Big Data Analytics and its Impact on Supply Chain Management

Transcription

1 Big Data Analytics and its Impact on Supply Chain Management Dr. Mahesh Ramamani Management Consultant, Business Analytics & Strategy IBM India July 2015, CII Conference on Redefining Supply Chain in the light of Indirect Taxes and GST 2015 IBM Corporation 1

2 Evolution of New Era Supply Chain Enterprise efficiencies Streamlined Global processes Information sharing New Era Supply Chain Reinvention Smarter Supply Chain Globally Integrated Enterprise Advanced Analytics, Optimization, Big Data Mgt Supply Chain Visibility Multi-enterprise supply chain transformation Cloud, Mobile, Social Supply Chain Transparency Predictive, prescriptive analytics Agile / Resilient Data Driven / Digitally Executed Evolving Supply Chain Management from cost center to value center 2015 IBM Corporation 2

3 Business being re-defined by three shifts Data is becoming the world s new natural resource, transforming industries and professions. The emergence of cloud is transforming IT and business processes into digital services. Mobile and social are transforming individual engagement creating expectations of value in return for personal information. Data is the new basis Cloud is the path to of competitive advantage new business models Engagement requires 2015 IBM Corporation a systematic approach 3

4 What data are we talking about? Data is becoming the world s new natural resource, transforming industries and professions. Data Exhaust from: RFID, POS data, Geo location of inventory Social media feeds, customer complaints, call center logs returns logs warranty issues Data is the new basis of competitive advantage 2015 IBM Corporation 4

5 The changing IT landscape and creating new market dynamics Cloud Apps that aggregate Demand Data Call Center Logs, Transcriptions, Customer Complaints Mobile Engagement Sensors from Manufacturing Systems Social Engagement Analytics 80% of data growth is unstructured Social Media Feeds 2015 IBM Corporation RFID data from Warehouses 5

6 How does Big Data and Analytics Impact SCM fundamentally? Traditional Analytics approach Bull whip effect mitigation Forecasting demand Production Planning Efficient Routing Changing Paradigm with Big Data Analytics Not just Bull whip mitigation, demand visibility capitalization Sensing demand and capitalizing on the same Production planning to stock and to demand Dynamic Routing

7 Adaptive Inventory with RFID Enable tracking of real-time inventory of any item in any location: Automated replenishment signals integrating with SCM workflow. Automated receiving and verification of items and quantities received at stores and warehouse, Automated validation of fulfilled orders.

8 Predicting Inventory with Geo Location Real-time visibility of in-transit inventory and would allow sensing real-time demand signals to make this inventory productive. Real-time location sensing for better supply-demand match, and reduce the fulfillment lead-time and inventory levels required without affecting service the customers. Combining the RFID for cold-chain perishable goods and real-time GPS location, improve efficiencies to reduce the goods damaged due to temperature variations and expiration dates.

9 Integrating POS Data with Supply Chain Use POS data to provide a real-time demand signal with price information. This will help in intelligent inventory deployments to optimize the inventory in the system. Use early trends detected for seasonal goods can help better manage the open orders when demand goes up and reduce potential clearance losses when it goes down. Price optimization that can be fine-tuned with real-time POS data to optimize the profitability.

10 Optimize SCM with Social media inputs Use Big Data from unstructured data sources like call center logs, customer complaints, warranty returns, Twitter, Face Book to glean for Customer service related discussions, statuses etc. Create context out of it and find the pattern of the discussion, get the gist of it, get the sentiment, get the prevalent complaint on a product line make a decision if intervention has to be made, notify to relevant link in the Supply chain workflow.

11 How do I succeed with Big Data Initiatives in my firm? Project deployment & readiness to change Iterative approach Incentive alignment Start with a business pain point As critical as the math and analytics expertise are, transformation leadership and execution/operations expertise is even more important (3-in-the-box management system) It is OK to start small and build towards major impact Incorporate cycles of learning into the analytics solution Design Compelling business benefits for each supply chain participant (win/win/win) Reflect benefits in business partner terms and conditions Have a visualization and user interface strategy Iterative approach allows you to improve your capabilities along the way and build progressively stronger stakeholder support Encourage utilization with personal performance metrics 2015 IBM Corporation 11

12 For more information Dr. Mahesh Ramamani IBM.com Big Data & Analytics Learn More