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  • Top 6 Logistics Management Software (LMS) features that you KNOW you need

    Top 6 Logistics Management Software (LMS) features that you KNOW you need

    You know it. You need the most market-ready Logistics Management Software (LMS) that’s primed for your ground realities. Openlane’s LMS has the workflow and tools perfect for all users reflecting the needs of the drivers, handlers, managers, consigners, consignees, etc. The logistics management software seamlessly merges with all enterprise systems with zero data latency or duplications. It’s real-time updates and notifications all around. It’s just plug-and-play and can even be a standalone solution without the support of an incumbent enterprise system.

    Let’s keep this straight and simple. We promised the top 6 features… well, here they are.

     

    Simplifying Pickup and Delivery with Digital Solutions

     

    Transitioning from paper to pixels, Openlane’s logistics management software (LMS) completely digitizes the pickup and delivery process. This automation reduces manual errors and speeds up the entire operation. With Openlane, every step, from the initial order to the final delivery, is managed digitally, ensuring seamless operations. This capability is particularly vital for businesses looking to improve scalability and adaptability in a competitive market. Logistics companies using this software can expect smoother operations with enhanced customer satisfaction due to faster and more reliable service.

     

    Automated Route Plans for Swift Dispatch

     

    Openlane’s logistics management software automates the creation of dispatch-ready orders and runsheets, integrating seamlessly with an ePOD app for real-time delivery updates. This level of automation ensures that route planning is quicker and more accurate, reducing the likelihood of delays and improving the overall efficiency of the logistics schedules. By leveraging advanced algorithms, the software analyzes traffic patterns and delivery windows to optimize routes, making dispatch operations more predictive and reliable. This feature is indispensable for logistics managers aiming to uphold stringent delivery timelines and enhance route efficiency.

     

    Navigating Regulations with E-way Bill & Invoice Automation

     

    Compliance is a critical aspect of logistics management, and Openlane’s software makes it effortless. The logistics management software automates updates to E-way bills and ensures all regulatory requirements are met before dispatch. This automation extends to invoicing, enabling one-click invoice creation after deliveries, which significantly expedites the billing process and improves cash flow. Such features reduce the workload on staff and minimize human errors, ensuring that compliance is consistently maintained. For businesses, this means smoother operations and reduced risk of regulatory penalties.

     

    Live Tracking & Analytics for Informed Decision-Making

     

    Openlane’s logistics management software includes a live tracking dashboard that offers real-time shipment updates. This instant access to data empowers logistics managers to make well-informed decisions swiftly. The software also provides analytics on performance metrics like delivery times and route efficiencies, enabling businesses to pinpoint opportunities for improvement. By understanding these metrics, companies can fine-tune their operations, reduce costs, and increase reliability. Analytics also play a crucial role in strategic planning, helping firms anticipate challenges and adapt to changes in the logistics landscape.

     

    Enhanced Data Management with Consignor-Consignee Address Book

     

    The accuracy of consignor and consignee data is vital for successful logistics operations. Openlane’s logistics management software enhances this aspect with a geo-coded address book that ensures precise routing. The software’s contract management feature further simplifies the order and invoice processes, reducing administrative burdens significantly. These automated systems save time and ensure data integrity, leading to fewer delivery errors and optimized logistics operations. For logistics companies, this means improved relationships with shippers and receivers through more reliable and accurate service delivery.

     

    Intelligent Order Creation & Optimized Route Planning

     

    Openlane’s logistics management software streamlines the complex tasks of order input and route planning. By supporting intelligent order entry, the software minimizes data entry time and expedites the initiation of deliveries. It also dynamically optimizes routes based on traffic, delivery priorities, and other relevant factors, ensuring efficient resource use and timely deliveries. This feature is particularly beneficial for logistics operations looking to maximize throughput and minimize delays, thereby enhancing customer satisfaction and operational efficiency across the board.

     

    This is just a gist of the features, once you go deeper – each feature has a subset of features that further cater to the fine-tuned needs of the users within the supply chain. For a more detailed snapshot matching your requirements… just reach out.

     

     

  • How Can You Leverage Generative AI for Enhanced Supply Chain Efficiency?

    How Can You Leverage Generative AI for Enhanced Supply Chain Efficiency?

    Generative AI is revolutionizing the logistics and supply chain industry by offering a myriad of innovative solutions. From demand forecasting to financial optimization, businesses are leveraging this cutting-edge technology to enhance efficiency, reduce risks, and stay competitive in the dynamic market. Lets see the areas of logistics and supply chain management where businesses can majorly benefit with Generative AI –

    1. Demand Forecasting:

    Generative AI creates sophisticated models by analyzing extensive historical sales data, incorporating factors like seasonality and economic conditions. This enables businesses to generate more accurate demand forecasts, facilitating improved inventory management and anticipation of market trends.

    1. Supply Chain Optimization:

    Generative AI models analyze diverse data sources, such as traffic conditions and weather forecasts, to identify efficient routes and schedules for transportation. By presenting multiple scenarios, AI suggests options for cost savings, reduced lead times, and improved operational efficiency across the supply chain.

    For in-depth insights into supply chain optimization, refer to our comprehensive article on AI use cases in supply chain optimization.

    1. Supplier Risk Assessment:

    Generative AI processes large volumes of data, including supplier performance and financial reports, to identify patterns related to supplier risks. This aids businesses in evaluating supplier reliability, anticipating disruptions, and implementing proactive risk mitigation strategies.

    1. Anomaly Detection:

    Generative AI identifies unusual patterns or deviations from the norm across the supply chain, enabling businesses to quickly detect and address potential issues before they escalate, such as bottlenecks, quality problems, or unexpected changes in demand.

    1. Product Development:

    Generative AI processes market data, customer feedback, and competitor information to generate insights, guiding businesses in the development of products or services that cater to emerging trends or customer satisfaction criteria.

    1. Sales and Operations Planning:

    Generative AI integrates data from sales, marketing, production, and distribution to generate accurate and comprehensive plans. This aligns strategies across departments, optimizes resource allocation, and enhances responsiveness to changes in demand and market conditions.

    1. Price Optimization:

    Generative AI analyzes customer demand, competitor pricing, and market conditions to generate optimal pricing strategies, helping businesses maximize revenue, profit margins, and market share while maintaining a competitive edge.

    1. Transportation and Routing Optimization:

    Generative AI plays a vital role in optimizing transportation and routing within supply chain management, enabling route optimization, vehicle fleet optimization, and dynamic routing to adapt to disruptions and delays, ensuring a resilient supply chain.

    1. Inventory Management:

    Generative AI models analyze demand patterns and lead times to determine optimal inventory levels. By suggesting reorder points and safety stock levels, AI minimizes stockouts, reduces excess inventory, and lowers carrying costs.

    1. Financial Optimization in Supply Chain:

    Generative AI in supply chain financial services improves efficiency, reduces risks, and enhances decision-making processes.

    • Credit Risk Assessment:

    Generative AI analyzes credit history and financial statements to assess the creditworthiness of suppliers, partners, or customers, helping manage financial risks and identify potential defaults.

    • Fraud Detection and Prevention:

    Generative AI models analyze transaction data to detect potential cases of fraud, minimizing financial losses and ensuring the integrity of supply chain operations.

    • Risk Management:

    AI analyzes various risks, providing insights to develop risk mitigation strategies, helping supply chain stakeholders better manage financial risks and maintain stability.

    The integration of generative AI into supply chain processes offers unparalleled opportunities for businesses to optimize operations, mitigate risks, and stay ahead in the competitive landscape. As the industry evolves, embracing these advanced technologies becomes imperative for sustained growth and success.

    At Openlane Solutions, we strive to bring the best technology integration for companies to enable fast, accurate and seamless sypplychain and logistics operations. If you are someone looking to explore Generative AI use cases in supplychain, connect with us and we can help to foray into the world of Gen AI and enable your supplychain and logistics operations to adopt and leverage Gen AI models. Openlane has a suite of SaaS products for logistics and transportation management, warehouse management, PR to PO and Procurement management. We work closely with customers and use our tech platform and architecture to build custom modules, workflows and functionalities which results in high tech adoption and resilient SCM processes. Contact us to learn more.

  • “Wow” your consumers! The right logistics management software would get you there

    “Wow” your consumers! The right logistics management software would get you there

    The world goes round and round, and within – it’s the continuous logistics movement that keeps things running. Everything from a banana or a chip, or banana chips gets marked and scanned as they move from one region to another, and finally through the last mile distribution into our hands (so to speak). We just experience the timeliness and the quality of the delivery and product. We use this to judge (and rate) the company, the logistics partner, and even the essence of the product itself.

    The consumer can only judge through their experience. Companies know this, and toil to create impeccable experiences with faster and better deliveries.

    Peeling the logistics onion further, we discover that instituting and sustaining speedy and effective deliveries isn’t easy. There’s an entire supply chain that needs to work in the same beat to make it happen. The history of the banana chips is tracked through their journey from the factory to the eventual stores. The last mile van picks them up from a distribution center to the destined delivery point, going through their route and stopping along their milk run for other equally important deliveries.

    One step deeper, the trailers or trucks haul the shipment from factories to the distribution centers. Sometimes it takes different trailers moving through intermediary centers or even effecting the start of the glorious multi-modal logistics journey.

    All-in-all, logistics planning and execution across multiple domains, stakeholders, regions, warehouses, trailers, and people – compound to make those few moments of consumer experience truly memorable.

    Ensuring a robust, streamlined, controlled, tracked, manageable, replicable, and scalable logistics management process – isn’t just a need – it’s the whole core of creating end-consumer value. Delayed or erroneous deliveries may end up eroding the millions in advertising the charming product. You can’t look away from this.

    Logistics management software | The gist of what it can do to streamline logistics

    You need to know exactly what product, in which batch has been set up through the purchase order to move out of the warehouse – at what time and bound for which location – all through one simple and intuitive screen. It should be at your fingertips.

    An effective logistics management software makes this happen. You have full visibility of the available stock and the resources (like vehicles and drivers required for delivery fulfillment). You can easily pull info from the master database to auto-fill your orders (also known as lorry receipts – LR – in some quarters).

    The system aligns the order with the preset structures and tolerances of your in-built rate and contract management process. This process is pre-learned on all client and branch info with exact details of rates for each contracted product.

    The idea is to make the ‘through’ processing of orders or LRs streamlined enough to be done by anyone and from any medium like a laptop or mobile device. It’s just a few steps – and you’re done.

    Trip or Runsheet creation | Real-time tracking | Electronic proof of delivery | Invoice automation

    The orders can be assigned to a trip (or Runsheet) in a few clicks. This trip or Runsheet is what is associated with the drivers/trailers. The system can auto-assign the driver and vehicle as per the capacity and location requirements of the trip.

    This further streamlines the dispatch process – once the checkpoints of documentation are complete. The system helps with easy updating of regulatory documents like e-way bills so all the validations are seen and processed in one go.

    Once dispatched, the managers can track the exact movement in real-time. They can get timely notifications of delivery status updates, as they happen. The driver, on unloading and scanning out the packages, snaps the electronic proof of delivery (ePOD) with their mobile device. This has the time and location stamp along with the visual delivery confirmation – whether partial or full.

    This validated delivery confirmation helps automate the invoicing. As it has the proofs attached, the clearances are quick with minimal claims. The entire process is further simplified by automated invoice generation and posting (for approvals).

    End-to-end visibility and control for logistics management

    The process is only as good as its usage. Customers (the ones with the factories) can access their customer portal to directly set up orders. The logistics service providers or warehouses can pull in the orders, automatically within the system, and set up the order creation process with high-priority notifications to stakeholders. The customers can track the order status and shipment movement through their customer portal – including the final delivery validation with the ePOD.

    The managers with the service provider or carrier can also track the entire order creation and delivery process from their user-specific dashboards. The entire system enables end-to-end visibility and control over aspects of the process.

    The reporting and analytics are the enhancement levels that help you quickly find caveats in your operations and optimize them accordingly. This turns the system into a pseudo-self-learning entity that gets better with regular iterations. When done right, the logistics management software can not just enhance the final consumer experience, but make it profound enough to merit consumer loyalty.

    Read More: How Smart Cities Can Help Build a Better Post-Pandemic World

    This is just a very quick overview of logistics management software. We know the extent of the possibilities as we have been enabling this for multiple customers – with proven results.

    Do you want to talk about this and see if this is something you wish to unlock? Just drop in here and we will have a quick chat.

  • Introducing Openlane Solutions | Revolutionizing Growth and Efficiency for Logistics Service Providers 🚀

    Introducing Openlane Solutions | Revolutionizing Growth and Efficiency for Logistics Service Providers 🚀

    We are thrilled to announce the official launch of OpenLane Solutions, a pioneering force in transforming logistics businesses with innovative technologies and tech driven processes. Our goal is to empower logistics service providers and 3PL organizations worldwide by enhancing their productivity, last mile efficiency, and overall success.

     

    At Openlane Solutions, we understand that modern logistics service businesses face complex challenges in today’s rapidly evolving market dynamics. That’s why we’ve developed cutting-edge logistics and supply chain management tech platform tailored to meet the unique needs of small and medium sized logistics service providers gloabally. Our team of experts combines deep logistics and supply-chain domain knowledge with advanced technological prowess to deliver game-changing results.

     

     

    Here are a few key reasons why Openlane Solutions stands out:

    1️⃣ Digital Transformation Expertise: We assist logistics companies in harnessing the power of digital technologies to drive growth and unlock new opportunities. From automation to cloud computing, our solutions empower logistics service providers to stay ahead in the digital age.

    2️⃣ Data-Driven Decision Making: Our data analytics and operations intelligence control tower provide valuable insights that enable informed decision-making. Leverage the power of data to identify trends, optimize logistics and warehouse operations, and make strategic choices that drive success.

    3️⃣ Logistics Process Optimization: Openlane’s logistics and supply chain management software platform helps businesses optimize their logistics operations by streamlining processes, reducing inefficiencies, and enhancing overall productivity. Unlock hidden potential within your organization and achieve operational excellence.

    4️⃣ Customized Solutions: We understand that every business is unique. That’s why we offer tailor-made solutions designed to address your specific pain points and requirements. Our team works closely with clients to deliver bespoke solutions that drive tangible results.

    Ready to take your logistics operations to new heights? Explore our website to learn more about our comprehensive logistics management software platform with custom modules. Follow our LinkedIn page for regular updates on industry insights, thought leadership, and success stories.

    Join us on the journey to business excellence and unlock the full potential of your organization with Openlane Solutions! 💼🌟

    Let’s Talk About Your Logistics Challenges 

  • How Smart Cities Can Help Build a Better Post-Pandemic World

    How Smart Cities Can Help Build a Better Post-Pandemic World

    This article was previously published by our author Faiz Shaikh on, Readwrite, link – https://readwrite.com/how-smart-cities-can-help-build-a-better-post-pandemic-world/

     

    If we look back on the past five years, we would find many breath-taking tech advancements. Smart cities, micro-drones, Internet of Things, connected logistics, artificial intelligence, etc. have put us on a platform where pride comes naturally. We can talk about the coronavirus pandemic and lockdowns all we want. However, we shouldn’t forget one thing. Technology has empowered us with numerous advantages to fight this crisis.

    We are in this together. It’s not just a statement, it’s a fact. Let’s pause for a minute and evaluate the ‘tomorrow’ beyond the current pandemic. When we do get through this tunnel, we should endeavor to build a better and more connected world together.

    In this article, we would talk about: why this is important; what we can improve; and how we should go about doing it.

     

    How global cities measure up during this pandemic.

    We kept speaking about disruption and innovation for years. The starting point for both was ‘need identification’. Where are the gaps, and why aren’t they being filled? Let’s look at some of these points.

     

    1. Information overload with minimal applications.

    The world has been consuming information and data at an extravagant rate. Hence, the current slowdown (in all news other than the pandemic) has pushed people into consuming coronavirus updates like candy. This, inevitably, pushes us towards information overload.

    This has led to misinterpretations, misinformation, and misrepresentations. In short, there’s too much information that doesn’t lead anywhere. It doesn’t have any application or doesn’t solve anything. It’s just noise.

     

    1. Multiple labor and logistics bottlenecks.

    Lockdown and travel restrictions have prioritized essential services (medical, food supply, utilities, etc.) over all other goods or people’s movement. This sounds good on paper. However, there have been problems with getting the right people and the right supplies to where it’s most needed.

    Some cities and states have shut down their borders. Shutting down borders further hinders the smooth logistics movement. There are (understandably) multiple checks and balances. Checks and balances, also delay the delivery and availability of essential goods and services.

     

    1. Longer reaction times due to inertia.

    The above points (and many intermediate ones) culminate into longer reaction times. The authorities get stuck with firefighting and decision inertia. These decisions, in turn, lead to food and supply insecurities among the masses, especially the poor. Another point of worry with decision inertia is the inadequate or delayed testing, reporting, and isolation of possible infections.

     

    The Smart City Approach: What it means and how it can help

    Let us now develop a scientific approach towards the crisis management. What are the facts and how do we proceed? The underlying, and inherent benefits of smart cities, here, turn into essential tools.

    The ‘Smart City Approach’ is when authorities within the city leverage real-time insights and updates. With this, they streamline their crisis response, plan for process improvements, and ensure seamless logistics.

     

    1. Detection and reporting: Fast and decisive action.

    We need better ways to detect and report possible Covid-19 cases. Moreover, we also need better reporting for other emergencies relating to the operations and governance of major cities. Cities like New York, London, Singapore, and Mumbai have been global travel hubs for decades. These globally-connected cities need faster case (or emergency) detection and reporting.

     

    1. A collaborative approach from cities, states, and nations.

    Cities and countries need to be on the same page with the fight against this unprecedented crisis. We have discovered common threads of empathy and compassion that have connected us all, across demographics. We want this to continue beyond the pandemic. The connectivity and collaboration will help us recover, as companies and cities, faster.

     

    1. Stakeholder mapping and planning.

    The crisis has thrown many curveballs. It seems like when cities solve one issue, another rears its head. There are migrant workers and homeless people who stand to be worst affected by the lockdowns. The people on the frontline of the crisis: the doctors, nurses, police, utility, and sanitation personnel, etc. need more attention. They need to be protected with the timely deliveries of necessary equipment and supplies.

     

    1. Real-time tracking and information.

    Overall, the cities need to function as one. Each development, each shortage, each victory needs to be tracked, recorded, and utilized. Smart cities cover all these aspects with aplomb. These cities have the power to handle live information and turn them into key insights.

     

    The Application: How smart cities can be better equipped.

    We have talked about improving the connectivity and conditions of our cities by turning them into truly ‘smart cities’. The current crisis is unprecedented in every way. We are at a point where we need to minimize the damage, protect the assets (people and economies), and revitalize our operations (in cities).

    We must learn and adapt using the intrinsic smart city concepts to better equip all cities.

     

    1. Drones as a catalyst for better visibility.

    Many cities in China, the United States, India, etc. are either planning to use small or micro-drones or are already using them. These drones primarily help:

    • gather intel with regular lockdown surveillance (spotting suspicious activities or simply supervising local operations);
    • spray disinfectant in areas with active Covid-19 cases (reported);
    • detect elevated body temperatures of random people on the streets (used in Hunan, China);
    • deliver essential medical supplies (especially masks or sanitizers), etc.

    Drones can help local city authorities build situational awareness. The mayor or emergency service officials can view live video updates of sensitive (quarantined) zones without putting on-ground forces in harm’s way.

    All information is encrypted and transmitted back to a central repository for current or future use. The drones also ease the pressure on the overworked essential forces within the city.

     

    1. Connected logistics and contactless deliveries.

    People under different levels of lockdowns depend on their local stores for their groceries and essentials. Hopefully, we are past the initial frenzy and panic buying. Now, the essential goods and equipment must move seamlessly within and outside the cities.

    Many retailers and e-commerce players within major cities have, previously, reaped the benefits of a real-time package and shipment tracking. They used route-planning software to identify short and ideal travel routes. This gave them the cumulative benefits of speed, cost, and end-customer satisfaction.

    We need to extend this AI-enabled route planning and live shipment tracking to ensure that all essentials are evenly distributed across districts. Retailers and foodservice providers, along with the local authorities, should engage with this technology as equal collaborators. We will cover more on this in the next point.

    People have been confined to their homes and have become more and more dependent on hyperlocal deliveries of food and groceries. Delivery service companies have stepped up their response with contactless deliveries where prepaid orders can be left at the doorstep.

    The entire ‘proof of delivery’ is conducted in-app. The delivery person sends the receiver a photo of the package (at the receiver’s doorstep). The receiver, then, confirms the delivery. The network interconnectivity within smart cities is the linchpin for such sharp adaptability within delivery companies.

     

    1. Centralized city info-system for essential services.

    Local and central governments are keeping a close eye on all relevant developments within cities (and the nation as a whole). Smart cities have been historically more adept at collating and pushing actionable insights. These insights have been critical in effective decision making.

    The authorities, now, must scale and interconnect all related services in the city into one central info-system. It will:

    • give the exact cluster map of active and suspect Covid-19 cases (with live health and status updates)
    • show live drone-surveillance through key-areas giving real-time intel about select or sensitive areas
    • enable retailers and suppliers to update their stock-levels as they depreciate in real-time
      • This will trigger automated delivery requests.
      • The authorities can track delivery trucks in real-time, through in-vehicle trackers, and direct them to the shops with lower supplies.
    • help plan and execute structured disinfecting of different areas in the city
    • ensure proper law and sanitation upkeep through automated and regular drone-surveillance
    • ensure on-time food packet deliveries to the elderly, homeless, and needy (this can be enabled through interconnected community-based reporting)

    A connected and centralized info-system ensures effortless smart city management. This leaves the authorities with enough insights (as they study cluster patterns) to tackle and overcome the pandemic.

     

    Beyond the crisis: Recovery and rebuilding.

    According to sources, we are in the midst of a recession. We will understand the full extent of the economic backlash once we emerge from the current crisis. However, we have our work cut out for us.

    Technology and connectivity have helped us fight this pandemic. Smart cities with emerging and innovative tech applications have witnessed faster and effective testing and reporting. These cities have set the benchmarks for adaptability and recovery. We must embolden more cities with smart and connected technology. This will strengthen us and hasten the rebuilding phase for our communities.

    Future generations would read about this pandemic in their history books. Let’s turn our response to it, as a global community, into something that would motivate them for years.

  • Machine Learning and Exception Management – A Logistics Tech Game-Changer

    Machine Learning and Exception Management – A Logistics Tech Game-Changer

    This article was previously published by our author Faiz Shaikh on, Readwrite, link – https://readwrite.com/machine-learning-and-exception-management-a-logistics-tech-game-changer/

     

    There has been a lot of talk about machine learning in logistics management. The idea is simple: optimize, infer, implement and repeat. Here is: machine learning and exception management — a logistics tech game-changer.

     

    What is included in the different pillars of logistics management?

    A system optimizes the different pillars of logistics management that include order planning; vendor performance management; fleet capacity optimization (management); dispatch management; in-transit shipment tracking; and delivery management.

    Next, the system infers the points or bottlenecks within these pillars (logistical processes) which can be fixed, improved, or enhanced. These inferences or analytics are then ‘implemented’ back into the logistics set-up. The learning mechanics start back from optimization. Over-time the system evolves and improves all the connected logistics management processes. This is machine learning in logistics management.

     

    What is exception management in logistics?

    A logistics exception (issue) is a deviation from planned or expected process execution. Here are a few examples.

    • Shipment loads aren’t mapped properly to available fleet options (creating capacity-mismatches and loading/dispatch delays).
    • In-transit shipments are detained at a spot for more than two hours (or are violating service level agreements with speeding or harsh braking).
    • Consignees didn’t receive all the SKUs (stock-keeping units) as per the initial purchase order.

    Every transportation management system (TMS) involves some or many human touchpoints. A person supervises these system or process interactions (touchpoints). This can be anything from checking the shipment assignment schedule and ensuring that the handlers are following the planned loading patterns. Similarly, many other touchpoints work to ensure that the gap between plans and ‘actuals’ is minimal.

    The goal of exception management is to minimize this gap between planned and on-ground results. Overall, the machine-learning aspect of exception management induces accountability and efficiency within the company’s and logistics network’s culture. This can be with the supervisors, warehouses, freight forwarders, logistics service providers, consignees (distribution points), etc.

     

     

    6-stages of machine-learning enabled exception management system.

    The 6 stages are Discovery, Analysis, Assignment, Resolution, Records, and Escalation.

    Discovery:

    It detects and reports issues or anomalies within the processes. This can be through temperature sensors (cold-chain logistics), real-time movement tracking, order journey tracking (in-scan and out-scan of each SKU), etc.

     

    Analysis:

    It analyses and processes the issue or exception as per protocols (or learnings). It categorizes and pushes ahead all exceptions – either to an assignment or to an escalation.

     

    Assignment:

    It matches the exception with the right person or department (best-suited to resolve the exception on time).

     

    Resolution:

    It tracks the speed and effectiveness of the person’s (assignee) resolution. It moves the ‘resolution’ through multiple criteria and validations before satisfactory ‘completion’.

     

    Records:

    It records and analyses each exception right from discovery to resolution. The system processes these records to throw-up insights or best-practices for future applications.

     

    Escalation:

    This is an important aspect of dynamic exception management. The system constantly tracks each issue within the system.

    • If at the analysis or resolution stage, the supervisor (or system) deems the issue – critical or complicated, then it’s escalated through special ‘analysis’ and resolution. It mostly includes people with different skill-sets or authority.
    • If the system detects that an issue hasn’t been resolved in its time-frame, it’s again escalated.

    Through these 6-stages, the system constantly weeds-out inefficiencies from within itself. It helps propagate a more transparent, accountable, agile, and responsive culture. Furthermore, it helps reduce errors and delays, which, in turn, improves profit margins. A few new-age TMS start-ups, like Fretron, are trying to capture market share using this 6-stage exception management.

     

    Real-world applications of escalation management in logistics

    Let’s consider a real-life use-case for an exception management system (EMS) – a fast-growing retailer in India focusing on Tier-2 and Tier-3 cities.

    Their biggest challenge was an unorganized logistics (vendor/freight forwarder) network and weak city infrastructure. Even though the retailer had opted-in for total logistics automation, they still weren’t able to implement it to the full extent. The client was looking for a tech-enabled process and culture change.

    Let’s take vendor performance management as an example.

    • The EMS helped cut down discrepancies in billing and settlements. A single synchronized TMS was able to track each order (at the SKU level) as it moved through crates, pallets, trucks, cross-dockings, and final delivery. The out-scan could automatically highlight all the missing items.
    • The EMS would process the information and mark the exact point of deviation where the item went missing. This helped with issue resolution and also to plug these operational gaps. It cut down invoice-level disputes and hastened the settlements.
    • The EMS enabled fast and error-free invoicing which incentivized the carriers and freight forwarders to work in a more organized fashion. Through an iterative learning process, the system improved upon itself. It brought a higher degree of transparency and accountability within the logistics ranks (in the company).
    • On the back of machine learning-enabled EMS, the company was able to deliver on-time value (better shelf choices) for its end consumers.

    Conclusion: Exception management, in logistics, is a game-changer

    EMS successfully bridges the gap between tech-induced efficiency and on-ground employee efficiencies. It’s especially effective in unorganized or traditional markets that are riddled with such ‘exceptions.’

    If machine-learning backed EMS is used in the right manner, many mid-level companies can scale fast and improve their outlook within the next five years. At this time of COVID-19, scaling faster may be the only option to save your company.

  • Break the Mold with Real-World Logistics AI and IoT

    Break the Mold with Real-World Logistics AI and IoT

    This article was previously published by our author Faiz Shaikh on, Readwrite, link – https://readwrite.com/break-the-mold-with-real-world-logistics-ai-and-iot/

     

    We have been talking a lot, lately, about the Internet of Things (IoT) and Artificial Intelligence (AI). So much so that it’s now difficult to differentiate the real from the not-so-real or purely ‘marketing’ IoT and AI. Data mining isn’t AI. Marketers have been doing it for a good three decades, and others likewise. It’s using intelligent correlations and cohorts to find patterns and latent needs. That’s not much that is artificial about the issue nor situation.

    There should be a new marketing codebook with these lines: “Thou shalt not cite IoT and AI in vain.” I don’t know how, but the salesperson calls my latest watch “AI enabled,” whether they have AI or not. The clock is not even smart; at best, it’s just digital. When you wipe off the not-so-real jargon and look at the actual applications of AI and IoT, they are aplenty. But how do we find what is actually true — in a world so taken with these terms? It’s simple.

     

    Just know the story behind the pitch. Does the product or solution improve over time? In a customer-facing scenario, does it customize itself to your language (maybe like the Amazon Echo).

     

    In a more enterprise setting, does it offer better/faster delivery routes for your logistics movement each time you use it? Does it incrementally better itself with a singular goal of improving the results, learning and adjusting? If yes (to any), then it’s AI.

     

    A system which learns on itself and tells right from wrong;

    A recent use-case comes to mind. The company I am associated with, LogiNext, used Kalman filters (algorithm). NASA made the Kalman filter famous when they used the algorithm in their effort to better direct satellites in near and outer space. According to a paper, right back from 1985,

     

    “The Kalman filter in its various forms has become a fundamental tool for analyzing solving a broad class of estimation problems.”

     

    The company in question used an updated iteration of the Kalman filter to fix vital tracking information of hundreds of trucks moving across the country. Hence, each tracking point was, then, accurate up to 3×3 yards. What’s the impact?

    • Precise knowledge of where each truck is located.
    • Where the truck will be in the future.
    • And when this vehicle will reach the destination; down to the minute.

    The updated algorithm, with the layer of Kalman filter, learns from the tracking errors. It is essential as the tracking is hardware and network coverage dependent. It identifies patterns in the tracking data to understand what is ‘credible’ monitoring and what’s an error. The system would itself know which tracking data to use and which to ignore, growing the accuracy with continued functioning.

    In turn, this would ensure that the information going into the system for processing and route planning is accurate. More importantly, avoiding another case of ‘garbage in, garbage out.’ It would be more consistent with incrementally better plans each time it’s used.

     

    Here’s the IoT you can use, with complete logistics streamlining.

     

    Logistics is primarily a game of Service Level Agreements, SLAs. A company/carrier needs to adhere to these basic unit agreements, SLAs, or minimum viable service levels. It may be when a shipment leaves, the quality of the truck or environment for the cargo, the time when it needs to reach, etc. These SLAs are the code of conduct for carriers, drivers, and companies. They are specific to each shipment. SLA breaches are a serious affair and may result in delays and eventual penalties.

    So, with SLAs at the center stage, when you must track a package from perhaps LA to NY, you would expect a continuous flow of information regarding the location and state of your package, along with tracking the adherence to the all-important SLA, the ‘promised delivery time.’ How is your estimated time of arrival (ETA) looking as the package is exchanged between carriers, hubs, delivery centers, and the final mile couriers?

    It’s a dynamic logistical world where even local traffic and weather may become disruptors. If you simplify the entire end-to-end movement of your package – there’s the pickup, the hub-to-hub movement, and the delivery. It’s possible that all this would be dealt with different drivers, trucks, etc., changing multiple hands. How would you know if any of these drivers are more prone to speeding or delays? How would you know if the truck loaded with your package is well-equipped to handle it? All of the maneuverability allows logistic leaders to use AI right now.

     

    Here’s how IoT and AI help.

     

    It’s the system, an intricate-interwoven-intelligent ecosystem of software and devices where right from the moment the package leaves your hand; it’s tracking capture the unique id and driver details, aligning-in all possibilities, down to the climate in New Jersey a day from the end-delivery time.

    This system picks the best-suited driver and trucks for the package as per the promised timelines, nature of the package (perishable, fragile, sensitive, burdensome, etc.), route requirements and delays expected/predicted, hours of service for each driver (ELD/DoT compliances), etc.

    All the information is beamed-up into a single screen where a manager can view all his/her trucks across state lines, and the possibilities of any delays whatsoever. This monitoring empowers the manager (and the brand involved) to take on corrective measures and avoid final delays for the end-customer.

    Furthermore, this kind of detailed analysis and pin-point accuracy of multiple systems seamlessly talking to each other adds on a layer of predictability. Here the manager can efficiently predict, how many, trucks would continue to accommodate the possible load coming in, correctly. This is without having the need to dip into the spot markets.

     

    Conclusion? Only the beginning for IoT, AI, and yes — Machine learning, too.

     

    All this brings us to the summation of the main ‘gains’ of IoT and AI with real-world applications in logistics.

    1. 1.  Risk estimation – Cutting down on possible delays, SLA breaches, and service disruptions.
    2. 2.   Cost savings – Companies that can predict their carrying capacities (of trucks) precisely as per load variations (seasonal, regional, random aberrations), can plan better with their owned and market-sourced vehicles and boost their margins with favorable freight rates.
    3. 3.   Customer satisfaction – The ‘holy grail’ comes within grasp, as companies can reverse engineer the perfect delivery experience using AI (exhaustive delivery route permutations to get the quickest one, consistently), and deliver on time, every time.

    Perhaps it’s time we speak of AI and IoT as “tools,” which they are. They aren’t ‘magic’ solutions to each of our problems. Just last week my investment advisors told me that they could double my savings. When I asked them how they planned to do it, they quickly came back with ‘We’ll use AI.’ The funny part was that I wasn’t supposed to ask anything else. Well, I did, and now I am looking for better investment advisors.

    Moral: Don’t let the terms bog you down. Look beyond them to the real-world applications, and they may amaze you.