating the lowest possible prices with suppliers, can backfire over time, potentially leading to quality issues that may escalate into expensive product recalls, customer dissatisfaction, and reputational harm. Strategic partnerships and collaboration within the supply chain can instead become an opportunity to create additional value that goes beyond simply reducing costs, allowing the procurement officer to consolidate spending or uncover shared efficiencies to encompass a range of key issues and benefits such as promoting sustainability, co-investing in innovation and finding new avenues to enhance customer satisfaction. These partnerships can help mitigate supply chain risk, improve resilience, foster digital transformation and facilitate regulatory compliance.

Collaborative procurement strategies

Effective cost management in supply chains therefore extends far beyond reducing raw material costs and covers every stage of the supply chain, from sourcing and logistics to inventory management and payment terms. That’s when collaborative procurement strategies come into play. These strategies are based on building trust and transparency, fostering beneficial partnership with the supplier with the aim of achieving cost saving without compromising quality. Open dialogue and transparency are at the core of this approach, allowing buyers and suppliers to collaborate openly, sharing objectives and creating mutual benefits. Sharing demand forecasts helps suppliers optimise production processes, minimising waste, lowering operational costs and reducing prices.

Key to achieving this transparency are real-time procurement platforms that grant visibility to both companies and suppliers and can also improve demand management and inventory needs synchronisation, prevent overproduction, as well as enabling more efficient resources allocation, production schedules and inventory management, ultimately reducing unnecessary costs. While it’s important for procurement to have visibility, trust is a two-way process and a sometimes overlooked component of supplier collaboration is committing to on-time payments. Consistently paying suppliers on time fosters trust, which can lead to improved payment terms or pricing advantages.

Thanks to these platforms it is also possible to enable Just-In-Time (JIT) processes. In fact, partnering with suppliers to implement JIT inventory systems can help minimise excess stock and storage costs, while ensuring timely delivery of goods. This is particularly relevant for industries handling bulky items, perishable goods, or material requiring strict temperature control, such as those managed within the cold chain. In the pharmaceutical sector, for instance, JIT helps reduce waste and improve efficiency by ensuring medicines or devices are ordered and delivered only as needed for production, significantly reducing the likelihood of having to deal with unused or out-of-date stock.

Efficiency gains

Conducting regular supplier relationship evaluations using scorecards provides another avenue for efficiency gains by identifying areas for improvement, uncovering potential cost-saving opportunities, and strengthening collaboration. These evaluations also offer a transparent foundation for discussions and renegotiations with suppliers and offer the opportunity to raise issues or share ideas for improvements such as a new supply route or material. Centralized platforms that automate transactions, facilitate communication, and provide advanced analytics allow businesses to identify inefficiencies and optimize procurement strategies. By leveraging intelligent technologies, companies can enhance decision-making, mitigate risks, and access diverse data sources, without overburdening internal teams or suppliers with excessive manual data entry and updates.

Procurement’s focus is shifting from cost control to driving value creation, and supplier collaboration is emerging as a pivotal strategy for achieving not only sustainable cost savings but also broader operational improvements. Success in this area hinges on building trust, ensuring transparency, and adopting a comprehensive approach that balances cost savings with other factors like quality, supplier diversity, long-term sustainability, and risk management. This approach relies on a strong data foundation across the entire source-to-pay process, supported by advanced spend analytics. With these tools, procurement leaders can develop and implement strategies that deliver significant value for both buyers and suppliers, while nurturing strong, cooperative relationships with every actor of the supply chain.

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Data: The Driving Force Behind the Logistics Industry

Data is the key driver of the logistics industry. Organisations require information about the time they need to process an order, get the shipment ready, arrange for transport, put the item on a transport vehicle and make a timely delivery. Without data, companies may not know how to address inefficiencies or protect themselves from disruptions in transportation routes. Fortunately, data tools for logistics are abundant. Businesses can integrate technology into existing systems to optimise routes, find problems in order processing and cut costs. By implementing these technologies, logistics professionals can guide effective decision-making that improves efficiency and accuracy.

Gain Insights About Transportation Patterns

Logistics professionals have to remain current on the latest transportation patterns, which they can achieve with data. Descriptive analytics uses past data to identify changes in preferences over time. Predictive analytics can take this data to highlight changes to transportation patterns and potential disruptions to movement. With this information, logistics companies can be certain they have the most accurate information for forecasting and order management.

Optimise Routes

The choice of shipping route affects costs, delivery time and overall efficiency, highlighting opportunities for technology to optimise the route. Companies select shipping routes based on a variety of factors, including traffic, cost of fuel and the potential for lengthy delays. Optimising the route helps to reduce costs and time spent making a delivery, particularly in the last few kilometres of a journey. Prescriptive analytics can provide detailed information based on historical and current trends, automatically highlighting routes that improve performance.

Improve Efficiency

Data can provide the tools to increase efficiency at all points in the process, from forecasting demand and increasing the robustness of the supply chain to improving the order process. Companies need to know how demand is changing for a particular product, so they can maintain an ideal inventory to handle it. Predictive analytics can also highlight weaknesses in the supply chain, so that businesses can identify alternatives. AI can automate various aspects of the order management process, to minimise bottlenecks and complete order processing more accurately.

Reduce Excess Costs

Cognitive analytics, as part of a comprehensive package of data analysis, can reduce excess costs at every stage. Companies spend more to have a human perform tasks that AI can do autonomously. Implementing an AI system allows a business to verify inventory and process an order quickly, highlighting any problems for prompt review. The system can also use past data

to identify existing problems with various processes, so that professionals can address them. These improvements increase the accuracy of each order, decreasing the financial impact of returns or lost clients.

Increase Customer Satisfaction

Ultimately, the incorporation of data into a transport management system leads to better outcomes in customer satisfaction. Customers expect orders to be processed efficiently, calling for an accurate and sensitive inventory management system. They also want deliveries to occur quickly and accurately, with tracking that provides relevant information and does not compromise their personal security. Integrating analytics into all systems can ensure that customers get everything they need during each step of the process.

Data integration is transforming the efficiency and accuracy of many worldwide industries, transportation and logistics in particular. With technology’s ability to handle massive amounts of data in record time, the benefits are obvious. Recording and processing data provides crucial information for businesses to improve their processes to meet the needs of the future. Using data analytics to analyse past problems, evaluate the potential for solutions and create a plan to weather future changes can save companies significant time, money and effort.

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UK Parcel Delivery to Lead Europe This Festive Season

A new study released today by FedEx, forecasts that parcel carriers will collectively distribute 1.29 bn shipments across the UK between October and December 2024, 10.9% more than in the same period in 2023.

The independent study was conducted by Effigy Consulting, which analysed its courier, express and parcels (CEP) database with 500,000 data points on more than 300 carriers in 41 countries.

The data shows a significant increase on the UK figures for 2023, up from 1.17bn parcels to 1.29bn in 2024. The UK will be the busiest market for parcels this Peak season, representing 21% of the total deliveries made, equating to 12 parcels per person across the UK and Europe.

Germany and France will be the second and third busiest markets, with Germany accounting for 17% (1.1 bn) and France making up 8.4% (524 mil) of the total parcels delivered across Europe. This growth is being driven by a rise in e-commerce which accounts for nearly 70% of shipments going directly to consumers across the European market.

Alun Cornish, Vice President Network Operations at FedEx commented: Peak season is a critical period for UK businesses, with many relying on transportation and logistics to meet increased demand and deliver for their customers. Online shopping, ecommerce, and a shift towards deferred services will continue through this year’s peak, reflecting changing consumer behaviour and ongoing cost-consciousness in the market.”

FedEx’s networks will scale and adapt to meet the UK’s increased demand, with options for air and road transportation, as well as more predictive technologies to manage potential disruptions and make the ‘golden quarter’ a success.”

Across the whole of Europe, 6.2bn shipments will be made between October and December 2024, 9.0% more than in the same period in 2023. The UK is one of the fastest growing major European countries with a growth of 10.9% on last year, outpaced only by Portugal and Poland and countries such as Turkey, Croatia and Bulgaria.

To illustrate the scale of the Peak, the total European volume (4.878 bn cubic feet) would equate to filling the entire structure of Wembley Stadium thirty-four times over. The total weight of goods transported across Europe at this Peak will be almost 7.5m tonnes, which equates to around 15 kg for every person living in the EU and the UK.

The countries with the highest volume of shipments during this Peak season are the UK (1.3bn) and Germany (1.1bn), followed by France with just over half a billion (524m), with twelve parcels sent for every person in the UK and EU during the three-month period.

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How Data-Driven Maintenance Transforms Materials Handling

Data-driven insights can help optimise the performance, maintenance and sustainability of warehouse automation and materials handling, explains Dan Migliozzi, Sales & Marketing Director, at Invar Group.

Current materials handling and intralogistics equipment is amazingly reliable. Nonetheless, there is a lot to go wrong – all those mechanical parts like rollers, bearings, motors, belts, not to mention switches, sensors and the rest of the electronics. For many businesses this equipment is fundamental – if it’s offline, everything stops.

Unexpected failures, and unplanned maintenance and repair, don’t just increase costs and impair customer service, they have direct and significant environmental and sustainability impacts. But by implementing data driven maintenance strategies these cost, performance, and environmental impacts can be greatly reduced.

Don’t be blinkered

Some companies, particularly those with limited in-house capabilities, work on an ‘if it ain’t broke, don’t fix it’ basis. This may appear to reduce unnecessary downtime and cost, but is a high-risk strategy. There’s a well-known law that states if something can fail, it will, and at the worst possible moment – peak season, rush order, Bank Holiday weekend when the spare parts stockist is closed. Not recommended.

A more sophisticated approach is that of planned, scheduled maintenance. Components subject to wear, or otherwise likely to fail, are replaced at regular intervals – as recommended by the equipment manufacturer, or based on bitter experience. This approach too has disadvantages.

The expected life of a part is a statistical construct – some will fail early; others may be good for much longer. Maintenance intervals are often based on the calendar, rather than the amount and nature of the usage the equipment has experienced – typically, all the parts of a given ‘lifespan’ will be replaced whether they need it or not. Perfectly good parts are sent for scrap. Meanwhile, the performance of other components may be degrading, well in advance of their ‘due’ replacement date. This may have knock-on effects on the condition or

life of other system components, while increasing the consumption of energy, lubricants and other consumables. None of this is good for sustainability.

An intelligent data-driven approach

Maintenance doesn’t have to be this arbitrary. Most materials handling automation gathers a plethora of condition monitoring and other data that can be used in a preventative maintenance approach – key parameters, perhaps the energy consumption of motors, or the temperature of bearings, can be monitored, and generate alerts and warnings before the worst happens.

But instead of maintenance staff merely reacting to warnings that an element is, or is about to go, out of its performance envelope, we can use intelligent analytical software to drive the maintenance process in the most efficient and sustainable directions.

We can bring together both historical and real-time data, from SCADA and other systems, to identify failure areas and causes – both one-time events and regular wear-and-tear, mean times between failures, and downtimes required to take action. We can use data on actual loadings and usage, rather than elapsed times, to predict which components are likely to require replacement and when – and which identical components should still be okay. All the sites we instal have this data waiting to be used and we have the software tools capable of analysing this data, to inform our decisions on the most appropriate, proportionate actions to take.

Further, software empowers learning, encouraging continuous improvement and potentially revealing where investment in new equipment, or appropriate upgrades and enhancements – or indeed staff and operator training – may be needed.

Data driven maintenance mean that equipment can operate longer at maximum capacity, and reduce those minor jams and other incidents, while necessary downtime can be optimised to suit patterns of work. This makes best use of engineering staff (internal or external), to anticipate the need for, and ensure the availability of the necessary spare and replacement parts so that maintenance downtime is not wasted.

Sustainability strategies

Data analysis of warehouse automation and its maintenance needs contributes to a wider suite of environmental goals and strategies.

Analytics allows for efficient use of a most critical resource – planning where and when trained staff will be needed, and what their training needs are.

Effective maintenance strategies support waste reduction goals by reducing the unnecessary use of costly (in economic and environmental terms) replacement parts. Parts may be recovered when they are still able to be reconditioned rather than scrapped.

Data driven preventative maintenance ensures efficient performance of the automation, thus reducing consumption of energy and consumables – a badly worn conveyor belt may consume 2-6 times as much energy as one in good condition. More generally, analytics can be used to drive the automation in the most energy-efficient modes.

The consumption and waste of packaging materials and their contents, damaged by underperforming or failed equipment, is reduced. Automation also reduces or eliminates the use of more polluting forms of materials handling equipment such as lift trucks.

Automation can mitigate or eliminate many of the Health & Safety risks associated with warehouse operations, such as lifting. Equipment that is well maintained so as to stay within its designed operational envelope is inherently safer.

Importantly, analytics can reveal differences in the lifecycle impacts of parts and materials from different suppliers, which can help inform sustainable procurement policies.

And whilst the physical maintenance operations inevitably incur downtime and another round in the age-old battle between operations and engineering, machine monitoring means the need to stop the line for inspection and assessment is largely eliminated. Ironically, disassembly of equipment for inspection is itself a recognised cause of failure!

We are all rightly concerned about the sustainability of our companies’ operations. Intelligent warehouse automation supported by a data analytical approach to maintenance which predicts and prevents equipment failures, will reduce downtime, improve costs and service levels, and significantly reduce the environmental impact of operations, maintenance, and repairs.

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How Digital Dispatchers are Revolutionising Fleet Operations

In the long-haul full truckload (FTL) industry, dispatchers have traditionally relied on manual processes and years of experience to navigate a complex regulatory landscape, fluctuating fuel prices and evolving customer demands. While functional, this approach is far from optimal, putting pressure on dispatchers and leading to inefficiencies and missed cost-saving opportunities.

But this is finally starting to change. The logistics landscape is undergoing rapid digital transformation, and the dispatcher’s role is no exception. No longer a route and schedule coordinator, the modern dispatcher is evolving into a data strategist, harnessing technology to optimise fleet operations and drive efficiency. So, what technologies are driving this change? And how can we expect the dispatcher’s role to evolve further?

From dispatcher to data strategist: The power of predictive analytics

In the past, dispatchers had to scramble to gather information from various sources in order to estimate disruptions (e.g. weather forecasts, GPS and messaging applications). Often, they relied on a reactive ‘firefighting’ approach, using manual processes to calculate and recalculate available driver hours and ETA.

However, predictive analytics – such as utilising AI and machine learning to identify the likelihood of future outcomes based on historical data – is transforming dispatcher operations. Thanks to this, dispatchers can forecast potential disruptions, such as congestion, adverse weather events or vehicle maintenance requirements, and preemptively adjust routes, schedules, and resource allocation. Data suggests dispatchers see time-savings of 25-45% from the automation of itinerary monitoring and recalculation.

Predictive analytics tools transform dispatchers into proactive data strategists, allowing them to play an active role in boosting the bottom line by minimising delays, reducing operational costs and enhancing customer satisfaction.

Data-driven decisions: Real-time insights

The same FTL long-haul trip can have hundreds of different execution plans depending on driver availability, day of the week, time of year, planned roadworks, customer requirements and more. The possibilities are endless. Experienced dispatchers are great at putting together feasible execution plans considering these factors. However, relying on real-time data is the best way to make an optimal choice.

Real-time data is only useful if companies have the tools and resources to analyse it and action the resulting insights. Dispatchers are perfectly placed to help maximise the power of real-time data. They just need the right tools.

Thanks to recent advances in AI and ML, algorithms are emerging that simultaneously consider commercial tasks (loading, unloading, secure parking, etc.), non-commercial tasks (parking, refuelling, border-crossing, etc.), driver regulations and route planning to create the ‘ideal’ trip execution plan which is a game-changer for dispatchers. For instance, recent data indicates that dispatchers can save an average of 2.5 cents per litre simply by optimising refuelling, given that fuel prices differ by up to €0.60 per litre across Europe. This might seem small, but it adds up to €30,000 in monthly savings for a fleet of 500 trucks.

Some compare these algorithms to a ‘digital version’ of an experienced dispatcher’s brain. But the truth is much more nuanced. They won’t replace dispatchers, but enhance their capabilities and empower them to make better decisions based on real-time data.

What’s next for dispatchers?

The dispatcher’s role is evolving from a tactical executor to a strategic orchestrator of complex logistics networks. In short, the digital dispatcher isn’t just a trend – it’s the future of logistics.

The next era of dispatching lies in embracing technologies like AI and ML to automate routine tasks and analyse vast datasets. To gather the data needed for AI and ML algorithms, we’ll see greater use of IoT sensors on trucks, enabling dispatchers to monitor vehicle performance in real time, predict maintenance needs and prevent costly breakdowns.

The above technologies free dispatchers from tedious manual calculations, allowing them to focus on higher-level strategic decision-making. By embracing them, they can unlock new levels of efficiency, productivity, and customer satisfaction, ultimately driving the success of the business and the entire industry.

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eBook: End to end Costing in Express Logistics

Logistics Business magazine, together with the Information Factory, have produced a new 6 page digital magazine on managing end to end costing in express logistics. Editor Peter MacLeod talks to iFactory CEO Robert Jordan to understand how transport and logistics businesses can manage costs and grow. Learn how accurate costing of each individual process within the supply chain can be used to make commercial and operational decisions that are absolutely key to driving a business forward.

Read the free eBook here.

Understand costs and grow your business

Ever-higher levels of visibility across the logistics and wider supply chain sectors offer businesses considerable knowledge of the status of goods in transit and storage. But whilst the digitisation of the sector helps identify to a granular level where any individual item may be located anywhere in the world, the knowledge of what are a business’s key end-to-end cost drivers is less widely known.
In logistics and transport, operations are often highly complex and feature innumerable variables. But if the cost information on which decisions are based is either unreliable or – worse – non-existent, businesses can miss the opportunity to make decisions that have the potential to improve profitability in a sector where margins are sometimes wafer-thin. Furthermore, they may inadvertently make a decision that could prove costly to the business.

read the previous eBook on data driven logistics here

eBook: Data Driven Logistics

 

 

The Future of Physical Operations

Senior Executives at Samsara are forecasting trends in physical operations for next year and beyond.

Philip van der Wilt (pictured), SVP and GM EMEA of Samsara says, “physical operations will continue to be challenged by the uncertainty surrounding fleet electrification and the need to double down on fuel efficiency. Businesses are waking up to the fact that it’s not petrol, diesel or electricity that powers fleets — it’s data.

“Those who have already invested in technology and IoT platforms to manage their fleets are already better off. Fleets that have already invested in connected data platforms are better able to identify which routes, vehicles, and tasks are best suited to the electrification of their fleets.

“They’re also using these same fuel-agnostic systems to identify other technologies that will lead to fleet decarbonisation. It’s now up to the rest of the industry to play catch-up or risk being hit with a double whammy — falling behind on electrification plans while being unable to manage sprawling fuel costs.”

Stephen Franchetti, CIO, Samsara, added: “As the AI explosion continues, an organization’s ability to stay competitive and innovate will come down to their enterprise data strategy. Over the past year and a half, there’s been a significant explosion of ‘ready for prime time’ generative AI, opening opportunities for enterprises to benefit from intelligent automation. There’s no denying that AI will continue to increase efficiency, accuracy, and overall business agility in 2024.

“With this, we’ll start to see an increased need for a robust foundation of reliable and well-governed enterprise data. Utilizing the power of this data is paramount for training precise machine learning models, deriving insightful analytics, and enabling intelligent decision-making. As AI technologies continue to evolve, the quality and accessibility of enterprise data could significantly impact an organization’s ability to assess large datasets in real-time, stay competitive, eliminate bias, and free up more time for innovation.

“Expect to see an increase in vertical use cases for AI and a tight race between incumbents and emerging vendors to solve more nuanced, complex problems for these users.

“There’s already a race for incumbent players to infuse AI into every facet of their platforms. At the same time, we’re seeing several new emerging apps coming onto the scene that are purpose-built for vertical use cases within the business – like Sales, Marketing, Legal, and IT. As AI models become more robust and sophisticated, they will be able to handle the nuanced and complex tasks needed for these vertical teams. This will ultimately enable better integration between systems and processes and lead to improved operational efficiencies, as well as cost savings.

“Amidst emerging threats, increased regulation and data privacy laws, organizations will lean on technology for management and protection. With a global focus on data privacy, organizations must leverage technology to identify and mitigate risks quickly and effectively. In 2024, leaders will invest in AI-driven security to monitor network behavior, detect anomalies, and protect against potential threats – all in real time. This proactive approach will allow organizations to enhance their ability to safeguard data and operations.

“This technology, however, is only effective when coupled with a robust data strategy that leverages a zero-trust model. In the new year, more leaders will adopt this approach, which requires verification at every step of the data access and transfer process, significantly reducing the potential for breaches.”

Finally, Evan Welbourne, Head of AI and Data for Samsara, says, “explainable AI will play a key role in the broader acceptance and trust of AI systems as adoption continues to increase.

“The next frontier in AI for physical operations lies in the synergy between AI, IoT, and real-time insights across a diversity of data. In 2024, we’ll see substantial advancements in predictive maintenance, real-time monitoring, and workflow automation. We may also begin to see multimodal foundation models that combine not just text and images, but equipment diagnostics, sensor data, and other sources from the field. As leaders seek new ways to gain deeper insights into model predictions and modernize their tech stack, I expect organizations to become more interested in explainable AI (XAI).

“XAI is essential for earning trust among AI users – it sheds light on the black-box nature of AI systems by providing deeper insights into model predictions and it will afford users a better understanding of how their AI systems are interacting with their data. Ultimately, this will foster a greater sense of reliability and predictability. In the context of AI Assistants, XAI will reveal more of the decision-making process and empower users to better steer the Assistant toward desired behaviors. In the new year, I anticipate XAI will advance both the functionality of AI Assistant and the trust of AI systems.

“The evolution of generative AI across industries will focus on advancements in domain-specific knowledge and expertise, making specialized talent increasingly competitive.

“The advent of ChatGPT this past year showcased the potency of large language models (LLMs) in understanding and generating human-like text, which has accelerated investments and innovations in generative AI. Moving into 2024, I anticipate a continuous maturation of generative AI technologies, particularly emphasizing domain-specific knowledge and real-time adaptation to evolving scenarios. This convergence of generative AI with domain expertise will facilitate more nuanced and valuable insights, making AI a quintessential partner in decision-making processes across industries.

“With this, the demand for AI and machine learning talent will continue to surge in 2024, as businesses increasingly integrate AI not just into their products, but into their operational frameworks. Apart from foundational skills in machine learning, statistics, and programming, I expect to see an increased demand for expertise in domain-specific AI applications and AI governance.”

Mastering Supply Chain Resilience with Data

In the aftermath of the pandemic, businesses faced unprecedented disruptions, laying bare vulnerabilities within their supply chains, writes Suki Dhuphar (pictured), Head of International Business, Tamr.

The question that arises is: What steps can leaders take to prevent future catastrophes in the supply chain? The solution lies in a robust approach that leverages data to bolster resilience. Proactive data utilisation not only mitigates present risks but also equips companies to navigate future disruptions with agility and foresight. By extracting invaluable insights, companies can authentically confront supply chain challenges.

Let’s explore six strategic approaches that can empower business leaders to harness data effectively, guaranteeing a fortified and optimised supply chain.

1. Finding Alternatives Quickly
Inaccurate or incomplete data about parts and suppliers can lead to the selection of inappropriate alternatives, causing production delays and added costs. To address this challenge, implementing data validation processes is essential to ensure the accuracy of parts and supplier information. This includes regularly updating and cleansing the data to remove duplicates and errors.
2. Locating the Entire Supply Chain
Incomplete or outdated supplier data can result in a lack of visibility into the supply chain, making it difficult to identify vulnerabilities. To enhance this visibility, it’s crucial to continuously verify and update supplier information. Additionally, consider investing in data enrichment services to gather comprehensive data about suppliers, their subsidiaries, and distribution networks.
3. Streamlining Supplier Onboarding
Inaccurate data during the onboarding process can lead to compliance issues, delays, and misunderstandings with new suppliers. You can mitigate these risks with data enrichment services that enhance supplier data with additional information. This can include real-time verification of tax IDs, business registration numbers, and compliance with industry regulations.
4. Tracking Price Changes
Inaccurate or delayed data on price changes of raw materials needed for production can lead to incorrect financial projections and hinder the ability to adapt to market fluctuations. To address this issue effectively, it is essential to implement real-time data feeds for pricing information. Additionally, verifying the accuracy and timeliness of data sources is crucial to ensure reliable price tracking and enable timely and informed decision-making.
5. Building Collaborative Networks
Inaccurate data about distributors can lead to poor partner selection and collaboration inefficiencies. To maintain accurate distributor information, you should regularly update data and gather insights into your performance and capabilities. Data enrichment processes can also be employed here to enhance the accuracy and completeness of distributor details.
6. Optimising Procurement Resourcing
Inaccurate spending category data can lead to misallocation of resources and missed opportunities for optimisation. To ensure its accuracy, continuous auditing and validation processes are vital. Artificial intelligence (AI) and machine learning (ML) algorithms can rigorously identify anomalies, guaranteeing the data accurately reflects spending categories and their unique characteristics. This enables more effective resource allocation, unlocking hidden optimisation opportunities.

Data-driven resilience

In safeguarding your business from supply chain disruptions, a comprehensive grasp of your supply chain is crucial. Utilising accurate and well-maintained data on suppliers, costs, and materials empowers you to anticipate and navigate risks effectively. This data not only promotes collaboration within and beyond your organisation but serves as the paramount resource for mitigating supply chain vulnerabilities. By harnessing clean, curated and reliable data, you not only enhance adaptability but also fortify the resilience of your supply chain, ensuring a proactive and efficient response to evolving challenges.

Challenges of Peak Season Logistics

As the holiday shopping season rapidly approaches, shippers and carriers are yet again gearing up to tackle the formidable logistical and customer service challenges that inevitably come with peak season volumes. However, this year, their task is further complicated by ongoing supply chain disruptions all while grappling with the increasing uncertainty based on the geopolitical situation. Yet amid these challenges, customer expectations continue to soar, demanding fast, convenient, and on-time deliveries accompanied by real-time communication. To paraphrase Game of Thrones, Winter is certainly coming.

Shippers, carriers, and customers alike are no strangers to the stress involved in the months leading up to Christmas. With Black Friday, Christmas and Boxing Day sales just around the corner and unforeseen circumstances and delays, the potential for overwhelm is ever-present. However, proactive planning and more organised transportation operations can alleviate these concerns, ensuring that any potential threats to deliver a seamless peak season can be avoided.

Therefore, the need for swift and intelligent delivery solutions is more critical than ever. Transportation Management Platforms (TMP) emerge as a key enabler, allowing stakeholders to optimise delivery times, enhance agility, and streamline their sustainability and costs, all while meeting rising consumer expectations. In this article, Christian Dolderer (pictured), Head of Market Intelligence Europe Road & Intermodal at Transporeon explains why it’s vital that retailers should prepare a seamless end-to-end supply chain before the run up to 2023’s peak season.

The Beauty of Data

Shippers and carriers are facing a delicate balancing act of keeping costs down while meeting the needs of increasingly demanding consumers. An empty shelf isn’t just a lost sale for someone – it’s a reason for customers to switch to another brand. So, businesses looking to drive as much value as possible from their operations also must ensure resilience against disruptions that, according to McKinsey, are becoming increasingly frequent.

Achieving an equilibrium between value and resilience starts with digitisation. The truth is that shippers and carriers aren’t as digitised as they should be. The era of Excel spreadsheets, manual searches, and endless route and rate browsing have become relics of the past. This inefficient administration burns valuable resources and fails to deliver optimum outcomes.

Now is the time for enterprises to pivot from mere data collection and embark on the process of generating transactions with the data at their disposal. Automated, data-driven decision-making within a collaborative and interconnected network, leveraging historical patterns, real-time data, and future predictions, will enhance transportation operations and enable reactions to fluctuating customer demands and adaptations to unforeseen events, such as border closures or dangerous weather conditions.

At the same time, tapping into data will provide balance in optimising their operations. Consider a day-to-day product such as toilet rolls, which is transported from warehouses to multiple countries and hundreds – if not thousands – of locations within those countries on a near-daily basis. These transports may have to cross international borders, adapt their routes due to traffic jams or road closures, and sync up with countless other transports. The logistics involved are staggering, but data can act as the common thread that ties such a complex operation together.

By investing in a smart Transport Management Platform, carriers and shippers can unlock multiple benefits such as optimising their operations and building greater profit margins. However, achieving it requires businesses to think beyond basic automation.

We’re Better Together

At times like peak season, it is more important than ever for enterprises to unite and work together to unlock operational benefits. For example, there’s no reason for trucks to travel hundreds of empty miles when a similar truck, equipped for the task, is more than likely unloading nearby. It’s time for shippers and carriers to forge connections with one another, establish common business standards, foster collaboration and embrace a platform that facilitates network-wide interoperability.

During peak season, connecting shippers, load recipients, service providers, brokers, forwarders and asset-based carriers is integral to creating a collaborative transportation community. By adhering to common standards and promoting interoperability, all stakeholders can uncover new business opportunities while achieving economies in their operations. This spirit of collaboration will grant the transportation market resilience and agility – both critical components, as highlighted in the 33rd Annual State of Logistics (SoL) report.

Long before the holiday season, shippers and carriers must be prepared to build deeper relationships and drive collaboration with other industry stakeholders within one connected network. They must work together to realise the economic gains available. It’s also clear that only through the implementation of digital tools, automation of the decision-making processes, and the harnessing of real-time insights, can the necessary steps be taken to establish the connectivity and interoperability required to bring logistics businesses together.

Dexory Announces Investment from Schenker

Dexory has secured additional investment with Schenker Ventures, the corporate investment arm of DB Schenker, strengthening further their position in the market. This investment will allow greater focus on introducing the DexoryView solution across Europe and into the US in the coming months.

Following the recent $19m Series A funding announcement in June, this partnership continues to strengthen Dexory’s leading position on providing real time visibility across the supply chain.

Dexory’s solution addresses the urgent need for improved visibility, better space utilisation and increased efficiency in warehouse operations around the world. Dexory brings together autonomous robots, capable of capturing rich image and sensor data from across a warehouse, with powerful analytics and insights. This powerful combination provides comprehensive visibility across individual warehouses of any size, as well as connecting sites across the global supply chain through Dexory’s digital platform, DexoryView.

For warehouse operators, guaranteeing flawless ‘on-time, every time’ order fulfilment is paramount to satisfying the expectations of today’s consumers. “Technology that operates autonomously, provides real-time insights, possesses intuitive interfaces, and seamlessly integrates can lead to a revolutionary transformation in the day-to-day efficiency, productivity and precision of warehouse operations”, says Andrei Danescu, CEO and Co-founder of Dexory. “I’m delighted DB Schenker shares our vision for full visibility across supply chains and have great confidence in our technology, ambitions and growth plans. Their industry expertise will help us grow into new territories and maximise the capabilities of the tech while bringing fantastic value to their sites, a great partnership for both.”

DexoryView, a one of a kind platform, conducts comprehensive warehouse scans within a few hours – a 100 times faster than human efforts and other inventory collection technologies. Moreover, DexoryView serves as a digital replica of the physical warehouse, nurturing not only management but also performance optimisation. This innovative feature empowers the software to simulate, optimise, and forecast future scenarios, freeing warehouse colleagues to engage in more complex tasks.

“The potential and evident success of Dexory’s technology within the global logistics landscape in a short space of time is impressive. Dexory has engineered a solution that not only boasts seamlessness and user-friendliness, but also provides a remarkable depth and speed of inventory data collections setting Dexory apart, enabling efficient and accurate insight.” says Paulina Banszerus, Head of Venture Capital, Schenker Ventures.

The strong execution-driven team behind the vision for DexoryView goes beyond inventory management, the technology’s visualisation is impressive, whilst being scalable in the future. And that’s what makes Dexory a great fit to our innovative portfolio. We’re really pleased to be part of Dexory’s exciting future.”

With ongoing conversations to partner with DB Schenker in the various territories, Dexory aims to continue to embed accurate real-time data into its customers’ supply chains worldwide, making it the new standard for the warehouse of the future.

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