Meghana Sridhar

Thrilled to share my latest blog post on the transformative power of Data Science in Supply Chain Management! 📊🌐 Through my experience at MIT Supply Chain Management Master's Program, I've witnessed the impact of simulation and optimization techniques in building resilient supply chains. Check out the link to learn more about my journey tackling the Traveling Salesman Problem and how these methods can drive real-world results. Always passionate about connecting with others and leveraging my skills to enable digital transformation and drive innovation within organizations. Let's collaborate to build the supply chains of the future! 🤝 #SupplyChain #DataScience #MIT #SCM #DigitalTransformation

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📜 Are you curious about how AI technologies can enhance supply chain efficiency and resilience? Check out this article review on AI in Supply Chain Optimization! The article covers how AI has evolved from basic rule-based systems to advanced machine learning, evolutionary algorithms, and hybrid approaches. 💡 Machine learning techniques like neural networks and decision trees are crucial for demand forecasting and inventory optimization. On the other hand, evolutionary algorithms optimize supply chain design and logistics by exploring large solution spaces and adapting to changing conditions. 📈 Combining multiple AI techniques, hybrid approaches tackle complex optimization challenges by leveraging the strengths of each method, enhancing performance in dynamic supply chain environments. 🧠 Reinforcement learning (RL) offers a flexible framework for dynamic decision-making in uncertain supply chain environments. RL helps adaptation to changes and improves operational efficiency through interactions with their environment. 🚚 The article summarizes that investing in data quality management and fostering collaboration between data scientists and supply chain experts can maximize AI-driven optimization benefits. With the transformative potential of AI in supply chain management, advanced AI techniques are crucial to remain competitive in the global market. Share your story with AI in Supply Chain! What methodologies are you using, and what observations have you made? I am curious and open to collaborate to learn more, do suggest if you have come across any interesting articles and case studies. #machinelearning #supplychain #artificialintelligence #industrialengineering #innovation

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💎 Supplier Quality 💎 💟 Delving into Supply Chain datasets has always fascinated me. I recently revisited an insightful dataset shared by Enterprise DNA focusing on supplier quality. While the challenge has ended, my interest in deriving actionable insights from this dataset remains strong. ❗This dataset offers a limited scope, primarily capturing number of defects and downtime. However, what intrigues me most is not the quantity of data, but rather how we can leverage it to drive meaningful improvements. 🔅Utilizing AI (ChatGPT), I've grouped >250 defect types to 6 defect groups based on material consumption flow: Shipping - Packaging issue - Physical Damage - Incomplete/Insufficient components - Specification (wrong or bad). This approach aids in structuring our analysis effectively. 💡In designing an intuitive dashboard tailored for Procurement professionals: ℹ 1. Purpose and Audience: It's crucial to prioritize what matters most to them - specifically, vendor performance and vendor-material combinations rather than plant performance. ℹ 2. Metrics: 🔸2.1. LESS focus on detailed views of individual defects or downtime and MORE on total supplier performance, which requires a proper scoring logic + Define a score table for defect and downtime from 1 to 10 (step by 1) using percentile 0-1 (step 0.1) at level Date - Vendor - Material + Score for each Date - Vendor - Material + Criteria weights: suppose 50:50 + Score = (Score defect/10)*5 + (Score downtime/10)*5 => Max = 10 🔸2.2. One more aspect that stands out in this dataset is the significant impact of "No Impact" defects, which constitute over 40% of both total defects and downtime. Addressing this anomaly could lead to substantial quality process improvements and supplier enhancements. ℹ 3. Performance benchmark Incorporating historical data comparisons provides valuable insights into year-over-year performance improvements. ℹ 4. Story flow Procurement-centricity - from high-level vendor and material performance summaries to detailed analyses (benchmark comparison, by plant, by timing) aimed at problem-solving. This approach ensures clarity and relevance, guiding users from overarching insights to specific actionable items. ℹ 5. Visualization Applying storytelling principles such as enclosure, alignment, contrast, appropriate chart components, and color usage to declutter and focus attention. Each visual element is meticulously chosen to enhance clarity and highlight key insights. 💟 Glad you've stayed here this far! Challenging myself by practicing and refining my skills through practical applications like this, I'm driven to contribute valuable knowledge to community from each exploration. Here's to continuous learning and making meaningful contributions through data-driven insights! 🔗Link to the Interactive PowerBI dashboard: https://lnkd.in/g5zxpTSb #powerbi #enterprisedna #procurement #sourcing #purchasing #supplychain #vendor #supplier #quality #supplierquality

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📣 Transforming the supply chain with disruptive technology  - A must 🎧 LISTEN podcast 🎥 Some of the highlights from the podcast with Amit Sinha, Senior Manager at Deloitte Consulting 🔌 How does the transformation in a supply chain affect the businesses? 🎯 What are the technologies and capabilities about these? and most importantly, what advice can you offer for the business leader when they wanted to start the transformation? 🔋 Do you recommend any playbook or steps to transform the supply chains to DSN (Digital Supply Network)? 🎙️ Listen to the full episode https://lnkd.in/ehiZZP5S Credit: VCARE Academy and BICARA Supply Chain, The Podcast #supplychain #logistics #leadership #certification #sustainability #futureofbusiness #SupplyChainInnovation #FutureofLogistics #manufacturing #supplychain #ai #blockchain #machinelearning #robotics #sales #forecasting #supplychain #logistics #manufacturing #production #inventorycontrol #warehousing #sustainability #circulareconomy #demandplanning #ddmrp #salesandoperationsplanning

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Here’s an insightful post by Victor Lee on leveraging knowledge graphs for digital twin modeling for supply chains. #knowledgegraph #digitaltwin #supplychain

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🔍 Article Review: Understanding 'How Machine Learning Will Transform Supply Chain Management' Source: https://lnkd.in/gayT4DJU ✔ The article introduces a novel approach called Optimal Machine Learning (OML) that leverages machine learning to transform supply chain planning and decision-making. ✔ Traditional supply chain planning methods rely heavily on demand forecasting, which often suffers from inaccuracies and misalignment among stakeholders. OML addresses these shortcomings by directly linking historical data on supply and demand drivers to supply chain decisions, bypassing the need for explicit forecasting. ✔ The core of OML is a decision-support engine that uses machine learning to build a mathematical model connecting data inputs to planning decisions. This model optimizes key performance indicators (KPIs) such as profits, revenue, product availability, and inventory turns while considering business constraints and priorities. ✔ Second critical component, and the most exciting aspect of OML is a digital twin, a detailed digital representation of the entire supply chain network. This virtual model enables accurate performance measurement, scenario testing, and evaluation of risk mitigation strategies, enhancing supply chain agility and resilience. ✔ The article highlights the successful implementation of OML at two Fortune 500 companies, demonstrating its ability to increase revenue, product availability, and customer service levels while reducing inventory investments. ✔ OML requires an end-to-end data architecture that integrates data from various sources, including suppliers, customers, and internal functions (e.g., marketing, finance, logistics). This data-driven approach, combined with cross-functional collaboration and redesigned planning processes, enables faster and more responsive supply chain decision-making. ✔ Overall, the article positions machine learning, particularly the OML methodology, as a transformative technology for supply chain management, addressing long-standing challenges in demand forecasting, stakeholder alignment, and risk mitigation. By leveraging historical data and optimizing decisions directly, OML offers a promising path toward building agile, resilient, and high-performing supply chains. 🤓 I am eager to witness the development of novel methodologies like optimal machine learning and new challenges they pose in a critical domain like Supply Chain Industry. #HBR #SCM #AI #ML #OML

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Constrained Supply Chain? A #constrainedsupplychain means companies operate with limited resources and functionality. Businesses don’t have sufficient materials to meet current demand, which results in stock-outs, lost #profits, dissatisfied consumers, and other detrimental effects. When #demand outweighs #supply, all stages of the #supplychain suffer. Companies need to fulfill orders and meet #consumerdemands to stay #profitable. Without the necessary materials, processing orders or maintaining healthy #productcycles becomes impossible. Anything from staff shortages to floods can restrict supply chain operations. These restrictions can cause #production delays, poor #cashflows, #transportationdisruptions, and other adverse outcomes. Managers are pressured to meet the same deadlines and #demands, but their limited #resources make it more challenging to achieve typical business goals. What Causes a Constrained Supply Chain? 1.Rising costs: #Inflation has adverse effects worldwide. As prices increase, it becomes harder for companies to access the resources and services they need for operation. To keep up with rising costs, companies could cut back on resources but still try to operate at full efficiency. This approach can lead to missed production deadlines and employees feeling burnt out.  2.Tight job #markets: When the number of jobs available is higher than the number of people looking for work, it causes severe constraints on #supplychainproductivity. Businesses have more difficulty meeting typical consumer demands if they have staff shortages.  3.Travel restrictions: International travel restrictions prevent shipments from arriving on time. They can also limit international workers from filling vacant positions. 4.Material shortages: If demand rises for specific products, obtaining the necessary materials for their production can become challenging. Raw materials could increase in #price, limiting business #finances even further. Without enough raw materials, it becomes difficult to produce items at a consistent pace. Examples of Supply Chain Constraints 1. Production Constraints a. Machine operations b. Staffing levels  c. Employee performance d. Workflow efficiency 2. Distribution Constraints a. Weather conditions b. Transport limitations 3. Storage Constraints a. High #costs b. Facility capacities 4. #FinancialConstraints a. Demand changes b. Cash flows c. General #expenses How Can Supply Chain Managers Navigate Constrained Supply Chains? 1. Identify #OperationalBottlenecks a. #Inventorylevels b. Facility locations c. Products or parts made d. Level of part importance for your #operations e. Typical operational times or capacities f. Average distribution times 2. Use #DemandForecasting 3. Upgrade Your Technology #valuechain #sap #mrp #erp #supplychainmanagement #supplychainoptimization

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“So… what’s the plan? MBA or Job” is what everyone is asking graduates again And let’s be honest… we’ve all wondered if it was. If we talk in numbers, average monthly job openings with MBAs have dropped by 55% in 2023 versus just a year back. Whereas over 230,000 MBAs are joining the job sector every year. Today if you talk to any founder, they will say “We need X skills. You’ve got it? Let’s work together!” And if you talk to an MBA graduate: “I want to be paid Y amount at least” But where are these jobs? The cost of an average MBA degree ranges from 15 to 40 lakh rupees. After investing so much, students aspire to earn a certain amount which unfortunately companies aren’t ready to pay today. While some people agree that 😣Companies are hiring less 😣The investment is a lot more 😣Gives you lots of sleepless nights 😣Someone with skills is preferred You can’t deny that an MBA (only from extremely reputed colleges) 👏Provides you with a network 👏Compels you to manage your time well 👏Helps you think outside the box I would not tell you to just choose now… But take into consideration your goals, priorities, and what do you want your future to look like. MBA may not be the right decision for a lot of people but it will still be a great choice for some. Think about yourself What do you think about MBA? Would you have done it? #mba #job

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I just got notified that my article about AI that was published last year in Journal of Supply Chain Management is one of the most cited papers in JSCM last year. Super proud of this! However, it's almost a year old, and right now in AI research, that basically makes it ancient knowledge. Some thoughts: - I highlighted that AI can take a more assistive or more autonomous role across supply chains. Many professionals are exploring the assistive role of chatbots, and many of the leading AI developers are working on autonomous AI agents. It's interesting to follow along how fast autonous AI systems will be integrated throughout supply chains. - I suggested that AI will disrupt theory, for instance because the technology will change the notion of agents in a supply chain. We are not there yet, but it is great to follow the contributions in the field by people such as Samuel Fosso Wamba, PhD-HDR and Maciel M. Queiroz. - I suggested a more integrative perspective whereby researchers consider both the operational impact of AI as well as the way employees and managers make sense of the technology. We are only now seeing in-depth empirical work concerning post-ChatGPT (or, really, post-GPT-4) adoption of AI, and I'm pretty excited to conduct some of this research myself and follow others who are doing so, too. If anyone are coming to EurOMA this summer in Barcelona, feel free to drop by my presentation about my current research on how employees adopt Generative AI in their everyday operations. Thanks to Wendy Tate and Tingting Yan for their help and expertise getting this piece out! Link to the article (open access) can be found here: https://lnkd.in/dTiqy5KN

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Operations & Supply Chain Management in the News: June 2024 Welcome to "Operations and Supply Chain Management in the News," a monthly LinkedIn series that delves into the latest trends, innovations, and insights shaping the future of Operations and supply chain management. In 2024, the landscape of operations and supply chain management is witnessing transformative trends driven by technological advancements and evolving business needs. Here are some key highlights: Digital Supply Chain Integration: The ongoing digital transformation in supply chain management is not just a trend, but a beacon of hope. By integrating big data, analytics, and artificial intelligence (AI), companies are not only improving efficiency and resilience but also driving significant cost savings and improved customer satisfaction. This shift is empowering businesses with enhanced visibility, predictability, and decision-making capabilities across their supply chains, promising a brighter future for supply chain management​. Transparency and Visibility Beyond Tier 1: The need to extend connectivity and visibility across the entire supply chain, beyond the first-tier suppliers, is not just a suggestion but a necessity. This is crucial for mitigating risks and meeting regulatory requirements. Technologies such as control towers and digital twins are being employed to achieve deeper insights into the supply chain ecosystem. Adoption of Low-Code Platforms: Many organizations are adopting low-code platforms to address the complexities and dynamic nature of supply chains. These platforms enable rapid development and deployment of applications with minimal coding, allowing businesses to adapt quickly to market changes and disruptions. This approach reduces development time and empowers business users to create and implement new capabilities without extensive technical knowledge​ Focus on Scope 3 Emissions: Environmental sustainability is not just a buzzword but a growing priority. There is a significant emphasis on tracking and reducing Scope 3 emissions, including all indirect emissions in the value chain. Companies are investing and committing to digital platforms to collect and report supplier emissions data. The aim is to establish a comprehensive emissions baseline and set ambitious reduction targets. Enhanced Supply Chain Resilience: The ongoing global disruptions have highlighted the need for more resilient supply chains. Companies are focusing on building agility and resilience in their operations through advanced risk management strategies and by investing in technologies that enable real-time visibility and rapid response to disruptions. This includes shifting towards more localized and circular supply chains to reduce dependencies and enhance sustainability.​ Stay tuned for updates on the latest operations and supply chain management developments. Sources: KPMG: Supply Chain Trends 2024 ASCM: Top 10 Trends Report 2024

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Key attributes of a “chain” in supply chain concept: ·     A chain cannot exceed the capacity of the weakest link ·     A break in the chain makes the chain non-functional ·     All links must move in synchronization ·     All links have an interdependency These are actual attributes and characteristics of a "chain" within a supply chain or supply network however, it can also be perceived from the perspective of a team/group that are collaborating for one goal and purpose. They must all rely on each other for strength and agility. Harmoniously leveraging on each other's expertise, divers cultural experiences and network, to achieve their expected goal. Let me know what you think! #logistics #supplychain #teamwork #collaboration #networking

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We had some nice discussions on the supply chain analytics job market at our recent SCAI conference. Professor Yao Zhao and his student developed this short survey https://lnkd.in/enSWNcux for collecting your inputs. Your participation is great appreciated. Survey results will be shared with you after sufficient data are collected. #SCM #Supplychain #analytics #jobmarket

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Optimizing Supply Chain with Push-Pull Boundary: Insights from Sunil Chopra In supply chain management, the push-pull boundary is crucial for balancing efficiency and responsiveness. As highlighted by Sunil Chopra, this boundary marks the shift from push processes, driven by forecasts, to pull processes, driven by actual demand. Positioning the push-pull boundary strategically helps manage inventory, reduce costs, and enhance customer satisfaction. Factors like product characteristics, market demand, and supply chain capabilities influence this positioning. For instance, products with stable demand suit push strategies, while fluctuating markets may benefit from pull strategies. Chopra suggests hybrid approaches, postponement, effective inventory management, and technology integration to optimize the boundary. For example, Dell's hybrid strategy pushes components to assembly plants based on forecasts and pulls final assembly by customer orders, enabling mass customization and efficiency. Understanding and applying the push-pull boundary concept helps companies adapt to dynamic markets, ensuring operational excellence and customer satisfaction. PC : https://lnkd.in/dNqk3M7N #SupplyChainManagement #Logistics #Efficiency #CustomerSatisfaction #BusinessStrategy #InventoryManagement #LeanManufacturing #SunilChopra #Operations #SupplyChainOptimization

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Are you in supply chain, or procurement, looking to update 🚀 or upgrade 🛠️ your financial skills? Check out this workshop delivered by my esteemed colleague 🤓, Robert Greene! #supplychainfinance #niscl

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Back in 2018, I had two opportunities at hand, 1. An admission for MBA in one of the world's best institutions in India 2. An admission for a pre-master program with a conditional admit for master in Data Science in Netherlands. While most people advised me to go for an MBA as it was a more practical choice, I listened to my heart and took the second option. I choose curiosity over practicality, job risk over job security, foreign country over homeland. It was not an easy decision, but it definitely felt right and exciting at that time. In the past 6 years, there were many circumstances when I wondered if I made a poor decision, if I would've benefitted more with an MBA and imagined all kinds of alternate scenarios. But after every introspection, I always ended up with same conclusion of making the RIGHT CHOICE FOR ME in the given circumstances and that always made me feel confident and content. To all those struggling to decide between opportunities, my advice is to decide what feels best for you in your given circumstances and whenever in self-doubt, remember to focus on the positives of the chosen decision and imagine the worst case scenarios of the ignored option. This gives a sense of affirmation and motivates you to get best out of your already made decision. Hope this helps! 😇

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In supply chain management, both forecasting and backlog management are crucial but serve distinct purposes. The COVID-19 pandemic disrupted global supply chains, leading to a significant semiconductor shortage, impacting automakers like Ford and GM. I would like to explain both in a very crisp way. A. Importance of Forecasting: 1. Demand Planning: Accurate forecasting could have helped automakers predict the surge in post-pandemic car demand. 2. Inventory Management: Apple used advanced forecasting to secure semiconductor supplies and maintain optimal inventory levels. 3. Resource Allocation: Nvidia's accurate forecasts ensured aligned production capacities, minimizing delays. 4. Supplier Coordination: Samsung's strong forecasting facilitated timely supplier communication. 5. Strategic Planning: Forecasting helped companies plan capacity expansion and explore alternative sources. 6. Customer Satisfaction: Tesla adjusted production plans to minimize delays and maintain customer satisfaction. B. Importance of Backlog Management: 1. Order Fulfillment: Toyota prioritized production schedules to fulfill orders timely. 2. Production Scheduling: Efficient backlog management helped companies prioritize critical demands. 3. Revenue Realization: Ford managed its backlog to optimize cash flow by delivering high-demand models first. 4. Capacity Management: Intel managed production capacity effectively by understanding backlog levels. 5. Performance Metrics: Monitoring backlog tracked lead times and improved efficiency. 6. Customer Communication: Clear backlog management allowed effective communication about order status. So, which one is More Important? For proactive planning and long-term strategic decisions, forecasting is more critical. It enables businesses to anticipate market trends, plan resource allocation, and ensure readiness for future demand. Whereas for immediate operational efficiency and customer satisfaction, backlog management takes precedence. It ensures that current customer orders are fulfilled promptly and efficiently, directly impacting revenue and customer relations. #SupplyChainManagement #Forecasting #BacklogManagement #SemiconductorShortage #BusinessStrategy #OperationalExcellence #CustomerSatisfaction #InventoryOptimization #StrategicPlanning #SupplyChainSolutions

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"Never chase the hot thing." This is a famous piece of advice from Jeff Bezos. What did he mean by the "hot thing"? Well, hot things are the latest trends that are popular in the short term, but may not have a lasting value. Dot com bubble was a hot thing. Companies jumped on the train without a valid and sustainable business model. Okay, in the hindsight, we are all experts. How do we know if AI is not the next bubble? It's not, because it is already having a profound impact on the businesses and societies and will continue doing so. Investing in AI infrastructure, models and services will give a huge competitive advantage to those firms in the long-term. Right now many companies are trying to copy each other with different features built on GenAI models. A significant portion of those features will disappear sooner or later. Now, this is chasing the hot thing - getting obsessed with features that won't bring long-term benefits. Chasing short-term trends can lead to wasted resources and missed opportunities for more sustainable growth. Smarter companies invest in long-term value, even if it’s not the hottest trend at the moment. ♻️ Please feel free to share this post if you find it useful. ⬇️ Also, let me know what you think in the comments. 🤗 #AI #genai #business #bubble #Amazon #jeffbezos

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My Uber driver was a business analyst. What are the odds?? 👀 On my way to pick up my glasses, I was speaking with a mentee who has an interview in the next few days, explaining how when an interviewer says “walk me through your resume” they mean tell me what I cannot pick up from reading your resume. Of course I added that as a BA, one of your core competencies is being able to manage stakeholders in workshops, keeping them engaged through that 30 or so minutes session. So that skill needs to come though during the interview. After the call, he said to me what do you do?? And we had a lovely chat about how he has to chose his family first because as a BA, he just did not have the time to focus on his young family. He has over 25 years experience as a BA and even though from time to time he picks up contracts (never during the schools hols), he is extremely happy with where he is at! We learn all these analysis tools as #businessanalysts and sometimes, we forget to take a look at what matters. I am extremely happy for him. #businessanalyst #businessdevelopmentanalyst #businessdevelopment

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2024 Gartner Top SCM Graduate School Rankings, pg. 4: https://lnkd.in/gMQAx4U9. Another rather random ranking, Top 10 SCM Schools (MIT is on this one): https://lnkd.in/ettmB534. Yes, tough to argue with these lists, just pay attention to ROI. Should You Give Up Your Salary and Go to Grad School? Well, that darn MBA degree still has a great ROI...“Over their lifetime, an MBA grad can expect to earn $3M more than someone w/ only a bachelor’s.” Great ROI!?...At about 98% of universities that offer MBAs, grads typically made more money 2 years out of school than they had borrowed. That stands in contrast to law schools, where roughly 6% of programs had grads w/ higher median earnings than debt in the same time frame. Note, the MBA route requires careful thought. See: https://lnkd.in/gGAx4QyK. Five reasons why CEOs need to drive supply chain excellence from the top: “Some of the world’s leading CEOs today emerged from supply chain roles. Many have carried over their relentless focus on supply chain excellence into their leadership approach, proving to be invaluable in recent times….A deep understanding of supply chain issues is now a critical skill set for any C-suite leader.” https://lnkd.in/gVXyzaEn. I had a student ask: Shouldn’t I major in Finance or Accounting if I want to become a CEO? I said: Well, being able to talk CFO talk is critical to long term success, but you might want to give this supply chain thing some thought… https://lnkd.in/ganuUD6r Note, (I encourage my SCM students to get an Accounting minor): College Accounting to me feels like Supply Chain Finance. The Accounting Minor for SCM Majors seems like a great fit & has grown on me. Long term in your careers, understanding SCM Finance will be critical…https://lnkd.in/gBPZJsVq. https://lnkd.in/guejd-vi. Two classes in our Accounting minor, good fit for SCM types, right?: 3220: Cost & Managerial Accounting and ACTY 4220: Cost Mgmt & Analytics. FYI, we make EVERY business major take FIN 3200 - Business Finance Decisions. More: https://lnkd.in/gtUMdsiT.

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