Business Turnaround Strategies - SAIMM N T Bingudza.pdf · Business Turnaround Strategies. BINMAK...

BINMAK SOLUTIONSWe Deliver On Our Promise

Tirwirei BingudzaBINMAK CORPORATION

Business Turnaround Strategies


Investopedia

“A turnaround is the financial recovery of a company that has been performing poorly for an extended time.

To effect a turnaround, a company must acknowledge and identify its problems, consider changes in management, and develop and implement a problem-solving strategy”

Introduction to Binmak

Turnaround Strategy Steps

Operational Turnaround Strategies

Case Studies

Operational Turnaround Results

Agenda


The Binmak Solutions….

We partner with your teams to Define, Measure, Analyse, Improve, and Sustain Results Driven Operational Performance

We partner with your teams to ensure that the Right Work is done at the Right Time in the Right Way for predictable, consistent business results and to deliver to expectations

We partner with your teams and equip them to implement the World renowned ISO55000 Physical Asset Management Standard to reduce risk to the business processes by increasing equipment reliability.


Who We Are

The Binmak Solutions team has over 25 years of experience in the mining industry gained across diverse geographies, several commodities and various mining value chain steps. With significant experience in:

– Capital Project Management

– Integrated Business Planning

– Strategy Development

– Business Performance Improvement

– Physical Asset Management

– Information Technology Systems

The Binmak Solutions team brings:– A unique and powerful combination of expertise and experience.

– Broad, yet in-depth knowledge which gives us a holistic view grounded in solid experience

– Ability to help operations perform better and optimise capital and resource deployment

– International experience covering South Africa, USA, Chile, Brazil, The Philippines, The Republic of Ireland, Namibia, Botswana and Zimbabwe which gives us perspectives and insights that bring significant value to our diverse range of clients.


The Binmak Approach

Five factors differentiate Binmak Solutions:– Results as the means, as well as the end: We use progressive success to breed more

success while building confidence and capability of the client.

– Delivery of value – not just recommendations: We partner with our clients to improve Key Value Drivers.

– Speed used to mitigate risk: We help organizations improve performance in short time frames - often less than 100 days - and then leverage these achievements to inform larger transformations.

– Integrated approach across organisational hierarchy, value chain & disciplines: We work across the organisation in order to create broad ownership for the process, the results and for the changes that are critical to achieve desired outcomes.

– Development of our clients: We believe that sustainability depends on capability hence we strive to empower our clients through training and coaching.


Our Clients




Case Studies


Agenda


Turnaround Strategy Steps Define The Problem

– Define The Solution – Questions are the answers

Company Strategy– Vision, Mission, Values

Financial Strategy– Breakeven Analysis– Balance Sheet Restructuring– Free cashflow– Financial Forecast

Marketing Strategy– Revenue Streams– Client Retention.

Competitive Strategy– Competitive Analysis

Management Strategy– Rightsizing– Talent Retention Plan

Operating Plan– Performance Improvement


Strategy Review ProcessV

isio

n

Mis

sion

Internal Analysis

ExternalAnalysis

Resource/ Capability Linkage

Imple

mentatio

n

Goals

KeySuccess Factors O

bje

ctive

s

Strategy

Feedback & Control

Outp

ut


1

1

Business Portfolio (Illustrative)

Prospective Global Demand Growth (2007-17 CAGR)

(5%)

0%

5%

10%

15%

20%

25%

30%

0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0%

Copper

Nickel

Thermal Coal

Aluminium

Uranium Platinum

Group Metals

Diamonds

= Bubble Size Represents Avg. 2008-17 EP of c.$560M= Markets in Which Anglo Participates

= ‘Un-served’ Markets

Average GDP Growth

Gold

Silver

Zinc

Mineral

Sands

Seaborne

Coal

Seaborne

Iron Ore

41%

Rela

tive R

etu

rns


1

2



(5%)

0%

5%

10%

15%

20%

25%

30%

0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0%

Copper

Nickel

Thermal Coal

Aluminium

Uranium Platinum

Group Metals

Diamonds



Average GDP Growth

Gold

Silver

Zinc

Mineral

Sands

Met

Coal

Seaborne

Iron Ore

41%

High

CASH COW

Large +

Cash Flow

STAR

+ or –

Cash Flow

Low

DOG

+ or –

Cash Flow

QUESTION MARK

Large –

Cash Flow

Low High


1

3



(5%)

0%

5%

10%

15%

20%

25%

30%

0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0%

Copper

Nickel

Thermal Coal

Aluminium

Uranium Platinum

Group Metals

Diamonds



Average GDP Growth

Gold

Silver

Zinc

Mineral

Sands

Met

Coal

Seaborne

Iron Ore

41%

High Selectivity /

Earnings

Invest to

Hold

Invest to

Grow

Medium Harvest /

Divest

Selectivity /

Earnings

Invest to

Hold

Low Harvest /

Divest

Harvest /

Divest

Selectivity /

Earnings

Low Medium High


WHAT IS THE CORRECT MEDICINE?

Internal

Factors

External

Factors

Strengths (S)5-10 most substantial

internal strengths

Weaknesses (W)5-10 most serious internal

weaknesses

Opportunities (O)5-10 most important

opportunities

SO StrategiesStrategies that use

strengths to take advantage

of opportunities

(Growth)

WO StrategiesStrategies that take

advantage of opportunities

by overcoming weaknesses

(Turnaround)

Threats (T)5-10 major threats

ST StrategiesStrategies that use

strengths to avoid threats

(Diversification)

WT StrategiesStrategies that minimize

weaknesses and avoid

threats

(Defensive)


Business Operating System

Business

Strategy

Boundary

Control

System

Business

Control

System

Interactive

Control

System

Belief

System

Strategic control of a business cannot be achieved through performance measurement systems but through levers of control


Scenarios(Unknown Unknowns)

How to Compete

Business Planning

Business Operating System

Vision

Business

Strategy

Belief System

Strategy as a

Perspective

Boundary Control

System

Strategy as a

Position

Business Control

System

Strategy as a

Plan

Interactive Control

System

Strategy as

Patterns in action


17

Business Control System

Plan

Execute

Check

Act

Performance Targets

Operating Master Schedule

Production Strategy

Service Strategy

FinancialSchedule

Co

st &

Wo

rk

Ap

pro

val

Wo

rk P

lan

nin

g

Wo

rk S

che

du

ling

Wo

rk E

xecu

tio

n

Process Work Management

Social

Measure Performance

AnalyseImproveFeedback

Resourcing

Imp

rove

me

nts

/ A

dju

stm

ents

Bu

sin

ess

Exp

ect

atio

ns


18

Strategic ContextKnowing desired competitive position on cost curve is critical

Lion Story

MMX Corumbá SystemCloud Break/Christmas CreekSishenSerra Norte (Carajas) West Angelas

500

0

900800700600400

Yandi

100 300200

20

10

1,0000

80

70

FOB

Real Cost

US$/t

60

50

40

30

Mount Whaleback/OB 29,30

Tubarão Complex PelletsKhumani

1,100

Transport

Marketing Mining

ProcessingRoyalties

Pelletizing

Source: - AME 2010 FOB cost curve

Quartile 1 Quartile 2 Quartile 3 Quartile 4


1

9Source: - AME 2010 FOB cost curve

MMX Corumbá SystemCloud Break/Christmas CreekSishenSerra Norte (Carajas) West Angelas

500

0

900800700600400

Yandi

100 300200

20

10

1,0000

80

70

2017 FOB Real Cost US$/t

60

50

40

30

Tubarão Complex PelletsKhumani

1,100

Transport

Marketing Mining

ProcessingRoyalties

Pelletizing


Khumani

1,3001,200300

80

600

Area CSerra Norte (Carajas)

700

MMX Corumbá System

1,100

40

50

90

30

10

110

YandiTom Price

900 1,400400200

SishenMount Whaleback/OB 29,30

20

60

70

800 1,500

100

2021 FOB Real Cost US$/t

0

0 1,000500100

ProcessingRoyalties

Marketing

TransportPelletizing

Mining


Moves to third quartile ore cost curve by 2021


2

0

Confidential

Prospective Net Realised Turnover (2017)

Prospective Competitive Position

Mines are forecast to be at competitive parity in 2017, delivering 21¢/dmtu

FOB Revenue2

(¢/dmtu)

Production (M dmtu)

* Captures committed and probable seaborne production; Notes: (1) 59.4% lump and 40.6% fines with 64% Fe lump and 63.5% Fe fine; (2) includes product quality premiums and discounts Royalties are

included in realised revenue calculations, and excluded from business costs; (3) Effective tax rate of 36% assumed for Sishen and 33% for all other mines (4) Excludes China; Source: CRU

Q1 Q2 Q3 Q40

20

40

60

80

100

120

140

160

180

0 200 400 600 800 1,000

Kiruna

MalmbergetAlegria

Carol Lake

Mont-

Wright

Faleme

Simandou

Southern

System

Mt Newman

West Angelas

Caemi

Northern

System

Khumani

Casa de Pedra

MR Phase 1

Jack Hills

Area C

Sishen

Various CIS

Hope Downs

Ciudad Piar

Mount NimbaHamersley

Various India

Cloud Break

Sishen South

Mesa J

Zouerate

Yandi

MR Phase 2

Weld

Range

Sishen C-

Grade

Prospective Economic Profit (2017)

Production (M dmtu)

EP (¢/dmtu) Total EP: $21B

(Avg: 21¢/dmtu)

(50)

(40)

(30)

(20)

(10)

0

10

20

30

40

0 200 400 600 800 1,000

Northern System

Area C

Caemi

Hamersley

Jack Hills

Southern System

Mt Newman

Casa de Pedra

West Angelas

Yandi

Sishen

Hope Downs

Cloud Break

Ciudad Piar

Simandou

SEP 2

MR Phase 1

MR Phase 2

Faleme

Alegria

Mount Nimba

Carol Lake

Sishen C-GradeWeld Range

Mesa JKhumani

Mont-Wright

Zouerate

Various India

Kiruna

Malmberget

Various CIS

Sishen

South

SEP 2


EFFICIENCY VERSUS EFFECTIVENESS

Strategic Management

Effective Ineffective

Efficient

Inefficient

Thrive Die slowly

Die quickly Survive

Operational

Management

1 2

43


22

Building The Strategic Plan

Develop the Strategy

Strategic Analysis

Strategy Formulation

Plan and execute

Strategic Initiatives

Planning and resourcing

Accountability

Translate the Strategy

Map & Link to Goals

Set measurable objectives

Measure and set targets

Clarify the Vision

Mission, Values

Strategic Shifts (From - To)

Strategic Framework

Strategicplan

•Value gap•Change agenda•Vision

•Strategic issues•Strategy Direction•Strategic Themes

•Goals & Objectives•Measurement framework•Performance contracts

•Priorities•Resourcing•Initiative Teams




Case Studies


Agenda


Why Business Performance

Improvement?

“There is a Hidden Mine behind every mine. Effective Asset

Optimisation will unearth this Hidden Mine”

24


25

“If a company tells me they experience moving bottlenecks, my response is:

You have NO bottlenecks and most of your resources have at least 30%

spare capacity”

– Dr Eli Goldratt


26

“If you want to make money, ...

most of your resources MUST be IDLE from time to time”

– Dr Eli Goldratt


27

“A production chain with 80% availabilities can produce at

lower unit cost than a chain with 90% availabilities”


Business Performance Improvement

(BPI) Process


Value Creation Through Strategy Delivery

29

Value Waterfall

0.02

0.020.01

1.30

0.340.13

0.92

0.57

1.49

1.01

0.18

0.84

0.300.540.080.3620.0

19.5

19.0

20.41

19.87

Limpopo

Growth

Value ($bn)

0.05

Bene-

ficiation

0.32

2e

Footprint

19.94

20.77

TotalTotal

0.20

Solar

Project

19.96

20.98

Total

+1.78(+11%)

+2.02(+11%)

+0.57(+3%)

0.0

16.5

17.0

17.5

18.0

18.5

Northern

Cape

Growth

0.08

Kolo-

mela

Total

18.76

18.66

0.10

Logistics

0.10

Niche

Product

Strategy

Current

Ops

21.0

18.18

Thaba

0.05

AONew NPV

17.21

17.21

Prod

uctio

n

0.54

Budget

Changes

0.71

LOM

Changes

Q1’11

Price

Change

+ Macro

Econ’s

Current

NPV

16.40

20.5

18.18

Leg1: Current Operations Leg2: Value Chain Leg3: Growth Leg4: SD


Key Questions Addressed by Value Optimisation

What is the realistic business expectation?1

What is the realistic business aspiration?2

How should the asset be strategically managed to optimise value potential?

3

Is there material risk in delivery?4

What are the key risks faced by each asset?5

A Capability vs Budget: Determine gap between current

capabilities (C80) and Budget

B Likely production (C80): Level which will be achieved on

average with a confidence of 80%, assuming no changes to the

process

C Potential incremental improvement (P75): A production level

that could be achieved in the near future if the process is

stabilised and optimised (aspirational)

D Appropriate optimisation strategy for asset: Distribution

shape - Indication of required effort to improve output

Mean (C50)

AB C

D

E

E


Type of Intervention Required for

ImprovementAnalysis of the shape of the Capability Histogram may indicate where the process

resides on the Output/Effort curve and hence give an indication of the intervention

required and where the operation is relative to full potential


VariationHow did you do? What can the process do?


The key focus of value optimisation will be on stabilising the process to get predictable

and consistent performance

Change design or strategy

Focus on Execution &/or Resourcing

Asset strategies to optimise value…


Variation Range 3 to 4,

Average/Shift = 3.5

Variation Range 1,2,3,4,5,6

Average/Shift = 3.5

Key Learning:

• Coupled variation causes

constraints

• Process capacity causes

constraints

• Seldom does everything

‘align’ to give full potential

• Reducing the variation in

each process step caused

whole system to perform

significantly better

0

20

40

60

80

100

120

140

160

180

200

24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72

Simulation of Production: With Dice Output 1,2,3,4,5,6

0

20

40

60

80

100

120

140

160

180

200

24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72

Simulation of Production: With Dice Output 3 & 4


37

10Input Output

10

12

0

Pe

rfo

rman

ce

Time

Max

Ave

Min

Scientific Fact 1All Resources Fluctuate Over Time


38

Scientific Fact 2Interdependence Impacts The Whole Chain

The variations do not average out!

A B C ED FMineralResource

Product

StarvationBlockage X


39

Time

Pe

rfo

rman

ce

12

10

0

10 10

The poor performance of one link gets passed onto

the flanking link, and ultimately to the rest of

the chain


40

Time

Pe

rfo

rman

ce

12

10

0

5

10 10 10 1010 10

Combined Effect of

Variation and Interdependence


41

Time

Pe

rfo

rman

ce

12

10

0

10 10 10 1010 10

>25%

Combined Effect of

Variation and Interdependence


Appropriate and specific value improvement strategies will be determined for each asset depending on its position on the value optimisation curve

Roland

Hossy

Saffy

NewmanK3

Value Optimisation Strategies…

1B/4B

E3

E2


Tool set for analyses

Value Stream Mapping & Statistical Analysis (Process Capability, Paretos,

Control Charts, Constraints Analysis)

Throughput: Do we have a Rate or Operating Time problem?

Benchmark/

BACActualReduced

Advance/Blast

Reduced Blast

FrequencyReduced DOH Reduced Grade

Value Driver Analysis: Which are the biggest value levers?

Operating Profit ,Volume, Unit Cost, Sensitivity & Attribution Analysis

Performance Improvement: “The most powerful driver of better performance is better performance itself”


Output: Determination of full potential of

operations, summarized by 4 waterfalls...

34

21

Throughput (Mtpa)

BAC/

Benchmark

Potential

TonsDrill &

Blast

Load CrushHaul Mill Improvements

34

2

1

Unit Cost ($/t)

Plan/

BudgetBAC/

Benchmark

Actual BDPImprovements

3

4

21

Productivity (t/FTE)

Plan/

BudgetBAC/

Benchmark

Actual BDPImprovements

NPV ($m)

Full

Potential

Actual BDPThroug

hput

Plan/

BudgetUnit

Cost

Produc

tivity


Summary of AO Strategy in Action

45

Hauled

Tons

Truck OEE

Cycle Time

Empty time

Full timePayload

Fleet Size

Utilisation (DOH)

Operational

Delays

Actual

Benchmark

Engineering

Downtime

Actual

Benchmark

Shovel OEE

Drill & Blast

ProcessTransferLoadLogistic

sHaul

Theory of constraints tells us where to focus e.g. hauling

Value driver model tells us what to focus on within the constraint

Gap analysis vs. benchmark tells us how muchwe can improve

Target setting keeps us focused on delivery

Variance and Attribution analysis shows us the impact on business drivers

FY 2012FY Budget

YTD 2012

Cycles/HourDOHPayloadTrucks Fleet

YTD 2011

Performance excluding project

AO Benefit


Examples of Some of the Analysis

that will be Produced

34

21

Base Case

Capacities & Constraints

Best AttnCapacity

PotentialTons

Impact of interdependent variables(Example: Change drilling burden)

% Change in cost

% change in revenue

= Bubble size

equals NPV of

the specific

initiative only.

Not the

aggregated

value of the

initiatives

Initiative 2

Initiative 1

Base Case

% Change in cost

% change in revenue

= Bubble size

equals OP

impact of the

specific metric

only.

Not the

aggregated

Impact

Drill

cost

Labour

Cycle time

Lump/FinePayloa

d

Drill Yield

Plant YieldExplosive

s

Floor Stock

Load/ Haul

JIG/ DMS

Transfer Drill/ Blast

Focus on bottleneck

Attribution and Sensitivity Analyses to

determine focus areas and impact


Journey Towards Commercial

ExcellenceMigrate from Passive Marketing to Integrated Miner

• Long position for trader

• Value chain not fully optimised

• Limited emphasis on customer interface, i.e. uses agencies and deals with traders/merchants

• Value chain partially optimised

• Interfaces directly with customers – limited use of agencies and traders/merchants

• Small in house trading unit with limited scale

• Value chain mostly optimised

• Interfaces directly with customers - Trading unit sells all equity volumes

• Sizable fraction of 3rd party volumes sourced and traded

• Value chain fully optimised

Marketing functionshared with traders

Marketing optimisesphysical value chain

Primary focus of marketing

Model

Marketing maximises value of upstream assets

1 Passive marketing model

2Active Value-Chain Optimisation

3Customer centric marketing model

4Integrated miner-trader model

Marketing as important as mining and source of

profits on its own


Value potential of Asset Backed Optimisation

Basic trading levers with potential to lift HCCL's total value

175

150

125

100

75

50

25

0

Total

EBITDA

potential

67-125

More

sophist.

levers

Annual trading EBITDA ($M)

28-58

Initial

target

EBITDA

39-67

Long-term

sourcing

14-26

Freight

arbitrage

2-4

Geographic

arbitrage

18-30

Quality

arbitrage

4-7

First trading steps –

Basic levers only

Additional

upside

I

II

III

IV

Quality arbitrage – Blend different

coal qualities to match customer

needs and achieve higher net price

realisation

Long-term sourcing – Enter long-

term off-take agreement with smaller

producer at favourable price and

market its volumes on own account

Geographic arbitrage – Capture

regional price differentials by shifting

coal from low- to high- price markets

Freight arbitrage – Capture

differential between index-implicit and

real freight rates, eg. by switching

from FOB to CIF

II III IVI

ABO Concept


Value proposition for clients Value proposition for stakeholders

IV – ORGANISATIONAL RESPONSIBILITY AND CAPABILITY

Res

ou

rce

sFi

nan

cial

Clie

nts

Best price?C.1

Stak

eho

lder

s

Best quality?C.2 Best

delivery?

C.3 Best place to work?

S.1 Social compromise?

S.2

Environmental compromise?

CS3

xxx xxx xxxP4.1

xxx xxx xxxP4.2

xxx xxx xxxP4.3

xxx xxx xxxP4.4

Maximise Shareholder’s ValueF.1

Increase RevenuesF.2

Reduce CostF.4

Reduce RiskF.3

INPUTS INPUTS INPUTSOUTPUTS OUTPUTS

III. DELIVER ON GROWTH PROJECTS II. CAPTURE VALUE ACROSS VALUE CHAIN

Grow new production volume

P3.1

Increase pipeline value

P3.2

xxx xxx xxxP3.3

xxx xxx xxxP2.1

xxx xxx xxxP2.2

xxx xxx xxxP2.3

I. OPTIMISE VALUE OF CURRENT OPERATIONS

Improve operational efficiency

P1.1

Improve operational effectiveness

P1.2

xxx xxx xxxP1.3

Inte

rnal

Pro

cess

es

STRATEGY TRACKING USING STRATEGY MAPS




Case Studies


Agenda


Turnaround Strategy Implementation Strategy deliverables

– White paper– Strategy document– Long-term financial plan

Refreshing the Strategy– External Analysis

• World & Zimbabwe economic analysis• Medium and Long-term coal supply and demand• Updated short-medium and long term price line• Political, Legal & Regulatory Environment • Competitive environment, Suppliers, Buyers

– Internal Analysis• Operational Issues, Challenges & opportunities• Commercial & Marketing Issues and Opportunities• Updated project info• Risk management• Cultural assessment

– Emerging Strategy• Update HCCL strategy incorporating changes in internal environment• Derive plan for implementing strategy (KPI’s; Time line; Performance contracts)

Key Milestones– White paper– Department & HOD Workshops– Strategy document and Business plan– Long-term financial plan– Board Strategy and Risk Workshop


Key Success Factors

Senior Management Support

Dedicated Senior BPI Manager Reporting Directly to CEO/MD

Well resourced, Focussed Teams

BI & AM Skills Development and Capability Building

Expert Input, Support and Facilitation

Medium to long term commitment to transformation


Strategic Pillars


54

Need to move from 3rd Quartile of cost curve to

1st Quartile

Khumani

1,3001,200300

80

600

Area CSerra Norte (Carajas)

700

MMX Corumbá System

1,100

40

50

90

30

10

110

YandiTom Price

900 1,400400200

SishenMount Whaleback/OB 29,30

20

60

70

800 1,500

100

FOB

Real Cost

US$/t

0

0 1,000500100

ProcessingRoyalties

Marketing

TransportPelletizing

Mining

Source: - AME 2015 FOB cost curve



Financial & Management

Strategies

Balance Sheet Restructuring

– Liquidity & Operating Cashflow

Organisational Structuring

– Organising for success


Operational Performance

Improvement

Theory Of Constraints Production Flow

Rapid Results Implementation

Physical Asset Management Improvement


High levels of variation on a day to day basis at overall production

implies that substantial potential improvement can be gained by

stabilising the process.

Key area of opportunity going forward seen in reducing number of days

with zero production and narrowing the production range.

There is also a potential opportunity in reducing extreme swings in

production which currently ranges from zero to over 8,000 tons per day

Total Tons Produced

1

2 Production capability histogram skewed extremely to the left indicating

potential for improvement by shifting to the right.

Realistic budget for HCCL that can be achieved with 80% confidence

without change in process and practices is 16,214 tons/month and

37,230 tons/month with 50% confidence

Potential aspiration of 58,948 tons/month could be reached in 6-12

months with process improvements

Budget Confidence

1

2

Detailed capability and operational stability analysis indicated the confidence of delivering 2017-2021 Budget is

0% without substantial changes to current processes and practices. The analysis indicated that there is a huge

potential for upside performance improvement by stabilising the process, reducing variation, eliminating

interdependencies and creating predictable and consistent performance.

Operational Stability1

Daily Tons 2017 BudgetAug 2015 to

Dec 2016 MeanC80 Confidence P75

Monthly 100 000 37 230 16 214 0% 58 948

Quarterly 299 178 111 384 46 142 0% 176 358

Annual 1 200 000 446 760 194 562 0% 707 370

HCCLChabaCoalTons_CCDate between #08/01/2016# and #12/31/2016#

IndividualsSet 1: UCL = 11 381,54, Mean = 3 304,00, LCL = -4 773,54 (not shown) (2016/08/30 - 2016/09/25) (mR = 2) (Lloyd Nelson option)

UCL = 11381.54

Mean = 3304.00Daily Budget = 3 334,00

Daily Average = 1 474,10

Daily Capacity = 7 000,00

2016

/08/

01

2016

/08/

08

2016

/08/

15

2016

/08/

22

2016

/08/

29

2016

/09/

05

2016

/09/

12

2016

/09/

19

2016

/09/

26

2016

/10/

03

2016

/10/

10

2016

/10/

17

2016

/10/

24

2016

/10/

31

2016

/11/

07

2016

/11/

14

2016

/11/

21

2016

/11/

28

2016

/12/

05

2016

/12/

12

2016

/12/

19

2016

/12/

26

0

2 000

4 000

6 000

8 000

10 000

12 000

HCCLChabaCoalTons_OCHDate between #08/01/2016# and #12/31/2016#

Histogram

0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000

0

20

40

60

80

100

120

Mean =

1 4

74,1

05

US

L =

3334

Targ

et = 1

960

Basic Statistics

153 Data points

8 925Maximum

1 474,105Mean

0Minimum

Within 1 Sigma (e) 15,7%



Capability Indexes

0,491Cp

Specifications

3334Upper

1960Target


Histogram

0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000

0

20

40

60

80

100

120

Mean =

1 4

74,1

05

US

L =

3334

Targ

et = 1

960

Basic Statistics

153 Data points

8 925Maximum

1 474,105Mean

0Minimum




Capability Indexes

0,491Cp

Specifications

3334Upper

1960Target


Histogram

0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000

0

20

40

60

80

100

120

Mean =

1 4

74,1

05

US

L =

3334

Targ

et = 1

960

Basic Statistics

153 Data points

8 925Maximum

1 474,105Mean

0Minimum




Capability Indexes

0,491Cp

Specifications

3334Upper

1960Target


Histogram

0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000

0

20

40

60

80

100

120

Mean =

1 4

74,1

05

US

L =

3334

Targ

et = 1

960

Basic Statistics

153 Data points

8 925Maximum

1 474,105Mean

0Minimum




Capability Indexes

0,491Cp

Specifications

3334Upper

1960Target


Histogram

0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000

0

20

40

60

80

100

120

Mean =

1 4

74,1

05

US

L =

3334

Targ

et = 1

960

Basic Statistics

153 Data points

8 925Maximum

1 474,105Mean

0Minimum




Capability Indexes

0,491Cp

Specifications

3334Upper

1960Target


Histogram

0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000

0

20

40

60

80

100

120

Mean =

1 4

74,1

05

US

L =

3334

Targ

et = 1

960

Basic Statistics

153 Data points

8 925Maximum

1 474,105Mean

0Minimum




Capability Indexes

0,491Cp

Specifications

3334Upper

1960Target


Histogram

0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000

0

20

40

60

80

100

120

Mean =

1 4

74,1

05

US

L =

3334

Targ

et = 1

960

Basic Statistics

153 Data points

8 925Maximum

1 474,105Mean

0Minimum




Capability Indexes

0,491Cp

Specifications

3334Upper

1960Target


Histogram

0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000

0

20

40

60

80

100

120

Mean =

1 4

74,1

05

US

L =

3334

Targ

et = 1

960

Basic Statistics

153 Data points

8 925Maximum

1 474,105Mean

0Minimum




Capability Indexes

0,491Cp

Specifications

3334Upper

1960Target


Histogram

0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000

0

20

40

60

80

100

120

Mean =

1 4

74,1

05

US

L =

3334

Targ

et = 1

960

Basic Statistics

153 Data points

8 925Maximum

1 474,105Mean

0Minimum




Capability Indexes

0,491Cp

Specifications

3334Upper

1960Target


Histogram

0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000

0

20

40

60

80

100

120

Mean =

1 4

74,1

05

US

L =

3334

Targ

et = 1

960

Basic Statistics

153 Data points

8 925Maximum

1 474,105Mean

0Minimum




Capability Indexes

0,491Cp

Specifications

3334Upper

1960Target


Histogram

0 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000

0

20

40

60

80

100

120

Mean =

1 4

74,1

05

US

L =

3334

Targ

et = 1

960

Basic Statistics

153 Data points

8 925Maximum

1 474,105Mean

0Minimum




Capability Indexes

0,491Cp

Specifications

3334Upper

1960Target


58

SAFETY

Theory Of Constraints Operational Flow

Model for Open Cast Mining Operations

OverburdenRemoval

TreatCrushingLoad & Haul

Drill &Blast

Ore Body

ROMBuffer

Floor Stock

ExposedOre

PlantStock Pile

Flowing OUT

Flowing IN

PEOPLE Material MaintenanceEquipment Services

Total Subordination to the CORE PROCESS

Quality Quality

Slimes

Simulate - Measure - Improve

Product


Buffer of Blasted

Power Coal

Top Bench

Bottom Bench

HIC

Buffer of Drilled Blocks

Buffer of Exposed

Coal

Buffer of Blasted Substrip


Buffer of Prepared

Blocks

Buffer of Blasted Prestrip


Buffer of Marked & Prepared

Blocks

Drilled Meters

Drilled Meters

Tons Hauled

Tons Hauled

Tons Hauled

Chaba TOP HIC ROM Stockpile

Chaba HPS ROM Stockpile

Primary Tip Stockpile

Chaba Plant A Tons

Processed

Tons Hauled To Primary

Tip

Secondary Crusher

HPS Tons

ESC Conveyor

HPS Bunker

Buffer of ESC Bunker

Tons

Buffer of HPS

Stocpile

Bottom HIC NPD Stockpile

Bottom HIC NPD Tons

Hauled to No.2

J&F Bottom HIC NPD Stockpile

Chaba Bottom

HIC ROM Stockpile

Drilled Meters

Chaba Plant B Tons

Processed

Bottom HIC Peas Stockpile

Primary Crusher

HPS Tons

ESC Conveyor HPS Tons

Moved

Power Coal

Buffer of Blasted HIC

No.2 Processing

Washed Coal

Clean Coal Stockpile

Raw Coal Sales

Top HIC Peas

Stockpile

Buffer Of Diesel

Buffer Of Diesel

Buffer of Explosives

Buffer of Explosives

Available Materials

Top HIC Nuts

Stockpile

Top HIC Cobbles Stockpile

Bottom HIC Duff Stockpile

Top HIC Duff

Stockpile

Buffer Of Drill Steel

Buffer Of Drill Steel

Buffer Of Oil

Buffer Of Oil

Buffer Of Drill Bits

Buffer Of Drill Bits

iEngineering ServicesEngineering Services

Buffer Of Service Kits

Buffer Of Service Kits

Engineering Skills

Engineering Skills

Preventive Maintenance

Preventive Maintenance

Corrective Mantenance

Corrective Mantenance

HWANGE COLLIERY COMPANY LIMTED

TOC PRODUCTION FLOW SHEET

2017/03/22


Constraints (TOC) Analysis and Bottlenecks

Illustrative ExampleKOLOMELA DAILY WAR ROOM: Leeuwfontein

Block = One block of 40mx40m

Process (Rate) Process (Rate) Process (Rate) Buffer Buffer Buffer Process (Time) Process (Rate) Process (Rate)

Converted

Total Tonnes Buffer Buffer Buffer Process (Rate) Process (Rate) Buffer Buffer Process (Time) Process (Rate) Process (Rate) Process (Rate) Buffer Buffer Floor Stock Process (Rate) Process (Rate) Process (Rate) Process (Rate) Buffer Buffer Process (Rate) Buffer Process (Rate) Buffer Buffer Process (Rate)

Day Date Total DrillingTotal Load &

Haul (incl DH)

Total Tons

Ex-pit

Cleaned

Waste/Ore

blocks

Prepared

Drill BlocksStaked Blocks

Blocks being

drilled

KOLO Drilling

Meters

BC Drilling

Meters

Waste

Drilling

Tonnes (38t)

Drilled blocks

to be charged

Charged

blocks

Blasted

Waste

Tonnes

Load & Haul

Waste Tonnes

Cumulative

Waste Tonnes

Prepared

Drill BlockStaked Blocks

Blocks being

drilled

KOLO Drilling

Meters

BC Drilling

Meters

Ore Drilling

Tonnes (66t)

Drilled blocks

to be

charged

Charged

blocks

Blasted Ore

Tonnes

Load & Haul

DSO Ex Pit

Total

Load & Haul

non-DSO Ex

Pit Total

Lab:

Operat io ns

Samples

P ro cessed

Lab: Geo lo gy

Samples

P ro cessed

Finger Stock

A1 Tonnes

Finger Stock

A3 Tonnes

Primary

Crushing

Tonnes

Primary Stockpi le

Tonnes

Screen

Tonnes

Final Product

Lumpy

Final Product

Fines

Load Out

Tonnes

For the day For the day For the day Available Available For the day Available For the day For the day For the day Available Available Available For the day

For the

month Available For the day Available For the day For the day For the day Available Available Available For the day For the day For the day For the day On stockpile On stockpile For the day On stockpile Daily On stockpile On stockpile Daily

Target 2,899 143,000 30,501 10 8 1,815 616 92,378 1,400,000 89,001 4 468 0 30,855 400,000 26,101 2,901 33 50 400,000 200,000 30,000 12,000 30,000 250,000 200,000 30,000

Threshold 2,635 130,000 30,500 6 4 1,650 560 83,980 800,000 89,000 2 425 0 28,050 200,000 26,100 2,900 30 25 240,000 170,000 30,000 8,000 30,000 100,000 100,000 30,0001,140 1140

Day 1 Fri 01-Feb 4,070 109,719 23,235 5 2 3 5 1,686 2,354 153,520 4 4 949,000 61,404 61,404 0 2 0 30 0 1,980 3 1 10,106 13,129 23 25 716,938 259,964 36,519 33,661 0

Day 2 Sat 02-Feb 3,031 132,197 15,124 5 2 2 5 993 1,508 95,038 4 4 861,000 88,182 149,586 0 0 2 530 0 34,980 3 1 15,124 0 32 0 712,931 235,080 44,493 34,401 34,200

Day 3 Sun 03-Feb 1,576 153,394 12,591 5 4 0 5 331 0 12,578 4 8 752,000 109,221 258,807 0 0 2 1,245 0 82,170 3 1 515,000 12,506 85 36 0 682,710 233,719 44,869 7,000 41,741 128,222 142,125 34,200

Day 4 Mon 04-Feb 2,716 121,676 18,710 5 3 1 5 656 1,286 73,794 4 10 670,000 81,591 340,398 0 0 2 165 609 51,084 3 1 500,500 15,900 2,810 39 25 673,212 222,480 39,625 5,000 41,198 116,548 159,841 34,200

Day 5 Tue 05-Feb 3,634 99,760 30,274 8 4 1 4 1,694 1,030 103,512 1 13 603,000 66,427 406,825 0 0 1 0 910 60,060 4 1 470,000 28,649 1,625 32 25 673,755 222,324 35,722 1,000 39,859 127,030 170,500 34,200

Day 6 Wed 06-Feb 3,644 107,093 33,340 6 7 0 3 1,835 1,433 124,184 0 14 542,000 60,787 467,612 2 0 1 0 376 24,816 4 1 452,000 17,618 15,722 23 25 661,090 226,546 33,212 0 35,649 146,581 170,913 0

Day 7 Thu 07-Feb 2,817 97,897 23,244 5 7 0 4 200 2,016 84,208 6 0 1,007,000 74,653 542,265 3 0 2 601 0 39,666 4 0 590,000 4,333 18,911 9 25 661,090 226,546 0 0 0 146,581 170,913 34,200

Day 8 Fri 08-Feb 2,809 116,377 24,526 5 7 0 4 268 2,045 87,894 6 3 926,000 80,606 622,871 3 1 2 496 0 32,736 4 0 18,484 6,042 16 25 661,090 230,729 25,259 20,840 34,200

Day 9 Sat 09-Feb 2,663 100,676 26,456 2 3 4 4 990 1,341 88,578 6 3 867,000 59,463 682,334 3 1 2 332 0 21,912 4 0 17,483 8,973 36 25 661,470 229,249 36,709 2,000 32,701 34,200

Day 10 Sun 10-Feb 1,830 127,105 29,421 3 3 3 6 1,487 0 56,506 6 3 785,000 82,319 764,653 3 1 2 343 0 22,638 4 0 549,000 23,351 6,070 31 25 653,308 214,164 43,255 7,000 38,840 176,099 132,366 34,200

Day 11 Mon 11-Feb 3,383 103,653 29,181 3 7 0 4 1,310 1,096 91,428 2 9 719,000 65,817 830,470 0 3 1 161 816 64,482 5 0 529,000 20,594 8,587 24 0 652,559 206,258 35,228 9,000 33,171 127,963 154,682 34,200

Day 12 Tue 12-Feb 3,177 99,580 32,157 3 7 1 5 725 1,167 71,896 2 12 652,000 67,423 897,893 0 0 3 455 829 84,744 4 1 500,000 27,380 4,777 26 25 652,559 206,208 39,350 15,000 32,663 135,087 167,436 34,200

Day 13 Wed 13-Feb

Day 14 Thu 14-Feb

Day 15 Fri 15-Feb

Day 16 Sat 16-Feb

Day 17 Sun 17-Feb

Day 18 Mon 18-Feb

Day 19 Tue 19-Feb

Day 20 Wed 20-Feb

Day 21 Thu 21-Feb

Day 22 Fri 22-Feb

Day 23 Sat 23-Feb

Day 24 Sun 24-Feb

Day 25 Mon 25-Feb

Day 26 Tue 26-Feb

Day 27 Wed 27-Feb

Day 28 Thu 28-Feb

Responsible Person C hapman C hapman C hapman V ernon/ N elson V ernon/ N elson Jacques dL Jacques dL C hapman C hapman C hapman V ernon/ N elson V ernon/ N elson V ernon/ N elson C hapman C hapman V ernon/ N elson Jacques dL Jacques dL C hapman C hapman C hapman V ernon/ N elson V ernon/ N elson Jacques/ M art in C hapman C hapman Elisna Elisna C hapman C hapman J B reed t J B reed t J B reed t J B reed t J B reed t J B reed t

Frequency

10 20

14

8

5

6

PROCESSINGWASTE (Soft & Hard) ORE

8

5

Load & HaulStake

DrillingStake

ScreenPrimary Crushing

Presplit &

Buffer

TotalDrilling

Buffer Buffer Stake Buffer LabTotal Load & Haul Buffer Buffer Stake Buffer BufferDrillingLoad and Haul Lab Buffer Buffer Buffer Buffer BufferLoad-Out

BufferBuffer

200 000175 000

125 000100 000

250,000200,000

150,000100,000


TOC Production Flow Implementation

Daily Ops War Room

A Business Process with the objective of assessing the client's current asset management maturity against best

practices, as well as its asset performance against benchmarks. Recommendations are

made about improvement actions to address the main gaps.

Asset Management Improvement

4

4

Remove barriers to

performance

KPA: Asset Care PlansElement 1

Practice-Performance ModelAMI Approach


Asset Management Self

Assessment

Performance Measurement

Shutdown and Outage Management

Life Cycle Management

Support Facilities and Tools

Work Planning and Control

Defect Elimination

Contractor Management

Condition Monitoring

Maintenance Tactics

ERP Utilisation

Maintenance Management Strategy


0

1

2

3

4

5

BP and KPI MaturityBP Maturity

Excellence

Optimising

Preventing

Stabilising

Fire Fighting


Excellence

Optimising

Preventing

Stabilising

Fire Fighting

Fire fighting Stabilising Preventing Optimising Excellence

0

1

2

3

4

5

0 1 2 3 4 5

KP

I

BP

AM Maturity Assessment Summary

1. Strategy Management

2. Maintenance Tactics

3. Condition Monitoring

4. Work Management

5. Defect Elimination

6. Maintenace Facilities

7. ShutdownManagement8. ContractorManagement9. Asset Life CycleManagement10. ERP Utilisation(Ellipse)


Asset Management Priorities

Asset Life Cycle Management (LCM)– Restore critical production fleet capacity

– Mid-Life interventions for critical equipment

– Component Management

– Equipment lifecycle & deployment decisions

Set up a reliability department– Appointment of a Reliability Engineer

– Resourcing of the reliability department with the right skills

Organisational development– Resource the Engineering department with

the right skills

– Asset management training and coaching

Physical Asset Management Strategy – Formulation and implementation

– Communication and engagement

Physical Asset Register and Financial Asset Register Cleaning up, Updating, Structuring

Criticality Analysis: Equipment, Components and Inventory

Ellipse Implementation and Training

Work planning, scheduling and control

Work management and effective quality control

Maintenance Tactics selection for critical equipment

Defect Elimination

Establish SLAs with Key OEMs


100 Day Rapid Results Projects

A 100 day programme to kick-start the year long operational turnaround programme. The ultimate aim is to ensure that the right work is done at the right time and the right way by:

Mobilising & energising teams

Shifting the focus onto results ·

Empowering staff to unlock their full potential.

Delivering sustainable change.

Inspiring culture change & Motivation.

Driving innovation & employee ownership


Rapid Results Roadmap


Operation XXX

Winning the Hearts & Minds and Empowering our employees


Results Of Turnaround

Strategy On Production

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

1-Jan 1-Feb 1-Mar 1-Apr 1-May 1-Jun 1-Jul

Coal Production Tons 2017

Actual Budget




Case Studies


Agenda


Trucks & Shovels Performance Improvement

Project

Average Total Tons Handled/day

*OEE – Overall Equipment Effectiveness – Good OEE = 63%, Great OEE = 72%, Benchmark

OEE Improved from 51.1% to 64.8%

Total Tons handled increased from 218kt/d

to >300kt/d

Baseline Performance = 275t/day

Mining Target for with current fleet

and waste aspirations = 320kt/day

Focus for 2010 :

• Sustain the current performance of Trucks and Shovels

• Focus on Secondary Equipment to support

the Increase in OEE’s and fleet sizes of mining equipment

• Implementation of Tips of Mining now in implementation at

Drilling and Blasting (Pilot)

• Unmanned Equipment despite over compliment of staff

• Discipline – how should FLM address generic issues

• Mining Technical Training Program

150000

170000

190000210000

230000

250000

270000290000

310000

330000

Bas

elin

e

Mar

Ap

r

May

Jun

Jul

Au

g

Sep Oct

No

v

Dec

Jan

Feb

TTH Baseline 2 per. Mov. Avg. (TTH)

Baseline increased

with increase in Fleet


Drilling & Blasting Performance Improvement

Average Meters Drilled/day

*OEE – Overall Equipment Effectiveness – Good OEE = 50%, Great OEE = 65%, Benchmark

OEE Improved from 39% to

48.1%

Total average meters drilled

increased from 1598m/d to ~

2350m/d

PRODUCTION

DRILLS10001500200025003000

Bas

elin

e

Jun

Jul

Au

g

Sep Oct

No

v

Dec

Jan

Feb

Meters/Day Baseline 2 per. Mov. Avg. (Meters/Day)

Baseline increased with

increase in Fleet

Focus for 2010 :

• Consolidation of Mining Improvement Projects – Drilling &

Blasting pilot section for implementation• Unmanned Equipment despite over compliment of staff

• Discipline – how should FLM address generic issues

• Operators available to undergo the behavioral

workshops

• Block Preparation

• Critical Tasks BI Target = 2550 m/day


Initiatives Implemented• Increase Shutdown interval from 4 to 6 weeks, adding 6 prod. days = 240kt

(Changed chemical composition of Secondary Concave Liners)

• Increase Tertiary Crusher & JIG ROM Supply,by addressing screen efficiencies, liner life,secondary crusher settings and ROM

Quantity and Quality supply. Q4 2009 produced an additional 103.4kt.

• Improvements on JIG Level sensors in the hutch tank and reducing the vibration on pump pressure sensors reducing the

sensors replaced/m from 25 to 1.75.

JIG Plant Performance Improvement Project

JIG Module Run Hours per week

To Achieve budget of 12.6 Mt/pa we need to

have 19.9 Run hours/day.

To achieve BITarget of 13Mt/pa we need 20.5

run hours/day

10

11

12

13

14

15

16

17

18

19

20

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar

= Budget = BI Target

JIG product increased from 32.5Kt/d to > 40Kt/day

ROM Supply and throughput increased from 58.7 tot 61.2 kt/day

Run Hours of Jig Plant improved from 17.1 h/d to 18.9 h/d.

Focus Areas:Next generation of impprovment Projects to specifically increase

the Run Hours of the JIG plant to the Target of 20.5/day.

• Stackers & Re- Claimers

• Blockages

• Gates sticking & wearing

• RCA

• PAM Strategy


76

Implementation of volume growth projects and enhancing fleet efficiencies will reduce unit cost (ZAR Real)

Implementing volume

growth projects will

result in 9% reduction

in unit cost

219

201

192

150

160

170

180

190

200

210

220

230

240

2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

R/t

, R

ea

l 20

12

Sishen Mine - Growth and AO Impact on Unit Cost (FOR)

Sishen Mine, base After Growth Projects After AO

Growth Projects: SEP1B, Jig Discard, DMS Conc, Slimesdams Conc

Enhancing fleet

efficiency through

AO and phasing

out of contractors

evident from 2014

will further reduce unit cost by 4%

Asset Optimisation Impact on Unit Cost


Asset Optimisation Value Creation

Operating Profit $m Reported From Improvement Projects

16.80

70.00

17.403.40 1.00

16.80

12.701.90

0.0010.0020.0030.0040.0050.0060.0070.0080.00

DR

ILL

ING

MA

INT

EN

AN

CE

SH

UT

DO

WN

PA

YL

OA

D

JIG

MIN

I_T

T&

S M

INI_

T

D&

B M

INI_

T

SH

OR

TF

AL

L

TA

RG

ET

20

10

JIG

RU

N T

IME

TRU

CK

OEE

LOA

DER

OEE

PAY

LOA

D


How We Help

Strategy Review & Implementation

Business Performance Improvement

Asset Management Assessments

Turnaround Strategy Implementation

Business Performance Improvement Training

Asset Management Training

Integrated Planning & Execution


Thank you!

Business Turnaround Strategies - SAIMM N T Bingudza.pdf · Business Turnaround Strategies. BINMAK...

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