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GitaCloud SAP IBP Webinar Response & Supply July 25th 2017

This is the slide deck for GitaCloud SAP IBP Webinar focused on Response & Supply Application.

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GitaCloud SAP IBP Webinar Response & Supply July 25th 2017

  1. 1. © 2017 GitaCloud, Inc. All Rights Reserved. IBP Response & Supply Webinar: Time Series Supply Planning 25th July 2017
  2. 2. © 2017 GitaCloud, Inc. All Rights Reserved. Moderator Introduction, Housekeeping • Welcome to this webinar focused on IBP Response & Supply: Time Series Supply Planning & Optimization • This webinar is brought to you jointly by SAP and GitaCloud • Housekeeping Items: • Questions & Answers: Type your questions into chat section at any time during the webinar • All attendee microphones will stay muted • This webinar is being recorded and will be available later on SAP website and GitaCloud website 2 Webinar Moderator: Puru Goyal – Consultant, GitaCloud  Data Scientist and IBP Consultant at GitaCloud  Comes from IIT Kanpur, India (Gold Medalist); graduate from UC Berkeley  Specializes in Demand & Supply Optimization using Advanced (Prescriptive) Analytics  Recently led a Statistical Forecasting IBP client engagement, where he was able to cut Forecast Error by > 500%
  3. 3. © 2017 GitaCloud, Inc. All Rights Reserved. 3 Our Speakers Jay Foster – SCM Solution Management, SAP America  Director, Solution Management at SAP America  Solution Owner for SAP IBP for S&OP  20+ years in leadership positions as CIO, SVP of IT, VP of Operations, and VP of Sales Ashutosh Bansal – Founder & CEO, GitaCloud  23+ years enabling Business Transformation at 25+ Fortune 500 companies in US  SCM/IBP SME: Ashutosh has led sales & delivery for multiple IBP engagements  ex-SAP: where Ashutosh played High-Tech Industry Principal and Services Sales Executive roles  Ashutosh blogs actively on IBP topics at www.GitaCloud.com/blog and LinkedIn (7K+ followers) Navin Kumar Prasannam – Solution Advisor – Digital Supply Chain, SAP  Navin is a Presales Solution Advisor with focus on Digital Supply Chain  Navin having graduated from the SAP Presales Academy in California, USA  Worked with a reputed CPG company in India prior to joining SAP  Navin’s educational background combines engineering and business management
  4. 4. © 2017 GitaCloud, Inc. All Rights Reserved. Agenda Need for Feasible & Optimal Supply Response in S&OP SAP IBP Response & Supply Showcase Wrap-up 10 min Kick-off 5 min 15 min 15 min Puru Goyal Ashutosh Bansal Navin Kumar Prasannam All 4 SAP IBP Response & Supply Introduction 15 min Jay Foster
  5. 5. © 2017 GitaCloud, Inc. All Rights Reserved. Agenda Need for Feasible & Optimal Supply Response in S&OP SAP IBP Response & Supply Showcase Wrap-up 10 min Kick-off 5 min 15 min 15 min Puru Goyal Ashutosh Bansal All 5 SAP IBP Response & Supply Introduction 15 min Jay Foster Navin Kumar Prasannam
  6. 6. © 2017 GitaCloud, Inc. All Rights Reserved. Supply Chain Excellence: Winners and Losers 6 Source: Supply Chains To Admire 2016 and 2017 Reports from Supply Chain Insights
  7. 7. © 2017 GitaCloud, Inc. All Rights Reserved. Polymer Manufacturers: Competitive Landscape 7 1. Handful of large, vertically integrated players provide 80% of polymer demand globally. 2. Profit is hurt by increased feedstock prices (linked to price of crude oil). 3. Cost increases cannot be passed to customers in the short term. 4. Extremely competitive price sensitive market. 5. Commodity product. Quality / Delivery reliability are assumed by customers. 6. Make To Stock. Customers expect instantaneous delivery. Source: Kadipasaoglu, S., Captain J. and James, M ‘Polymer supply chain management’, Int. J. Logistics Systems and Management, Vol. 4, No. 2, pp.233–253.
  8. 8. © 2017 GitaCloud, Inc. All Rights Reserved. Polymer Manufacturers: Supply Chains 8 1. Feedstock Supplier and Polymer Manufacturer belong to the same group of companies. 2. Plants typically located closer to Raw Materials than customers (near pipelines supplying feedstock). 3. Regional Supply chains: plants, DCs in a Region serve demand in that region. 4. 3-6 plants; 2-10 lines per plant 5. 250-1000 customers. Customers have multiple ship-to locations. 6. Distribution networks vary by region. Rail in North America, Sea in Middle East, Trucks in Europe. 7. North America: Plants have limited storage capacity, polymer is stored in railcars, then shipped to 10- 60 bulk terminals (DCs). Shipment Lead Time from Plan to DC: 10-14 days. 8. Long transit times (14 days) + lengthy production campaigns (30 days) = High Inventory Needed at DC Source: Kadipasaoglu, S., Captain J. and James, M ‘Polymer supply chain management’, Int. J. Logistics Systems and Management, Vol. 4, No. 2, pp.233–253.
  9. 9. © 2017 GitaCloud, Inc. All Rights Reserved. Polymer Manufacturers: Manufacturing Wheels 9 1. Hybrid of Batch and Continuous Processing 2. Capital intensive large plants need to operate at full capacity given slim margins. OEE is a critical metric. 3. 10-30 campaigns in a cycle (firm production sequence). 5-30 main products  50-400 end products  even more SKUs. 4. Product transitions produce lower grade material for a while, which sells at a discount. 5. Lines are dedicated to campaigns. Source: Kadipasaoglu, S., Captain J. and James, M ‘Polymer supply chain management’, Int. J. Logistics Systems and Management, Vol. 4, No. 2, pp.233–253.
  10. 10. © 2017 GitaCloud, Inc. All Rights Reserved. Polymer Manufacturers: Integrated Business Planning 10 1. Long lead time to make/ship product. Customers demand instant delivery. Volatile demand (10- 20% random fluctuations). High forecast variability  high safety stock needed at DCs. 2. Multiple packaging options (bulk, box, bag) create high number of SKUs. Large number of customer ship-to locations in a region. Complex distribution network (1000s of Product/Locations). 3. Plants need to run at full capacity with minimum transitions. Breaking campaigns is not desirable. Schedule updates can change the plan up to 30%. 4. Optimization can be to minimize cost or maximize margin. Minimum lot size constraints need to be modeled. Transition time and lower-grade transition material needs to be modeled. Source: Kadipasaoglu, S., Captain J. and James, M ‘Polymer supply chain management’, Int. J. Logistics Systems and Management, Vol. 4, No. 2, pp.233–253.
  11. 11. © 2017 GitaCloud, Inc. All Rights Reserved. Polymer Manufacturers: Case for an IBP Solution to deliver Margin Optimization 11 1. Complex & volatile demand & raw material pricing environment. 2. Need to forecast market demand, optimize DC inventory, plan manufacturing resources, and Raw Material buys optimally with minimal latency in the process. 3. High Production Line Utilization and minimal transitions are key given margin hit for transition materials. 4. Profit Optimization is key given slim profit margins. 5. This requires an integrated planning system that stretches from Demand, Inventory, Supply, Response, to Supplier & Customer collaboration. This system needs to optimize margin and be able to optimize on what-if demand / pricing scenarios. Source: Kadipasaoglu, S., Captain J. and James, M ‘Polymer supply chain management’, Int. J. Logistics Systems and Management, Vol. 4, No. 2, pp.233–253.
  12. 12. © 2017 GitaCloud, Inc. All Rights Reserved. Agenda Need for Feasible & Optimal Supply Response in S&OP SAP IBP Response & Supply Showcase Wrap-up 10 min Kick-off 5 min 15 min 15 min Puru Goyal Ashutosh Bansal All 12 SAP IBP Response & Supply Introduction 15 min Jay Foster Navin Kumar Prasannam
  13. 13. PUBLIC Jay Foster, SAP, Director, Solution Management July 25, 2017 SAP Time Series Supply Planning Overview 13
  14. 14. © 2017 GitaCloud, Inc. All Rights Reserved. SAP Integrated Business Planning for Response & Supply Fast, flexible supply planning supporting a variety of approaches, suitable for many industries, including:  Support of tactical (time series) supply planning in the context of S&OP  Unconstrained heuristics or constrained optimization  What-if analysis  Support of operational supply planning (orders)  Creates supply orders (planned orders, purchase req., distribution req.)  Generates allocations to feed to live ATP process  Constrained priority rules-driven planning, optimization based (roadmap) and unconstrained heuristic (roadmap)  What-if analysis  New order data store and tight integration with ERP  Support of response planning (orders)  Adjust create supply orders, and reschedule sales orders  What-if analysis  New order data store and tight integration with ERP 14
  15. 15. © 2017 GitaCloud, Inc. All Rights Reserved. Tactical Planning using Heuristic or OptimizationCreate advanced supply planning simulations for S&OP based on forecasts, orders, and inventory or safety stock targets  Utilize either heuristic or optimization algorithms to develop an unconstrained or constrained supply plan  Development of rough cut capacity plan  Multi level sourcing determination for both distribution and Bills of Material  Meet optimized inventory targets set by IBP for inventory  Gain visibility for projected stock or shortages at relevant levels of aggregation  Scenario planning capabilities
  16. 16. © 2017 GitaCloud, Inc. All Rights Reserved. Tactical Planning Use Cases Supply Simulation Collaboration Supply Overview Rough Cut Capacity Planning 16
  17. 17. © 2017 GitaCloud, Inc. All Rights Reserved. Tactical Planning – Optimizer Example  The objective of the Optimizer is to minimize the total costs or maximize total profit of the supply plan.  Optimization is performed via a mathematical model using Mixed Integer Linear Programming (MILP).  The output is an optimal and feasible Times Series plan that takes into consideration modeling constraints. DC1 DC2 Plant 1 Plant 2 Customer1 Customer2 Customer Transport costs Transport costs Customer Transport costs Fixed Production Procurement Cost Production Procurement Rate Inventory Holding Cost Rate Safety Stock Violation Rate Inventory Holding Cost Rate Safety Stock Violation RatePrice Price Transport costs Fixed Production Procurement Cost Production Procurement Rate 17
  18. 18. © 2017 GitaCloud, Inc. All Rights Reserved. Tactical Planning – Optimizer Constraint Types Soft Constraints  Should be satisfied, violations are penalized in the objective function  Examples:  Variable/rate costs for transports, production, external receipts  Non-delivery costs for customer demands (rate)  Fix costs for transports, production and external receipts  Inventory holding costs (rate) and safety stock violation costs (rate) Pseudo-hard constraints  Soft constraints with a very high penalty cost (usually higher than the sum of all other costs)  Gets satisfied if possible, but still allows for a solution if not possible  Examples:  Manual adjusted values (internal to the optimizer, very high cost if violated) Hard Constraints  Must be satisfied, no solution if not possible  Examples:  Max stock  Minimum and Maximum lot-sizes (unless overwritten by adjusted values)  Resource Capacities  Stock Balance 18
  19. 19. © 2017 GitaCloud, Inc. All Rights Reserved. Customer Adoption Since Fall 2016  Consumer Products (7)  Industrial Manufacturing (7)  Oil & Gas/Chemical (4)  Hi-Tech (3)  Automotive (3)  Other (5) 29 companies subscribing 19
  20. 20. © 2017 GitaCloud, Inc. All Rights Reserved. Agenda Need for Feasible & Optimal Supply Response in S&OP SAP IBP Response & Supply Showcase Wrap-up 10 min Kick-off 5 min 15 min 15 min Puru Goyal Ashutosh Bansal All 20 SAP IBP Response & Supply Introduction 15 min Jay Foster Navin Kumar Prasannam
  21. 21. © 2017 GitaCloud, Inc. All Rights Reserved. IBP Response & Supply Showcase 21 Feasible & Optimal Supply Planning in Action…
  22. 22. © 2017 GitaCloud, Inc. All Rights Reserved. Agenda Need for Feasible & Optimal Supply Response in S&OP SAP IBP Response & Supply Showcase Wrap-up 10 min Kick-off 5 min 15 min 15 min Puru Goyal Ashutosh Bansal All 22 SAP IBP Response & Supply Introduction 15 min Jay Foster Navin Kumar Prasannam
  23. 23. © 2017 GitaCloud, Inc. All Rights Reserved. 23 SAP IBP Response & Supply Workshop July 29th – Aug 6th, 2017 SAP IBP Response & Supply hands-on 4 day Workshop • Link to Register Scope: • SAP IBP Supply Overview • Supply Heuristic, Supply Optimizer • SAP IBP Response Overview • Response Heuristic GitaCloud: SAP IBP Upcoming Workshops SAP IBP Demand & Inventory Workshop September 16th – September 24th, 2017 SAP IBP Sales & Operations Planning Workshop August 19th – Aug 27th, 2017 SAP IBP Sales & Operations Planning S&OP hands-on 4 day Workshop • Link to Register Scope: • SAP IBP Platform Overview • SAP IBP Basic & Advanced Configuration • S&OP Capabilities: Planning & Analytics • Mock Implementation SAP IBP Demand & Inventory hands-on 4 day Workshop • Link to Register Scope: • SAP IBP Demand: Statistical Forecasting, Demand Planning, Demand Sensing • SAP IBP Inventory: Single Stage Inventory Optimization, Multi-Stage Inventory Optimization visit www.gitacloud.com/products to learn more
  24. 24. © 2017 GitaCloud, Inc. All Rights Reserved. 24 Wrap-up: Q&A IBP Response & Supply optimizes Net Profit Margin Rules Based Planning Cost Based Optimization
  25. 25. © 2017 GitaCloud, Inc. All Rights Reserved. Ashutosh Bansal Founder & CEO, GitaCloud +1-925-519-5965 6200 Stoneridge Mall Road, 3rd Floor, Pleasanton, CA 94588, USA ashutosh@gitacloud.com www.gitacloud.com

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