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SAP IBP USE CASE SCENERIOS
Presenter: Ayan Bishnu
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.
AREAS ADDRESSED WITH IBP ( A HAWK EYE VIEW )
Operational Validation Demand Validation
Demand and Supply Review S&OP Meeting
IBP PLANNING ARCHITECTURE
Use of IBP for demand (demand sensing) with APO (DP and SNP)
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
XYZ INC DEMAND PLANNING FLOW
Step1:Gather & cleanse historic
data
Run or schedule thestatistical forecasting job for background
processing
Solve potentialissues or
inconsistencies within the
forecast and overwrite the
created values manually if
needed
Use the DemandPlan that is
generated in SAP APO DP for further
processingin APO SNP
Load historic salesdata and use SAP BW functionality & to correct outliers or substitute missing
values
Define the way theforecast 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
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.
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.
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.
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.
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.
BETTER FORECASTING METHODS
FeaturesDemand sensing algorithms (short termforecasting)
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 rulesUser 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)
orPick the best
Regression based algorithms: Multiple linear regression (MLR)
More flexibility & options in terms of Statistical forecasting & regression
based methods
MANAGING FORECAST MODELS
RUNNING FORECASTING IN EXCEL
IBP SUPPLY CHAIN CONTROL TOWER
Supply Chain MonitoringEnable supply chain professionals tonavigate, analyze and profitably manage the end-to-end supply chain in real-time
Integrated Business Planning (IBP)
••
Increase end-to-end visibilityIncrease on-time delivery performance tocustomer
Increased forecast accuracy. More accurate sales evolution reporting
•
• Increase supply chain agility and reducesupply chain cost
User ExperienceIBP for sales & operations
IBP for demand IBP for supply IBP for inventoryIBP 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.
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.
DEMAND SENSING FOR OPTIMAL BLENDS & BETTER PREDICTION
Weekly AdjustmentsOpen Order datacorrelationcorrections Output
Optimal blend by lag patternsBias Tracking
Controls
Intelligent forecast consumption logic
Optimal weightingand patternrecognition
Daily DisaggregationDaily outputs for executionsystems
Aggregated weekly or monthly values for planning and reporting
Bias and variability calculations
•
Forecast patterns•
Shipment patterns
•
Demand Signaldata 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.
DEMAND SENSING USING EXCEL
Navigation for demand Sensing Issues from the Fiori Launchpad
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
ABC GROUP DEMAND PLANNING FLOW
Step1:Gather & cleanse historic
data
Run or schedule thestatistical forecasting job for background
processing
Solve potentialissues or
inconsistencies within the
forecast and overwrite the
created values manually if
needed
Use the DemandPlan that is
generated in SAP APO DP for further
processingin APO SNP
Load historic salesdata and use SAP BW functionality & to correct outliers or substitute missing
values
Define the way theforecast 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
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.
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
ABC GROUP PAIN AREAS IN SUPPLY PLANNING
Step1:Inputs /
PIR from Demand module
Step2:Net
Demand Planning
(Unconstrained 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
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 (Unconstrain
ed Plan)
1) High or uncontrolled inventory levels.2) Inadequate customer service levels or inventory availability.3) Multiple planning and inventory target setting processes.
INTEGRATED INVENTORY KPI DASHBOARD
Step2:Net Demand
Planning (Unconstrain
ed Plan)
1) High or uncontrolled inventory levels.2) Inadequate customer service levels or inventory availability.3) Multiple planning and inventory target setting processes.
REPRESENTATIVE IMAGE
INVENTORY BUILT UP SCENERIO
Build inventory0
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 (Unconstrain
ed Plan)
1) High or uncontrolled inventory levels.2) Inadequate customer service levels or inventory availability.3) Multiple planning and inventory target setting processes.
SUPPLY SHORTAGE SCENERIO
• Business Event: Demand Loss or Production/Capacity Reduction
Production loss leading to drop in fulfilment
1
Production loss of 300 TPD0
DEMO SCENARIO
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 ?
PRODUCTION / RESOURCE VIEW
• Analyze Production Goods Receipt and Issue in Daily Buckets
• Ability to Review Resource Capacities and Consumption
WAREHOUSE VIEW
• Analyze Warehouse Goods Issue and Receipt along with Inventory Targets and Projections
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 ?
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 ?
IBP SUPPLY CHAIN CONTROL TOWER
Supply Chain Monitoring
Enable supply chain professionals tonavigate, analyze and profitably manage the end-to-end supply chain in real-time
Integrated Business Planning (IBP)
••
Increase end-to-end visibilityIncrease on-time delivery performance tocustomer
Decrease overall inventory levels while reducing risk
•
• Increase supply chain agility and reducesupply chain cost
User ExperienceIBP for sales & operations
IBP for demand IBP for supply IBP for inventoryIBP for response
SAP HANA Platform
Supply Chain Control Tower
Step4:Review alerts & adjust
supply plan
1) No end-to-end visibility2) No on-time delivery performance3) High inventory levels
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.
IBP PLANNING OUTCOME
IBP will be used in parallel with existing APO solution
APO Responsibilities IBP ResponsibilitiesCustomer sourcing optimization
Demand and supply planning including order generation Production scheduling anddeployment planning
Integration with ECC
S&OP support tool, facilitateexecution and data visualization
What-if scenario modeling, including revenue and cost analysisAggregate product line supply planning
Tenets for parallel solutions:Supply optimization results in IBP must be as closely aligned to APO SNPoptimization results as possible:
Relative cost structure for optimization must be aligned
Master data for supply chain network must be aligned
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
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 viewswithin
• 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
IBP JOURNEY – EARLY SUCCESSES
• Excessive downtime issue was discovered and corrected within minutes inIBP. This allowed business to move forward in addressing capacity questionsand 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 newlocation, 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}
CLOSING
Questions ?