the bw and apo business solution succeeding in bw and apo demand planning integration

The BW and APO Business Solution

Succeeding in BW and APO Demand Planning Integration

Introductions

Gary SuteraGary has been involved in multiple full-cycle SAP Business Information Warehouse and

APO Demand Planning implementations and has witnessed the evolution of the products first-hand. He has 5 years of ERP and data warehousing implementation experience and 10+ years of industry experience in plant management, sales, and material maintenance. He has also been involved in numerous business process improvement and data warehousing endeavors. He is certified in BW 2.0 and 3.0.

Gary is the Business Intelligence thought leader for CoreVal, developing strategies and solutions to aid clients in data storage and reporting initiatives. He is a member of APICS and has become a skilled Value Chain analyst drawing on his years as a plant manager in the Packaging Industry and his many software implementations.

He has written several industry white papers on the evolution of BW, and the utilization of BW as a data warehousing solution. He has also engaged in business development initiatives, including demonstrations and presentations at several industry conferences.

Introductions

Jack SpringerJack has been involved in ERP consulting for the last seven years, assisting clients in

determining the appropriate solutions that deliver return on investment. Previous consulting projects have involved Business Case and ROI Rationalizations, business strategic planning, acquisition and divestiture strategies, project planning and management throughout the full SAP implementation cycle, including strategic planning, analysis, design, development, and implementation.

Prior to consulting, Jack has over 15 years of experience as V.P. of Finance and CFO in the Discrete Manufacturing and Retail industry sectors. He has worked in multiple computing environments. He possesses extensive functional expertise in financial, manufacturing and distribution systems in a variety of industries, including medical products manufacturing, discrete, repetitive and process manufacturing, consumer products, distribution, and others.

Jack has led multiple business process reengineering activities and ROI Rationalizations for initiatives during his career within industry and consulting. In Q1 of 2002, he was the featured speaker in the “Achieve Tangible Returns on Investment’ Summit, held in ten cities across the United States. This Summit was sponsored by Microsoft, HP and SAP.

Agenda

• IntroductionsIntroductions• State of Supply Chain AmericaState of Supply Chain America• Version and integration enhancements for

BW and APO• Case study

– Real Life Client Improvements – Alignment of Strategic Objectives to ROIC

Model • Questions and Answers

The Opportunity


Optimized Plant and Supplier Scheduling Optimized Plant and Supplier Scheduling

BusinessPlanningBusinessPlanning

Transportation Planning &Scheduling


ExecuteExecute

Sales & Ops Planning

DP Master

Scheduling

Demand/Supply

Network

Optimization

Production Planning

Business Opportunities

DistributeDistribute

ServiceService

Collect CashCollect Cash

• Integration from business plan to collection of cash

• Integration of business processes into SAP tool

Integrated, Aligned Collaborative Technology Tools

• Lower costs

• Customer satisfaction

• Correct inventories

• Process improvement

• Best Practices

• Enhanced forecast accuracy

State of Many Organizations






ExecuteExecute


DP Master

Scheduling

Demand/Supply

Network

Optimization

Production Planning


ServiceService


Excel Spreadsheets

SAP Core R/3

Pla

nt T

ools

Legacy Systems

Access Databases

The Solution


Holistic view of the organization

Process improvement mentality

Alignment of technology tools to support processes

– Core R/3

– BW and APO

–Non-SAP solutions

Utilization of KPM’s to measure improvement and performance

Total customer focus

Business Process Mindset

Elimination of Steps,

Activities and Non-value Add

System Alignment to

Business Processes

Agenda

• Introductions• State of Supply Chain America• Version and integration Version and integration

enhancements for BW and APOenhancements for BW and APO• Case study




Show of Hands:• Looking to implement both BW and APO• Have implemented BW; looking at APO• Have implemented APO; looking at full BW• Have implemented both APO and BW; looking to

improve

Our Focus Today






ExecuteExecute


DP Master

Scheduling

Demand/Supply

Network

Optimization

Production Planning


ServiceService


APO DP

APO Full Functionality


Application Overview

SAP BW:• Business Information Warehouse• Part of SAP’s Business Intelligence suite, along

with SAP Enterprise Portal

SAP APO DP:• Advanced Planner and Optimizer; Demand

Planning• Part of SAP’s Supply Chain Management suite,

including all other APO modules (SNP, PP/DS, TLB, TP/VS, gATP), Inventory Hub, and Event Manager modules


BW 2.0B

BW 2.1C

APO 3.0 (BW 2.0B)

BW 3.0A

BW 3.0B

X

X

X

X

X

X

X

X

X

X

X

X

APO 3.1 (BW 2.1C)

SCM 4.0 (BW 3.0B)

Integrated Compatibility

BW 3.1 Content X X X

Beginning with BW 2.0B, a stand-alone BW solution integrates with APO 3.0 and later versions


BW 2.0B

BW 2.1C

APO 3.0

BW 3.0A

BW 3.0B

X X

X

X

X

X

X

APO 3.1 SCM 4.0

Embedded BW Functionality Available

BW 3.1 Content

•SAP APO 3.0 contains an embedded SAP BW 2.0B

•SAP APO 3.1 contains an embedded SAP BW 2.1C

•SAP SCM 4.0 contains an embedded SAP BW 3.0B


Application EnhancementsSAP BW:• More robust integration with other SAP solutions• Better data management capabilities

– DB Connect– Open Hub

• Improved data optimization tools• Improved data presentation tools

SAP APO DP:• More robust automated forecasting tools• Collaborative forecasting• Improved use of BW functionality for demand planning


Example of Aggregated Forecasting


Integration Enhancements and Benefits:• Integrated data warehousing• Combination of structured and unstructured reporting• Quicker time to information• Quicker turn-around of demand plan to production plan• Faster S&OP process cycles• Streamlined business processes• Improved organizational communication• Data consistency• Web-enabled reporting


Landscape Considerations:• Performance

– Size of initial and on-going data loads– Timing of data loads vs. APO DP usage– Use of BW for overall reporting

• System Optimization– APO Demand Planning: forecast runs– BW queries: data retrieval runs

• Version Compatibility– Stand-alone BW vs. Embedded BW

Agenda

• Introductions• State of Supply Chain America• Version and integration enhancements for

BW and APO• Case studyCase study




Client Situation• It takes 2 weeks of each month to get through the Sales &

Operations Planning process• 7 plants, each doing their own forecasting, using

independent methodologies• Legacy mainframe, Access DB, and Excel are being utilized for

forecasting process• Many one-time reports are being created, with no regulation• No integrated data between sales history and forecasts• Each product line’s sales rep is updating their own

forecasts, with no consideration to common sub-products

• Excel forecasts are e-mailed into central location from individual sales reps

• No automated forecast tools are being utilized


As-is Application Landscape:

PlantsLegacy Mainframe

Sales

repsE-mail

Demand PlannersE-mail

Plants

Demand Planners E-mail

Sales

reps

E-mail

Excel

Access DB


Client Objectives• Cut S&OP process cycle time from 2 weeks to 1 ½ weeks• Consolidate forecasting of 7 plants into centralized

department – top down forecasting• Integrate current sales data with sales history• Automatically account for promotions in forecasting• Measure forecast accuracy against history• Implement a forecast model that takes trend analysis and

seasonality into account• Automatically publish demand plans to OLTP MRP and

production planning• Develop web reporting on company intranet of demand plan

versions, for sales rep updating


Solutions: driving a true picture of sales forecasting

• S&OP process cycle time cut from 10 days to 6 days• Each plant uses APO DP interactive planning within an

individual planning book, saved to liveCache• BW MultiCube is used to integrate current sales data, historical

sales data, and different versions of forecasts– Reports created to measure forecast accuracy and forecast trends,

with running timelines that point out seasonal trends• APO DP promotion functionality used• Central demand plan is automatically sent from liveCache to

R/3 MRP module• Executive-level reporting developed that highlights forecast

accuracy• Exception reports are sent to each plant that highlight cross-

plant forecasts of common products


New Application Landscape:BW APO

Interactive Demand Planning

Plant specific planning books

Reporting

R/3 Source System

Sales data

Plan data

MultiCube

Sales data

Reporting

Sales rep updates

Reporting

Unconstrained Forecast

Plants Sales

reps

Flat FileSales History On-going Sales

Demand Planners


OptimizeCash Flow

Foundation for Global,Integrated DW Environment

Optimize the S&OP Process

All initiatives, including APO and BW, should be able to support one or more of an organization’s strategic objectives or initiatives. Below is a representation of the Case Study Client objectives and the alignment of the APO benefits to the Objectives.

• Reduce the S&OP process from two weeks to 1 ½ weeks

• Vastly improved forecast accuracy

• Capitalize on the tight integration with Core R/3

• View Forecasts by Product Families, Geography, Business Unit over variable units of time

• Incorporate Promotions and seasonality adjustments into process

• Utilize integrated and consolidated forecasting techniques

Reduce excess inventory levels

Reduction of safety stocks

Identification of optimal inventory levels for products and customers

Strengthen the Balance Sheet

Correct utilization of plant and manufacturing assets

WEB based access, data creation and reporting

Consolidated data from multiple source systems

Multi-dimensional data modeling


Soft Benefits Achieved

• S&OP process cycle time cut from 10 days to 6 days• One definition of forecast accuracy company-wide• Optimized forecast process supported by technology• “What if” analysis and data versioning promoted many views

and considerations before conversion to the actual forecast• Automated, accurate and integrated forecast means a realistic

forecast• WEB based entry, reporting and analytics delivered efficiencies

in the sales force and analytics process


Invested Capital

Net Working Capital

Net PP&E

ROIC

Profit

Revenue

CostsSG&A

COGS

Inventories

Strategic Objectives: Optimize the S&OP Process

Optimize Cash Flow

Foundation for Global, Integrated DW Environment

Demand


Demand

Enabling Technologies ResultsMetrics Rationale

Constraints

BusinessProcess Enabler

SG&A

Increased revenue through increased customer fill rates and reorders

Forecast Accuracy measurement

Elimination of headcount

Interest Expense

Legacy maintenance fees

APO DP BW

APO DP BW

Forecasting Order

Fulfillment

Forecasting

Extraordinary demand variation

Forecast accuracy increased needed available inventory resulting in higher fill rates of 4% and average reorder cycle improvement of 16 days

Promotion functionality enabled more correct inventory builds for revenue spikes

Increased revenue of $9.6 million @ 32% margin generated realizable ROI of $3,072,000

Consolidated forecasting techniques will allow a centralized concept of forecasting, eliminating the need for personnel at all seven plants

Reduction of interest on inventory borrowing

Elimination of legacy forecasting & reporting

Elimination of (3) headcount (loaded) generates annual reduction of $215,000

Formula of 50% availability on inventory @ 7% = $238,000

Elimination of fees & support of $82,000

Execution of redefined, centralized forecasting process


COGS

Enabling Technologies ResultsMetrics RationaleConstraints

BusinessProcess Enabler

Inventories

Material cost & variance

Labor cost & variance

Expedited transportation costs (incoming)

Inbound freight/material acquisition costs

Inventory days of supply (Product, Group, Customer)

Inventory obsolescence

Material overstock Forecast accuracy

APO DP BW

APO DP BW

Forecasting Order

Fulfillment (Make)

Forecasting

False trends Promotion, trend analysis and seasonality functionality enabled planning and smoothing of production schedules reducing “surprise demand”. Expedited materials and packaging were reduced and O/T and outsource labor were reduced.

Decrease in raw material premiums and price variances of $380,000

Reduction of excess demand generated overtime and outsource premiums of $178,000

Expedited inbound freight costs were reduced by $20,000

Improved forecasting and demand planning resulted in decreased safety stocks carried by some plants

Significant reduction of obsolescence

Rationalization of inventory by product and customer

Net inventory reduction of 9% representing $6.8 million

Offline systems and processes

Change management required to trust and use new system


DemandDemand

SG&ASG&A

InventoryInventory

S&OP Cash FlowDW

Foundation

$3,072,000 $0 $0 $3,072,000

$215,000 $238,000 $82,000 $535,000

$0 $6,800,000 $0 $6,800,000

$10,985,000$3,865,000 $7,038,000 $82,000

ROI Summary

COGSCOGS $578,000 $0 $0 $578,000

Strategic Objectives

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Session Code: [204]

the bw and apo business solution succeeding in bw and apo demand planning integration

Documents

business strategic planning

project planning

business case

business intelligence

multiple business process

years of industry experience

evolution of bw

utilization of bw