optimizing manufacturing operations using big data and analytics

Copyright © 2012, Oracle and/or its affiliates. All rights reserved.1

Optimizing Manufacturing Operations Using Big Data and Analytics

Rajasekhar Katta, OracleRamasamy Palaniappan, FCS

Gareth Foster, Wm Morrison Supermarkets PLC


Agenda

Oracle BI Applications – An Overview of Oracle Manufacturing Analytics

Customer Success Story – Wm Morrison Supermarkets PLC


Oracle Business Analytics

IntegratedAnalytic

Applications

Any Data, Any Source

Full Range of Analytics

On Premise, On Cloud,On Mobile


BI Applications – Rapid Performance InsightCRM ANALYTICS

ORACLE BUSINESS INTELLIGENCE FOUNDATIONAND OTHER OPERATIONAL AND ANALYTIC SOURCES

SOURCE ADAPTERS:

SALES

• Pipeline Analysis• Forecast Accuracy• Up-sell/Cross-sell• Cycle Times• Lead Conversion• Sales Team

Effectiveness

MARKETING

• Campaign Effectiveness

• Customer Insight• Product Propensity• Market Basket

Analysis• Campaign ROI

SERVICE & CONTACT CENTER

• Service Effectiveness• Customer Satisfaction• Resolution Rates• Service Rep Efficiency• Service Cost• Service Trends

PRICE

• Price Segments• Price Waterfall

Analysis• Deal Life Cycle• Deal Desk Analysis • Product Pricing

Performance

LOYALTY

• Member Demographics

• Membership Trends• Promotion Cost• Promotion

Effectiveness• Points Analysis

ERP ANALYTICS

FINANCIALS

• General Ledger• Accounts Receivable• Accounts Payable• Cash Flow• Profitability• Expense Management

PROCUREMENT & SPEND

• Direct & Indirect Spend• Buyer Productivity• Contract Compliance• Supplier Perf.• Purch. Cycle Time• Employee Expense

SUPPLY CHAIN & ORDER MGMT

• Revenue & Backlog• Inventory Analysis• Fulfillment Status• Customer Status• Order Cycle Time• BOM Analysis

PROJECTS

• Project Funding and Budget

• Product Cost• Project Revenue• Project Billing• Project Profitability

HUMAN RESOURCES

• Employee Productivity• Compensation• Talent Management• Recruiting Analysis• Learning Analysis• Workforce Profile

MANUFACTURING

• Plan to Produce• Work Orders• Inventory and WIP• Quality• Resource Usage• Bill of Material• Costing • Kanban

ENTERPRISE ASSET

MANAGEMENT

• Maintenance History• Maintenance Costing• Asset Genealogy• Breakdown &

Preventive • Quality• Inventory

http://www.siebel.com/

http://www.sap.com/index.asp

http://www.peoplesoft.com/corp/en/public_index.jsp


Oracle BI ApplicationsDeeper than Dashboards

• Business Analytics Warehouse

• Over 100 star schemas

• Designed for analysis and reporting

• Over 9,000 metrics • Additional pre-

defined calculations

• Based on best practices

• Pre-mapped integration

• Fusion, EBS, PSFT, SEBL , JDE, SAP, IBM

• Role-based Security

• Over 500 Dashboards and Pages

• Over 3,000 reports• Across Lines of

Business

Pre-Built Analytic Warehouse

Best Practice Metrics

Certified App Integration

Role Based Dashboards


Oracle Manufacturing Analytics Overview


Business ChallengesDemand Uncertainty• How can I quickly respond to constantly

shifting customer demand?• How do I create a flexible production

environment that supports mass customization?

Operational Complexity• How do I simultaneously minimize costs and

ensure consistently high quality?• How do I optimize the use of resources while

balancing execution needs and production constraints ?

Quality Expectation• How can I quickly respond to quality issues

in manufacturing execution?• How do I reduce process variability?

Supply Chain Execution• How can I synchronize sales orders,

purchases, and production?• How can I increase inventory velocity &

customer service levels?

Your Company

Suppliers Customers


Issue Materials

Produce and CompleteBatch /Work OrderCompletion Date

Schedule ProductionPlannedStart Date

Release Planned OrdersRelease Date

ForecastCustomer Demand

Generate andapprove productionplan

Open Batch/Work OrderActualStart Date

Assign Lots

Sales Orders

Close Batch/Work OrderClose Date

Complete Operations

MoveCompletionsto Sub Inventory

ConsumeResources

How much did the planned production change between plans?

What % of the plan was executed as planned?

What is the current forecast and forecast accuracy?

What is the cycle time from work order release to actual start?

What is the variance in material usage?

What is the % of resource utilization by department?

What are all the finished product lots that consumed a certain raw material lot?

What % of Inventory will expire in the next 14 days?

What is the formulation yield for a certain batch?

Analyze work order cycle times

What % of the work orders started late?

Manufacturing Execution

The Need for Analytics


Manufacturing Execution

UpdateAR / GL

Capture Costs;Analyze VarianceProduce and

CompleteBatch /Work Order

Close Batch/Work Order

Complete Operations

The Need for Analytics

Standardize

Sample

Analyze

Disposition*

Report

Quality Open Batch/

Work Order

What are the test results by collection elements?

What are results by collection plan and specification?

What % of completions were scrapped and reworked?

What is the First Pass Yield?

What is the cost incurred variance by cost element?

What is the cost relieved variance by cost element?

Which GL Variance Account has the largest variance?


• Limited information on production attainment to plans, plant performance etc• Quickly identify exceptions in current performance and root cause analysis

to identify bottlenecks in the production process• Monitor and track resource and material usage and variances

• Need to balance customer service levels while minimizing inventory• Inability to anticipate stock-out & excess inventory situations• Lack of visibility into enterprise-wide inventory status• Track sales order fulfillment in conjunction with supply

• Poor visibility into production costs• Lack insight into reasons for cost variances• Identify causes for cost variances by cost element details and take

corrective action

• No knowledge of critical work orders that are stuck and need to be expedited• Little visibility into work order cycle times and work order aging of open orders• Track execution of “perfect work orders” that are on-time and high quality

Lack of visibility into plan to produce process to help eliminate bottlenecks

No insight into detailed production costs and cost variances

Unable to identify work order performance related to on-timecompletions and quality

Lack of Inventory Visibility

to Improve Return on Assets

Key Challenges

Examples


Oracle Manufacturing Analytics

Delivers an integrated view of planning, manufacturing execution, manufacturing quality and inventory builds

Summary level KPIs with drill down capabilities to identify exceptions

Cross-functional analysis capabilities with Supply Chain and Order Management , Procurement & Spend and Financial Analytics

Analyze current state manufacturing execution against targets and historical trends

– Track all major points in the process by work order & operation

– Track costs, quantities and amounts of usage

– Track dates between major points in the process

Oracle Exalytics and BI Mobile certified

Insight into the Plan to Produce Process


Big Data & Structured Data DiscoveryUsing Endeca Information Discovery


Manufacturing Analytics – Key Objectives and Questions by Role

ProductionExecutive/VP of Operations

Plant wide visibility into production execution against budgets and targets

• What is the production attainment for the current month?

• What is the planned production volumes for the next quarter?

• What are the bottlenecks in the current production process?

• How much revenue was lost due to rework and scrap?

ProductionCostAccountant

Complete visibility and tracking of manufacturing and inventory costs

• What are my cost variances at period close by cost element?

• What are my item gross margins?

• What are the trends in Manufacturing costs by Quarter?

• What is the value of Inventory on hand?

OperationsManager/Supervisor

Monitoring and controlling shop floor execution

• Are there bottlenecks on the production floor that is causing WIP inventory to build up?

• Are there bottlenecks on the production floor that is causing excessive production lead time?

• Is there excessive rework or scrap?• Is the actual production just the right

amount indicated in the production plans?

• Is there a shortage of resource that will cause production bottleneck?

Role Based Best PracticesProvide Relevant and Actionable Insight for Everyone


Manufacturing Analytics: Sample DashboardsPrepackaged Manufacturing Analytics

Manufacturing Executive Production PerformancePlan to Produce

Production Costs Inventory

• Overview• Operations

• Inventory• Demand Fulfillment

• Plan Attainment• Pegging Analysis

• Plan Comparison

• Overview• Trends• Balances• Aging

• Exceptions• Activities• Returns• Bill of Materials

• Overview• Variance Analysis

• Overview• Production Backlog• Material Usage• Resource Usage• Work Order Aging• Work Order Cycle Time• Production Quality


Manufacturing Analytics: Sample MetricsSample Analysis & Metrics

Production Execution Work Order Analysis Production Quality

• On Time Production• Production Past Due Backlog• Production Backlog• % Change in Production Quarter Ago• Resource Utilization• Material Usage Variance

• Work Order Age• # of Open Work Orders• Work Order Cycle Times• Start Quantity• Completed Quantity• Late Work Order %• Backlog Quantity

• Scrap %• Rework %• First Pass Yield• Test Quantity• Result Value• Consumed Quantity• Sample Quantity

Costing Planning Inventory

• Planned Cost• Actual Cost• Completions Cost• Cost Incurred Variance• Cost Relieved Variance

• Plan to Produce Linearity• Planned Amount• Production Attainment - Monthly• 0-15 days Demand quantity• 0-15 days Supply quantity

• Inventory Turns• Inventory On Hand Quantity• Obsolete Inventory• Expired Inventory• Expiring Inventory


How are we tracking to monthly production targets?

Are we producing to plan?

Are we producing on-time and with desired quality?

How much of production backlog is past due?

Are the Inventory levels aligned with demand?

Sample Dashboard


Oracle Manufacturing AnalyticsHierarchy of Metrics

Action Level

Metrics

OperationalLevel Metrics

Strategic Level MetricsGL Variance

Account

Work Order Cost Variance

Cost Variance By Cost Element

Standard Material Cost

Actual Material Cost

First Pass Yield

Scrap%

Rework%Scrap

ValueProduced

ValueWork Order Completions Qty Start Qty Scrap Qty

Production Linearity

Plan-to-Produce ratio

Service Level

Resource Utilization

Yield Variance

Late Work Orders%

Planned Value

Resource Cost Charged

Actual Yield

Formula Yield

# of Open Work Orders

# of Work Orders On-hold

Resource Time Charged

# of Late Work Orders

Drill t

o Det

ail

Identify Exceptions

Root Cause Analysis


Hierarchy of Metrics – Production Cost VarianceDrill from GL Variance Account to Work Order Details

Drill to

Detail


Oracle Manufacturing AnalyticsHierarchy of Metrics

Action LevelMetrics

OperationalLevel Metrics

Strategic Level Metrics

Demand Fulfillment Backlog

Inventory On Hand

Open Work Order Quantity

Planned Order Quantity

Production Attainment of Plan

Scrap Value

Produced Value

Work Order Completed

Quantity

Production to Plan Linearity

Sales Order Fill Rate

On Time Shipments

Production Backlog

Late Started Work Orders%

Planned Value

Ordered Quantity

Shipped Quantity

Planned Order QuantityWork Orders

Scheduled CompletionActual Completion

On Time Work Orders %

Work OrdersScheduled StartActual Start


Oracle BI ApplicationsCross Module Analysis

Manufacturing

Supply Chain and Order Management Analysis spans one or

more OBIA modules


Complementary Oracle BI Applications

Manufacturing Analytics

Oracle Manufacturing Analytics

Module Example of Cross-Functional Analysis

Supply Chain and Order Management Analytics

• Consolidate supply and demand to project fulfillment shortages• Sales Order to Work Order pegging

Procurement and Spend Analytics • Identify purchase order delays and it’s impact on production backlog

Financial Analytics • GL variance account drill down to work order details to analyze cost variance exceptions

Enterprise Asset Management Analytics • Provides visibility into spares inventory to analyze enterprise wide valuation of inventory

• Drill down from bottleneck resources to review planned and unplanned downtime trends for these resources


BI and EPM Practice Introduction

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Platinum Partner

Development Alliance Partner

BI Pillar Initiative Partner


Why FCS

• Oracle R&D co-development partner• Demand Signal Repository

• Oracle On-Demand partner• Largest BI Partner in North America• In house Exalytics, Exalogic and Exadata machines and CoE• #1 Oracle recommended partner for large Global deployments like

General Electric, Schlumberger, Emerson, Sony, Clorox, Activision

• Oracle R&D recommended partner for Manufacturing and EAM Analytics

• Deep domain experience in Oil & Gas, Industrial, Hitech Manufacturing, CPG


FCS BI Practice Summary

400+ Dedicated Resources

• 250+ successful live implementations• Tailored processes, templates and reporting for BI Apps implementations / upgrades• Technology Areas – OBIA, Informatica, OWB, ODI, DAC, OBIEE, GoldenGate etc.

Tools / Implementation Accelerators (FCS Innovations)o Products to fulfill OBIA gaps –Salesforce Analyticso BI setups using BI Configurator for Peoplesoft, JD Edwards and E-Business Suiteo Requirements Gathering using Business Requirements Generatoro Flexfields, Chart Fields, User defined fields setup using BI Flex Generatoro OBIEE Regression Testing using BI Assurer o BI, ETL data lineage using Path Findero Project Reporting on mobile using PMO Signal

Data WarehousingBusiness Intelligence ApplicationsOracle Business Intelligence Foundation

Platinum Partner

Development Alliance PartnerBI Pillar Initiative Partner

Oracle E-Business Suite Supply Chain ManagementOracle E-Business Suite Financial Management


Manufacturing Transformation at Wm Morrisons PLC

Discovery – Build vs. Buy

Implementation

Roll-out and Stabilization

User Adoption

New Plant Roll-out

Managed Services

Welcome to Morrisons ManufacturingAn introduction to all manufacturing divisions and sites.

•2nd largest fresh food Manufacturer in the UK• 18 manufacturing sites across the UK, & 1 manufacturing site in Holland• Plans for more sites• A unique ‘Vertical Integration’ business model

Morrisons Manufacturing

Morrisons•18+ Billion £Turnover for Morrisons Plc •FTSE 40 •562 Stores•130,000 employees

Drivers for Oracle BI Application•Single version of the truth

•Lots of data, but a lack of meaningful information

•Decisions made on instinct not facts

•Standardization - KPI’s not aligned across sites

•Time and effort spend on producing report rather than analysis

•Incorrect KPI’s that don’t drive the correct business behaviour

•Timely information

•Spread sheet culture

Process•Oracle recommended FCS - Teksystems as there was gap in Manufacturing offering with BI Application then

•Got the reporting requirements created across plants

•Evaluated different options – Build vs. Buy

•Decided upon Build and Extend - out of the box installation of Manufacturing Analytics with customisation leveraging FCS-Teksystems

•Built and tested the solution

•Trained users and rolled out solution across multiple plants

Key Areas of Focus

•Stock Holding

•Plan Attainment

•ASCP Plan

•Yield

•Variance analysis

•Lot Traceability

•Quality

•Usage Tracking

Reduction

•Stock Days reduced

•Reduction in working capital

•Reduced Wastage

Improvement

•Improved Freshness

•Increased flexibility

•Job enrichment

•Informed and timely decisions

•Promotes the right behaviour

Key Learnings

•Use standard reports where possible

•Consider end to end flow and not just reports

•BI is not an just IT project, it affect people jobs and the people element of BI needs consideration.

•If implementing BI and the vertical system only do business critical reports which are needed for day1.

•Have several smaller releases rather than one major release

•Have a clear business requirements

•Be flexible as requirements change.

Key Learnings

•Business engagement is essential

•Be aware that BI will need continuous development after the implementation

•Challenge requirements - ensure any requirements drive action

•Standardise requirement across business units

Future Plans•KPI relationships and cross functional working

•Integrate Manufacturing and Retail

•Near real time loads

•Integrate non EBS systems

•HR analytics

•Significant improvement in quality of Data and master data

•Logistics/ Capacity


Thank You!

Learn More:Oracle.com/businessanalytics

optimizing manufacturing operations using big data and analytics

Technology

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