 Hello everyone, welcome to this course on supply chain digitization. This course is offered by IIM Mumbai and three of us including myself, Professor Priyanka Varma Professor Sushmita Narayana and Professor Deba Pratadas are going to teach this particular course. We have covered first week where we have discussed on the fundamentals of supply chain and going forward we will be talking about supply chain segmentation in the second week. This is going to be the first session on supply chain segmentation, but before going into the details of supply chain segmentation it is very important that we understand the different challenges with which the supply chain gets affected and that will help us understanding the need of segmentation in supply chain. The first and foremost challenge of supply chain which anybody will agree to this is on demand forecasting which you can see that it is a very difficult part reason being it is very difficult to understand the requirement of the customer and to accurately predict it properly. So we can see that because of the inaccurate forecasting it will always lead to the over stocking of the product or the stock outs that can that the supply chain can face. So this is one of the critical challenge which any supply chain faces on a day to day basis. Let us see this challenge with a very simple example. If you have a clothing retailer which is trying to over stock on winter clothing maybe because of some inaccurate forecast it will definitely lead that retailer to carry unnecessary stock of the winter clothing and this will again leads to excess inventory which the retailer has to carry. This will get translated into the extra inventory cost and this which will further reduce the profit margins for the particular retailer. So what can be done in this case and how does digitization can help us in ensuring that the forecasting is more accurate and this information can help the different supply chain players in managing their inventory and other decisions in a better way. For this purpose nowadays there are so many digital tools which are being used like your RFID and similar tools which can be used for real time data collection and if we can integrate them with the advanced analytics our purpose of analyzing this will be more useful and it can also help in forecasting in a better way. So what can be done in this case if we have enough data about the given product the historical data can be analyzed in a better way and this can be used for understanding the different market trends which the product or the company or the business is facing and sometimes some other relevant factors are also covered which will help in again forecasting or decisions in a better way. Followed by this we have machine learning algorithms which gets covered under predictive analytics and there are different type of algorithms available in predictive analytics which can be used very nicely for accurately forecasting the demand and once you have a accurate way of forecasting your demand it can be translated easily in improving your levels of inventory that you are trying to carry. So we can see over here that all the decisions are interlinked we started with the demand forecasting and we can see that carrying excess demand will lead to overstocking and carrying less number less quantity of inventory will lead to stock up. So these are the two extreme conditions which the supply chain always faces and one of the very interesting way for solving this problem is by using digitization and different type of data analytics and using this accurate way of demand forecast can be achieved. The second challenge which is again related with the demand forecasting is the inventory management. So in inventory management the business always try to have a match between inventory and the demand. So as soon as the demand is raised the customer always expect to get that demand fulfilled if this is the requirement it is important that the inventory is that the sufficient inventory is available with you so that you are able to fulfill that demand. So it is important that the inventory is closely following the demand so that there is no option of stock out in this case. So but we know that if we carry extra quantity of product this is going to increase our holding cost and that is becoming a challenge in this case. So here the focus is all about how can you minimize your holding cost and because of the complexity involved in this decisions we can see that this is again a critical supply chain challenge to be managed. To understand this particular challenge let us see one simple example over here. Suppose we have a consumer electronics company which is actually quite popular and its product is quite accepted by the customer and that is why it is always expected from the customer end that the product will always remain available whenever the demand is there. Though there was a good demand of the product but the demand was not estimated accurately and resulted into the stock out of this popular product. Now imagine a case where a product which is quite famous but which is quite in demand but it is not available to the customers when they need it. Obviously this will lead to the other competitors to launch similar products and this can lead to lot of losses to the given product. So how this can be taken care? There is another possibility that there is a less popular product and the company or the businesses are carrying excess inventory of this particular less popular product and you can see that because of its less popularity the product remains unsold. So this is again another type of problem which the companies can face. So these are two again extreme cases a popular product which has got high demand but the product is not available because the demand was not predicted accurately and similarly less popular product but carrying excess stock which was not required and unnecessary your inventory carrying cost is getting is increasing. So what is the solution for this and we know that in today's time this is again quite complex we do not we want to see that products are being the inventory is being available but parallelly you also do not want to carry excess inventory so that you always want to minimize your cost of the associated product. So the solution for this particular challenge in digitization and in data analytics is installing of some inventory tracking system some digital inventory tracking system maybe some IOT devices internet of things and RFID technology we will be talking about these technologies in more detail in our last module but these are right now we are just talking about these technologies that how these technologies are available in today's time for ensuring these challenges related to inventory management to be taken care. So these technologies has got a huge benefit and they ensure that there is a real time visibility of the levels of these different inventory of the products and the user department is able to track the inventory levels and can accordingly decide about their ordering decisions about the holding decisions and transportation decisions and many other related decisions in this case. The role of data analytics in inventory management is again very critical it can be used for optimizing the stock levels means how much stock you should carry so that you have to incur minimum carrying cost it also helps in understanding which are the slow moving items and then again the slow moving items can be accordingly managed in the inventory management process. Parallel if there are certain items which are which are having a requirement of just in time as a part of the processes then this again can be highlighted this can be flagged and accordingly the just in time inventory practices can be adopted for that particular group of products. The next type of supply chain challenges which is again heavily dependent upon one of your partner that is your supplier. So any supply chain we have seen so far is typically is dependent on their partners what role they are playing and how much they are sharing their responsibilities in between them. So here the supplier again is a very very important player in any supply chain and it is important that we see that the relationship with the suppliers are properly managed. If there is a supply chain where the dependency is very high on certain limited number of suppliers this is a case of alarm and obviously any time any supplier is not able to perform due to any internal or external challenges it can lead to severe disruptions in the supply chain. So we have seen this case in recent times as well. So let us try to understand this challenge again with a simple example over here. We have referred to the automobile supply chain in our previous session and imagine there is an automotive manufacturer which is actually experiencing the production delays and it was explored that what is the reason that why this delay is happening. Then it was observed that there is one prominent supplier which is unable to meet the quality standards. So maybe the requirement is not fulfilled by this given supplier and because of this the whole process is getting delayed. So we can see that because of this the complete process is not able to operate and this has resulted into a temporary halt in the whole manufacturing process. So we can see that how critical it is to manage your supplier and any time even one supplier is not able to fulfill his responsibilities or requirements for any reason will affect the whole supply chain. So it is important that we should always have alternative suppliers to see that the disruptions are taken care in any supply chain. Apart from it what are these digitization and data analytics solution for this particular challenge. In this case the companies or the businesses can opt for some digital platforms and which can be integrated with the suppliers and their performance can be easily tracked through these digital platforms. There are many businesses in today's time who are working on these type of digital platforms. Talking about the data analytics it can be very efficiently used for assessing the supplier performance for tracking the lead time for evaluating the risk factors and so on. So we can see that the whole procurement process can be digitized by using this digital solution that has been introduced so far and once we have the proper data analytics in system we can identify the potential issues and using this data analytics some informed level of decisions can be taken very nicely. Let us talk about the next very important challenge which is again on transportation and logistics delays. We have discussed about the process of transportation but the very important or critical challenge with transportation and logistics is the delays associated with them with them. Sometimes there are challenges related to the capacities that in a not enough capacity is available. Parallely we know that in today's time the transportation costs are rising like anything and all of these are going to impact the efficiency of the supply chain. So these are the challenges which we can see related which are related to transportation and logistics. Let us see with the help of this one simple example. Suppose we have a shipping company which is trying to make the delivery to the production facility but unfortunately it is facing delays in making this delivery and when analysis is done for the reason behind that it was observed that there is a strike going on in the port and this strike because of this strike there is a delay in the delivery and because of this the whole manufacturing schedule has got affected. So we can see that how simple change into your transportation and logistics has resulted into the delays or has affected the schedule of your manufacturing processes. So what can be done in this case? Here we can use the digitalization and data analytics once again and see that how these transportation and logistics can be made more efficient. So we have digitizing logistics operations as one of the solution where we can implement systems like GPS tracking which can be useful for real time monitoring and also it will ensure that large amount of data is available. This data can be again used for planning your routing and optimization of these routes can be done which will be helpful in streamlining the whole process. So data analytics is again very useful over here and it can optimize the routes. It can predict the maintenance needs of the different vehicles and it also helps in providing insights to the enhanced overall logistics efficiency. The next challenge is about technology integration. Here we have we now so far we have discussed about so many technologies but it is important that how these technologies can be integrated so that we can get a benefit of this particular advancement in the technologies in supply chain as well. So here the major challenge is about integrating and optimizing the technologies like IoT that is Internet of Things, AI, Artificial Intelligence and Blockchain. So integrating these different type of technologies and to take the benefits out of it is again quite challenging in the supply chain domain. Suppose there is a company which is struggling to implement IoT based tracking system. Now what type of challenge it is facing? It is actually it observed that there is a compatibility issue of these technologies with the existing software, maybe the software has got upgraded. This is going to hinder the seamless flow of real-time data across the supply chain. As we know that now supply chain is all is not only about moving products from one location to another but it is also about moving information from one place to another. So if we do not have sufficiently well software systems the flow of the real-time data will get affected and that is what is coming as a big challenge in the technology integration part. Then we have the digitalization solution is again provided in form of digital platforms which can provide you the opportunity of integrating these technologies. The data analytics again plays a very important role over here as well as it can be used for analyzing the data, the large amount of data available using these technologies and using this the actionable insights can be developed which can be further implemented and ensure that they are helpful in improving the supply chain performance. The next challenge is about regulatory compliance. This is again a very recent challenge and a very critical challenge to be managed by different businesses. So here there are regulations which are required to be taken care and because of the complex supply chain processes these regulatory compliance are required to be followed. Suppose we have a pharmaceutical company which is actually facing challenges about its labeling regulations. So there is a new labeling regulation and it is expected from the pharmaceutical company that it is able to comply with this new labeling regulation. If this is not done as per the requirement it is going to affect your product shipments that is it will get delayed and it will also lead to the possible find which the business has to pay. So these are we can say that there are certain regulatory compliance with the company are required to follow. So how this can be again taken care through digitalization and data analytics. Again there are certain digital platforms which will try to automate the monitoring of all the compliances and depending upon the requirement the compliances can be taken care. There can be this can be integrating the relevant regulations into the supply chain processes. So again we can see that how the supply chain processes are developed and observed. So that these regulations are followed in all the processes. Talking about the data analytics the organizations can take the benefit of data analytics by continuously monitoring and analyzing the relevant data points which are very critical for your regulatory compliance. So this can be closely monitored and any deviation on these particular data parameters can be given as a alert to the system and the system can accordingly be prepared to take the actionable item on it. The next type of supply chain challenges is about sustainability and environmental concerns. As we all know in today's time that it is important that the companies also follow their sustainability course and it is the careful monitoring of these processes are very important. Because to understand this with example there is a food and beverage company and they unfortunately they are facing resistance from the environmental groups because of the excessive packaging which they are following and this is leading to the reputational damage and also the potential regulatory scrutiny. So in this case we let us see that how we can help through digitalization and data analytics. So again here they can be some digital platforms and IoT sensors and the focus can be on some key sustainability indicators like carbon emission, energy consumption and waste reduction. The data analytics again can look after the environmental impact and see that how they are going to implement the strategy to meet your sustainability target. So we can see that sustainability is again a very important requirement of the supply chain but meeting these sustainability goals is again an interesting supply chain challenge in today's time. The next and very new challenge which has appeared in recent time is all about cybersecurity threats. As we have seen that data is getting captured from different points in a given supply chain it is important that we should know about cybersecurity as well because of so much data flowing around us. We know that some of this data is quite sensitive you cannot share your bank account details and so on. So protecting these type of sensitive data is a very important and particularly from the cyber threats and that is why this is one of the critical challenge of the problem. So there is one example on this. We have data breach in a retailer's online platform and because of this breach the customer information has got exposed. Once the customer is knowing this information obviously it will lead to the loss of the customer trust, financial losses and it will be followed with the potential legal consequences. So that is why cybersecurity is again it is a recent challenge but again a very critical challenge in today's time when we are doing most of the things using digital solutions only. How this can be taken care through digitalization and data analytics? So if we can implement some robust cyber security measures these processes can be taken care in much control. In terms of data analytics again the continuous monitoring can be done on critical parameters and anything which is deviating from their routine processes can be alarmed. In terms of the analytics again the anomalies in the network activity can be predicted and some possible machine learning algorithms can be used in this case as well. Talking about the last challenge in supply chain in today's scenario this is about how do you manage your talent shortages and the skills gap. So finding and retaining the skilled personnel in supply chain management is one of the most critical challenge with respect to your skills available. So there is a logistic company which is trying to struggle to hire and retain the experience supply chain analytics but this is going to impact the organization's ability to optimize the operations and respond to market changes effectively. So we can see that how this skills is going to play a key role in managing your supply chain, your complex supply chain. So what is the solution provided by digitization? Digitization can help you in automating your routine tasks very efficiently. So you can save a lot amount of time in this case. Similarly if this supply chain professionals are able to free get are able to get some time free for themselves then they can use this time for focusing on some strategic decision making. In terms of the data analytics it can be used for identifying the skill gaps in workforce enabling the organizations to invest in the targeted training programs and so on. So we can see that this is again a new and recent challenge in any of the supply chain. Not all of them were quite interesting and different from each other. Some of them are known to us beforehand but some of it coming as the new challenges because of the introduction of the digitization and data analytics in our today's time. So we have seen that what are the existing supply chain challenges but in order to handle these challenges what are the solutions for that. So one of the solution through which the supply chain can be managed is segmenting your supply chains and that is what the second module is going to be focused on the supply chain segmentation. We will try to understand the different ways of segmenting your supply chains and then again how the segmentation will help us in ensuring that these challenges are properly managed and we are going to discuss on the supply chain segmentation in our upcoming sessions. So with this we will close this particular session and thank you for listening it patiently. Thank you everyone.