IBP Implementation Analysis
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SAP IBP can address pain areas in demand and supply planning for ABC Group. IBP allows gathering and cleansing historic data from multiple sources. It offers improved forecasting methods like demand sensing and statistical algorithms. IBP enables what-if scenario modeling and integrated inventory KPI dashboards. Alerts can be better managed to adjust forecasts and plans. IBP provides supply optimization and a supply chain control tower for end-to-end visibility. IBP would be implemented in parallel with APO, with master data and optimization results closely aligned between the two systems.
IBP Implementation Analysis
- 1. SAP IBP USE CASE SCENERIOS Presenter: Ayan Bishnu
- 2. 2 WHAT IS BEING COVERED Pain Areas Addressed with IBP (High Level). IBP Landscape Architecture (High Level). XYZ Inc Use Case Scenario for IBP Demand Planning. ABC Group Use Case Scenario for IBP Demand. ABC Group Use Case Scenario for IBP Inventory. Wrap Up.
- 3. AREAS ADDRESSED WITH IBP ( A HAWK EYE VIEW ) Operational Validation Demand Validation Demand and Supply Review S&OP Meeting
- 4. IBP PLANNING ARCHITECTURE Use of IBP for demand (demand sensing) with APO (DP and SNP)
- 5. XYZ INC IMPLEMENTATION THE CHALLENGE Highly Manual & Time consuming Process Financial Planning not integrated in S&OP Inefficient data visualization THE SOLUTION SAP IBP solution implementation leveraging supply optimizer Integrated with SAP APO, SAP BI, COPA systems THE BENEFIT Excel Based User Interface Effective KPI tracking Integrated with multiple stakeholders Quick what-if Analysis
- 6. XYZ INC DEMAND PLANNING FLOW Step1: Gather & cleanse historic data Run or schedule the statistical forecasting job for background processing Solve potential issues or inconsistencies within the forecast and overwrite the created values manually if needed Use the Demand Plan that is generated in SAP APO DP for further processing in APO SNP Load historic sales data and use SAP BW functionality & to correct outliers or substitute missing values Define the way the forecast should be calculated, parameters, algorithms, etc. Step2: Simulate & select forecast models Step3: Run mid / long term forecasting Step4: Review alerts & adjust forecast Step5: Reuse forecast for other process
- 7. XYZ INC PAIN AREAS IN DEMAND PLANNING Step1: Gather & cleanse historic data Step2: Simulate & select forecast models Step3: Run mid / long term forecasting Step4: Review alerts & adjust forecast Step5: Reuse forecast for other process 1) Multiple data sources. 2) Issue with Integration. 3) Data Accuracy. 1) No S&OP process in APO. 2) Limited Disaggregation capabilities. 3) Limited WHAT IF simulations. 1) Limited alert based actions. 2) Manual adjustments based on gut fill. 3) Demand Sensing not available in APO.
- 8. LOADING HISTORICAL DATA Step2: Simulate & select forecast models Load historic sales information (e.g. Confirmed QTY, Delivered QTY, etc) via the HANA Cloud Integration (HCI) Load historic sales information (e.g. Sales Orders, Confirmed QTY, Delivered QRY, etc) via the WebUI Step1: Gather & cleanse historic data 1) Multiple data sources. 2) Issue with Integration. 3) Data Accuracy.
- 9. CLEANSING HISTORICAL DATA Step2: Simulate & select forecast models Step3: Run mid / long term forecasting Step4: Review alerts & adjust forecast Interactive charts provides better visualization to users for the changes done in the historical data. Excel based UI provides better flexibility to planners to perform data cleansing Step1: Gather & cleanse historic data 1) Multiple data sources. 2) Issue with Integration. 3) Data Accuracy.
- 10. SAP Integrated Business Planning for sales and operations Create the optimal business plan to drive revenue growth and increase market share Effectively balance demand and supply and attain financial targets Increase speed and agility of planning and drive most profitable responses Improve forecast accuracy and on- time delivery across all levels Deliver a cross departmental sales and operations plan balancing the impact on inventory, service levels and profitability Step2: Simulate & select forecast models 1) No S&OP process in APO. 2) Limited Disaggregation capabilities. 3) Limited WHAT IF simulations.
- 11. WHAT-IF SCENARIO MODELING • Tactically review monthly supply imbalances at a facility and conduct gap closure • New forward warehouse and assess cost/margin impacts • New products and associated prospective customer demand, with cost and revenue impacts • New customer and associated demand to support revenue scenarios • Alternative cost and pricing inputs • Compare multiple scenarios Step2: Simulate & select forecast models 1) No S&OP process in APO. 2) Limited Disaggregation capabilities. 3) Limited WHAT IF simulations.
- 12. BETTER FORECASTING METHODS Features Demand sensing algorithms (short term forecasting) Statistical Methods (mid- / long-term forecasting) Pre-Processing algorithms Time series algorithms Regression based methods Integration with ERP and APO Exception management Fiori Apps and Excel as a planning front-end Data model: Key figures and attributes Key figure calculations Aggregation/Disaggregation rules User management and authorizations Pre-Processing algorithms: Substitute missing values Outlier correction with interquartile range test and variance test Time series algorithms: Simple moving average Weighted moving average Single exponential smoothing Double exponential smoothing Triple exponential smoothing Automated triple exponential smoothing with parameter optimization 1st order exponential smoothing with adaptive alpha Croston’s method for intermittent demand Combination of these algorithms (similar to composite forecasting in APO) or Pick the best Regression based algorithms: Multiple linear regression (MLR) More flexibility & options in terms of Statistical forecasting & regression based methods
- 14. RUNNING FORECASTING IN EXCEL
- 15. IBP SUPPLY CHAIN CONTROL TOWER Supply Chain Monitoring Enable supply chain professionals to navigate, analyze and profitably manage the end-to-end supply chain in real-time Integrated Business Planning (IBP) • • Increase end-to-end visibility Increase on-time delivery performance to customer Increased forecast accuracy. More accurate sales evolution reporting • • Increase supply chain agility and reduce supply chain cost User Experience IBP for sales & operations IBP for demand IBP for supply IBP for inventory IBP for response SAP HANA Platform Supply Chain Control Tower Step4: Review alerts & adjust forecast 1) Limited alert based actions. 2) Manual adjustments based on gut fill. 3) Demand Sensing not available in APO.
- 16. ADVANCED ALERT MANAGEMENT • Alerts that were raised for statistical forecasts can be monitored via the Monitor or Alerts app. Those are dependent on the user’s or company’s alert definition and thresholds. • Based on alerts, from concerned departments, the mid-to long-term demand forecast can then be manually adjusted via the SAP IBP add-in for Microsoft Excel. • The outcome is a consensus demand plan that acts as the final mid-to long- term demand forecast, as agreed between the different departments. Step4: Review alerts & adjust forecast 1) Limited alert based actions. 2) Manual adjustments based on gut fill. 3) Demand Sensing not available in APO.
- 17. DEMAND SENSING FOR OPTIMAL BLENDS & BETTER PREDICTION Weekly Adjustments Open Order data correlation corrections Output Optimal blend by lag patterns Bias Tracking Controls Intelligent forecast consumption logic Optimal weighting and pattern recognition Daily Disaggregation Daily outputs for execution systems Aggregated weekly or monthly values for planning and reporting Bias and variability calculations • Forecast patterns • Shipment patterns • Demand Signal data patterns Step4: Review alerts & adjust forecast 1) Limited alert based actions. 2) Manual adjustments based on gut fill. 3) Demand Sensing not available in APO.
- 18. DEMAND SENSING USING EXCEL Navigation for demand Sensing Issues from the Fiori Launchpad
- 19. ABC GROUP - PROTOTYPE DRIVEN ENGAGEMENT OBJECTIVE Evaluation: Transition from SAP APO to SAP IBP Integrated with SAP APO (transition phase), SAP BPC, SAP ECC ENVISIONED SOLUTION SAP IBP solution implementation leveraging IBP Demand, Response & Supply, Supply Chain Control Tower SOLUTION BENEFITS Tight integration between logistical and financial planning Increased collaboration and progress tracking Ability to balance demand supply in a user friendly way Enable greater planning flexibility: Rapid scenario analysis
- 20. ABC GROUP DEMAND PLANNING FLOW Step1: Gather & cleanse historic data Run or schedule the statistical forecasting job for background processing Solve potential issues or inconsistencies within the forecast and overwrite the created values manually if needed Use the Demand Plan that is generated in SAP APO DP for further processing in APO SNP Load historic sales data and use SAP BW functionality & to correct outliers or substitute missing values Define the way the forecast should be calculated, parameters, algorithms, etc. Step2: Simulate & select forecast models Step3: Run mid / long term forecasting Step4: Review alerts & adjust forecast Step5: Reuse forecast for other process
- 21. APTERGROUP PAIN AREAS IN DEMAND PLANNING Step1: Gather & cleanse historic data Step2: Simulate & select forecast models Step3: Run mid / long term forecasting Step4: Review alerts & adjust forecast Step5: Reuse forecast for other process 1) Multiple data sources. 2) Issue with Integration. 3) Data Accuracy. 1) No S&OP process in APO. 2) Limited Disaggregation capabilities. 3) Limited WHAT IF simulations. 1) Limited alert based actions. 2) Manual adjustments based on gut fill. 3) Demand Sensing not available in APO.
- 22. ABC GROUP PRESENT SUPPLY PROCESS FLOW Step1: Inputs / PIR from Demand module • Update Resource Capacity • Update other constraints for optimization • Identify Resource overloads • Identify other constraints thresholds • Solve potential issues or overloads within the generated plan. • manual Planner Intervention for correction. • Use the agreed supply plan that is generated in SAP APO SNP for further processing in APO Deployment / TLB. • Forecasted demand from Demand Planning • Target inventory requirements (Master data) • On hand inventory including stocks in transit • Execute net demand planning • Unconstrained production plan. Step2: Net Demand Planning (Unconstrained Plan) Step3: Capacity leveling / Optimization Step4: Review alerts & adjust supply plan Step5: Reuse supply plan for other process
- 23. ABC GROUP PAIN AREAS IN SUPPLY PLANNING Step1: Inputs / PIR from Demand module Step2: Net Demand Planning (Unconstra ined Plan) Step3: Capacity leveling / Optimization Step4: Review alerts & adjust supply plan Step5: Reuse supply plan for other process 1) High or uncontrolled inventory levels. 2) Inadequate customer service levels or inventory availability. 3) Multiple planning and inventory target setting processes. 1) How often can we plan production? 2) Do we have to order in specific batch sizes? 3) Are supplies commonly on time, early, or late? 4) What are the bottlenecks ? Already addressed in IBP Demand Planning Already addressed in IBP SCCT
- 24. SAP IBP FOR INVENTORY OPTIMIZATION Optimize inventory targets to increase service levels, considering supply chain uncertainties • Improve customer service levels • Maximize the efficiency of inventory and working capital • Standardize planning processes for inventory targets • Improve planner productivity (planning time reduced by 2 days) • Reduce production and distribution costs (approx. 2.6 %**) Achieving the right balance between inventory and service levels Step2: Net Demand Planning (Unconstrai ned Plan) 1) High or uncontrolled inventory levels. 2) Inadequate customer service levels or inventory availability. 3) Multiple planning and inventory target setting processes.
- 25. INTEGRATED INVENTORY KPI DASHBOARD Step2: Net Demand Planning (Unconstrai ned Plan) 1) High or uncontrolled inventory levels. 2) Inadequate customer service levels or inventory availability. 3) Multiple planning and inventory target setting processes.
- 26. INVENTORY BUILT UP SCENERIO Build inventory 0 As we are already throttling at 100% capacity is not possible to build inventory 1 Setting inventory targets based on available capacity2 DEMO SCENARIO Step2: Net Demand Planning (Unconstrai ned Plan) 1) High or uncontrolled inventory levels. 2) Inadequate customer service levels or inventory availability. 3) Multiple planning and inventory target setting processes.
- 27. SUPPLY SHORTAGE SCENERIO • Business Event: Demand Loss or Production/Capacity Reduction Production loss leading to drop in fulfilment 1 Production loss of 300 TPD 0 DEMO SCENARIO
- 28. SAP IBP FOR SUPPLY OPTIMIZATION Create advanced supply planning simulations for S&OP based on forecasts, orders, and inventory or safety stock targets • Simulate either constrained or unconstrained production and distribution plans, using heuristics or optimization based algorithms • Multi level sourcing determination for both distribution and Bills of Material • Development of rough cut capacity plan in a times series bucketed supply plan • Simulation capabilities for scenario planning Step3: Capacity leveling / Optimization 1) How often can we plan production? 2) Do we have to order in specific batch sizes? 3) Are supplies commonly on time, early, or late? 4) What are the bottlenecks ?
- 29. PRODUCTION / RESOURCE VIEW • Analyze Production Goods Receipt and Issue in Daily Buckets • Ability to Review Resource Capacities and Consumption
- 30. WAREHOUSE VIEW • Analyze Warehouse Goods Issue and Receipt along with Inventory Targets and Projections
- 31. SOURCING VIEW • Ability to Track Sources Among Locations and Between Customer and Locations Step3: Capacity leveling / Optimization 1) How often can we plan production? 2) Do we have to order in specific batch sizes? 3) Are supplies commonly on time, early, or late? 4) What are the bottlenecks ?
- 32. OPTIMIZER COST VIEW • Ability to build ahead only runner items as there is more certainty of demand Step3: Capacity leveling / Optimization 1) How often can we plan production? 2) Do we have to order in specific batch sizes? 3) Are supplies commonly on time, early, or late? 4) What are the bottlenecks ?
- 33. IBP SUPPLY CHAIN CONTROL TOWER Supply Chain Monitoring Enable supply chain professionals to navigate, analyze and profitably manage the end-to-end supply chain in real-time Integrated Business Planning (IBP) • • Increase end-to-end visibility Increase on-time delivery performance to customer Decrease overall inventory levels while reducing risk • • Increase supply chain agility and reduce supply chain cost User Experience IBP for sales & operations IBP for demand IBP for supply IBP for inventory IBP for response SAP HANA Platform Supply Chain Control Tower Step4: Review alerts & adjust supply plan 1) No end-to-end visibility 2) No on-time delivery performance 3) High inventory levels
- 34. ADVANCED ALERT MANAGEMENT • Alerts that were raised for stock outage or low stock can be monitored via the Monitor or Alerts app. Those are dependent on the user’s or company’s alert definition and thresholds. • Based on alerts, from concerned departments, the mid-to long-term plan can then be adjusted via the SAP IBP add-in for Microsoft Excel. • The outcome is a moderately constrained supply plan that takes into consideration, overall S&OP, inventory policies at all level of the supply chain.
- 35. IBP PLANNING OUTCOME IBP will be used in parallel with existing APO solution APO Responsibilities IBP Responsibilities Customer sourcing optimization Demand and supply planning including order generation Production scheduling and deployment planning Integration with ECC S&OP support tool, facilitate execution and data visualization What-if scenario modeling, including revenue and cost analysis Aggregate product line supply planning Tenets for parallel solutions: Supply optimization results in IBP must be as closely aligned to APO SNP optimization results as possible: Relative cost structure for optimization must be aligned Master data for supply chain network must be aligned
- 36. IBP JOURNEY – OVERALL IMPRESSIONS • User interface – both Excel and Web UI easier to learn than other traditional SAP applications • Merging supply chain, commercial and financial information can be challenging • Business needs to agree on fundamentals of how the data aligns between each group • Level of detail required by all groups needs to be considered up front to ensure proper design and configuration
- 37. IBP JOURNEY – OVERALL IMPRESSIONS • Data integration always takes extra time and refinement • Data modeling differences between IBP and APO to overcome • Some learning curve with aggregating/disaggregating planning views within • Data management can be underestimated – • • Need to consider full lifecycle of data in the design IBP is really both a planning tool and a reporting/analytics tool all in one
- 38. IBP JOURNEY – EARLY SUCCESSES • Excessive downtime issue was discovered and corrected within minutes in IBP. This allowed business to move forward in addressing capacity questions and building a scenario. Able to make quick changes to demand and see impact to supply which has saved hours of work for the Demand Planner. Completed several what-if analysis scenarios which provided very realistic output on impact to gross profit and results shared in Executive review process. Provided decision support on a project factoring in things like a new location, new demand, and sourcing changes. As proficiency continues to build expect to do scenarios and gross profit/margin analysis much more efficiently than in the past. • • • • • 24 “All in all we are feeling pretty excited about what we will be able to accomplish.” {Operational Planning Manager in XYZ INC}