Table of Contents
2. Literature Background
4. Operations Impacted by AI
- Supply Chain and Demand Forecasting
- Customer Experience
- Store Operations
- Pricing and Promotion
- United Parcel Service
6. Results and Conclusion
List of Figures
Figure 1: The AI Ladder
Figure 2: The Rise of Robotics and AI
Figure 3: Evolution of Emerging Technologies
Figure 4: Retail Store Featuring Robot
Figure 5: Robots used in Amazon Warehouse
Figure 6: A Snapshot of Amazon-Go Store
Figure 7: Amazon Prime Air Drone
Figure 8: Walmart Self Service Kiosks
Figure 9: Self Piloting Robots in Walmart
Figure 10: Summary of Expected Benefits in Marketing
This section will highlight the purpose of the report, challenges in existing methods of operation management and definitions of new technologies.
The purpose of the report is to discuss the impact of Artificial Intelligence (AI), Machine Learning (ML) and Industrial automation on the fundamentals of operations management and production analysis. The above-mentioned technologies are gaining popularity due to their widespread use and advantages in both manufacturing and services. These technologies are creating a profound impact in forecasting, inventory management, Master Production Scheduling (MPS), Material Requirement Planning (MRP), budgeting and aggregate planning. When AI and ML are incorporated with the principles of above-mentioned approaches, researchers have found a significant improvement in the results and huge cost savings. MNC's like Amazon, UPS and Walmart are investing millions of dollars to modernise their operations using AI, ML and Automation to become competitive in terms of cost, quality and service.
Although these technologies are influencing and improving the approaches in production analysis, the biggest challenge is the high initial investment for their implementation and whether small businesses will be able to afford it? The report aims to give a solution to this problem as well.
This section aims to discuss the need of investing in these technologies to revolutionise the approaches to operations management. The existing methods of operations management have various drawbacks and shortcomings which directly impact the financials of a company. As there is a famous saying, "Necessity is the mother of invention", the following challenges have motivated the researchers to develop solutions which are more sustainable and efficient in improving the accuracy of the systems and lead to better decision making. Some of the challenges are –
Inaccurate demand forecast for retail industry either leads to lost profits due to stock outs or excessive inventory due to actual sales being less than forecasted sales. This challenge is even bigger when talking about perishable items having shelf life less than a week .
Keeping inventory levels optimum by avoiding excessive inventory and avoiding stock outs .
Keeping an eye on real time data of demand and backorders .
AI is focused on planning, designing and building algorithms to make machines capable of thinking, analysing and reacting like humans. In order to achieve this goal, machines need vast amount of data in the form of inputs from the surroundings . Knowledge engineering is an integral part of AI as it concentrates on the rules which are applied on data to analyse it like a data analyst. The human problem-solving ability is transferred into a code which can analyse the input data and arrive at same conclusion as a human .
Figure 1: The AI Ladder 
Machine Learning (ML) is another branch of AI in which a machine improves itself automatically from its past experience and does not need to be reprogrammed. It has the power to learn from its mistakes. AI and ML are a perfect fit for executing tasks which computers can do better than humans. Hence, this technology has all the qualities required for a perfect demand forecast, by using models that can make predictions based on past data .
2. Literature background
The 21st century is considered as a century of machines. Many companies have invested and still are investing a huge amount of revenues in transforming their supply chains with a special focus on robotics and automation. Nowadays everybody wants swift supply chains with excellent service levels.
Moving back to 1961 which is considered as a great year in terms of the automation revolution. Unimate which is the first-ever industrial robot helped in performing special tasks of material handling in the General Motors car factory. In 1994, the concept of instinctual graphical user interface came into the picture that enabled to operate the robot via the internet.
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There has been a huge revolution in the development of robots. The robots these days are considered of two types, behavioural and industrial robots . There was almost no importance given to the robots in the field of supply chain a few years ago. The robots were considered unintelligent and stagnant. Moreover, when logistic companies thought of using robots for operating the business, there was a lack of technology to carry out intricate operations . InDepth research disciplines like mechanical and electrical engineering etc. as needed, making robotics a huge expense on the industry.
In this era of industrial globalization, many supply chains are using a blend of automation with other smart technologies like AI, additive manufacturing and so forth . The figure shown below represents the evolution of robotics in different eras of industrialization.
Fig 2: The Rise of Robotics and AI 
Then came the era of smartness i.e. Artificial Intelligence (AI) and it has transformed the supply chains and businesses completely. Before AI the systems we're using traditional tracking techniques for example RFID that involved some limitations like:
- A lot of time consumption in labelling leading to larger lead times.
- Greater chances of human mistakes.
- Lack of diagnosis and contextual information.
AI has changed it all. The IoT sensors in collaboration with real-time monitoring connected processes and stakeholders in a supply chain in a single window. AI not only reduced the delivery times by quick tracking of the products in the warehouse but also improved the demand forecasting models that enabled the organizations to take the strategic decisions like whether to adopt a push strategy or pull strategy. AI has made it easy through its advanced statistical models.
These techniques worked to a greater extent but failed to manage the supply chains like predictive maintenances of assets and their impact on production demands. Then Machine Learning (ML) came into the picture that has shifted the paradigm. As ML can analyse large data sets from a vast range of resources with much accuracy, it is transforming the production techniques. Industrialists can now make a predictive maintenance schedule with many accuracies thereby reducing the breakdowns and defects.
In the era of revolution, the businesses are talking about uniting the supply chains. Many of the big groups have employed robots for almost every task viz. transportation, material handling, drone deliveries, chatbots etc. The following figure represents the future of robotics changing the production techniques.
Fig 3: Evolution of Emerging Technologies 
Implementing the AI Solutions in Retail Sector:
Identify the Problem
The first step in problem solving and decision making is to identify the problem. Adding various AI capabilities to the services can enhance the business and profit margins like getting the future demand of any seasonal product with forecasting models along with the assistance of artificial intelligence.
After defining and identifying the problems, the potential AI implementations identified should be accessed. To prioritize the possibilities, on a short-term basis, the financial value for the company should be known and the high-level executives in the management hierarchy can contribute in developing and accessing the possibilities.
Acknowledge the Capability Gap
After prioritizing, acknowledging the capability gap is of utmost importance. It helps the management know the gap between what they want to accomplish and what can actually be attained according to the organizational ability. This process can also help the company to internally evolve before implementing the solution.
Once the idea is ready to be implemented, then it's the time to start building and integrating but keeping in mind what is known and what still needs to be known in the newest technology. This is the time when the expert consultants in AI are externally hired. The work of AI experts and the internal management, those who are having the vast knowledge of the business plan, can be combined to set long-term and straightforward targets.
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After having the expert's hands on the business plan, it is the time to implement the data plan. Starting simple and constantly extending the use of AI to prove facts and values can help expand the use of the new technology. Being selective and specific in what the AI will be reading for example, pick a problem which can be solved using AI, and then provide particular solutions rather than throwing everything at it.
Embrace AI into Daily Life
With the artificial intelligent automation, workers and employees have a tool which can be additionally used in their daily life instead of replacing it. Transparency can be achieved into resolving the technological issues in a workflow. This way, employees can clearly visualize how AI is helping improvise their roles and responsibilities instead of eliminating the workforce.
Build and Measure Success
After the implementation of desired plan, measuring flaws are essential. Learning from the mistakes can help achieve better results which in turn improves the organization's productivity. Artificial intelligence embraces itself by learning from its mistakes which can further help the organization generate more revenue and earn more profits.
4. Operations Impacted by AI
The most important aspect of new technology is to implement the blueprint of what has been decided by looking at the trends. Artificial Intelligence, an emerging technology in this scientific world, is a machine intelligence similar to the one shown by humans. This technology learns from past-experience and can analyse the factors which affect product demand. Some established retail industries started utilizing Artificial Intelligence and the planning stage is more focused on the following 6 areas :
- Supply Chain Network
- Demand Forecasting
- Customer Experience
- Marketing, Advertising, and Campaign Management
- Store Operations
- Pricing and Promotion
Supply Chain and Demand Forecasting
With the increase in population worldwide, there is an increased demand for the products which in turn is helping the retail stores earn more profits. But to cope up with this increased demand, artificial intelligence should be implemented in the supply chain which can even boost the productivity of the organization.
Managing the Warehouses
Warehouse robots are automatically pulling out the products which need to be shipped to the retailers. The usage of these robots is preventing most of human injuries because these robots started performing difficult and dangerous tasks instead of humans. Once taught, the robot will never forget where the exact location of the product is and where it should be binned while stocking and this newest technology can work well with manpower as it can avoid obstacles easily .
Planning inventory ahead of the sales is the most tiresome job for any operations engineer or manager. But with the assistance of Artificial Intelligence, future demand can be predicted by using forecasting techniques which includes seasonal demand and then the managers can know the optimal quantity to stock in order to satisfy the variable demand and reduce the inventory holding cost which further helps to utilize the warehouse space as well .
The shipping of the products has been improvised, thanks to AI. As the driverless cars are still under testing, AI can make a precise prophecy about the in-transit time of the products. TransVoyant is using machine learning artificial intelligence to predict the weather forecasts and road conditions in order to avoid any delays in delivering the products to the customer .
Better the customer experience, more will be the customer satisfaction which in turn leads to more loyalty towards the company. Artificial Intelligence can help accelerate customer experience in any retail firm. AI can always support the sales and marketing department of the organization. AI-powered solutions can help generate better problem-solving skills and techniques that can never be achieved by humans alone. With the use of Service robots in a retail store, the response time of the customer queries can be reduced significantly .
Steps to get the live and quick understanding of the customer's questions are:
- Plan the customer experience strategy by voluntarily taking the lead in the department and designing the service robots accordingly.
- Map and analyse the customer's journeys to know the critical paths taken by the customers and the most favoured products by them.
- Track and measure success using the key performance indicators and aim for the bottlenecks.
Figure 4: Retail Store featuring Robot 
Artificial Intelligence is helping in designing daily scheduling store staff, in-store customer traffic, customer preferences to enhance customer satisfaction. Established data streams such as IoT sensors, drones and cameras can help in providing the safe anti-theft system which will further help in diminishing the costly labour. The day is not far when all the work like product receiving, backroom operations, and sales floor operations will be done by the self-learning robots .
Pricing and Promotion
Pricing and promotion of the product are one of the highly impacted areas by artificial intelligence in retail. Because of machine learning, mechanics are validated to see the market trend and thrive at the pace of the competitors. The company always tracks their rivals' price before pricing their own goods. If the demand for the product is high, prices will also be inflated. Using the data analysis software along with AI, the firm sets the real-world retail pricing for the win-win situation .
United Parcel Service
United Parcel Service is a multinational company which delivers package around the globe. It is known as one of the top companies in supply chain management. Apart from package delivery, UPS also has divisions in cargo airline, overnight transportation and retail-based deliveries .
The company has produced a robot name UPS Bot which started its groundwork in just time interval of three months of its thought. This machine can imitate like a customer service representative who can have efficient interaction with customers. The bot uses artificial intelligence and has all information like the nearest outlet, tracing progress and rates for shipping from one location to another. These bots are further combined with "UPS My Choice" where the customers are given the information about when, where and how the UPS service will leave the delivery package without providing them with the tracking number. However, it has been only three months of implementation so the system is being optimised to give more features and reliability to the customers .
Orion (on-road integrated optimization and navigation) is the other artificial intelligence tool that UPS uses. It is used for selecting the best route for the deliveries by which the vehicle has to travel the least to ship maximum orders. This tool is not only limited to this, but it also gathers data regarding accidents and weather conditions by which the driver can change the route at any time if any of these occurs. Moreover, it not only saves the cost but also saves time and reduce the emissions to the environment .
Apart from trucks the UPS also developed drones which have several applications that drive it to success. There are many places like islands, rural areas where it is difficult for a truck driver to reach out for its deliveries. These drones provide vital importance by which it can go to any remote areas and saves a lot of costs. The drones can be launched from the top of the truck which uses artificial intelligence to reach out to the appropriate location. Apart from these this the drones also help in the warehouses where it finds the empty spots located at top shelves, places the items and makes a record of it into the system .
Federal Express is a multinational courier company that delivers packages to customers along with offering freight services and business services. It is the world's largest express transportation company covering 90 percent of the world's gross domestic product .
The FedEx company has developed a personal mobility device called as FedEx bot to deliver packages. FedEx bot is an autonomous robot that can optimize the route and reduce the overall cost. The FedEx bot can deliver packages to customers by traveling on sidewalks and along the roadsides. Also, there is one feature developed in iBot, which includes the safety of pedestrians and zero-emission. This device is operated by a battery and contains multiple cameras obtaining continuous feedback .
All these features are joined with machine learning algorithms to guide a safe path for bot neglecting all the obstacles, following the safety rules. The bot is designed in such a way that it can travel on off-road conditions providing excellent delivery service .
Amazon is a multinational technology company that works in the e-commerce sector, digital streaming, cloud computing, and artificial intelligence. It is considered one of the biggest technology companies around the world .
The company is planning to use automated robots for doing repetitive tasks in the warehouse. The robots are programmed accurately to perform multiple tasks in less amount of time. The tasks of picking the products in the warehouse to delivering it to the accurate place can be performed quickly by robots .
Amazon has made one artificial intelligence-powered robot called blue who has a pair of humanoid arms linked with a central system. The company is working on a technique known as reinforcement learning which teaches a robot to perform tasks more precisely similar to humans. The robotic arm named kinder sort is used, to perform dynamic product picking by using automation. Small robots named as drives are being used in warehouses to deliver large stacks of products .
Figure 5: Robots used in Amazon Warehouse 
Amazon has made a new store named AMAZON GO where no checkout is required.
Customers can shop for the products and leave the store. The bill is sent directly to amazon's account and a receipt too. There are multiple cameras and sensors attached to the whole store monitoring what customers buy and pick from the store. The cameras would be clicking the photos at each stage while picking items from the shelf and while leaving the store. Here artificial intelligence is used in the form of facial recognition, user information, biometrics and even purchase history .
Figure 6: A Snapshot of Amazon Go-Store 
Amazon is planning to use drones for delivering packages to the destination. The drones built can travel up to 15 miles per hour and can delivery parcels under five pounds in less than half an hour. Amazon is planning that 75 to 90% of deliveries can be technically handled by the drone. By using drones, delivery time can be reduced significantly. So, by using drones a lot of money and time can be saved .
Figure 7: Amazon Prime Air Drone 
Walmart is the world's 2nd largest retailer, due to cut thrown competition it has adopted the use of AI (artificial intelligence) to reduce the waste and improve customer satisfaction by improving services. The company Is investing in machine learning, IoT and Big data to grow its business better than its competitors.
Due to growing inventory more than its sales, Walmart had to adapt the use of RFID (radio frequency identification) it solved the inventory cost to some extent.
Walmart launched 16x8 foot self-service kiosks that help the people to retrieve their online ordered items in 45 seconds on the counter placed at the entrance of the store .
Figure 8: Walmart Self Service Kiosks 
Walmart uses face recognition to identify the customer's response towards the services of the store, this could only be possible by its investment in machine learning technology. The technology triggers additional floor associates to help customers with frustrated and or unhappy responses .
The store has an array of sensors, cameras, and processors arranged above the aisle, it is responsible for the detection of the voids on the shelves or display, it also notifies the associate to refill the shelve; by using this technology they can improve the availability of the product as well as product inventory .
Walmart introduced the self-piloting robots which run in all the aisle and scans rows and shelves so that if there are any unavailable items, misplaced items, mispriced items, it can be notified to the managers and necessary steps can be taken to solve them. This technology increases the profit of the store and customer satisfaction .
Figure 9: Self Piloting Robots in Walmart 
6. Results and Conclusion
Considering the challenges faced by supply chain management industries and the impact of AI, Machine learning and Robotics on mitigating these challenges, it can be concluded that the emerging technologies have a positive impact on the industry. The figure 9 below shows the expected benefits for major retail brands in US & Canada from implementing AI and Machine learning in Marketing function. We have also seen how UPS, Walmart, Amazon and Fed Ex have boosted their productivity, increased customer satisfaction, reduced lead times for delivering packages, therefore the benefits are not only limited to marketing but can also be seen in Planning, Operating, Customer service and Logistics. These technologies have improved accuracy in shipping & logistics, scheduling, forecasting and inventory management.
Figure 10: Summary of Expected Benefits in Marketing 
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