The real benefit of AI is combining human intelligence and raw data to bring value to its users

Logistics has been an integral part of human evolution. The procurement, maintenance and transportation of goods have been the key to any trade from the very beginning of human history. Therefore, it might seem absurd to know that logistics has been considered as a business function only after the 1950s. Before the 1950s, logistics was thought of just in military terms. It had to do with the supply chain management of military facilities, material, and personnel. And even though the benefits of goods reaching at the right time was for everyone to see, still businesses hardly ever focused on their supply chain.

In the later years, as the demand increased and businesses grew, the operations of organisations needed to become more structured and supply chain came into notice for the first time. Still, supply chain was thought of as pipelines where human beings simply did mechanical work. When there was a need to increase the output, more staffs were hired. When the production needed to be slowed down, people were let off. Simple.

It was after the second war, that machines made their entry into the market. Many operational jobs were soon automated, and technology took centre stage when it came to productivity and transportation. However, the technology still only helped with manual tasks. The entire decision-making process was always left for the human brain.

However, the modern market is altogether a different beast. E-commerce has grown exponentially, and customer expectations are through the roof. Home-deliveries are the new normal, and every retailer wants an omnichannel presence. Logistics complexities have reached a whole new level. To understand the situation, let’s have a look at a potential real-life scenario. Imagine trying to deliver 100 units of furniture. The decision maker needs to consider — the cost contract for different vehicle types; types of furniture that can or cannot be delivered together, which service associate should be assigned for assembling these units of furniture, addresses and timings of the loading hub along with real-life constraints of traffic conditions and fuzzy delivery addresses.

Such complexities are beyond the comprehensive capabilities of the human brain, and this is where AI comes into the picture. Modern AI-based algorithms use historical data for future projections. Advanced decision-making engines like Locus account for real-world on-ground scenarios and business constraints. The algorithms are modeled to continuously adapt, improve and help supply chain managers in making better business decisions.

Also read: 4 ways artificial intelligence is innovating e-commerce

AI is helping supply chain managers in answering the where, when and how? Leaders in the supply chain have now access to make the best decisions regarding the deployment of not only inventories but also the transportation assets needed to connect all the dots from origin to the customer location. What vehicles to use? What commitments have been made? Where are the customers? How to save logistics costs?

Answering these questions successfully and quickly will save a lot of time and money of organisations around the world. Businesses estimate they spend on average per week around 55 hours doing manual, paper-based processes and checks; 39 hours chasing invoice exceptions, discrepancies and errors, and 23 hours responding to supplier inquiries (mhlnews.com 2017). This loss has been equated to around 6,500 hours, during the work year, that businesses are throwing away by processing papers, fixing purchase orders and replying to suppliers. A cross-industry study on AI adoption conducted in early 2017 by McKinsey found that early adopters with a proactive AI strategy in the transportation and logistics sector enjoyed profit margins higher than 5%.

India’s leading courier delivery services company has saved 60% of their sorting time, decreased 70% of sorting personnel and has maintained over 95% of route mapping accuracy using our AI-enabled solutions.

We have also worked with Rollick, one of the largest frozen desserts manufacturers in eastern India. Rollick had traditional processes for distribution planning that relied on human intelligence and intuition. This resulted in inconsistent delivery schedules and suboptimal fulfillment of orders leading to higher costs and inefficiencies. There was also a lack of visibility in terms of the performance of different units – Stock keeping units (SKUs), distributor, transporters and salesman.

Dispatcher, our intelligent route planning engine, helped them in shifting from a traditional ad-hoc distribution planning to a scheduled one. Locus also used its Network Optimization solution to inform Rollick about the ideal location of the next cold store and manufacturing unit. Locus solutions had the following impact on Rollick:

8% of logistics cost saved.
2-3 hours of planning time saved daily.
100% increase in visibility of resources.

Our company applies artificial intelligence to help enterprises reduce logistics cost, enable on-time deliveries and provide a delightful end user experience. The company’s innovative logistics optimisation solutions serve a number of sectors including E-commerce, 3PL, Home Services, Retail, CPG and FMCG.

The benefits are as follows:

60% decrease in shipment processing time
25% decrease in operational costs
27% increase in order deliveries per rider
75% decrease in dispatch planning time
14% increase in SLA adherence

One of the major complains often associated with AI is its tendency to replace human intelligence. The real benefit of AI, however, is combining human intelligence and raw data to bring value to its users. When used appropriately, AI only removes disguised unemployment and actually empowers the user by helping him or her to choose better options.

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For companies to embrace AI-based solutions, they need to ensure that their on-ground resources are comfortable in using the new platform. Therefore, organisations need to partner with technology partners who can help them in the change management process and smoothen out the transition to newer platforms.

The future of AI in logistics depends upon its use in decision-making capacities. AI considers historical data and real-world constraints before suggesting the optimal solution to a problem. Those who consider these suggestions in their decision-making process can lead the logistics sectors in the years to come. AI has real implications for the industry, and if harnessed appropriately, will propel forward-thinking companies ahead of the competition.

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