One of the most relevant solutions is the use of bicycles for last mile distribution or known as Cyclologistics. Cyclologistics consists of strategies that seek to promote the use of bicycles and other sustainable mobility vehicles to reduce the carbon footprint. However, in order to be successfully applied to cities, certain requirements must be met to facilitate its implementation and use.

If you want to learn more about the keys needed to boost cycling, read on:

Identify areas with high delivery density

It is one of the first steps to be taken before implementing other strategies that promote cycling and involve changes in the city's infrastructure. To do so, it is necessary to have information that can be provided by logistics operators or parcel services.

From residential neighborhoods to commercial districts, any of these areas can fall within the delivery "heat map". This will make it much easier to design efficient delivery routes for sustainable mobility vehicles using a route optimizer.

Installing Urban Hubs

It is undoubtedly one of the most indispensable elements for the promotion of cycling, since, without them, delivery with bicycles and other light vehicles is not possible. This is because most last-mile distribution starts from logistics centers located in industrial parks on the outskirts of large cities. Therefore, without the presence of logistics hubs, heavier vehicles such as vans are needed for deliveries.

But it is not only a matter of installing urban hubs per se, but also of carefully studying the strategic points of the city where an urban hub and its fleet of bicycles would reach their maximum potential. To do this, it is necessary to take into account the volume of deliveries by zones, the traffic on the roads, other streets that are difficult to access for larger vehicles, etc. 

Collaboration between public entities and private companies

In recent years, several companies and startups have emerged with very interesting proposals to promote cycling in last mile distribution, such as Washa Logistics. However, in order to carry out their proposals, it is essential to have the collaboration of public entities.

From municipalities to certain institutions focused on urban mobility, close collaborations should be established to give the green light to cycling projects. Particularly, if the initiative requires some changes in public infrastructures, such as more parking places for light vehicles.

Improving cycling infrastructure

It is common for larger cities to have several circulation zones with approximately bike lanes. However, there are cities that lag a bit behind in the number of lanes, so cyclists are obliged, according to Spanish regulations, to ride on the right side of the traffic lanes. This lack of adaptation of roads for cycling can slow down distribution and make the roads more unsafe for delivery drivers.

To do this, it is necessary to identify the areas with the highest bicycle traffic and analyze the best ways to implement the lanes without affecting the circulation of other vehicles. With such improvements, delivery vehicles will circulate on safer and more efficient roads, enhancing cycling.

In addition to more bike lanes, there are also parking spaces for bicycles and other light vehicles. This means that delivery drivers will have more parking spaces at their disposal to deliver orders.

Establishing incentives and public policies

In recent years, authorities are starting to establish low-emission zones and limiting the entry of heavier or polluting vehicles with the aim of reducing carbon dioxide emissions. It is therefore essential that they also establish incentives and public policies to facilitate the promotion of cycling.

Such incentives may include subsidies, economic bonuses or tax reductions that facilitate the transition from the use of fuel vehicles to the acquisition of light vehicles for sustainable mobility. In addition, in order to strengthen the use of bicycles for both delivery and personal use, it is advisable to promote the use of this type of vehicles with road safety education campaigns and programs.

Conclusion

Cycling is becoming a very attractive trend for urban logistics and last mile distribution because of the many advantages it offers: reduced emissions and more efficient delivery routes. However, it needs to form a close collaboration with municipalities and other public entities to, if necessary, adapt public roads and facilitate as much as possible the delivery with sustainable mobility vehicles.  

At Hedyla we work with customers with use cases focused on parcel and delivery to focus delivery routes by zones in order to save time and deliver excellent quality of service.

Meritxell Vázquez

SEO & Inbound Marketing
Video Game Design and Production graduate currently training in Digital Marketing with a focus on SEO and Inbound Marketing.

Creating articles of value and supporting communication to the technology sector.

hedyla.com

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.

IOT and Blockchain

One of the rising trends in the logistics and transportation sector is the use of Blockchain technology in the supply chain. And this is because, together with IoT and AI, a digital bill of lading (BOL) can be created that provides traceability of products along the entire supply chain.

The combination of Blockchain and IoT can bring many advantages to any sector that distributes products, especially when it comes to quality items such as wine. For example, with BOL, a smart contract can be created to know the origin of the product and its path to the end customer. You can also apply GPS trackers that can calculate temperature, humidity, among other things to ensure compliance with the contract.

It should be noted that Blockchain technology allows stored data to be more secure because they are decentralized, have irreversible transactions and are highly encrypted. For these reasons, the probability of being stolen or suffering cyber-attacks is reduced. 

Route optimization and fleet planning

One of the most important aspects of route planning is traffic patterns, i.e., the flow of traffic on certain roads and other public roads. AI, thanks to its learning capabilities, can study such patterns to detect peak traffic hours, maintenance works, among other features. IoT devices can also add more information by tracking and collecting data for future analysis and better planning.

It should be noted that the main objective of a route optimization solution is to save fuel, other related resources and costs. However, greater efficiency in the distribution of goods translates into a more satisfactory and competitive service, especially in the case of last-mile distribution.

Safety of personnel and property

Safety within logistics operations can be improved through IoT or AI solutions. On the one hand, predictive maintenance can be performed on trucks and other machines using IoT devices to detect potential problems and prevent accidents. On the other hand, cameras and other AI-enabled systems can detect suspicious movements of potential thieves in warehouses and alert those responsible, while IoT-enabled sensors can automatically lock connected doors.

It is worth mentioning that the estimated useful life of a truck is approximately 10 years, however the average age of trucks circulating in Europe is 14.2 years and in Spain the average is slightly higher at 14.3 years. Therefore, predictive maintenance of vehicles not only prevents breakdowns, but is also very useful to carry out good practices and extend the useful life of the fleet.

Conclusion

It is clear that AI and IoT technologies are often merged for the technological advances needed by the logistics and transportation sector to meet the current needs of the industry. Such as meeting increased demand, bringing order transparency to customers or cost reduction in the face of an uncertain situation.

At Hedyla our software relies on AI to analyze common routes, traffic patterns and other characteristics to generate various planned route models and choose the most optimized result that fits the customer's needs.

Meritxell Vázquez

SEO & Inbound Marketing
Video Game Design and Production graduate currently training in Digital Marketing with a focus on SEO and Inbound Marketing.

Creating articles of value and supporting communication to the technology sector.

hedyla.com

It is very important to establish logistics KPIs because they have one of the highest costs along with manufacturing and marketing expenses. This would result in huge losses if they are not properly monitored. This is when we ask ourselves, what are the essential KPIs to accurately measure your logistics objectives?

If you want to learn more about the different areas of logistics where the logistics KPIs cannot be missing in the dashboard, take a look!

Storage

It should be noted that warehousing should not be confused with inventory or stock because these indicators do not indicate the stock itself. KPIs are about analyzing the internal processes that take place in warehouses, such as picking and order preparation.

An example of logistics KPIs used in warehousing is the unit cost of warehousing which calculates their respective expenses. Apart from that, to analyze warehouse performance and productivity there are the KPIs of on-time complete delivery rate and internal cycle time that serve to calculate the time elapsed between the order request and the dispatch of the order itself.

Inventory

This is, of course, one of the most important sections of logistics because it deals with the products themselves and the stock that circulates through the supply chain. In addition to the fact that classifying and sorting the different types of stock is paramount to its proper functioning, so is assigning objectives and their respective logistics KPIs.

For that, the KPIs to be commonly taken into account are the following: Stock Breakage to analyze how many times the inventory has been emptied and what can be improved, Stock Turnover to estimate how many times the inventory needs to be renewed and, of course, inventory costs. It is worth mentioning that a high Inventory Turnover means that profits are being made on sales.

Suppliers

In almost all sectors it is essential to have a rigorous control over the supply and negotiation with suppliers. This is because it is one of the areas that cannot be taken care of directly and will depend on the relationships you have with them and their performance.

Its KPIs include procurement costs and purchasing lead times to ensure that the necessary money and time are invested in good suppliers. On the other hand, they highlight the level of supplier compliance and missed deliveries, which are responsible for calculating the number of orders delivered late and rejected, respectively, in order to estimate their performance.

Transport

It is known that transportation costs within logistics operations can represent more than 50% of total logistics costs, especially if they are last mile. That is why it is recommended to analyze that these budgets and their performance meet the objectives established in the logistics section.

One of the logistics KPIs that best calculates logistics costs is the cost of transportation over sales. Also to analyze the efficiency of transportation are On-Time Deliveries to see how many orders have been delayed and what actions need to be taken.

But if we are talking about saving resources and being more sustainable, logistics KPIs such as the level of fleet utilization help a great deal to know whether the full capacity of the interior of the trucks is being used, whether in kilograms or cubic meters. For this purpose, solutions such as the route optimizer indicate the available volume of each vehicle in order to optimize the loading of these vehicles.

Conclusion

There are many logistics KPIs pertaining to each section of the supply chain that help in analyzing and observing all quantitative and qualitative aspects of the processes in order to make decisions on how to improve them and achieve the objectives. However, it is not advisable to assign all possible KPIs because an overload of information is difficult to interpret and only the most relevant KPIs related to the established goals should be chosen.

At Hedyla, apart from optimizing logistics processes, we take care of supply chain consulting and show with analytics and business intelligence to improve the critical processes of your logistics.

Meritxell Vázquez

SEO & Inbound Marketing
Video Game Design and Production graduate currently training in Digital Marketing with a focus on SEO and Inbound Marketing.

Creating articles of value and supporting communication to the technology sector.

hedyla.com

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.

Route optimization

One of the most popular solutions within the logistics and transportation industry is to optimize delivery routes using AI software. It is also one of the most important in order to ensure on-time deliveries at the most economical price and fuel cost possible.

Among the functions of a route optimizationsoftware is to integrate data from various sources and use algorithms to plan routes according to the constraints to be applied at the time of deliveries. In this way, resources (vehicles and carriers) can be optimally organized, costs can be saved, and competent customer service can be provided.

Predictive maintenance

One of the current problems in the transportation sector is the lack of new vehicles on the market that can replace the old ones, thus requiring constant repairs to be operational. However, predictive maintenance is not as well known as one of the examples of artificial intelligence in logistics.

Using past and present data collected with IoT devices, machine learning algorithms can create predictions and maintenance recommendations for trucks, vans and other vehicles. In this way, the service life of vehicles is increased and further damage can be prevented thanks to these indications.

Conclusion

Several logistics processes are already being successfully automated and optimized thanks to AI. These solutions are key to overcoming the current challenges facing the logistics sector and offering a competitive and efficient service that responds to current trends and needs.

At Hedyla we offer several products and services developed with AI by our in-house engineering team that seeks to respond to the logistics needs of any sector.

Meritxell Vázquez

SEO & Inbound Marketing
Video Game Design and Production graduate currently training in Digital Marketing with a focus on SEO and Inbound Marketing.

Creating articles of value and supporting communication to the technology sector.

hedyla.com

Para encontrar la ruta definitiva que hará llegar antes a tus clientes se deben de tener en cuenta varias características de las paradas, vehículos y restricciones, entre otras. Además de mantener una comunicación sólida ante cualquier incidente que pueda ocurrir, ya sea un factor interno o externo.

If you want to know the key factors for optimizing delivery routes and how to reach your customer faster, take a look!

Distances between delivery points

Entre los principales factores que se piensan primero cuando se habla de optimizar rutas de reparto son las distancias entre el centro logístico y los puntos de entrega. Además de que es más sencillo calcular una ruta concreta en cuanto echamos un vistazo a la proximidad entre varios puntos de entrega.

Generally, if other factors and constraints are not taken into account, one of the best routes is the one that starts with the stop closest to the warehouse. And then follows the second stop close to the first, and so on until you have finished with all orders and return to the logistics center.

However, a simple glance at delivery points can hide narrow and difficult to navigate last-mile streets that can significantly delay deliveries. Consequently, this factor is one of the first to be considered when creating a "sketch" route and then assigning drivers, vehicles and other constraints.

Delivery and staffing schedules

It is known that, with a number of batches or individual orders for a specific day, a delivery time zone is agreed with the users when calculating routes. However, these customers are increasingly requesting more precise time zones, according to their needs. Therefore, such orders must be assigned to the carrier with shifts and agreements that are compatible with the assigned time slot.

It should be noted that special attention must be paid to labor restrictions for carriers. For example, drivers are not allowed to work more than 6 hours at a time without a break in a day, so they must rest for a minimum of 30 minutes. If it is a very long route, the appropriate time slot would be assigned in accordance with the regulations and, if necessary, another carrier would be assigned to cover the shift. Not to be forgotten are the hours when loading and unloading is allowed in the cities or at the logistics center receiving the delivery.

Road and traffic conditions

As mentioned above, last mile distribution is a challenge because of difficult access to certain streets, loading and unloading stops and peak hour traffic congestion. Of course, it is most advisable to unload outside of peak traffic hours, but it is possible to coincide with this time period.

It should be noted that it should not be forgotten that the road and traffic are often conditioned by multiple external factors that can cause cuts on highways and certain streets, from the presence of workers on construction sites to accidents. As these incidents are almost impossible to predict, in this situation it is essential to maintain a solid and effective communication with the customer (either by calls, SMS or WhatsApp) and report the problem in order to find the best possible solution.

Veicoli e merci

Por último, uno de los elementos clave a la hora de optimizar las rutas de reparto es el vehículo y las restricciones adjuntas, como la capacidad de su volumen y peso. Dadas las medidas actuales dentro de ciertas ciudades, como las zonas de emisiones bajas, es posible que vehículos con motor diésel o con cierta antigüedad no puedan entrar en dichos lugares, por lo que se deberían asignar otros vehículos. Por ejemplo, los light electric vehicles are the best option for driving on streets that are difficult to access.

In the same way that the goods are also an important factor in loading the assigned vehicles in the most optimal way possible, either in terms of the maximum weight and the maximum number of pallets or containers that can be transported. In this case, tools to control the loading of vehicles, such as a route optimizer , are of great help in choosing the right truck or van for a particular route.

Además hay que tener en cuenta que ciertos productos necesitan estar regulados y que el vehículo debe disponer de condiciones especiales para que pueda cargarlos con seguridad. 

Conclusion

As we have seen, there are many factors that affect route optimization and that, without an automated tool, are complex to organize. Not only does route optimization help to save fuel and time, but also the customer will appreciate good service and quality support, and good and long-lasting business relationships will be established. Therefore, there is no single answer to the question "how to reach your customer sooner".

In Hedyla tenemos múltiples módulos dentro de nuestras soluciones que se pueden añadir o quitar para trabajar eficientemente con las herramientas necesarias para cada caso de cálculo de rutas.

Meritxell Vázquez

SEO & Inbound Marketing
Video Game Design and Production graduate currently training in Digital Marketing with a focus on SEO and Inbound Marketing.

Creating articles of value and supporting communication to the technology sector.

hedyla.com

This year has been more crowded than last year thanks to the relaxation of the pandemic restrictions. On the first day, we have had the opportunity to make contacts both from companies interested in our services and from other companies, looking for possible synergies with us. In addition to that we have known the latest industry trends in terms of Big Data, Digital Marketing and, of course, e-commerce.

During the second day, the number of people was slightly lower than the first day; however, several people were curious about our services as we conducted several demos presenting the route optimizer with built-in delivery tracking and even the digital twin to compare the optimized routes. It is worth mentioning that the interested parties understood the importance of omnichannel, speed of service, logistics cost savings among other aspects to meet the growing demand of the e-commerce sector.

Apart from that, we were able to see the awards ceremony and, with it, we have seen more clearly who are the referents of the e-commerce and digital marketing sector.

That said, we look forward to returning next year to continue taking logistics to the next level.

Meritxell Vázquez

SEO & Inbound Marketing
Video Game Design and Production graduate currently training in Digital Marketing with a focus on SEO and Inbound Marketing.

Creating articles of value and supporting communication to the technology sector.

hedyla.com

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.

Traceability

Given the complexity and relative length of a supply chain, it is often very difficult to keep track of stock status, slowing down the identification and verification process due to tedious tasks. In addition to the fact that there are multiple factors that obviate some errors and then it is more costly to remedy how to manage the returns of a defective product line.

A traceability system with artificial vision assists in the streamlining and operation of identification and verification. This is thanks to cameras with image processing and analysis software that verify the identity of the merchandise and its current status. They can even monitor the moments in which the supply suffers any damage in order to speed up the processes to remove the product.

Route optimizer

Among the logistics decisions that Artificial Intelligence will make, there is no doubt that they are those that optimize more or less complex operations. These programs aim to save time and resources, especially when increasing demands and rising prices are not in their favor. In particular, the route optimizer stands out.

Apart from automating the cumbersome task of planning the routes your fleet of vehicles will take on a daily basis, it uses its algorithms to search for the best routes to take based on a series of parameters and restrictions applied by the same staff. These limits can range from the size and number of the fleet to the time slot of the carriers, adapting to any situation.

Conclusion

AI is increasingly present in the logistics sector, both in process automation and decision making. These are necessary technological advances in important processes such as in the streamlining of tasks and in the strategy directly focused on customer satisfaction, among others. In fact, there are companies that already rely on the logistics decisions that Artificial Intelligence will make.

At Hedyla we understand the current need in logistics to optimize operations such as picking or transport management.

Meritxell Vázquez

SEO & Inbound Marketing
Video Game Design and Production graduate currently training in Digital Marketing with a focus on SEO and Inbound Marketing.

Creating articles of value and supporting communication to the technology sector.

hedyla.com