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Digital Business Planning - Ashutosh Bansal - GitaCloud - Mumbai SCM Executive Roundtable 12th April 2017

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These slides were delivered to SCM Executives as part of keynote address from Ashutosh Bansal, founder & CEO of GitaCloud. The event took place in Mumbai, India on 12th April, 2017 and was jointly hosted by GitaCloud and SAP.

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Digital Business Planning - Ashutosh Bansal - GitaCloud - Mumbai SCM Executive Roundtable 12th April 2017

  1. 1. © 2017 GitaCloud, Inc. All Rights Reserved. Digital Business Planning powered by GitaCloud and SAP IBP Platform 12th April 2017
  2. 2. © 2017 GitaCloud, Inc. All Rights Reserved. Digital Business Planning - Agenda 2 9:00 9:15 Demand Driven / Outside-in: The next frontier in Value Network Planning capabilities Ashutosh Bansal, GitaCloud 10:00 SAP’s strategy and visions within Integrated Business Planning and Supply Chain Management Neeraj Athalye, SAP 10:45 Break: Light Refreshments 11:00 Deep Dive: SAP IBP Showcase •Integrated Scenario Planning with IBP for S&OP •Demand Sensing with IBP for Demand •Inventory Optimization with IBP for Inventory Akhilesh Pandey, GitaCloud 12:30 Panel Discussion: SAP IBP - Lessons learned & Implementation Best Practices Ashutosh Bansal, Vasan VS, Neeraj Athalye, Moderated by Akhilesh Pandey 1:15 Wrap-up, networking and lunch Kick-off & Welcome Vasan VS, GitaCloud, Neeraj Athalye, SAP
  3. 3. © 2017 GitaCloud, Inc. All Rights Reserved. 3 Which type of supply chain are you running?
  4. 4. © 2017 GitaCloud, Inc. All Rights Reserved. 4 • FMCG Company: • Seasonal products. High volume. High demand variability driven by weather, promotions, etc. • Low forecast Accuracy across the large SKU portfolio. • High service levels lead to high inventory of perishable product. Bullwhip effect on suppliers. • Constrained Raw Materials. RM buy needs to be timed. • Supply chain constraints (e.g., RM/PM) not modeled in current excel based production planning system • Short term market demand quite different from forecast. • Planner burnout with reactive management of supply chain. Looking for stress free supply chain. Challenges we have observed...
  5. 5. © 2017 GitaCloud, Inc. All Rights Reserved. 5 • Pharmaceutical Company: • Measuring forecast accuracy at Country level despite high number of Distribution Centers. • Measuring forecast accuracy with 1 month lag despite pharma supply chain lead-time being 3-4 months • High service level requirement. Low forecast accuracy at lead time at SKU/DC level. High inventory levels. • Low forecast accuracy for NPI, emerging markets, samples. • Ineffective process to model long term demand and capacity requirements. Challenges we have observed...
  6. 6. © 2017 GitaCloud, Inc. All Rights Reserved. 6 • Automotive Company: • Spare parts forecast accuracy very low for exports markets. • Long tail in Spares SKU portfolio. Manual forecasting approaches not scaling. • Response is to increase order lead time. Customer service issues. • Inventory optimization challenge with old SKUs. MOQ constraints. • Inventory visibility challenges. Challenges we have observed...
  7. 7. © 2017 GitaCloud, Inc. All Rights Reserved. What drives your supply chain? 7 Manufacturing Driven Deliver a Feasible Plan for Operations Match Demand with Supply Sales Driven Match Demand with Supply Business- planning Driven Maximize Profitability Demand Driven Maximize Opportunity Sense and Shape Demand Market Driven Maximize Opportunity and Mitigate Risk. Orchestrate Demand Market to Market Greater Benefit • Growth • Resilience • Efficiency
  8. 8. © 2017 GitaCloud, Inc. All Rights Reserved. Stage5 Value Creation Network MINDSET Inside-Out Outside-In Stage1 Silo’ed Goals Stage 2 Scaling SC Functions TARGETCost Service Stage 3 Integrated Supply Chain Stage 4 Demand Driven Value Networks 8 Gartner Five Stage Maturity Model
  9. 9. © 2017 GitaCloud, Inc. All Rights Reserved. SAP APO (Stage 3) vs. SAP IBP (Stage 4) Demand Sensing Inventory Optimization Sales & Operations Planning Control Tower Demand Planning Detailed Scheduling Distribution Planning Stage 3 Integrated Supply Chain Stage 4 Demand Driven Value Networks System of Differentiation SOD System of Record SOR 9 Supply Planning
  10. 10. © 2017 GitaCloud, Inc. All Rights Reserved. Digital Business Processes run differently 10 Adapt & Respond Act & Monitor Shape (to resolve gaps) Plan (to understand gaps) Sense
  11. 11. © 2017 GitaCloud, Inc. All Rights Reserved. IBP is much more than S&OP Sense / Predict Demand Enrich with Sales & Marketing Input Demand Shaping / Consensus Generation Plan Demand Unconstrained Consensus Demand Plan Scenarios Compare Current vs. Target Inventory Sales Input on Service Levels Inventory& Service Level Optimization Plan Inventory Target Inventory Levels by Demand Scenario Review Critical Resource Capacity Flow Demand through Network Supply Shaping / Cost Optimization Plan Supply Constrained Supply Response Scenarios Develop end to end Scenarios (Demand, Inventory, Supply) Sales & Operations Planning S&OP Balance Plans, Resolve Issues, Make Decisions Assess Forecasted Financials, Options for Trade-offs Balancing (Pre S&OP) Meeting Executive Decision Meeting S&OP Plans Release S&OP Plans for detailing & execution Sales & Operations Execution S&OE Publish Plans, Monitor Execution, Respond Monitor Short Term Demand-Supply Imbalances Monitor Execution Performance Respond to Variations from Plan Operational Response Functional Planning Processes Generate Plans aimed at Functional Excellence 11
  12. 12. © 2017 GitaCloud, Inc. All Rights Reserved. Business environment for the Demand Planner 12 Evolving Consumer Volatile Demand Demand Driven Value Network to sense & react near-real-time SKU Proliferation Omnichannel Fulfillment NPI Forecast Bias Promotion Modeling What is needed Impact Forecast accuracy ceiling High error & bias Planner burnout
  13. 13. © 2017 GitaCloud, Inc. All Rights Reserved. The Fallacy of High Forecast Accuracy 13 Product Family / Monthly SKU / Location / Monthly SKU / Location / Customer / Weekly or Daily 70-85% 55-70% 35-55% 1 2 3 Executive View SCM Manager View Demand Planner View Forecast Accuracy Iceberg
  14. 14. © 2017 GitaCloud, Inc. All Rights Reserved. SAP Integrated Business Planning Platform 14 Supply Chain Control Tower “End-to-End Visibility, Monitoring and Alerting” IBP for Sales & Operations “Strategic and Tactical Decision Processes“ IBP for Demand “Demand Sensing and Statistical Forecasting” IBP for Inventory “Multi-Stage Inventory Optimization” Supply “Constrained and Unconstrained Supply Planning” IBP for Response “Allocations Planning and Order Rescheduling” Unified SAP HANA Platform for Cloud Deployment &
  15. 15. © 2017 GitaCloud, Inc. All Rights Reserved. SAP IBP Webinar from GitaCloud SAP IBP Platform: Key Differentiators Scalable & Flexible Model Sales FinanceOperations Model any detail across time or function, Insights like never before Social, Connected Collaborate internally / externally Record full context of decisions Risk Profitability Real Time Scenario Planning Model risk and profitability in your plans. Simulate on the fly Real Time Insights Track Supply Chain KPIs Real-Time with Control Tower Modern Intuitive UX Millennial grade UX. Business Planner Adoption Enabler Data Integration Out of the box, simple, secure integration with SAP ERP and APO Rich Functionality Demand Sensing, Control Tower, Optimization, MEIO in One Solution HANA in Cloud HANA in-memory. Cloud based. Elastic compute with reduced TCO 15
  16. 16. © 2017 GitaCloud, Inc. All Rights Reserved. Demand Planning vs. Demand Sensing 16 time Forecast wk1 wk2 wk3 wk4 wk52… Demand Planning: E.g., executed monthly in weekly buckets Demand Sensing: Generally done daily in daily buckets Difference between short-term forecast and consensus mid/long-term forecast Demand Planning = Time series methods – based on history - trend and seasonal patterns Demand Sensing = Adjust the demand plan – data from present and recent past - pattern recognition algorithms
  17. 17. © 2017 GitaCloud, Inc. All Rights Reserved. What planning processes does Demand Sensing impact? 17 Deployment and transportation decisions Production and packaging sequences Material purchasing Short Term Planning Horizon Inventory Optimization Today
  18. 18. © 2017 GitaCloud, Inc. All Rights Reserved. Case Study: Weekly forecast accuracy improvement Global health and beauty care consumer products 18 Lag Demand planning wMAPE Demand sensing wMAPE Absolute difference % Change Week 1 61% 31% 30 49% Week 2 62% 46% 16 26% Week 4 65% 52% 13 20% Week 6 68% 56% 12 18% Compelling results seen in the PoC for internal signals 18%–49% reduction in forecast error across 6 weeks 6%–8% reduction in forecast bias across 6 weeks Driven by significant over-forecasting bias, 7–8 day average order lead times, and complexity from large number of SKU location combinations wMAPE = Weighted mean absolute percentage error
  19. 19. © 2017 GitaCloud, Inc. All Rights Reserved. 19 Single Stage Calculations: • Isolated planning results in over-buffering of inventory across the supply chain • Determining postponement strategy is challenging (To stock at upstream or downstream warehouse) Multistage Optimization: • Coordinated planning eliminates over-buffering of inventory and ensures services objectives are met 2 Stage S S S C C C 1 3 S S S C C C Inventory Optimization simultaneously optimizes inventory across the entire supply chain based on meeting customer service requirements with the lowest amount of inventory dollars Global (Multi-Stage) Inventory Optimization
  20. 20. © 2017 GitaCloud, Inc. All Rights Reserved. SAP Inventory Optimization: What is Being Calculated? Increase Achieve the Right Balance Between Inventory and Service Levels Fix the Mix of Inventory! 90% 92% 94% 96% 98% 100% Inventory($) Customer Service Level (%) Optimal inventory Company current performance -60% -40% -20% 0% 20% 40% 60% DecreaseIncrease 20
  21. 21. © 2017 GitaCloud, Inc. All Rights Reserved. 21 SAP Integrated Business Planning for Inventory Improve customer service levels Maximize the efficiency of inventory and working capital Standardize the inventory target-setting process at each tier within the supply chain to feed operational plans Inventory Demand Response and Supply Sales & Operations Supply Chain Control Tower Customer service levels lifted from 93.7% to 99.1 Improved service levels with a 20% reduction in days of inventory
  22. 22. © 2017 GitaCloud, Inc. All Rights Reserved. 22 Origins • Started in Mar 2015 • Incorporated in Delaware, USA • Founded by Ashutosh Bansal (ex- SAP; Industry Leader / Sales Executive at SAP America) Footprint • Headquartered in Pleasanton, CA • Regional office in Gurgaon, India • Website: www.GitaCloud.com Partnerships • SAP PE Services Partner • River Logic (Enterprise Optimization) Reseller • Snaplogic (Integration Platform) Reseller Mission Help enterprises and people make better decisions GitaCloud Overview
  23. 23. © 2017 GitaCloud, Inc. All Rights Reserved. 23 Expertise • Enterprise License / Services Sales • Supply Chain Transformation Advisory • SAP Implementation Services • SAP Optimization Services • Business Process as a Service: • Demand Sensing • Inventory Optimization GitaCloud Overview Domains & SAP Solutions • Integrated Business Planning with SAP IBP • Demand Sensing • Inventory Optimization • Control Tower • Supply & Response Planning • ERP with SAP S/4 HANA: • MRP Live, Advanced ATP • Supply Chain Solutions: SAP APO, SNC, EM • Digital Transformation with SAP IOT, PDMS • Enterprise Performance Mgt with SAP BPC, C4A • Collaborative Procurement with SAP Ariba Industries • CPG (FMCG) • Pharmaceutical • Automotive • Mining & Metals • Chemicals • Oil & Gas
  24. 24. © 2017 GitaCloud, Inc. All Rights Reserved. SAP IBP is a key focus are for GitaCloud 24 SAP IBP S&OP Webinar Jan 18th, 2017 SAP IBP Webinar focused on Revenue Forecasting in S&OP • Jointly with SAP: Kris Gorrepati (SAP IBP Solution Mgt) as Guest Speaker • Replay: SAP-GitaCloud IBP S&OP Webinar Recording SAP IBP S&OP Workshop Jan 28th - Feb 5th, 2017 SAP IBP hands-on 4 day Workshop • Sold out workshop. • 10 learners across NA and APJ Scope: • SAP IBP Overview • SAP IBP Configuration • SAP IBP Mock Implementation SAP IBP Inventory Webinar Feb 24th, 2017 SAP IBP Demand Webinar Mar 23rd, 2017 SAP IBP Webinar focused on Demand Sensing • Jointly with SAP: Tod Stenger (SAP IBP Demand Solution Owner) • Replay: SAP-GitaCloud IBP Demand Webinar Recording SAP IBP Webinar focused on Multi- Stage Inventory Optimization • Jointly with SAP: Jeff Majestic (SAP APJ Business Development) • Replay: SAP-GitaCloud IBP Inventory Webinar Recording
  25. 25. © 2017 GitaCloud, Inc. All Rights Reserved. SAP IBP is a key focus are for GitaCloud 25 SAP IBP Customer Event in APJ Apr 12th, 2017 Half a day Face-to-Face Customer Event • Location: Mumbai, India • Hosted jointly with SAP • Top customer brands in CPG, Pharma, Auto, Chemicals confirmed (25+ companies) • 40+ C-level, VP SCM or higher LOB executives • SAP India S/4 Initiative Head as Keynote Speaker • Expect to start 5 or more SAP IBP POCs SAP IBP S&OP Workshop Mar 25th – Apr 2nd, 2017 SAP IBP S&OP hands-on 4 day Workshop • Link to Register Scope: • SAP IBP Overview • SAP IBP Configuration • SAP IBP Mock Implementation SAP IBP Demand & Inventory Workshop April 29th – May 7th, 2017 SAP IBP Demand & Inventory focused hands-on 4 day Workshop for customers interested in Demand Sensing or Inventory Optimization • Link to Register Scope: • SAP IBP Demand Overview • Demand Planning, Demand Sensing in detail • SAP IBP Inventory Overview • Multi-Stage Inventory Optimization in detail
  26. 26. © 2017 GitaCloud, Inc. All Rights Reserved. GitaCloud Digital Transformation Methodology Rapid Supply Chain Assessment & SAP IBP POC Current State Assessment Best Practices Fit-Gap Target State Design Transformation Roadmap Review Current State • Current Organization (Roles, Responsibilities, Incentives) • Current Processes (Formal, Shadow) • Current Systems • Current Data Quality • Current Reports & Metrics Assess Gap vs. best in class • Peer Benchmarking • Maturity Assessment • Gap Analysis (Define & Prioritize Gaps) Envision Target State • Tied to current maturity • Define high-level processes • Define Solution Architecture, Data requirements • Define target state Org • Define target state policies & metrics Develop Transformation Game Plan • Recommended Business Releases • Solution Architecture Impact of in-transit states • High level timeline and dependencies • Value Roadmap (Business case) SAP IBP POC / Pilot Run a Pilot • Controlled data-set • Choose a process area with high level of Sponsorship or value • Show value quickly • Leverage Industry Reference Models 26
  27. 27. © 2017 GitaCloud, Inc. All Rights Reserved. 27 • Leading electrical car manufacturer • Customer challenged to come up with an accurate demand forecast for Remanufacturing Operations • Rapidly evolving platform; dynamic failure mix • Regional differences • Excel based complex solution (hundreds of tabs) • GitaCloud brought in Demand Sensing and Capacity Forecasting best practices • Showcased the solution with a rapid POC – convinced customer on solution value • Implemented and successfully went live in record time • Customer team completely satisfied with the solution and its benefits GitaCloud Client Engagements Case Study: Remanufacturing Planning at a leading Automotive Brand
  28. 28. © 2017 GitaCloud, Inc. All Rights Reserved. As a department manager supporting Remanufacturing department in a growing organization, forecasting and planning has high importance in driving results. We are impressed with GitaCloud. GitaCloud combines deep supply chain skills with the ability to develop targeted solutions to hard business problems. Alla Anashenkova, Department Manager, Remanufacturing Planning, Leading Automotive Manufacturer GitaCloud Client Engagements Case Study: Remanufacturing Planning at a leading Automotive Brand 28
  29. 29. © 2017 GitaCloud, Inc. All Rights Reserved. Ashutosh Bansal Founder & CEO, GitaCloud +91-8130654555, +1-925-519-5965 LEVEL 9, SPAZE I-TECH PARK, A1 TOWER, SECTOR 49, SOHNA ROAD, GURGAON, HARYANA, 122018, INDIA ashutosh@gitacloud.com www.GitaCloud.com

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