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GitaCloud SAP IBP for Inventory Webinar May 25th 2018

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This slide deck was used during the webinar jointly hosted by GitaCloud, SAP, and Demand Driven Institute on 25th May, 2018. It focuses on SAP Integrated Business Planning IBP for Inventory 1805 application capabilities.

The content includes:
1. IBP for Inventory Overview from Beatrice Hulde (IBP for Inventory Solution Owner, SAP)
2. Demand Driven MRP Overview from Chad Smith (Co-Partner, Demand Driven Institute)
3. Detailed showcase of SAP IBP for Inventory across MEIO and DDMRP approaches from Ashutosh Bansal (President & CEO, GitaCloud)

SAP IBP for Inventory can improve revenue and margin through a reduction in stock-outs related lost sales, reduction in expedite costs & inventory carrying costs, and help you run a more efficient business by right sizing inventories to release working capital. Interested in evaluating SAP IBP for your business? You can reach out to GitaCloud team at connect@gitacloud.com.

If you would like to ramp-up on IBP on your own, access learning.gitacloud.com for SAP IBP Digital Learning content.

Visit www.gitacloud.com to learn more about GitaCloud.

Published in: Education
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GitaCloud SAP IBP for Inventory Webinar May 25th 2018

  1. 1. 1© 2018 GitaCloud, Inc. All Rights Reserved. SAP IBP for Inventory Webinar GitaCloud Webinar Series 2018
  2. 2. 2© 2018 GitaCloud, Inc. All Rights Reserved. Moderator Introduction • Welcome to this webinar focused on IBP for Inventory 1805 release • This webinar is brought to you jointly by GitaCloud, SAP, and Demand Driven Institute • All attendee microphones will stay muted Webinar Moderator: Guenter Schmidt – Principal, GitaCloud • 25+ years implementing and supporting SAP Supply Chain solutions in Europe, North America and Asia • Expertise in Semiconductor / High-Tech, Aerospace, innovative and non-mainstream use-cases • ex-Broadcom Sr. Director Business Transformation and Sr. Director IT, responsible for SAP ecosystem • ex-TriQuint Semiconductor IT Applications Director, IT owner of Response Planning Processes
  3. 3. 3© 2018 GitaCloud, Inc. All Rights Reserved. Before we begin
  4. 4. 4© 2018 GitaCloud, Inc. All Rights Reserved. Our Speakers Chad Smith – Partner, Demand Driven Institute • Co-Founder and Partner at the Demand Driven Institute. Fully involved in operations, marketing and product development as well as speaking engagements throughout the world. • Co-author of Demand Driven Material Requirements Planning and several other books • Nearly 20 years of implementation experience with organizations including Unilever, Siemens, Intel and Boeing. • Began career working for and then with Dr. Eli Goldratt, author of The Goal. Beatrice Hulde – SCM Solution Management, SAP America • Solution Owner for SAP IBP for inventory • Digital Supply Chain specialist with a focus on Integrated Business Planning • Several years of expertise in SAP IBP, especially also S&OP and Supply Chain Control Tower • Working with customers from across the Globe and all industries Ashutosh Bansal – President & CEO, GitaCloud • Leading GitaCloud across General Management, Sales, Marketing, and Strategy functions. • SCM/IBP SME. With SAP IBP solution since its inception. Ashutosh has led sales & delivery for multiple SCM/IBP engagements globally. • 25 years of SAP Implementation Experience. Leadership roles at PwC, IBM, and SAP. • Ashutosh blogs actively on SCM/IBP topics at LinkedIn (12K+ followers)
  5. 5. 5© 2018 GitaCloud, Inc. All Rights Reserved. Agenda IBP for Inventory Overview IBP for Inventory Showcase Wrap-up, Q&A Kick-off 5 min 15 min 35 min Guenter Schmidt Beatrice Hulde Ashutosh Bansal All Demand Driven MRP Overview 20 min Chad Smith 15 min
  6. 6. 6© 2018 GitaCloud, Inc. All Rights Reserved. CUSTOMER Beatrice Hulde, IBP SolutionManagement May 2018 SAP Integrated Business Planning for inventory
  7. 7. 7© 2018 GitaCloud, Inc. All Rights Reserved. Legal Disclaimer The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the permission of SAP. This presentation is not subject to your license agreement or any other service or subscription agreement with SAP. SAP has no obligations to pursue any course of business outlined in this document or any related presentation, or do develop or release any functionality mentioned therein. This document, or any related presentation and SAP´s strategy and future developments, products and or platforms directions and functionality are all subject to change and may be changed by SAP at anytime for any reason without notice. The information in this document is not a commitment, promise or legal obligation to deliver any material, code or functionality. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for particular purpose, or non-ínfringement.This document is for informational purposes and may not be incorporated into a contract. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP´s willful misconduct or negligence. All forward-looking statements are subject to various risks and uncertainties that could actual result to differ materially form expectations. Readers are cautioned no to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions.
  8. 8. 8© 2018 GitaCloud, Inc. All Rights Reserved. What Problems Are We Solving? Business Volatility Today, companies are facing increased supply chain risk due to economic uncertainty, escalating customer expectations, demand volatility, and supply variability. To remain competitive, they must improve their ability to plan, analyze, and collaborate to help ensure long-term growth and profitability. Consequence ▪ Too much inventory ▪ Not enough inventory ▪ Right inventory, wrong place Finance Customers Planners
  9. 9. 9© 2018 GitaCloud, Inc. All Rights Reserved. But, this is not easy! Deploy inventory targets across the supply chain, meeting service level objectives at the lowest cost Customer challenge: Eliminate excess inventory and at the same time improve service
  10. 10. 10© 2018 GitaCloud, Inc. All Rights Reserved. SUPPLY CHAIN How much inventory do I need at my Distribution Center? How much inventory do I need at my Manufacturing location? Service level targets Forecast Forecast error Consistently over/under forecasting (bias) Intermittent demand Outlier sales or forecasts Multiple service levels and inventory thresholds Seasonality/promotions Internal and external demand DEMAND Lead times Lead-time uncertainty Internal service levels Schedule attainment variability Production/distribution batch sizes Supply reliability Capacity restrictions Frozen production/planning periods Multiple supply sources SUPPLY What makes this difficult to do
  11. 11. 11© 2018 GitaCloud, Inc. All Rights Reserved. With increasing supply chain complexity…  Supplier s  Customer s …these factors multiply
  12. 12. 12© 2018 GitaCloud, Inc. All Rights Reserved. What does IBP for inventory accomplish for the end-to-end supply chain? 90% 100% Inventory($) 92% 94% 96% 98% Customer Service Level (%) Optimal inventory Company current performance Achieve the Right Balance Between Service Levels and Inventory Investment 60% 40% 20% 0% -20% -40% -60% DecreaseIncrease Fix the Mix of Inventory!
  13. 13. 13© 2018 GitaCloud, Inc. All Rights Reserved. SAP Integrated Business Planning for inventory prescribes inventory activity to maximize profit while buffering uncertainty How about here? How much inventory here? Here?
  14. 14. 14© 2018 GitaCloud, Inc. All Rights Reserved. Unified Platform & Integrated Processes SAP HANA Supply Chain Control Tower Exception Handling and Business Network Collaboration Sales & Operations Strategic and Tactical Decision Processes Demand Demand Sensing, Statistical Forecasting & Consensus Planning Inventory Multi-Stage Inventory Optimization Response & Supply Allocations & Deployment Planning, Order Rescheduling Unconstrained & Constrained Supply Planning
  15. 15. 15© 2018 GitaCloud, Inc. All Rights Reserved. New Generation of Supply Chain Planning from SAP State-of-the-Art Architecture based on SAP HANA One Integrated Planning Model Real-time planning and what-if scenario simulation Embedded social collaboration platform SAP JAM Integrated business planning SCP processes Real-time insight, monitoring & alerting Smart algorithms incl. machine learning Simplified User Experience with SAP Fiori and Microsoft Excel Sales & Operations Planning Supply Chain Control Tower Demand Inventory Planning Optimization Response, Deployment & Supply Planning
  16. 16. 16© 2018 GitaCloud, Inc. All Rights Reserved. Integrated Business Planning, powered by HANA A single data model to swiftly drive collaboration and action in your business • Inventory: Master Uncertainty, drive S&OP decisions to the Planners - Efficiently position inventory to best absorb forecast error, demand variability and supply uncertainty - Multi-echelon (multi-stage) inventory optimization to solve the science of postponement - Drive S&OP decisions to inventory target recommendations forPlanners  Sales and Operations: Monthly and Weekly Planning - Balance demand and supply while providing organizational visibility and alignment - What-if scenarios, using “real time” information - JAM embedded communication, and analytics • Supply Chain Control Tower: Visibility - Achieve end-to-end visibility in the extended supply chain - ŸIntegrate Data from various Systems - ŸDrive visibility and action with configurable Analytics & Alerts and Case Management • Demand: Demand analytics, demand sensing. Forecast Better - Demand Sensing (predict and reforecast, pattern recognition) - Forecasting statistical techniques - Collaborative Demand Planning • Supply and Response: Master supply planning and response intelligence - Plan production, procurement, and distribution - Respond to daily disruptions through what-if analysis to change supply plans and reschedule demand - Manage allocations where supply is scarce
  17. 17. 17© 2018 GitaCloud, Inc. All Rights Reserved. What are the 3 key differentiators for SAP Integrated Business Planning for inventory? Multi Stage Inventory Optimization Maximum working- capital efficiency to meet service level targets Complete Scalable Model Demand, supply chain, and financial model at aggregate & detailed levels Supply FinanceDemand S S S C C C S S S C C C Executive Review &Real- Time Analytics Sales and Marketing Forecasting Consensus Demand Planning Revenue & Profit Impact Inventory TargetSetting & Projections Material & Capacity- Constrained Planning Real-Time What-if Scenario Planning Real-time scenarios and simulation on entire model
  18. 18. 18© 2018 GitaCloud, Inc. All Rights Reserved. Inventory positioning in network Inventory optimization ‘What if’ analysis on inventoryDrivers of inventory SAP Integrated Business Planning for inventory Sample Use Cases
  19. 19. 19© 2018 GitaCloud, Inc. All Rights Reserved. SAP IBP for inventory – sample process flow Model Assumptions • Products • Demand Forecast • Service Targets • Supply Chain Network • Inventory Policies • Planning Horizon • Owner: Business Function Master Data Input • Cleansing • Review • Integration • Frequency: Monthly • Owner: IT/Business Function IBP for inventory • Run Forecast Error Operator • Run Multi- Stage Optimization Operator • Run Inventory Components Operator • Frequency: Daily, Weekly, or Monthly • Owner: IT Finalize Inventory Plan • Approve and communicate final inventory plan • Integrate output results to ERP system • Frequency: Daily, Weekly, or Monthly • Owner: Business Function  Objective: Calculate safety stock proposals for all SKU/Location combinations in the network.
  20. 20. 20© 2018 GitaCloud, Inc. All Rights Reserved. Agenda IBP for Inventory Overview IBP for Inventory Showcase Wrap-up, Q&A Kick-off 5 min 15 min 35 min Guenter Schmidt Beatrice Hulde Ashutosh Bansal All Demand Driven MRP Overview 20 min Chad Smith 15 min
  21. 21. 21© 2018 GitaCloud, Inc. All Rights Reserved. An Introduction All contents © copyright 2018 Demand Driven Institute, all rights reserved.
  22. 22. 22© 2018 GitaCloud, Inc. All Rights Reserved. Material Requirements Planning “As this book goes into print, there are some 700 manufacturing companies or plants that have implemented, or are committed to implementing, MRP systems. Material requirements planning has become a new way of life in production and inventory management, displacing older methods in general and statistical inventory control in particular. I, for one, have no doubt whatever that it will be the way of life in the future.” Orlicky 1975 Joe Orlicky Features: • Time Phased Planning • Level by level BOM explosion • Dependent demand planning Benefits: • Component synchronization • Reduction in inventory • Improved priorities • MRP did become THE way of life for planning. • It was conceived in the 1950s with the prevalence of computers. • It was codified in the 1960s by a small group of practitioners. • It was commercialized in the 1970s • By 1990 most manufacturers of even modest scale had an MRP system .
  23. 23. 23© 2018 GitaCloud, Inc. All Rights Reserved. Supply Chain Characteristics 1965 Today Supply Chain Complexity Low High Product Life Cycles Long Short Customer Tolerance Times Long Short Product Complexity Low High Product Customization Low High Product Variety Low High Long Lead Time Parts Few Many Forecast Accuracy High Low Pressure for Leaner Inventories Low High Transactional Friction High Low Complex and Volatile is the “New Normal” Conventional planning rules have not appreciably changed since the 1960s. MRP still plans today the way it did 50 years ago! Today’s supply chains look VERY different from 1960’s supply chains when conventional planning rules were formulated but… .
  24. 24. 24© 2018 GitaCloud, Inc. All Rights Reserved. The New Normal and Inventory Implications Supply chains have elongated and fragmented while customer tolerance times have dropped dramatically. This disparity means holding stock at some strategic point is a must to keep and/or grow sales. Also, there are more products with shorter life spans to manage - many use common components and resources. This means managing stock positions effectively is a must for effective capital and resource management. This also means that planning horizons are more remote from actual demand realization (longer range forecast). This also means that detailed item level forecasting is much more difficult. How is the conventional approach faring with all of this? The three rules of forecasts: 1. They start out wrong 2. The longer the range, the more wrong they are 3. The more detailed, the more wrong they are .
  25. 25. 25© 2018 GitaCloud, Inc. All Rights Reserved. Conventional Inventory Management Effects We know there are two universal points with regard to inventory. Between these points there is an optimal range to maintain. Too MuchToo Little A B 0 Optimal RangeWarning Warning .
  26. 26. 26© 2018 GitaCloud, Inc. All Rights Reserved. Conventional Inventory Management Effects Most companies exhibit a “bi-modal distribution” – most of the inventory is either too low or too high 90% of companies report this issue! Too MuchToo Little #ofpartsorSKU 0 With every MRP run an oscillation effect often occurs in which inventory quickly moves from one distribution to the other. Optimal RangeWarning Warning A B .
  27. 27. 27© 2018 GitaCloud, Inc. All Rights Reserved. Three Bottom Line Effects to Companies: 1. Chronic Shortages 2. Excessive Inventory 3. High Expedite Expenses & Waste But the real problem is at a higher level! .
  28. 28. 28© 2018 GitaCloud, Inc. All Rights Reserved. The Collective SCM Problem Bull-Whip Effect: “An extreme change in the supply position upstream in a supply chain generated by a small change in demand downstream in the supply chain. Inventory can quickly move from being backordered to being excess. This is caused by the serial nature of communicating orders up the chain with the inherent transportation delays of moving product down the chain.” (APICS Dictionary, 14th Edition) End Item AssemblerFoundry Component Sub- Assembler Demand Signal Distortion Supply Continuity Variability Transference AND amplification of variability in BOTH directions. A true solution must deal with demand AND supply distortion together. The more parts to the supply chain – the worse the effect! .
  29. 29. 29© 2018 GitaCloud, Inc. All Rights Reserved. Demand Driven MRP A method to model, plan and manage supply chains to protect and promote the flow of relevant information and materials. DDMRP uses strategic decoupling points to drive supply order generation and management throughout a supply chain. Position, Protect and Pull Material Requirements Planning (MRP) Distribution Requirements Planning (DRP) Lean Theory of Constraints InnovationSix Sigma First articulated in 2011 by the Demand Driven Institute after 15 years of research and extensive application. Through innovation critical planning needs are fused with mainstream improvement disciplines based on FLOW. .
  30. 30. 30© 2018 GitaCloud, Inc. All Rights Reserved. The Five Components of DDMRP Strategic Decoupling Buffer Profiles and Levels Demand Driven Planning Position 1 Protect 2 3 Pull 4 5 Dynamic Adjustments Visible and Collaborative Execution .
  31. 31. 31© 2018 GitaCloud, Inc. All Rights Reserved. Position – Strategic Decoupling Strategically places decoupling points of inventory within the product structure and supply chain. 1 This stops the transfer and amplification of variability in BOTH directions where it matters most. End Item AssemblerFoundry Component Sub- Assembler Demand Signal Distortion Supply Continuity Variability Planning horizons shorten AND lead times compress. .
  32. 32. 32© 2018 GitaCloud, Inc. All Rights Reserved. Decoupling Placement Criteria 1 . Decoupling Point Placement Considerations Customer Tolerance Time The time the typical customer is willing to wait before seeking an alternative source. Market Potential Lead Time This lead time will allow an increase of price or the capture of additional business either through existing or new customer channels. Sales Order Visibility Horizon The time frame in which we typically become aware of sales orders or actual dependent demand. External Variability Demand Variability: The potential for swings and spikes in demand that could overwhelm resources (capacity, stock, cash, etc.). Supply Variability: The potential for and severity of disruptions in sources of supply and/or specific suppliers. Inventory Leverage and Flexibility The places in the integrated bill of material (BOM) structure (matrix bill of material) or the distribution network that enables a company with the most available options as well as the best lead time compression to meet the business needs. Critical Operation Protection These types of operations include areas that have limited capacity or where quality can be compromised by disruptions or where variability tends to be accumulated and/or amplified.
  33. 33. 33© 2018 GitaCloud, Inc. All Rights Reserved. Position – MRP versus DDMRP MRP (Everything Coupled) DDMRP (Strategically Decoupled) 1 MRP was never designed to decouple! It makes everything dependent forcing longer planning horizons and variability accumulation. Critical Difference: .
  34. 34. 34© 2018 GitaCloud, Inc. All Rights Reserved. Protect – Buffer Profiles and Levels 2 . = Order frequency and size Safety Primary coverage Group Settings (Buffer Profiles) x Individual Part Properties = Zone and Buffer Levels for Each Part Item Type PURCHASED Lead Time Category LONG (.25) Variability Category HIGH (.65) Lead Time 21 Minimum Order Quantity (MOQ) 300 Location (Distributed parts only) N/A Average Daily Usage (ADU) 17 233 357 300
  35. 35. 35© 2018 GitaCloud, Inc. All Rights Reserved. Critical Differences 2 MRP was NOT designed to manage stock positions – it was designed to be the perfect make to order calculator. MRP nets to zero. DDMRP NEVER nets to zero! Safety Stock .
  36. 36. 36© 2018 GitaCloud, Inc. All Rights Reserved. Protect – Dynamic Buffer Adjustment 3 Most conventional safety stock and reorder point positions are static NOT dynamic.Critical Difference: Buffer levels flex as Average Daily Usage (ADU) is updated. 0 20 40 60 80 0 200 400 600 800 1000 1200 Recalculated Adjustments Buffers are intentionally flexed up or down in anticipation of planned events or seasons. 0 20 40 60 80 100 0 200 400 600 800 1000 Demand Adjustment Factors .
  37. 37. 37© 2018 GitaCloud, Inc. All Rights Reserved. Pull – Demand Driven Planning Planned orders create supply orders in anticipation of need over a longer planning horizon Conventional MPS-MRP Planning ? Plant Planning Suppliers Logistics Forecast 4 A sales order is HIGHLY ACCURATE. A planned order is HIGHLY INACCURATE Critical Difference: Sales Order Plant Planning Suppliers Logistics Only qualified sales orders within a short range horizon qualify as demand allocations DDMRP Supply Order Generation Versus . It Starts With a More Relevant Demand Signal It Continues With a More Relevant Supply Order Generation Equation…
  38. 38. 38© 2018 GitaCloud, Inc. All Rights Reserved. 4The Net Flow Equation . Questions every planner cares about each day. What do I have?What is coming to me? What demand do I need to fulfill immediately? What future demand is relevant? Buffer Status and Supply Order Generation occurs through a DAILY application of the “Net Flow Equation”. Supply order issued for up to the top of the buffer Net Flow Position Qualified Sales Order DemandOn-Hand + Open Supply -
  39. 39. 39© 2018 GitaCloud, Inc. All Rights Reserved. Dependence Within Independence with “Decoupled Explosion” . MRP Explosion DDMRP Decoupled Explosion • In DDMRP parent demand passes through non-buffered components just the same as with MRP • That demand will stop at stocked points no matter what
  40. 40. 40© 2018 GitaCloud, Inc. All Rights Reserved. Pull – DDMRP Execution Easy to Interpret Signals on Open Supply Priorities Order # On-Hand Status Order Type Due Date Customer MO 12379 MTO May - 12 Super Tech MO 12401 12% RED MTS May - 14 Internal MO 12465 27% RED MTS May - 12 Internal MO 12367 53% YELLOW MTS May - 12 Internal MO 12411 61% YELLOW MTS May - 16 Internal Order # Order Type Due Date Customer MO 12367 MTS May - 12 Internal MO 12379 MTO May - 12 Super Tech MO 12465 MTS May - 12 Internal MO 12401 MTS May - 14 Internal MO 12411 MTS May - 16 Internal Order # On-Hand Buffer Status PO 819-87 27% (RED) WO 832-41 42% (RED) WO 211-72 88% (YELLOW) 5 MRP = Priority by due date DDMRP = Priority by buffer status Critical Difference: vs. .
  41. 41. 41© 2018 GitaCloud, Inc. All Rights Reserved. Say Goodbye to the Bi-Modal Distribution DDMRP is proven to allow companies to plan and execute in the optimal range at strategically chosen points! Too MuchToo Little Optimal Range #ofpartsorSKU Warning Warning 0 A B .
  42. 42. 42© 2018 GitaCloud, Inc. All Rights Reserved. DDMRP’s Proven Benefits Benefit Typical improvements Improved Customer Service Users consistently achieve 97-100% on time fill rate performance Lead Time Compression Lead time reductions in excess of 80% have been achieved in several industry segments Right-sizes Inventory Typical inventory reductions of 30-45% are achieved while improving customer service Lowest total supply chain cost Costs related to expedite activity and false signals are largely eliminated (fast freight, partial ships, cross-ships, schedule break-ins) Easy and Intuitive Planners see priorities instead of constantly fighting the conflicting messages of MRP . Case Studies Available at: https://www.demanddriveninstitute.com/case-studies
  43. 43. 43© 2018 GitaCloud, Inc. All Rights Reserved. THE authoritative book on Demand Driven Material Requirements Planning THE authoritative education on Demand Driven Material Requirements Planning www.demanddriveninstitute.com .
  44. 44. 44© 2018 GitaCloud, Inc. All Rights Reserved. Agenda IBP for Inventory Overview IBP for Inventory Showcase Wrap-up, Q&A Kick-off 5 min 15 min 35 min Guenter Schmidt Beatrice Hulde Ashutosh Bansal All Demand Driven MRP Overview 20 min Chad Smith 15 min
  45. 45. 45© 2018 GitaCloud, Inc. All Rights Reserved. IBP for Inventory Showcase Inventory Optimization in Action…
  46. 46. 46© 2018 GitaCloud, Inc. All Rights Reserved. 1. Supply Network, Master Data Review 2. Forecast Error App 3. Multi-Echelon Inventory Optimization (MEIO) Run 4. Inventory Plan Analysis Dashboards 5. Exception Management, What-if simulations, Publish Plan 6. Demand Driven MRP (DDMRP) Inventory Optimization Showcase Flow
  47. 47. 47© 2018 GitaCloud, Inc. All Rights Reserved. Customer Map by Sales Volume
  48. 48. 48© 2018 GitaCloud, Inc. All Rights Reserved. Supply Network Map
  49. 49. 49© 2018 GitaCloud, Inc. All Rights Reserved. Supply Network Model
  50. 50. 50© 2018 GitaCloud, Inc. All Rights Reserved. Input Quality Dashboard
  51. 51. 51© 2018 GitaCloud, Inc. All Rights Reserved. Input Quality Dashboard
  52. 52. 52© 2018 GitaCloud, Inc. All Rights Reserved. 1. Supply Network, Master Data Review 2. Forecast Error App 3. Multi-Echelon Inventory Optimization (MEIO) Run 4. Inventory Plan Analysis Dashboards 5. Exception Management, What-if simulations, Publish Plan 6. Demand Driven MRP (DDMRP) Inventory Optimization Showcase Flow
  53. 53. 53© 2018 GitaCloud, Inc. All Rights Reserved. Calculate Forecast Error
  54. 54. 54© 2018 GitaCloud, Inc. All Rights Reserved. Lagged Forecast vs. Sales Analysis
  55. 55. 55© 2018 GitaCloud, Inc. All Rights Reserved. Forecast Bias: App Settings
  56. 56. 56© 2018 GitaCloud, Inc. All Rights Reserved. Forecast Bias: Calculated vs. Used
  57. 57. 57© 2018 GitaCloud, Inc. All Rights Reserved. 1. Supply Network, Master Data Review 2. Forecast Error App 3. Multi-Echelon Inventory Optimization (MEIO) Run 4. Inventory Plan Analysis Dashboards 5. Exception Management, What-if simulations, Publish Plan 6. Demand Driven MRP (DDMRP) Inventory Optimization Showcase Flow
  58. 58. 58© 2018 GitaCloud, Inc. All Rights Reserved. Global (Multi-Stage) Inventory Optimization
  59. 59. 59© 2018 GitaCloud, Inc. All Rights Reserved. Calculate Target Inventory Components
  60. 60. 60© 2018 GitaCloud, Inc. All Rights Reserved. Expected Lost Demand
  61. 61. 61© 2018 GitaCloud, Inc. All Rights Reserved. 1. Supply Network, Master Data Review 2. Forecast Error App 3. Multi-Echelon Inventory Optimization (MEIO) Run 4. Inventory Plan Analysis Dashboards 5. Exception Management, What-if simulations, Publish Plan 6. Demand Driven MRP (DDMRP) Inventory Optimization Showcase Flow
  62. 62. 62© 2018 GitaCloud, Inc. All Rights Reserved. Inventory Plan Analysis
  63. 63. 63© 2018 GitaCloud, Inc. All Rights Reserved. Safety Stock Drivers
  64. 64. 64© 2018 GitaCloud, Inc. All Rights Reserved. Safety Stock Days
  65. 65. 65© 2018 GitaCloud, Inc. All Rights Reserved. Reorder Point
  66. 66. 66© 2018 GitaCloud, Inc. All Rights Reserved. 1. Supply Network, Master Data Review 2. Forecast Error App 3. Multi-Echelon Inventory Optimization (MEIO) Run 4. Inventory Plan Analysis Dashboards 5. Exception Management, What-if simulations, Publish Plan 6. Demand Driven MRP (DDMRP) Inventory Optimization Showcase Flow
  67. 67. 67© 2018 GitaCloud, Inc. All Rights Reserved. Safety Stock (Days) Alert Max: 60 Days Min: 10 Days
  68. 68. 68© 2018 GitaCloud, Inc. All Rights Reserved. Decomposed (Single-Stage) Inventory Optimization
  69. 69. 69© 2018 GitaCloud, Inc. All Rights Reserved. What-if Simulation: Transportation Lead Time Error CV
  70. 70. 70© 2018 GitaCloud, Inc. All Rights Reserved. 1. Supply Network, Master Data Review 2. Forecast Error App 3. Multi-Echelon Inventory Optimization (MEIO) Run 4. Inventory Plan Analysis Dashboards 5. Exception Management, What-if simulations, Publish Plan 6. Demand Driven MRP (DDMRP) Inventory Optimization Showcase Flow
  71. 71. 71© 2018 GitaCloud, Inc. All Rights Reserved. Recommend Decoupling Points
  72. 72. 72© 2018 GitaCloud, Inc. All Rights Reserved. Calculate DDMRP Buffer Levels
  73. 73. 73© 2018 GitaCloud, Inc. All Rights Reserved. DDMRP: Red, Yellow, Green Zone Calculations Type Key Figure Calculation Value Input Period Between Replenishment (Weeks) 1 Decoupled Lead Time (Weeks) 2 Lead Time Factor Per Buffer Profile Master Data for Medium Lead Time .6 Variability Factor Per Buffer Profile Master Data for Medium Variability .6 Propagated Average Daily Usage 4485 Output Minimum Order Quantity Per Production, Transportation Min Lot Size 0 Red Zone Base PROPAGATEDADU × DECOUPLEDLEADTIME × 7 × LEADTIMEFACTOR 4485 x 2 x 7 x .6 = 37674 Red Zone Safety PROPAGATEDADU × DECOUPLEDLEADTIME × 7 × LEADTIMEFACTOR × VARIABILITYFACTOR 4485 x 2 x 7 x .6 x .6 = 22604 Yellow Zone PROPAGATEDADU × DECOUPLEDLEADTIME × 7 4485 x 2 x 7 = 62790 Green Zone MAX (MOQ, PROPAGATEDADU × PBR × 7,PROPOGATEDADU × LEADTIMEFACTOR ×DECOUPLEDLEADTIME × 7) Max (0, 4485 x 1 x 7, 4485 x .6 x 2 x 7) = Max (0, 31395, 37674) = 37674 Top of Red Red Zone Base + Red Zone Safety 37674 + 22604 = 60278 Top of Yellow Top of Red + Yellow Zone 60278 +62790 = 123068 Top of Green Top of Yellow + Green Zone 123068 +37674 = 160742
  74. 74. 74© 2018 GitaCloud, Inc. All Rights Reserved. DDMRP: Top of Red, Yellow, Green
  75. 75. 75© 2018 GitaCloud, Inc. All Rights Reserved. MEIO vs. DDMRP: Results Comparison
  76. 76. 76© 2018 GitaCloud, Inc. All Rights Reserved. Agenda IBP for Inventory Overview IBP for Inventory Showcase Wrap-up, Q&A Kick-off 5 min 15 min 35 min Guenter Schmidt Beatrice Hulde Ashutosh Bansal All Demand Driven MRP Overview 20 min Chad Smith 15 min
  77. 77. 77© 2018 GitaCloud, Inc. All Rights Reserved. Release 1805 1. Potential data protection and privacy features include simplified deletion of personal data, reporting of personal data to an identified data subject, restricted access to personal data, masking of personal data, read access logging to special categories of personal data, change logging of personal data, and consent management mechanisms. 2. This is the current state of planning and may be changed by SAP at any time without notice. SAP Integrated Business Planning for inventory Product road map overview - key themes andcapabilities Inventory Optimization ▪ Network trees exposed in Inventory Operators ▪ Distribution attribute for consumption: Normal or Gamma distribution of forecast error in Multi-Stage IO Operator Demand-driven MRP Planning ▪ DDMRP operators output Critical Path Indicators and Decoupling Point Reasons ▪ DDMRP SAP Fiori app shows percentage change bar chart for scenarios Supply Chain Network Fiori app ▪ Symbol legend ▪ Order-based planning networks ▪ Rolling time period filters ▪ UI error logging Inventory Optimization ▪ Time-varying cyclical sourcing in algorithms (loops) ▪ Inventory Components Operator accounts for impact of lot size at upstream flow-through nodes ▪ Non-stocking nodes enhanced with lead time variability ▪ Forecast Error app outputs outlier periods and additional forecast error demand types (frequent & intermittent) Demand-driven MRP Planning ▪ DDMRP SAP Fiori app creates, edits and runs scenarios ▪ Forecast Error App calculates ADU based on blended horizon (historical & future) Supply Chain Network Fiori app ▪ Version-specific master data V1805 – Recent innovations(1) V1808 – Planned Q3/2018(1,2) V1811 – Planned Q4/2018(2) V1902 – Planned Q1/2019(2) Inventory Optimization ▪ Fractional-week lead times and PBRs used in calculation of backlog and propagated demand ▪ Inventory optimization using maximum constraints (storage tanks) ▪ “I” push calculation for downstream ▪ Improved scalability of concurrent inventory runs ▪ Inbound integration of Master Data Demand-driven MRP Planning ▪ DDMRP SAP Fiori app saves scenario results to baseline Supply Chain Network Fiori app ▪ Filter by Location ▪ Navigate to Analytics and Dashboard SAP Fiori apps Inventory Optimization ▪ Improved performance through adoption of normalization framework ▪ Inbound integration of Key Figures ▪ Outbound integration of safety stock and other inventory targets Demand-driven MRP Planning ▪ Outbound integration of decoupling point indicators and buffer profiles to S/4 HANA Supply Chain Network Fiori app ▪ Update time period filter ▪ Network layout enhancements
  78. 78. 78© 2018 GitaCloud, Inc. All Rights Reserved. Wrap Up - Integrated Business Planning for inventory • Achieve the Right Balance Between Inventory and Service Levels with Multi Stage optimization • Fix the Mix of inventory by item and location • Use inventory more efficiently to buffer risk and uncertainty – at least total cost Business Benefits ▪ Improve customer service levels 5-10%, with better order lead time variability ▪ Reduce working capital 15-30%, with corresponding reductions in obsolescence and inventory carrying cost ▪ Improve planner productivity with 20-40% less time spend expediting, and more effective supply plans
  79. 79. 79© 2018 GitaCloud, Inc. All Rights Reserved. IBP Inventory Functionalities • Inventory Reference Planning Areas: SAP3 (MEIO), SAP3B (DDMRP) • Planning Levels, Master Data, Attributes as Key Figures, Key Figures • Configuration: • Technical Weeks, Subnetworks, Multiple Modes of Transport, Safety Stock Policy Indicator • Functionality: • Supply Chain Network App, Manage ABC / XYZ Segmentation Rules App • Manage Forecast Error Calculations App: Lagged Error Measures, Intermittency Check, Bias Cap • Inventory Optimization Operators: Global Inventory Optimization, Calculate Inventory Components, Expected Lost Demand Calculation • Custom Alerts, Analytics, Dashboards • What-if Scenarios / Simulations: Single-Stage Inventory Optimization, Version specific Master Data • Demand Driven MRP Operators: Recommend Decoupling Points, Calculate Buffer Levels • DDMRP Buffer Analysis App • 1805 Recent Features: Network ID, DDMRP Critical Path Indicators, Decoupling Reasons, Buffer Simulations
  80. 80. 80© 2018 GitaCloud, Inc. All Rights Reserved. GitaCloud Digital Learning Platform Visit learning.gitacloud.com
  81. 81. 81© 2018 GitaCloud, Inc. All Rights Reserved. • Evaluate SAP IBP with GitaCloud Bootcamps: • SAP IBP 2-day Platform & Applications Bootcamp in Mumbai, India: July 9th – 10th, 2018 • SAP IBP 2-day Platform & Applications Bootcamp in Gurgaon, NCR, India: July 12th – 13th, 2018 • SAP IBP 4-day Platform & Configuration Bootcamp in San Francisco Bay Area, USA: Aug 27th – Aug 30th, 2018 • SAP IBP 4-day Response & Supply Bootcamp in San Francisco Bay Area, USA: Oct 1st – Oct 4th, 2018 • Visit www.gitacloud.com/events for full events calendar • Ramp-up on SAP IBP on your own schedule: • GitaCloud Digital Learning Platform: learning.gitacloud.com • GitaCloud YouTube Channel • Connect with GitaCloud for an SAP IBP Demo / Workshop at your premises: • Email: connect@gitacloud.com • Phone: +1-925-519-5965 • Address: 6200 Stoneridge Mall Road, 3rd Floor, Pleasanton, CA 94588, USA • Website: www.gitacloud.com Call for Action

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