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Technology

In this section of our blog you will find all the articles related to technologies applied to logistics, such as artificial intelligence or Big Data, among others.

How IoT and AI is making a big impact on the logistics sector

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Entrega autónoma concepto abstracto ilustración vectorial - Cómo se usa el IOT y la IA en la logística vector

For several years now, IoT (Internet of Things) technology has been increasingly known and applied in different fields thanks to its increasingly reliable and complete technology. Undoubtedly, among the industrial sectors in which the use of IoT technologies is trending, the logistics sector stands out due to the growth it has experienced in recent years and the needs it entails. 

It is well known that all logistics operations require rigorous monitoring and agility to run efficiently, from supply chain management to last mile distribution. For this, one of the most popular solutions is IoT and digitization of certain operations in the logistics department.

In this case, in which logistics operations is IoT technology used specifically? If you want to find out how IoT and AI are used in logistics, read on:

Predictive analytics

It is one of the best known tools where both AI technology and IoT are used. It consists of using previously collected data to forecast future results and, to do so, it organizes the data obtained, preprocesses them and develops predictive models so that the results can be validated later.

The advantages of applying predictive analytics to the logistics sector are varied. Some of its most frequent uses are:

  • Demand forecasting: We analyze the sales history together with the market and estimate the sales that would be generated on the products.
  • Supply chain planning and optimization: Thanks to a prior analysis of the demand, the right quantity and timing of the production of the goods can be calculated.
  • Inventory optimization: Demand estimates help in making decisions about optimal stock levels for each type of inventory.
  • Improved resource management and savings: By applying current data taking into account constraints and other characteristics, it is possible to optimize resources and reduce operating costs.

In general, predictive analytics act as a guide for decision making and to give us a more accurate estimate of future activities. In this way, a clear view of the current and future situation of the supply chain and company is obtained.

Real-time shipment tracking

The most important and essential thing that customers ask for today is transparency in reporting the status of the order in real time to ensure that it arrives at its destination at the agreed time without incident. Today it is possible to receive all the data thanks to geolocation algorithms received by sensors via wireless networks.

The advantages of order tracking focus on estimating delivery times and detecting and solving problems. For example, if an order is not going to arrive on time or has been lost due to a wrong address or accident, the incident can be solved as soon as possible or an alternative can be offered to the customer.

Mujer joven tomando fotografías de cajas de entrega - Cómo se usa el IOT y la IA en la logística foto

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How can carriers and delivery drivers be helped with a voice assistant?

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Mujer usando el teléfono mientras conduce en el coche. Ayudar a los transportistas con un asistente virtual foto

En uno de nuestros webinars se ha hablado sobre cómo facilitar la vida de los transportistas con un asistente virtual. En él, Gandolapp y Washa Logistics han debatido sobre las condiciones que viven los transportistas y repartidores actualmente y cómo, con un asistente virtual, se vería beneficiado su desempeño laboral. Dicho tema nos resultó muy … Read more

3 questions most frequently asked by customers about the supply chain

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Gente de negocios usando una tablet digital. Preguntas frecuentes sobre los modulos logisticos

More and more companies are betting on the digitization of their logistics processes in order to optimize costs, obtain visibility of the movement of goods, improve communication between staff, among others. The different logistics solutions on the market can focus on a single function or can come with several modules.

However, there are a number of questions that customers interested in Hedyla software often ask about lesser-known integrated modules that complement more complete solutions such as a TMS or route optimizer. What in particular do these modules consist of and how are they helpful?

If you want to learn more about the logistics software modules less known by the market, read on.

Digital Twin

As its name suggests, the Digital Twin is a physical representation of any object or process to be replicated. In this case, it is used to create simulations of delivery routes, either in route optimizer or in the TMS.

In order to create the digital twin, it is necessary to collect data from the company's historical routes. It is useful to contrast them with the optimized routes based on the applied operational and business constraints. In this way, you can see the changes that will be applied to the new delivery routes and the time and resources that will be required to implement them.

The scenario simulator is also used for consulting projects for scenario analysis. In this way, changes in the supply chain and production lines can be better evaluated, such as analyzing the location of new logistics centers, among others. Its main function is to make better decisions based on productivity, efficiency and costs.

Ilustración vectorial del concepto de asociación. Preguntas frercuentes sobre los modulos logisticos.

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4 challenges your company must take into account when installing a TMS

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Edificio isométrico de almacén con camión de reparto. retos al instalar un TMS

As new logistics software solutions are being created to improve part of the supply chain processes, there are also challenges or mistakes that are often made in the use and installation of a TMS system. While it is true that more and more companies are taking the step to digitize and optimize transportation management, it is possible that operations are not performing as well as expected.

Se queste irregolarità non vengono affrontate, si perde la fiducia nel sistema di soluzioni logistiche, con conseguente insoddisfazione dei clienti e dell'azienda. Quindi, quali sono gli errori o le sfide più comuni quando si implementa e si applica efficacemente un TMS? Va notato che si stima che tra il 20% and 30% of the companies actively use a TMS.

If you want to know the most common challenges when installing a TMS and using it effectively, take a look!

Data collection

One of the challenges in installing a TMS that are also important and notable in the supply chain is that logistics operators and carriers are not yet able to reconcile their data. Such a challenge poses a problem in case there are service failures that have not yet been detected.

It is evident that every company in every part of the supply chain collects separate KPIs or SLAs from those that are stored on their own servers and systems. By the time dashboards are made for analysts or errors are reported via e-mails or spreadsheets, the information received is usually not accurate and the process is very tedious.

Therefore, it is important that the TMS or other similar software such as an ERP be able to collect and share data from both operators and carriers, avoiding irrelevant or erroneous information. However, it is recommended that such sharing can be done as smoothly and efficiently as possible, avoiding delays that cause misinformation about the status of transport.

Revisione della strategia

Before considering installing a TMS, as with any project, it is essential to establish a solid and realistic strategy in order to assign coherent objectives related to this action. In addition, all documents on departments, carriers, among others, must be updated and in order to start implementing them in the TMS.

However, it is possible that the TMS may begin to show unsatisfactory results or detect more frequent and more serious errors. In the event that the TMS does not have many problems collecting accurate information, one of the most likely cases is that the current strategy has become obsolete due to internal company or external changes affecting a large part of the industry.

In such a case, the established strategies and objectives should be revisited to see if they fit with the current landscape. If inconsistencies are detected, the strategies and objectives need to be redirected. An example would be if there have been very large changes in fleet volume, either a reduction or expansion of vehicles and carriers.

gestión de la flota. Retos al instalar un TMS

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How has AI been successfully applied in the supply chain?

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examples of artificial intelligence in vector logistics

Artificial Intelligence is known to be a growing trend in many industries around the world. And it is no mystery when logistics and transportation are looking for ways to apply such technology for the improvement of all their operations within the supply chain. From back office solutions to IoT control solutions, there are several examples of artificial intelligence in logistics.

However, for people who are not deeply involved in the industry, it is not very clear to them what specific operations AI is involved in. What are the current supply chain issues for the supply chain to be optimized with AI? And what advantages does this technology confer over the competition?

If you want to learn how AI is being applied in supply chain management with these examples of artificial intelligence in logistics, take a look!

Warehouse automation

Sectors such as e-commerce have gained much relevance in recent years, so the increase in demand and the need for a more efficient storage management call for a solution. For this reason, there has been a notable trend in warehouse automation as one of the notable examples of artificial intelligence in logistics.

Warehouse automation encompasses various operations, from the application of automated storage systems with stacker cranes to warehouse management software. Within it, they use data analysis and demand forecasting to coordinate various processes in the warehouse.

And not only do they perform this step, but they synchronize the tasks of both the operators and the automated systems. In this way, personnel can focus on other tasks.

Inventory control

This operation usually goes hand in hand with warehouse automation and, it seems, is going to be an essential element for companies. Currently, it is known that the volume of shipments is dropping considerably due to inflation, as a result of which stock is accumulating and will take longer than desired to accumulate in the warehouse.

First, the warehouse is stocked with the right amount of inventory according to demand prediction based on previous sales, market analysis, among others. Then, automation systems would be unified with catalog control to improve stock visibility by alerting on low stock levels and detecting defective products and packaging before they are shipped via AI cameras or sensors.

Thanks to one of the examples of artificial intelligence in logistics, it is possible to reduce error margins and time spent on tasks, obtaining high customer satisfaction and competitive advantage over other companies where logistics plays a crucial role.

Primer plano de un ordenador portátil que ejecuta un algoritmo que analiza el código en el escritorio frente a los programadores que trabajan en equipo - ejemplos de inteligencia artificial en la logística foto

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4 Logistical decisions to be made by Artificial Intelligence

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Ilustración del concepto de cara de robot. decisiones logísticas que tomará la inteligencia artificial vector

Whether in the digitization of processes or digital transformation, artificial intelligence is increasingly present among companies in any sector. But logistics stands out, as companies today seek to streamline their digital operations and/or change their strategy to meet current industry demands, looking for the best logistics decisions that Artificial Intelligence will make.

There are currently many options and tools with AI on the market that, rather than offering a magic solution to all problems, help in the management of the most complicated processes and assist in making decisions in the face of difficult challenges to solve. Some of them have already been heard a lot about due to their recent use in large companies, but others are not so well known.

The following are the types of logistics decisions that Artificial Intelligence will make in both operations and strategy.

Demand forecasting

It is no mystery to know the most popular peak demand times such as Christmas or Black Friday, when most industries are affected. However, each sector and, in particular, each company knows its own order increases in more or less detail depending on the times and data from previous years, among other aspects.

Despite this, the optimal number of stock is not always right in order not to suffer losses due to excess or broken stock due to its incredible complexity determined by both external and internal factors. That is where AI comes in to plan demand based on algorithms that calculate previous years, marketing campaigns and even taking into account some external circumstances such as changes in laws.

Reverse logistics costs

Reverse logistics is known to be one of the biggest challenges for a company running a supply chain. This is because the cost of a return is much higher than that of a shipment because it is not only a matter of bringing the product back to the warehouse. It is not only a matter of bringing the product back to the warehouse, but also a rigorous administrative management to reintroduce it to the active stock, repair it if necessary, or destroy it if the previous steps cannot be applied.

At this point is when Artificial Intelligence comes in to make decisions based on several criteria, but whose main objective is to assess whether to process the return of the order or not. To do this, the AI takes into account such obvious factors as the cost of the refund, but also other not so obvious ones such as the condition of the product to consider its resale and even the buyer's history to analyze his behavior with the brand.

Once these facts have been analyzed, the AI can make two decisions: either not to process the return, but to pay the customer if the costs are not profitable, or to process it when the losses are not so serious for the company's economy. Not forgetting that the dissatisfied consumer is also analyzed in terms of his brand loyalty and whether he will be penalized for processing too many returns.

Hombre usando un asistente digital en su tableta. decisiones logísticas que tomará la inteligencia artificial

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Route planner and Google Maps

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planificador-de-rutas-y-google-maps-Foto-de-Personas-creado-por-lookstudio-freepik

Normalmente se cree que, para tener un planificador de rutas eficiente, se necesita un programa informático de alto presupuesto. Sin embargo, puedes tener la solución aquí mismo, en tu smartphone u ordenador. Basta con abrir Google e ir a su apartado Maps.

We are talking specifically about its route planner function and, relatively recently, adding stops to that path. It's not exactly new because it was created in 2016, but it can be of great use for delivery routes.

Tips for using the route planner

If you want to know how to get the most out of this familiar route planner, here are the tips that may be useful:

1. Set departure time or arrival time.

Most users who open the application create their route based on the actual time. However, Google Maps also gives us the option to change the date of departure or arrival, giving us room to start planning and arrive on time.

This proves to be very advantageous to get more information about certain roads and highways on which we may encounter setbacks more frequently. Apart from the fact that all possible routes are known in advance by means of the route planner.

2. Use several stops

Not only can routes be created from point A to point B, but it is possible to add multiple stops along the way and optimize in the process.

Although this function is widely used by tourists who want to make a customized tour, it is also very useful for transport and logistics. In this way, additional drop-off and pick-up stops can be added to generate the best delivery route.

3. Consult regular or real time traffic

Once the route is prepared, additional information may appear that can be very helpful. The traffic consultation on the routes may be one of the most useful tools of this application.

The traffic level is colored from green (very little traffic) to dark red (a lot of traffic) to better interpret the main routes and other alternatives.

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What software is used in logistics?

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What software is used in logistics?

Logistics software are all those digital solutions that allow you to manage, control and optimize the different logistics processes from both a strategic and daily operational point of view. In order to be prepared for today's needs, it is important to know what software is used in logistics nowadays.

Logistics is complex as it integrates a multitude of activities with many actors involved. Likewise, logistics has a great connection with the rest of the company's activities and, therefore, is affected to a great extent by decisions and situations derived from other factors that are not properly logistical, such as sudden changes in demand, new products launch or expansion to new territories, among many other examples.

The digitization is currently a key aspect for the future of companies of all sizes. However, the complexity of logistics mentioned above is also visible in the variety of types of software for logistics, or that have a direct relationship with it, for example systems for supply chain management or company management (ERP).

Logistics software

In addition, each type of software also has notable differences from others that are in exactly the same category. Therefore, it is necessary to go beyond the category and see the functionalities that each system offers to know exactly whether or not it adjusts to the needs of each company.

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7 women forerunners in technology

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Mujeres-precursoras-tecnología-top-secret-rosies

Cuando nos referimos a los inventos de la tecnología los primeros nombres que nos vienen a la cabeza son Leonardo da Vinci, Alexandrer Graham Bell, Nikola Tesla, Thomas Edison, Steve Jobs, Elon Musk, entre muchos otros y todos ellos hombres. Pero desconocemos el papel que la mujer aquí ha jugado, qué inventos ha llevado a … Read more

Balancing cost and quality of service in last mile distribution

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Cost vs Quality of Service Balance in Distribution

La distribución de última milla tiene un objetivo muy simple: mover bienes desde un almacén o hub hasta su destino final. Pero, de ser tan simple, no serían necesarios ni expertos en logística ni ningún software de optimización. Los factores más relevantes a la hora de planificar la distribución son las restricciones y el entorno, la calidad … Read more

Why delivery companies need fleet optimization algorithms

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Seguimiento de rutas de reparto

¿Por qué las empresas de reparto necesitan algoritmos de optimización de flotas? Durante los últimos diez años, el comercio electrónico ha cambiado la forma en que las personas esperan recibir sus compras en línea. Actualmente, cuando un usuario compra un artículo en línea, espera que la entrega sea rápida, fiable y gratuita. De esta manera, … Read more

Beyond Distribution Planning

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Más allá del la planificación de tu flota - hedyla

Ya seas un vendedor al por mayor, una empresa logística, o tengas un pequeño negocio que necesita distribución, seguramente te hayas encontrado el problema en la planificación de tu flota, incluyendo: Qué vehículos usar. Los pedidos que entregará cada vehículo. El orden de entrega de los pedidos. La hora de comienzo de las entregas. Aunque … Read more

Optimizing Rotation with Hedyla

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Docks Almacén

Vamos a hablar de uno de los muchos casos de uso de nuestras soluciones, en especial de cómo el Business Inteligence puede ayudarte a optimizar la colocación de artículos y detectar problemas. La rotación en almacenes Las referencias en un almacén se distribuyen, normalmente, en múltiples zonas (e.g., A,B y C) dependiendo del tiempo estimado … Read more

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Hedyla, the cloud platform to optimize logistics

Hedyla is a software company dedicated to optimize logistic processes of medium and large-sized companies through Artificial Intelligence.

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Hedyla Technologies S.L. ha sido beneficiaria de un Proyecto subvencionado por el CDTI con la colaboración del Ministerio de Ciencia e Innovación. Número de expediente SNEO-20201090
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