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You are head of transportation for a large apparel company with say 2000 stores spread over 900 cities across India. Every week you ship over 20,000 boxes though 15 logistics partners from 6 warehouses.

• You get a call from Head of Sales, blasting away about a shipment of latest designer wear delayed by over 30 days
• Three states have just opened lockdown and you have to scramble to deliver material to stores or consumers. You have to ensure 3X capacity given high season.
• Your boss wants to release contracts for logistics partner. He wants you to analyze performance of 20 plus partners over last one three tears and give him feedback. He also wants to check any impact of monsoon, festivals, marriage seasons etc. on delivery time.

Technology is key to handle above situations- real time tracking, responsive transaction systems and data analytics will help in above cases.

Traditionally, logistics industry has seen itself has a physical infrastructure industry with massive investments in vehicles, warehouses, ports, ships etc. Also, most of the workforce is unskilled or semi-skilled. Thus, investment in information technology was limited to handle specific functions of a company.

But the advent of global supply chains changed this dramatically. Companies source components globally to manufacture today’s products. A problem in chip-making factory in Taiwan creates production issues in car plants in Europe and India. To handle such a scenarios supply chains need to be connected digitally and information needs to flow between companies and countries in real time.

In last few years, there has been a massive investment in technology start-ups to digitize various parts of supply chains. Today, you can get data from a range of sources such as GPS trackers, IoT devices, Sensors in cold chain, Ship and Flight tracking systems, Warehouse control systems, Smart CCTV feeds. The mobile phones used by delivery vans and bikes generate immense amount of GPS data, Geo-codes of delivery locations, images of products and delivery documents.

In less than ten years, logistics has made a jump from too less information to an unlimited torrent of data. With increasing application of Artificial Intelligence and Machine learning, a number of tasks are now automated.

Despite all the advances in technology, human decision makers continue to play a central role in most logistics operations- especially in responding to exceptions.  

And exceptions are galore. Covid-19 pandemic created massive chaos in global supply chains and the same is yet to become normal.

When Suez Canal was blocked by Ever Given ship for less than 7 days- it created massive snarls in supply chains. A drought in Taiwan halted semiconductor shipments across world.

Number of extreme climate events such as Floods, Storms, Droughts in increasing every year. Most mathematical models fail to handle such outliers. Thus, human decision makers will always be needed to steer supply chains though.

The need of the hour is Techno-Logisticians.

Much like a weather forecaster, she will interpret data from a range of sources, apply data science models and adjust them with emerging data and take decisions. Much like Air Traffic Controllers, they will monitor a part of the supply chain and interact with their counter parts and “handover” movement of vehicles, ships, aircrafts and cargo in them for further control.

There are many challenges for wide adoption of such a model:

Limited talent pool. Current work force of logistics companies is yet to adopt technology as a way of doing business. Some Business Schools have already started programs combining logistics theory and technology but many more will be needed.

Fragmentation. Logistics execution has multiple layers. India has more than 4 mn transportation companies with most owning less than 5 vehicles. To reach deepest corners of India, consumer companies sometimes work with 30-40 partners- all of them with basic systems or none at all. There is a need to offer easy to system at low price to a large number of such players.

Lack of investment. Most end-customers do not put a premium on technology capability of service providers and focus on lowest cost model. This results in lower investment in technology and tech enabled manpower.

Many more challenges abound and not all will be solved in short term. But things are changing on ground quickly and many a times with simple solutions.

Also, a slew of Indian start-ups have identified the “unorganized” sector of logistics as their key market. They see opportunity in scale and also in offering range of related services to logistics such as lending, brokerage, sales of equipment etc.

In summary, we can see that technology is working more as an assistant in human decision making in logistics. Robots will play their role- but humans is where industry needs to invest more.