MET 305 MOD 5.pptx-ENTERPRISE RESOURCE PLANNING

MET 305-INDUSTRIAL AND SYSTEMS ENGINEERING-MODULE 5
ENTERPRISE RESOURCE PLANNING,ECOMMERCE,E BUSINESS,BI,CRM ETC

1. MET 305 ENTERPRISE RESOURCE PLANNING MODULE 5 VINAY.B NSSCE 1

2. INTRODUCTION In business, "enterprise" most commonly refers to a large, complex organization with multiple departments or branches.  It can also describe any business or project that involves initiative, risk-taking, and creativity, including small businesses and startups. Three decades back-very few challenges-stable environment-less competition. Various Departments Marketing, Materials management, Plant maintenance, Production, Finance, HR etc. Each in isolation-only departmental activities and its goals focused. VINAY.B NSSCE 2

3. ENTERPRISE RESOURCE PLANNING Need for Integrated Systems: The arrival of ERP was driven by the need to replace isolated, department-specific software with a single system that could integrate all business operations seamlessly. Advancement in Information Technology: The rapid growth of computer networks and database technologies in the 1990s enabled the development of ERP systems that could manage large volumes of business data efficiently across organizations. VINAY.B NSSCE 3

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5. Integration of Business Processes: ERP is required to integrate various business functions—like finance, production, sales, and human resources—into a single unified system, ensuring smooth data flow and better coordination across departments. Improved Decision-Making: ERP provides real-time, accurate information that helps managers make informed and timely decisions, improving overall efficiency and productivity. E.g : SAP ERP One of the most widely used ERP systems globally, known for its powerful integration and customization features. Oracle ERP Cloud A cloud-based ERP solution offering advanced analytics and automation. VINAY.B NSSCE 5

6. CORE ERP BUSINESS MODULES VINAY.B NSSCE 6

7. Finance & Accounting: Tracks Accounts Payable/Receivable, ledgers, and balance sheets. Automates billing, cash management, and financial reporting. Procurement: Manages purchasing, vendor lists, and purchase orders. Automates quote requests and updates inventory after goods arrive. Manufacturing: Plans and tracks production processes. Monitors raw materials, goods-in-progress, and output efficiency. Inventory Management: Prevents overstocking or stockouts through data analysis. Tracks stock levels, SKUs, and warehouse locations. VINAY.B NSSCE 7

8. Order Management: Manages orders from receipt to delivery. Ensures timely dispatch and reduces delivery delays. Warehouse Management: Optimizes space, picking, packing, and shipping. Integrates with inventory for faster order fulfillment. Supply Chain Management: Monitors movement of goods from suppliers to customers. Enhances coordination and reduces logistics issues. CRM (Customer Relationship Management): Stores customer data, communication, and purchase history. Improves service, sales tracking, and marketing insights. VINAY.B NSSCE 8

9. Professional Services Automation (PSA): Manages service projects, timesheets, and billing. Enhances collaboration and project tracking. Workforce & HR Management: Tracks attendance, payroll, benefits, and employee records. Supports performance reviews and HR compliance. E-commerce & Marketing Automation: Enables online sales and digital marketing campaigns. Integrates sales data, customer insights, and inventory updates. Marketing Automation: Manages digital campaigns across email, social media, and web. Improves lead generation and customer engagement. VINAY.B NSSCE 9

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11. Common challenges in ERP implementation Personnel and cultural challenges Resistance to change:   Employees may be accustomed to legacy systems and manual processes. Can stem from a fear of the unknown, job insecurity, or simply a reluctance to learn new procedures. Insufficient user training and adoption:  Inadequate or generalized training can lead to poor user adoption and frustration, preventing the organization from realizing the system's full benefits. Lack of executive support:   An ERP project without strong, active support from top management can easily falter due to a lack of resources, prioritization, and organizational alignment. Poor project team selection:   Placing the project in the hands of whoever is available rather than assigning the most skilled and knowledgeable internal resources can lead to poor project management and a lack of process understanding.  VINAY.B NSSCE 11

12. Data and technical challenges Complex data migration:   Moving data from disparate, legacy systems to the new ERP is a complex task. Common issues include inconsistent data formats, data corruption, and duplicate or incomplete entries. Data quality issues:  The principle of "garbage in, garbage out" is critical for ERP systems. Migrating inaccurate or poorly cleansed data can compromise reporting, decision-making, and the overall reliability of the new system. Integration problems:  Integrating the new ERP with existing third-party applications or specialized legacy systems can pose significant challenges due to technical complexities and inconsistent data. Over-customization:   While some customization may be necessary, excessive modifications can add complexity, inflate costs, and complicate future system upgrades .  VINAY.B NSSCE 12

13. Planning and management challenges Inadequate project planning:   Poor planning can lead to unrealistic timelines, underestimated costs, and overlooked dependencies, undermining the entire project. Budget overruns and scope creep:   A common ERP implementation pitfall is expanding the project's scope beyond initial estimates, which significantly increases costs and delays the timeline. Setting unrealistic expectations:   Stakeholders may have overly ambitious views of what the new system can do or how quickly it will deliver a return on investment (ROI). Managing these expectations is crucial. Insufficient testing:   Failing to conduct thorough and realistic testing of the new system before "going live" can result in critical errors, system instability, and costly downtime post-launch VINAY.B NSSCE 13

14. E-Commerce (Electronic Commerce) E-Commerce refers to buying and selling of goods and services over the Internet . It involves online transactions between businesses and consumers or between businesses themselves. Key Activities: Online buying and selling Online payment and billing Order tracking and delivery Online marketing and advertising VINAY.B NSSCE 14

15. Types of E-Commerce : B2B (Business to Business): Example – Manufacturer selling to wholesaler online (e.g., Alibaba). B2C (Business to Consumer): Example – Amazon, Flipkart. C2C (Consumer to Consumer): Example – OLX, eBay. C2B (Consumer to Business): Example – Freelancer selling services to a company. B2G (Business to Government): VINAY.B NSSCE 15

16. ADVANTAGES AND LIMITATIONS ADVANTAGES 24/7 availability Global reach Lower operational cost Quick transactions and delivery Convenience for customers LIMITATIONS Security and privacy issues Dependence on internet connectivity Lack of personal touch Delivery and return challenges VINAY.B NSSCE 16

17. E-Business (Electronic Business) E-Business is a broader concept that includes E-Commerce but also covers all electronic business processes , such as internal management, supply chain, customer relationship management, and business collaborations using digital technologies. Key Components: E –Commerce, E –Procurement, E-SCM, E-CRM, E-Marketing VINAY.B NSSCE 17

18. DIFFERENCES VINAY.B NSSCE 18

19. BUSINESS INTELLIGENCE Business Intelligence (BI) refers to the technologies, processes, and tools that help organizations collect, analyze, and present business information to support better decision-making . Objectives of Business Intelligence Improve decision-making quality Identify business trends and opportunities Support strategic planning Increase operational efficiency Provide data-driven insights VINAY.B NSSCE 19

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22. Types of BI Tools Reporting Tools: Generate reports (e.g., SAP BusinessObjects) Data Visualization Tools: Charts & dashboards (e.g., Tableau, Power BI) OLAP Tools: Analyze data from multiple perspectives Data Mining Tools: Discover hidden patterns and relationships Applications of BI Sales & Marketing: Customer segmentation, trend analysis Finance: Budgeting, forecasting, fraud detection Operations: Supply chain optimization HR: Performance tracking and workforce planning VINAY.B NSSCE 22

23. Challenges in BI Implementation Poor data quality High cost of tools and infrastructure Lack of skilled personnel Integration issues with legacy systems VINAY.B NSSCE 23

24. What is Data Warehousing ? A Data Warehouse is a centralized storage system that collects, integrates, and stores data from multiple sources to support business analysis and decision-making . Characteristics of Data Warehouse Subject-Oriented: Organized around major subjects (sales, customers, etc.) Integrated: Combines data from multiple sources (ERP, CRM, etc.) Time-Variant: Stores historical data for trend analysis Non-Volatile: Data is stable; once entered, it is not changed or deleted VINAY.B NSSCE 24

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26. What is Data Mining? Data Mining is the process of analyzing large datasets to discover hidden patterns, correlations, or useful information using statistical and AI techniques. Techniques of Data Mining Classification: Categorizing data (e.g., credit risk: high/low) Clustering: Grouping similar data (e.g., customer segmentation) Association Rules: Finding relationships (e.g., people who buy bread also buy butter) Regression: Predicting numerical values (e.g., sales forecast) Anomaly Detection: Identifying outliers or frauds VINAY.B NSSCE 26

27. DIFFERENCES VINAY.B NSSCE 27

28. ONLINE ANALYTICAL PROCESSING (OLAP) OLAP stands for Online Analytical Processing . It refers to a software technology that allows users to analyze data from multiple perspectives and perform complex queries quickly and interactively To support business analysis and decision-making To summarize large volumes of data To provide multidimensional views of business information VINAY.B NSSCE 28

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30. Key Features of OLAP Multidimensional Analysis: View data in cubes (e.g., Product × Region × Time) Fast Query Performance: Rapid responses to analytical queries Aggregations: Summarizes data at different levels (e.g., monthly → yearly) Interactive Exploration: Users can drill down or roll up data VINAY.B NSSCE 30

31. How are Online Analytical Processing (OLAP) Cubes Structured? OLAP cubes structure data by aggregating metrics (facts) over dimensions. Dimensions play a crucial role in organizing data, with examples including time, geolocation, and product categories. Star or snowflake schemas are commonly used to model data within OLAP cubes. These schemas provide a blueprint for structuring data hierarchically, ensuring efficient navigation and analysis. VINAY.B NSSCE 31

32. APPLICATIONS VINAY.B NSSCE 32

33. ADVANTAGES OF OLAP Quick, flexible analysis Easy visualization of trends and summaries Supports decision-making Integrates with BI and data mining tools VINAY.B NSSCE 33

34. SUPPLY CHAIN MANAGEMENT (SCM) SCM is the coordination and integration of all activities involved in producing and delivering a product — from raw material suppliers to the final customer. Key Components: Suppliers → Manufacturers → Distributors → Retailers → Customers VINAY.B NSSCE 34

35. Functions: Procurement & production planning Inventory control Logistics & distribution Demand forecasting Benefits: Reduced costs Faster delivery Efficient resource utilization Amazon’s real-time tracking and automated warehouses improve delivery speed and accuracy. VINAY.B NSSCE 35

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37. CUSTOMER RELATIONSHIP MANAGEMENT CUSTOMER RELATIONSHIP MANAGEMENT (CRM) CRM is a business strategy and technology used to manage interactions with customers to improve satisfaction, loyalty, and sales growth. Customer data management Sales & service automation Marketing campaign management Feedback tracking VINAY.B NSSCE 37

38. Types : Operational CRM: Daily sales & service automation Analytical CRM: Customer data analysis Collaborative CRM: Communication among departments Benefits: Better customer retention Personalized marketing Increased profitability Banks using CRM to track customer preferences and offer tailored financial products. VINAY.B NSSCE 38

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