Disruptive Tech Trends In Logistics And Supply Chain Management Part II

In the part 2 of the series, we highlight some more disruptive trends in logistics industry and supply chain management. Part one can be understood here. Please relish the innovation in tech and processes below:

6). Big Data Gathers Limelight:

Data plays a pivotal role in deciding the future of any economy, society, industry and market and such holds significance to logistics and supply chain field as well and when we put data in analytics, crucial insights are gained.

With data analytics, we get prime insights enabling quick action, which also lead to warehouse efficiency, logistics wealth are put to proper utilization and then monitoring and managing performance becomes easier too. Data can be gathered from a variety of sources such as weather forecasts, assessing fleet positions and their schedules for the day or week with which routes are advanced and such factors combine to draw efficiency in making deliveries and delivery planning. Besides, when market data is analyzed reflecting impressive insights, it helps in determining supplier pricing, checking inventory stock and producing risk management reports. Further, with advancement made in analytics, we have the understanding of unclear situations and can easily predict and plan maintenance solutions.

Nautilus – Monitoring Performance Becomes Easy:

Here, AI solutions are offered by this US based enterprise Nautilus Labs which enable (((maritime))) companies in checking fuel consumption which streamlines their functions and processes. The past voyage data is analysed by this software which is hosted on cloud, which then reports about optimal speed and fuel consumption. Besides, it also provides reports about the quality of vessel voyages and its management during such voyages which help in lowering fuel costs as well.

FACTIC – Prescriptive Analytics:

Such is a start-up located in US, putting forth an integrated Saas platform meant for food and beverage industries, producing solutions concerning predictive analysis. It enmeshes data mining and AI techniques, for data analysis which is sourced from internal and external sources to draw sales plan. Then, the platform fiddles with demand and supply quantities in order to enable automated procurement accordingly and then there are tools galore on this platform for the purpose of stock optimization by involving automated replenishment.

UPS: A Company With A Difference:

When it comes to consider success stories that centre around Big Data, UPS appears on the forefront. Clearly, when data is collected and put into rigid analysis so as to forecast demand, every enterprise is bound to acquire the paramount operational readiness while putting a brake on rising costs manifolds.

Now, emphasizing the point that there are around 80 thousand vehicles and prime sensors are fitted in each one of them (i.e. nearly 200 sensors on each vehicle), meant for different functions, such as, to record speed, check brake functions, locating destination, idle time calculation and back-up. Besides, some of the sensors are unique enough to collect data indicating faults or machine issues, likely to happen but are critical enough to take the vehicle to workshop for repair. For example, vehicle battery, air pressure in tires, engine performance etc. which, preemptive maintenance may be required. Not to drop jaws, but the end objective is to ensure that vehicle spends more time on road, operating to make deliveries rather than in workshops.

Also, when we rely upon predictive modelling, fully infected with big-data, management draws the benefit of route optimization as well.

Now, when we have realtime traffic updates and are able to adroitly maneuvers GPS and location software, logistic companies are able to develop precise delivery window. As such, with big data phenomenon on our side, routes can be altered in quick time, with 2 dominant reasons behind it:

 Certainly, the first one is to manage fuel, its usage, UPS has again risen to glory in this aspect, as the company utilizes has brought down fuel usage immensely, say about 1.5 million gallons in the year 2012 by riding high on big data which obviously added to profits,

 Then, mileage has shown a dip as well, as a result of route optimization on the back of big data.
Further, the deft management of UPS identified operational irregularity and inefficiency in outlandish way. Going by the philosophy of CEO, the trucks never make a left turn.

7). Cloud Computing:

In-line with above factor, we have logistics companies are thrilled to receive cloud-based Saas solutions that is available for pay-per-use models and are thus, extremely economical too, as costs of IT infrastructure is brought down to minimum possible. Besides, workforce can easily share data and communicate with other sections and locations in secured way. Then, when glued with cloud, seeking data from management and strategic systems becomes easier too and complete logistics processes can be monitored easily and broader data accessibility is ensured which is not limited to any location or section.

Linker – Cloud Platform:

This start-up was launched in Poland that offers services on a B2B cloud platform, empowering e-Commerce companies with logistics services and third-party logistics players are also charmed by it. Platform bears tools to refine labelling items and to aid in delivery services, while shipping processes are also managed. For challenges found in warehouses and among delivery groups, a specific set of utility tools are there. Finally, as the platform is served as pay-as-you-go, enterprises find it far economical.

Alpega – Cloud TMS

A start-up launched in Belgium, the company designs Saas Inet which is meant for managing transportation through cloud and targets end-to-end transportation challenges. Real-time inter-communication is designed to take place between manufacturers and warehouses and logistics providers. The processes and schedules of logistics are automated by Inet TMS and broader transport process, tasks, schedule and even the challenges are set-together onto a single framework. Then, shipment tracking is managed through an integrated mobile app. Customers are thrilled with upgraded software that this company releases on regular 3 months basis, while other software that are on-premise, only provides upgrades per annum.

8). Artificial Intelligence:

Companies find a great respite when AI algorithms which embed machine learning promote them onto next level in dealing with changes in demand. For instance, managers are assisted by predictive solutions powered by AI to carry out proper planning in supply chain processes and to curtail associated costs thereby. Not only this but smarter road technologies including self-driven vehicles that are again guided by AI, have revolutionized the delivery modes teeming with sheer automation. In final phase, AI also enables cognitive automation which simply auto-design the admin tasks and marshals info-centric operations on fast track.

Insite – Demand Forecasting

Tucked in New Zealand, this start up exudes sheer professional sheen in offering software solutions that hover around AI and a range of tasks are accomplished thereby, such as price determination, predicting demand and administering process flows, while initially as of now, only consumer packaged goods (CPG) sector is addressed alongside retailing companies. There are programmed specific modules right into the software to facilitate risk assessment too and when demand is speculated, manufacturing and packaging get to new high and in fact, all of the operational conditions are controlled in an automated manner.

Besides, the platform integrated with machine learning is capacious enough to collect and mesh data from various sources into a unique reliable unit for quick decision making. As an outcome, managers feel the real zeal when they have actionable insights on the table for a multitude of departments.

Adiona – Process Optimization

Such is based in Australia, acclaimed for having developed Optimization Software-as-a-service (OsaaS) empowering companies to refine their processes and optimize functions while reducing costs, in logistics. Adiona’s FlexpOps API fashions delivery routes by redirecting vehicles in judicious way as well as tackles other issues. Apart from this, crucial decisions are initiated in timely manner regarding fleets when certain conditions are forecast, such as demand, weather and the possible traffic delays when machine learning dictates. Finally, for workforce availability and skill level, solution also guides and goads the enterprise and enables contract hiring in automated manner.

9). Robotics

For pampering the factors of speed and accuracy, robotics and their use has become widespread in supply chain processes and man-made errors are thus reduced. Besides, with robots, uptime is increased while productivity and efficiency is also refined manifolds as compared to human staff. There is a concern that robots would replace humans in employment which is just a myth, as robots are designed and refined to collaborate with human workforce seeking operational diligence.

For instance, we have co-bots (collaborative robots) and autonomous mobile robots (AMR) which are put into service to pick boxes in warehouse and to transport them to necessary section or storage units. Moreover, for tasks that are repetitive in nature and are thus mundane, software robots are designed which enable human workforce with more time to deal with other tasks.

Canonical Robots – Collaborative Robots

As highlighted above, co-bots are designed to work closely with workforce and to assist them in delicate tasks and thereby enhancing their productivity in area of logistics. Such are tasked with picking, placing and even packaging goods in a short time and also check on critical human errors. In the field, there is a start-up launched in Spain, Canonical Robots which designs collaborative robotic machines to look after supply chain processes. Such co-bots come with 6 axle joints that enable a greater flexibility and movement just like a burly human arm and help human workforce in various activities mentioned above.

Actimai – Robotic Process Automation (RPA)

There are certain petty tasks that are repetitive in nature for which, RPA is involved for sake of automation and to wipe human error out as well as to control overhead costs. There is a wide range of operations which RPA handles, such as invoice processing, storage of data in automatically in audit trails and also handles the purchase orders input thereby. Here, Actimai a start-up nestled in Philippines performs a big role by designing, deploying, managing and optimizing RPA based solutions and by enmeshing swanky technologies of AI and big data along. The start-up refines software of robotic processes and produces insights for process adjudication.

Tags: Actimai- Robotic Process Automation, Alpega Cloud, Artificial Intelligence in Logistics, Big Data in Logistics, Canonical Robots, Cloud Computing In Logistics, Cobots, FACTIC, INET, Insite-Demand Forecasting, Last Mile Delivery, Linker Cloud Platform, Nautilus, Predictive Analysis in Logistics