Volume 3: Issue 03
Impact of autonomous trucking on the logistics Impact of Artificial Intelligence & Big Data on Supply Chain Management The increasing role of logistics in the Indian economy
KAIZEN VOLUME 03 ISSUE 03 MARCH 2019
SUPPLY CHAIN AND OPERATIONS MANAGEMENT CLUB (SCOMC) INDIAN INSTITUTE OF MANAGEMENT, ROHTAK
Editorial Team Editor
Editorial Assistant Design Assistant Design and Publication Review Team Marketing Promotion
Harendra Verma Ayush Kar Harendra Verma Amit Dhawan Akhil Verma Sukriti Gupta
DISCLAIMER The views presented in this magazine are those of the authors and do not necessarily reflect the opinions of the stakeholders of IIM Rohtak. Â© ALL RIGHTS RESERVED SCOMC IIM
EDITORâ€™S NOTE We are pleased to announce and publish the Third issue of the monthly club magazine â€œKAIZENâ€? 2019. This is our sincere effort to cover some of the relevant topics, concepts, news and buzz words/organizations in the industry that are coming up with disruptive field technological innovation to drive efficiency in supply chains and operational activities or business models altogether. This is an effort to progressively bring the audience of the magazine with quality and latest field and domain related content and to motivate fellow students and practitioners to share their knowledge about the same. We anticipate and encourage continuous support of our authors and readers to make this magazine a success. -SCOMC, IIMR March, 2019
IN THIS ISSUE 3 Impact of autonomous trucking on the logistics industry
6 Impact of Artificial Intelligence & Big Data on Supply Chain Management
9 The increasing role of logistics in the Indian economy
IMPACT OF AUTONOMOUS TRUCKING ON THE LOGISTICS INDUSTRY Google, Uber, Volvo, etc. are competing against each other to develop self-driving technology and it is considered to be the future of transportation. Driverless technology will have a higher impact on the logistics and supply chain more than the taxi operators. The biggest concern with the autonomous cars is that they usually commute in populated cities due to which the navigation becomes inefficient. The trucking industry, however, has a solution to this problem, and it can be established beyond doubt that logistics will be the biggest beneficiary of the driverless technology. The solution is that most of the trucks ply on hundreds of miles of almost empty routes between dispatch and receiving cities, autonomous steering takes care of this long stretch, and the manual drivers will only be required while navigating the trucks inside the departure and arrival cities. A single driver will be able to handle 7 to 8 trucks per day. In this article, we will focus on the impact which autonomous trucks will have on the logistics industry. Successful trials of automated driverless haul truck in El Teniente copper mine in Central Chile and Komatsu k930 trucks in Radomiro Tomic open-pit copper mine in Northern Chile in the mid-2000s has started commercial usage of automated or driverless trucks in mining industry specifically. Embark, a US-based start-up has started its fleet of
driverless trucks from its warehouse in Texas to a distribution centre in California, along the I-10 freeway with a distance of 650 miles in late 2017. Although a human has to be present regularly for now in Embark trucks, after seeing the safety level of driverless cars, it can be safely assumed that shortly there will be no need of human interaction during the voyage, once authorities allow driverless vehicles. We, as Supply Chain Managers will consider this technology if it is of any financial or operational benefit for us. Driverless trucking will provide the following benefits to the logistics industry: 1) High utilization: A typical manual truck has only around 40% utilization throughout 24-hours. This is due to the limits of a human driver, who needs rest and cannot drive regularly. This presents an opportunity to increase utilization by using driverless trucks. 2) Driver Salary Elimination: The median annual wage of a trucker for Walmart in the US is $73,000. Walmart has a fleet of 6000 trucks. The total yearly cost of drivers comes out of $438 million, which is around 32% of Walmart's profit in FY 2017. Although in driverless trucks, few supervisors will be employed to oversee the logistics remotely and navigate the lorry in cities. The cost of insurance 3
will also get reduced due to a smaller number of humans involved. 3) Cost of goods will fall: The increase in the utilization of a truck due to automation, will result in faster delivery, and eventually, drop in the product or service cost. It will help in achieving cost leadership. 4) Speedier delivery & low inventory: Since the utilization is near about 100% in automated trucks, it will lead to faster and on-time delivery, which will result in relatively short lead time. A shorter lead time leads to less inventory requirement resulting in saving of holding cost and an increase in inventory turnover ratio. Increased turnover ratio benefits mainly the perishable product traders. 5) Fuel Efficiency: Human drivers seem to drive fast from one point to another upon seeing a long stretch of empty road. This result in a frequent change of speed which increases fuel consumption. The computer driver will drive at the optimum speed in order to achieve the highest possible fuel efficiency. 6) Low Standard deviation in lead time: Since human errors will eliminate possible accidents or intermittent stoppages, it will reduce the standard deviation of lead time. It will lead to better planning of the truck fleet and other resources both at the receiving and dispatch side. Low standard deviation means lower safety stock requirement. It will make the operations lean and will also help in achieving six-sigma quality. 7) Road Safety: Tesla mentions on its website â€œBuild upon Enhanced Autopilot and order Full Self-Driving Capability on your Tesla. This doubles the number of active cameras from four to eight, enabling full self-driving in almost all circumstances, at what we believe will be a probability of safety at least twice as good as the average human driverâ€? . The autopilot of Embark trucks is also considered to be better than human drivers when it comes to safety. Automated trucks involve fewer accidents as compared to manual trucks, even the accidents
involving autonomous trucks happened only due to human error. A typical truck driver is also exposed to occupational hazards, removing driver from the truck will also save a human from working in a dangerous and undesirable situation. Some drivers may sleep accidentally behind the wheel, especially at night, due to fatigue. Some drivers get involved in substance or alcohol abuse, due to loneliness and stress, which increases the chances of road accidents. 8) Saving of air-conditioning cost: A human driver requires air-conditioning which also involves considerable cost. Eliminating human drivers will result in saving of AC cost. 9) Better opportunities for drivers: Trucking is an inhuman job in which a driver needs to concentrate on the road over an extended period of time on hundreds of miles of long stretches. They are meagrely paid especially in developing countries like India. In a 2015 report of American Trucking Association, there was a shortage of truck drivers in the US of 50,000 truck drivers, up from 30,000 two years before that, this number was 20,000 a decade before 2015. It means that fewer people are taking up truck driving as a profession or the jobs are increasing at a rate surpassing the rate of increase of drivers. Downsides of Autonomous trucking: It will not require much thought that a lot of drivers may lose jobs due to autonomous driving, especially those who are in this profession for a considerable part of their career. The price tag for a tesla driverless truck is around $300,000, and it will be a substantial cost if some company like Walmart replace its fleet of 6000 vehicles. Since there is no human involved in a long-haul autonomous truck, then it can lead to robbery or hacking of the AI system by unwanted elements of society. Understanding of road signs is also challenging for the AI system. In a developing country like India, there are few roads which are conducive to driverless vehicles. Interaction with traffic authorities will be challenging for an AI system if there is any traffic violation or a routine check-up. 4
According to CB Insights, a company which tracks the venture capital industry, In the year 2017 alone, companies and investors put around $1 billion into self-driving and other trucking technologies, ten times the level of three years ago. We can assume that investors are also bullish about the technology of driverless trucking. Trucking is a $700 billion industry, and autonomous trucking and its impact will hopefully be seen as a significant turning point in the logistics industry.
6) https://www.supplychain247.com/article/self driving_trucks_to_revolutionize_logistics
11) http://www.inboundlogistics.com/cms/article /how-driverless-trucks-will-change-supplychain-strategy/
1) https://techcrunch.com/2018/02/06/embarks -self-driving-truck-drove-2400-miles-acrossthe-u-s/ 2) http://embarktrucks.com/safety.html 3) https://www.tesla.com/autopilot 4) https://www.tesla.com/blog/tesla-model-sachieves-best-safety-rating-any-car-evertested
7) https://www.wired.com/story/embark-selfdriving-truck-deliveries/ 8) https://www.nytimes.com/2017/11/13/busin ess/self-driving-trucks.html 9) https://www.sciencedirect.com/science/articl e/pii/S0301420710000516 10) https://www.tagglogistics.com/driverlesstrucks-future-logistics/
12) https://www.techemergence.com/selfdriving-trucks-timelines/ 13) https://www.forbes.com/sites/jeffmcmahon/ 2016/10/21/behind-teslas-headlines-themilitary-drives-autonomous-vehicles/ 14) https://axleaddict.com/safety/Advantagesand-Disadvantages-of-Driverless-Cars
Zaid Bin Nafees is a first-year student of IIM Sambalpur; Zaid is having 5 years of experience in L&T in procurement. Zaid is passionate about Operations, Supply Chain, Logistics and procurement. Zaid has passion for writing articles and solving case studies. His article (With his batchmate Anuj Agrawal), â€˜Project Finance and the world of rising NPAs' has been a finalist in NITIE article writing competition and published in their magazine.
Anuj Agrawal is a first-year student of IIM Sambalpur; Anuj has 2 years of experience in SAP Logistics in Accenture. Anuj is passionate about Operations, Supply Chain, Logistics and procurement. Anuj has passion for writing articles and solving case studies. His article (With his batchmate Zaid Bin Nafees), â€˜Project Finance and the world of rising NPAs' has been a finalist in NITIE article writing competition and published in their magazine.
Impact of Artificial Intelligence & Big Data on Supply Chain Management Supply chain management forms one of
and make processes more efficient. This data along
the important branches of operations management.
with AI helps to understand purchase patterns and
It involves the flow of raw materials, inventory,
behaviors to predict the demand of products in the
goods, and information efficiently. Today, there is
future. Retailers can refine product availability and
a lot of hype about Artificial Intelligence (AI) in
increase customer satisfaction.
Supply Chain Management (SCM) these days due to its huge potential. AI is the shrewdness displayed by machines in making decisions. Often people confuse AI with automation. However, both are completely different concepts. Automation is a hardware or software which is capable of doing repetitive things on its own whereas AI takes decisions based on situations. Automation may or may not be based on Artificial Intelligence.
This new disruptive technology of AI and big data is also set to disrupt logistics industry. It has given rise to the trend of â€˜Anticipatory Logisticsâ€™ which reduces the delivery time by forecasting demand before an order is even placed. Anticipatory logistics also serves supply chain risk management. AI estimates maintenance requirements and potential uncertainties, alike transportation and disruption
We are living in a highly connected world where a
Manufacturing and transportation businesses use
lot of data is being generated every minute, and this
AI to speculate factory and vehicle maintenance.
big data gives us immense opportunity to optimize 6
Here predictive maintenance is built on sensor data
Inaccurate predictions might result in excessive
collected from smart machines and automobiles.
production, inappropriate stock levels, loss of sales
Apart from this, there is also a rise in the trend of ‘machine-human interaction' as the use of Augmented Reality (AR) accessed via ‘smart
etc. Hence forecasting customer demand has been one of the key challenges for organizations worldwide.
glasses’ exceeds expectations. The most recent
This is where artificial intelligence can make
example is of the Changi airport in Singapore
dramatic enhancements and impart superior
where staff started using smart glasses to scan
approaches to conquer this challenge. AI systems
can be employed to scan trillions of data records,
consignments. This helped to cut down loading
collect appropriate information from the market
time by 25 percent.
network, identify trend, seasonality or cyclicity and
When it comes to supply chain, the viable capacity of AI goes beyond production and logistics. In the upcoming days, AI and advanced algorithms can be the acumen behind supply chain – acting as an autopilot taking care of planning and fulfillment activities, observe inventory volume and adjust safety stock. There are already supply chain software in the market which is proficient enough to analyze different frameworks simultaneously and provide recommendation for the best course of action. The supply chain is the result of many activities in which ‘Forecasting' is the most important one. It is the activity where businesses spend a good amount of their time using different methods for it. It always requires complex statistical calculations with human intelligence and receiving 100% accuracy is always a difficult task. Apart from counting on existing software, these calculations also depend on expert's inputs to make it more accurate. One cannot deny the chances of mistake
forecast consumer demand more precisely. This can help to enhance flexibility across smart chains. The time is not far when AI chatbots will take customer orders, negotiate contracts with vendors or suppliers, and interact with the client. AI system can automatically identify customer priority established on their purchase trends. The AI-based systems
depending on the distinct nature of business operations. There is a lot of unstructured data present around in any supply chain management. This data can be processed through machine learning algorithms to obtain useful insights and information. Predictive supply chain and Big Data will help organizations to move away from ‘guess work’ in making estimates on the movement of materials. This will lead to more optimized inventory management, better analysis of aggregate distribution cost per unit and more adaptable shipping procurement options.
in this method as; currently, market software can
These smart machines are competent of self –
provide 60 – 70 % accuracy in forecasting.
diagnostics and can let the user know when 7
maintenance or service is required along with
Retail Supply Chain. Retrieved November 28,
Machine Learning, and a Predictive Supply Chain
can be a way of the future. However few challenges
such as technology expertise, integrate diverse data
origins and regulatory barriers need to be
conquered for widespread adoption. Souradeep Guhathakurta is an Electronics Engineer from Swami Vivekananda Institute of Science & Technology, Kolkata. Prior to joining SIBM Pune as a Marketing Major, he worked with Hitachi Data Systems as a Storage Consultant. He loves coding
Ovenden, J. (2017, September 26). AI And The Future Of Jobs In The Supply Chain | Articles | Big Data. Retrieved November 28, 2017, from https://channels.theinnovationenterprise.com/a rticles/ai-will-destroy-supply-chain-jobs
Raspberry Pi toolkits and watching superhero movies in his free time. References
Taylor, C. (2017, October 25). Artificial Intelligence and Logistics are Transforming Business. Retrieved November 28, 2017, from https://www.datamation.com/bigdata/artificial-intelligence-and-logistics-istransforming-business.html
Rohit Khanna is a second year PGDM student of IMI New Delhi. He is an Electronics & Communication Engineering graduate from Manipal Institute of Technology, Karnataka. He worked at TCS for two years He is interested in food blogging, Article writing & Current affairs.
Management - Kinaxis. (2017, January 12).
IMI, New Delhi (2017-2019)
Marr, B. (2017, September 12). Predictive Analytics And Machine Learning AI In The
The increasing role of logistics in the indian economy Logistics is nowadays regarded as the backbone of the economy; whose sole purpose is to provide an efficient and cost-effective flow of goods upon which the other commercial sectors depend. Sometimes it is the very function that determines the success of the organization especially in the case of e-commerce retailing. Indiaâ€™s logistics, currently a 160 bn dollar fragmented industry employing more than 22 million people is set to reach the 215 bn dollar mark in 2020. And The Economic Survey 2017-18 tabled in Parliament might also be right this time considering the GST implementations that have eased movement across states and simplified the tax structure. In the recent study done by the World Bank, India has jumped 19 positions to 35 in the Logistics Performance Index (LPI). The greater investment opportunity in the warehousing sector will offer a better investment return and lead to the growth of the business. The warehouse industry in
India is growing at a rate of 10 - 12% CAGR every year. The logistics market is experiencing high demand with the constant growth of the ecommerce retailers and manufacturing industries, especially the FMCG sector. In fact, some of the leading logistics companies are now giving tough competition to established companies like FedEx and Bluedart were spawned by manufacturers and retailers like Mahindra & Mahindra, Tata Motors, Jindal Group, and Future Group themselves as a separate entity to fulfil their need for creating a reliable and efficient logistics and supply chain system. This enables them an edge over their competition in terms of a larger revenue base, cost reduction, and more focused customer experience. In India, transport is the most crucial function of the logistics industry, accounting for 50-60% of the market size. Road transport like trucks and vans with 60% share, dominates the transportation sector. Sales of trucks in the heaviest Class 8 9
weight segment trucks surged 59% to 296,440 vehicles in 2017, according to ACT Research. Only 10% of Indian truck operators own a fleet exceeding 25 trucks. Most truck drivers today own single trucks and rely on third-party agents to handle orders. There are many attempts to aggregate the truck transport industry despite failed attempts of companies like Loadkhoj, Zaccheus, TheKarrier, Sastabhada, Truckmandi and Trucksumo. The share of transportation in the logistics industry by the Indian railways is 32%, followed by waterways (7%), and air cargo (1%). The next function of logistics is warehousing and storage which comprises of about 25-30% of the total market. The rest of the market constitutes mainly of value-added and freight forwarding services. India spends around 14.4% of its GDP on logistics and transportation compared with less than 8% by other developing countries. According to ASSOCHAM (The Associated Chambers of Commerce and Industry of India), India can save up to US$45 billion if logistics costs are brought down to 9% of the countryâ€™s GDP, thereby making domestic goods more competitive in global markets. The future of logistics, as it is for almost other areas is the advancement of technology. Technology has an important role in developing more efficient high-speed sorting systems with robotics and automation to prepare them for shipping and reduce lead time. These developments propel warehouse operations towards complete automation. It can also contribute in making a more centralized administration and better remote monitoring systems that can help in the consolidation of resources. Just as Nash Equilibrium was used for the most unexpected fields like economics and law by John Nash himself, blockchain technology (found by Satoshi Nakamoto for its use in the Bitcoin cryptocurrency) is now being applied in logistics for transparency throughout the supply chain to all players in the chain including the customer. This technology has the potential to transform certain industries where trust by consumers is paramount like the clothing and food industry and where laws
are often flouted like the coal and diamond industry. Block chain technology will enable easy central and public tracking of which goes into a product that reaches the consumer. This can be tracked right from the origin, throughout the movement and the delivery. This will make the entire Supply Chain more responsible and accountable, compliant due to transparency. Aggregation in logistics is going to be inevitable considering the increasing growth of technology and certain defragmented areas of logistics like trucking. Uber can be a good example to illustrate this concept. It is successfully augmenting available passenger capacities to provide more benefits to the customer without ownership of a single car itself. Aggregation is thus creating logistics providers that provide better logistics services through the aggregation of information instead of owning assets like fleets of vehicles or a warehouse. Mahindra had also entered the logistics service sector with Smart Shift â€“ a common platform for cargo owners and transporters to reach out to each other and reach the best logistics deal. The cargo owners access the Smart Shift service either through a mobile, the website or the dedicated call centre. It enables users to find cargo transporters based on the shipment size, weight and other specifications. Furthermore, the user can also negotiate and finalize the deal on the mobile app itself. With massive data available at all steps of a transaction, there is a dire need for data to be processed effectively to reduce transaction costs and the costs of logistics. Predictive analytics is being adapted in today's data-driven society for getting to market faster, forecasting analytics and increased transparency across the supply chain. Advanced predictive analytics are starting to form the brain of various enterprises, thereby creating a new digitally conscious organization that is committed in making sense of big data. Even though big players like Infosys, Oracle, Deloitte and Accenture have already set industry standards globally and locally in supply chain analytics, the field is still open for smaller players to play around in this increasingly data-intensive sector.
References: www.economictimes.indiatimes.com/articleshow/ 62693817.cms?utm_source=contentofinterest&ut m_medium=text&utm_campaign=cppst https://yourstory.com/2017/02/d7cc17cf0a-whyare-large-conglomerates-in-india-floating-theirown-transportation-companies/ http://www.bcone.com/IrfanTalks/future-oflogistics-and-supply-chain/
Mathew Thomas graduated B.tech Production Engineering in 2016, interned in Ashok Leyland as an Operations Analyst to increase the On Time In Full performance of the supply chain and currently working as a management trainee in ABFRL conducting a deep dive on partner and competition methods of working for Van Heusen.
We are pleased to publish the Volume: 3 Issue no:03 of ‘Kaizen’ – monthly magazine of Supply Chain and Operations Management Club IIM R. The...
Published on Apr 19, 2019
We are pleased to publish the Volume: 3 Issue no:03 of ‘Kaizen’ – monthly magazine of Supply Chain and Operations Management Club IIM R. The...