Improving production and supply chain performanceCase studies from EY/P&G and client partnerships

Richard Goussard - EY

Supply chains are under pressure to reduce costs, but also to increase agility and responsiveness …

Dri

ve

rs

Internal cost structures challenged

Challenging opportunities in emerging

markets

Increasinglycomplex routes to market

External cost pressures growing

Limited volume growth

in mature markets

Digital is shifting control

to the consumer

Higher numbers of promotions and innovations to try and grow or maintain sales volumes –introducing volatility into the SC and increasing cost

Operating in large number of diverse, volatile markets with strong local preferences creates significant SC complexity.

Rapid pace of technology change requires companies to rethink product, packaging design, marketing and fulfilment

Consumers are utilizing multiple channels any time, any place -with limited loyalty.

Retailers are pushing for more service requirements, increasing SC costs

Input costs are volatile, rising and difficult to hedge against across a number of areas - commodities, labour, energy

Excess capacity in mature markets is decreasing SC efficiency.

Margin leakage throughout the value chain counteracts cost saving programmes

Ch

all

en

ge

s

Customerbehaviour is changing

Costs are hard to control

Growth is challenging

… but despite numerous improvement programmes, COGs and DIO performance is still poor

100

60

80

40

20

16012080400

COGS and inventory performance trend (2014*)

Foods Beverages

HPC Tobacco

Sports wear

CO

GS

% o

f N

et

Sale

s (

2014)

DIO (2014)

*

Average: 67.5

* LTM data as on Jan. 2015Source: CapIQ, EY analysis

62

63

64

65

66

67

68

44%

46%

48%

50%

52%

54%

2010 2014

D I

O

CO

GS

% o

f N

et

Sale

s

COGS % of net sales DIO

Average: 47.8%

Manufacturing performance has become even more critical to delivering business results

Current situation

Manufacturing and SC working together

Relatively stable end demand

But signal amplification compounds

erratic production

..leading to volatile

inventory

..aligned to semi fixed rhythm wheel

approach

Forecasting parameters changed \sales ‘trust’ production

Driving stability in operations and 28%

lower inventory

• Current manufacturing performance at many companies is an obstacle to optimising the supply chain, and achieving revenue and margin growth

• Majority still suffer from significant planning and execution issues

• The bull whip effect “noise”, even in vertically integrated companies, adds cost and complexity to operations

• Organisations have embraced various manufacturing excellence programs

• However, they are still struggling to make a sustainable breakthrough in performance

• Unlocking an additional +30% OEE productivity has significant value• $200-300m of cost saving

• Increased manufacturing flexibility and responsiveness to support sales growth

• Ability to re-balance the supply chain and reduce inventory

• Ability to streamline distribution networks

• Synchronization combined with improved manufacturing discipline typically delivers:• 30%-50% inventory reduction

• Up to 10% improvement in agility and OEE

Operational excellence requires an operating model underpinned by Integrated Work Systems, to drive reliable performance

• Asset Reliability Management

• Throughput Optimisation

• Integrated Planning & Execution

• Cost & Margin Optimisation

• Safety & Integrity Management

• Supply Chain Integration

• Contractor & Contract Management

De

sig

n Do you have the right operating

model to deliver your ambition?

Imp

lem

en

t Do you have the operational capabilities required to operate?

Do your people do the right

things, the right way?S

us

tain

Organisation& Roles

Processes &Procedures

People &Capability

Policies &Standards

Leadership & Governance

Technology &Systems

Metrics &Performance

GeographicArchitecture

Market / Commercial

Model

OperatingStrategy

Integrated Work

Systems

Many leading companies have Operational Excellence standards and management systems in place

BP Bosch Toyota Chevron Shell

Operations Management System

Bosch Production System

Toyota Production System

Operational Excellence Management System

Operational Excellence Standard

About P&G

Largest CPG Co in World

• Sales: More than $80 billion

• 142 factories globally

• 127,000 employees

• About 4.4 billion consumers

Average plant is 300 - 500 employees

• SKUS 250-5000

• Changeovers are our daily work

Complex chemical making and ingredient processes

• Powder Making & Blending

• Enzymes, Bleaches, Chemistry

• Stamping Extrusion and Molding

• Filling liquids, creams and gels

• Solids / Powers / Tabs

• High speed precision assembly, paper, plastics and metal

• Line Speeds from 100 – 3000 items per minute

The Brands

• Among the most trusted in the world

• 50 leadership brands

• 25 billion-dollar brands

• Market leader in two-thirds of the 21 categories that they compete in

Source: P&G

History and current results from P&G’s Integrated Reliability

1990 2000 2012

$ 20 B $ 41B $ 83B

Vicks

Norwich

Noxell

Blendax

Sundor

PUR

Max Factor

IAMS

Milestone

Tambrands

Clairol

Wella

Gillette

Ambipur

Striving to be global… Truly Global

167 plants 154 plants 142 plants

IWS is a global competitive advantage for P&G

• +20 yrs. investing in a customised manufacturing system combining Lean, TPM, etc including 3 years with Toyota

• “Cash positive” factories

• Back to original high OEE performance within 14 days of any line change

• Successfully deployed manufacturing system in a high number of acquisitions

Over the past five years...

• Achieved savings of $700 m

• Generated $1bn in cash

• In 3 years moved capital from 7.5% to < 5% of NOS

• Global factories at 85-94% OEE

Source: P&G, EY analysis

OEE = Overall Equipment Efficiency

IWS addresses both the hard and soft aspects of the business

• Initial operational performance analytics establish a sustainable baseline for informed decision making and prioritisation of efforts

• Stabilises operational conditions by working with Production by first addressing frequent, erratic failures before predictable ones

• Maximises throughput by optimising MTBF, OEE, and process reliability – usually by running slower but smoother

• Starting with Leadership, building individual and organisational habits to focus on increasing uptime rather than reducing downtime

• A unique “Operator Led” accelerated performance improvement approach combining best of P&G and EY

• Line continually reducing system failures and quickly responding when failures do occur using root cause problem solving creating a safer, more reliable operation

• Operating behaviours are improved, building a culture of high reliability. Behaviours include

• Basic care of equipment• Minor adjustments• Cleaning equipment• Look, listen, smell, and feel

• IWS is P&G’s operational work systems. IWS has been purposely designed to unlock the collective intellectual capability of the workforce in a standardised approach to deliver the needs of the business.

• The 11 pillars combine manufacturing ‘know-how’ of P&G as well as insight gained through advanced analytics and EY’s global manufacturing experience and capabilities

• RTT is part of the overarching principle of IWS

MTBF = Mean Time Before Failure

Realizing the benefits

Quality improvements

Consolidate volume within factory and

across the network

Improve agility and responsiveness across

Supply Chain

Increase capacity of constrained lines

Activation of employees

Benefit Realisation Levers

Impact of benefit realisation lever

• Reduce level of rejects• Reduce waste and spoilage

• Reduce complexity by reviewing sourcing profile within plant and across the network, close lines / plants

• Consolidate volumes of one kind of product at one plant• Bring volume from co-packers to plants

• Avoid CAPEX required on constrained lines• Reduce inventory by reducing the need for stock build• Improve service level by improving order fulfilment

• Operator led involved and self managed teams • Daily management systems• Stable supply and operations• Total employee involvement and ownership

• Lower inventory by reducing safety stock through improved reliability• Ability to have more frequent change overs without increasing cost• Reduced manufacturing lead times and batch sizes• Move to “cash positive” factories

Cost savings• Reduce temporary direct and fixed labour• Reduce utilities costs• Reduce maintenance costs

Achieving operational excellence has several benefits for the organisation

Case Study

Leading cigarette manufacturer

Implementation approach

Implementations so far… Key Success Drivers

• Cultural change from reactive downtime focus to a preventative and stability oriented approach

• Leadership support for the required behavioural and organisational changes

• Empowerment of Line Structure and Operators

• Focus on reduction of (unplanned) stops, not downtime

• Eventual OEE improvement through increased line stability

• Brazil

• Turkey

• Russia

• Switzerland

• Mexico

• Poland

• Singapore

• Germany

• South Africa

• Nigeria

• Korea

• Bangladesh

• Netherlands

• Indonesia

• Romania

• The manufacturers own improvement programme was supplemented with EY/P&G’s Run To Target

(RTT)

• Between October 2013 and April 2014, the manufacturer partnered with EY/P&G in a pilot phase (PoC)

to test RTT effectiveness; RTT was then rolled out to additional plants

• EY teams worked alongside the client teams throughout implementation

RTT Language and Methodology

• RTT is part of the overarching principle of IWS

• Servant Leadership

• Stops focused vs. downtime focused

• Proactive (anticipation) vs. reactive (firefighting); shift losses from unplanned to planned - then control and reduce

• Dedicated Line Structure to coordinate and prioritize efforts

• Daily Direction Setting meetings

• Daily focus on top 3 losses of previous 24h

• Shifts more traditional maintenance tasks to operators

• Builds technical mastery of equipment

• Daily Management Systems serve as permanent countermeasure

• Centerlines (CL)

• Clean, Inspect, Lubricate (CIL)

• Defect Handling (DH)

• Incident Elimination (IE)

• Breakdown Elimination (BDE)

• Rapid Changeover (RCO)

• Maintenance Planning & Scheduling (MP&S)

• Change Management (CM)

Key Objective: Improve line performance using RTT / IWS

Improvement in Unplanned Downtime (UPDT) is a critical enabler of creating a highly reliable culture, generating upstream and downstream SC predictability

• A key driver for MTBF improvement has been rigorous daily focus on elimination of Top Stops • The focus on eliminating Unplanned Downtime improved MTBF, Availability, and Reliability,

resulting in increased Throughput

Ongoing focus on Top Stops

Ongoing focus on Top Stops

Line # Baseline Final OEE Points Improvement % Improvement

5D 29% 19% 10 35%

5E 30% 9% 21 70%

5F 24% 15% 9 38%

Source: EY analysis

Example Implementation Results

PlantResults

MTBF Stops UPDT OEE

Country 1increased6.8 � 9.5

reduced1,111 � 792

reduced16% � 14%

increased60% � 64%

Country 2increased3.8 � 4.7

reduced1,797 �

1,618

reduced18% � 13%

increased56% � 63%

Country 3increased5.4 � 13.2

reduced959 � 267

reduced27% � 20%

increased61% � 64%

MTBF = Mean Time Before FailureStops = unplanned stopsUPDT = Unplanned Down TimeOEE = Overall Equipment Efficiency

• Reduction in the number of stops (planned and unplanned)

• Stabilisation of the production system

• Understanding of leading practice regarding line reliability OEE

improvement

Lessons Learnt

• The quality of the data is key to the project and needs to be accurate enough to provide a good basis for analysis

• Operators & Shift Team Leaders have to be involved from the start as they are the ones owning the results, and transmitting information to subsequent shifts

• Production rate is a sensitive topic in a lot of plants; leadership might refuse to stop production or reduce the rate of the line as required in some interventions

• Some upskilling is often required to improve technician capability, and computer literacy

Source: EY analysis

Case Study

Leading mining company

Findings ways to increase value chain throughput

• Client operates a full pit-port operation

• Value chain runs from multiple mines through to a port

• Production growth from 187Mtpa to 212Mpta, and then upwards

Supply Chain Process Model – Pit to Port

Reliability Simulation

Based on 30 years of statistical research, designed to effectively model complex processes such as FMCG production, high volume manufacturing, and mining

Pre-mature Competing Cause

Wear Out

Cumulative

Competing Cause

Understanding root causes of losses

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80

60

40

20

0

Close Coupled, Linear Decoupled, Surge, Parallel

Loss allocation

RE Improvement

One -Click

Competing Cause

Simulation

System Complexity

Downtime Analysis

MTBF

Prioritisation

Perf

orm

an

ce

Loss Tree

Pareto

Losses

Planned Losses• Planned Maintenance• Cleaning and sanitisation

Competing Events

Cumulative Events Some Unplanned Losses

• Breakdowns with or with no forced deterioration

• Material replenishment

Unplanned Losses• Usually all minor stops• Usually all process failures• Breakdowns with forced deterioration

• Using past performance data it is possible to create a model that allows EY to identify the potential performance of the mine and processing plant, based on a set of standard archetypes

• Inputs include:• Production Rate• Availability and Repair Time• Fleet Size• Transportation Parameters

• As the model includes all experienced variables from the operation, the potential performance becomes the ‘benchmark’ and the factors making up the gap become the outputs of the diagnosis

• Outputs include :• Size of the performance gap ($$s,

tonnes, recovery)• Barriers to performance• High level improvement plan

Fines TL

Coarse Ore Stockpile

Mainline Train

ShuttleTrain

Conveyor from ore beneficiation Plant

Lump TL

Ore processing

Source: BHPBIO

Ore processing operations

Ore processing analysis

Complex operation, representing almost 25% of site production

Analysis identified that ore processing accounted for ~80% of the bottlenecks on a daily basis

It set the following improvement targets

• OP: 5.4 Mtpa (11% ↑)

• TL: 29.8 Mtpa (57% ↑)

Mine Control increased throughput and capacity by improving standards and operating practices:

• OP: ~ 2-3%

• TL: ~ 20%

Sophisticated Reliability Technology analytics complemented this by identifying and delivering additional % throughput improvements

Ore processing (OP)Ore processing:

Theoretical limit = 8000hrs / yrAvailability = 75%Utilisation = 80%OEE = 68% (49 Mtpa)

Reclaimer:Theoretical limit = 8000hrs / yrAvailability = 90%Utilisation = 55%OEE = 55% (55 Mtpa)

Train Loading (TL)

Lump:Theoretical limit = 8000hrs / yrAvailability = 90%Utilisation = 20%OEE = 19% (25 Mtpa)

Fines:Theoretical limit = 8000hrs / yrAvailability = 95%Utilisation = 35%OEE = 30% (36 Mtpa)

Analysis of the value chain using Pit to Port simulation

A diagnostic tool was used to model actual and ideal performance of the operation, quantifying the gaps and identifying the key improvement areas

Competing Cause Plots INSIGHTAn estimated $ xx M incremental profit from improved

productivity at bottleneck equipment by embedding advanced reliability technology capabilities

Rate Reliability Optimisation

Analysis of the ore processing plantP

rob

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ipm

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(%)

Time (minutes)

MT

BF

Pro

cess

Re

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ity

Th

rou

gh

pu

t F

act

or

(%)

Base Target Rate

Throughput

Factor

10%

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40

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20Pro

cess

Re

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bil

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Th

rou

gh

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t

Fact

or

(%)

tonnes per hour

Legend

Process Reliability

MTBF (min)

MTBF (max)

$ xx M

Incremental

throughput (Mtpa)

Potential

Margin

Uplift

Throughput

(Mtpa)

Value chain scenario analysis highlights opportunities for increasing throughput

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Options to increase throughput (Mtpa)

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