A location specific model to determine the benchmark criteria for mining operations in Suriname.
"What are the factors that influence the ability to mine bauxite at a competitive cost per tonne"
by
DENNIS BRUNINGS
SURINAME 2008
“This paper was submitted in partial fulfillment of the requirements for the Masters of Business Administration (MBA) degree at the Maastricht School of Management (MsM), Maastricht, the Netherlands, March 2008”
Eartha Kitt
I dedicate this thesis to the memory of my mother, Hilly who already has received her “diploma”.
She inspired me to be hungry for education.
I am learning all the time.
The tombstone will be my diploma.
Acknowledgements
Realizing the risk of forgetting a name, I first want to acknowledge everyone who has supported me in the period of Jan 2006 to March 2008. Without your support, motivation and understanding it would not have been possible to bring up the discipline to go to class after work and to spent free time on studying and assignments. I am forever in your debt.
There are some people that I would like to thank by name.
Patrick Pengel my partner in arms who became my brother, motivating me to keep on going. I will miss the “speeding” to class and late night stress before an exam. Of course the brother/sisterhood within the posse of 35 calling themselves MBA IV has made those after work sessions bearable, fun and worthwhile. You guys & girls really are the best. Uncle Hans (Lim A Po) who never failed to be there when the discipline needed refocusing. I have deep respect for the effort and commitment that he puts in these MBA courses. It was BHPB management who created the opportunity for me to do this MBA. In this the personal interest of the Managers Rudolf Elias, Eddie Scholtz and John Sew Atjon in the progress I was making with the study was a great push to keep going. My friends Caroll, Madeley and Enid whom made sure I didn’t go nuts but at the same time prohibited many leisure activities that might have taken time away from study. To them I say, thanks, we did it, let the party begin. Then there was Tony (Eltringham) who’s insight in the benchmark theory helped me focus. Tony, the enthusiasm with which you helped me did put me over this last “hurdle”. I sincerely thank you for that. I also want to thank the “BIG” man out of Malta who somehow managed to get me to put this paper in the academic perspective that I learned during the MBA course. David (Dingli), the promptness and quality of your responses are truly benchmark performance.
Last but not least I need to acknowledge my dear mother, god bless her soul, who has raised me with one rule : “Learning is a treasure that will follow its owner everywhere”. Mum I hope to have made you proud today, as my treasure grew with an MBA
Dennis Brunings March 11, 2008
EXECUTIVE SUMMARY
This thesis deals with the question “how to set benchmarks” for the mining industry in Suriname.
First, through literature, it was determined what “benchmark” means. Together with field data this was used to prepare a model that would allow the mining industry to properly select and compare data from benchmarking partners in order to improve their performances
Literature learned that benchmarking is basically comparing to something known. This enables you to determine if you are on a higher, lower or same level. Benchmarking does not judge whether the position relative to the benchmark is good or bad. This is the second lesson out of the literature.
Benchmarking depends on interpretation. This leads to the third lesson that claims that in the (mining) industry benchmarking applies to performance processes.
In this thesis it becomes apparent that the term “best in class” therefore does not substitute for
“being a benchmark”. Best in class refers to the best results while benchmarking looks at the best processes. In other words a company may choose to benchmark its administration with another company that is doing less on the bottom-line but whose results for this specific process are excellent.
Most industry uses the best in class method to set key performance indicators (KPI’s) and targets which as this thesis will show is not the way in which to benchmark or to use it’s benchmark figures.
The model developed in this thesis assumes that the “benchmarker” has in-depth knowledge of its processes and the accompanying bottlenecks or constraints. It looks at each of the mining core processes and it gathers data that will allow the benchmarker to analyze gaps between own data and that of the benchmark partner. It will also assist in highlighting possible areas of improvement after which these areas can be prioritized and addressed.
Model was designed using data from the management of the BMS Kaaimangrasie mine operations.
TABLE OF CONTENTS
Acknowledgements ...3
EXECUTIVE SUMMARY ...4
TABLE OF CONTENTS...5
GLOSSARY...7
CHAPTER 1 INTRODUCTION ...1
1.1 General ...1
1.2 Observations ...3
1.3 Scope of research ...4
1.4 Structure of the paper...4
CHAPTER 2 Research Design...5
2.1 General ...5
2.2 Problem definition...5
2.3 Research questions...6
2.3.1 Main research question ...6
2.3.2 Central questions...6
2.3.3 Hypothesis...6
2.4 Research objective ...7
CHAPTER 3 Background information ...8
3.1 Current Mining at BMS ...8
3.2 Current Mining at Boddington...11
CHAPTER 4 Literature research...13
4.1 Benchmarking ...13
4.1.1 What is benchmarking ...13
4.1.2 The History of benchmarking ...14
4.1.3 Why Should Companies benchmark...15
4.1.4 What can be Benchmarked ...16
4.1.5 Limitations of Benchmarking ...16
4.2 Benchmark focus...19
4.5 Summary Literature research ...23
CHAPTER 5 Criteria for a mining benchmark model...25
CHAPTER 6 Model design...32
6.1 Cost-model ...34
6.2 Location specific Benchmark (LSB) model design ...37
6.2.1 The LSB model ...39
CHAPTER 7 Conclusions...46
CHAPTER 8 Recommendations...48
BIBLIOGRAPHY...50
APPENDICES ...52
APPENDIX A : Cost report comparison BMS mines ...53
APPENDIX B : LSB model...54
APPENDIX C : Benchmark Checklist...55
GLOSSARY
Definitions
This section is to ensure that it is clear how this thesis interprets certain words, concepts etc. Some definitions as interpreted in this thesis may differ from the explanation in common dictionaries. :
Benchmarking
The process of determining who has the best performance, who sets the standard, and what that standard is. This is done by a systematic comparison of organizational processes and performance to create new standards or to improve processes.
LSB model Location Specific Benchmark model for gathering and analysing data from Benchmark partners
Costmodel A model that indicate how cost are grouped. Focus is to identefy the corebusiness cost contributors
Refined Costmodel A cost model of which only the corebusiness costcontributors are defined.
Cycletimes The time it takes the hauling equipment to complete one full cylce of loading, hauling , dumping and back to the loading area.
Carryback % The percentage of the hauled capacity per truck that stays in the dumptray.
Abbreviations
This section is to clarify certain abbreviations that may not be used by the general public or which have a different meaning in this thesis.
BMS N.V BHP Billiton Maatschappij Suriname LSB model Location Specific Benchmark model
OVD Onverdacht
KG Kaaimangrasie mine
KB Klaverblad mine
CBO Coermotibo mine
ROM Run of mine
BH Bakhuis mine
mhrs Manhours worked
“The reasonable man adapts himself to the world; the unreasonable one persists in trying to adapt the world to himself. Therefore, all progress
depends on the unreasonable man.”
“There is probably no greater waste in industry today than that of willing employees prevented by insensitive leadership from applying their energies and ambition in the interest of the companies for which
they work”
George Bernard Shaw Maxim for Revolutionists Man and Superman, 1903
Pat Haggerty, 1964
Former President of Texas Instruments
CHAPTER 1 INTRODUCTION
1.1 General
The Bauxite mining industry in Suriname started 90 years ago and has always been one of the main generators of export income for the Suriname government. Traditionally mining was performed in the coastal area. Mining sites were around Paranam, where an alumina refinery has been erected and Moengo (Coermotibo) which lies towards the east border of Suriname (see figure #1).
Typically the bauxite mined contained high levels of available Alumina. This was needed because of the capacity / setup of the refinery. Therefore the enormous bauxite reserves in the (south) West, which contained relative low available alumina, were not mined. Technological development as well as recent upgrading of the refinery has led to Bauxite from West Suriname being attractive to process.
Figure # 1 Map of Suriname (incl bauxite mine locations),(source :R.Elias, Project director Bakhuis Project)
In the west of Suriname (300 km from Paramaribo, see figure#1) lies is an enormous bauxite reserve.
The challenges for mining this reserve are:
• To compete in the global arena the production cost must be at competitive levels.
• The distance from the refinery. How to transport the ore (by road / barge- pipeline, etc).
• As the mine is projected for 30+ years one must keep in mind: future mine planning, planning for labor and equipment, etc.
In the world of today “benchmarking” is a widely used term when talking about competitive performance and achievements. In the very competitive world we live in, companies often take to
“benchmarking” against the “best in class” as a tool to ensure that they remain competitive.
“Best in class” generally means having more favourable results then peers. Benchmarking on the other hand is comparing to the “best” you can achieve provided the circumstances that you are operating under. The latter is what this thesis will look at.
This thesis claims that currently BHP Billiton corporate management sets targets based on the
“best in class”. This results in targets for headcount, overhead cost, equipment, etc. It is therefore argued that setting such individual targets without taking into account the whole picture of all influencing factors is not correct.
Research was done into the possibility to create a model that takes into account certain factors which facilitate the setting of a realistic key performance indicators (KPI’s) to ensure benchmark performance.
Using the Brook Hunt “Bauxite and Alumina cost” database a cost curve (see graph#1) of the mines located in the western world was generated and analysed.
Because of sensitivity the actual $ values have been omitted.
This graph clearly indicates that the Suriname mines (except for Coermotibo) are higher up the cost curve which is not good for the competitive position. They rank # 4, 11 and 15 out of the 23.
Looking at the graph it is also not strange that the Boddington (#2) operation in Australia is perceived by BHPB management as to be the “Best in class”
Graph # 1 Brook Hunt “Bauxite and Alumina cost” ranking of mines
Cost Curve 2007 ($/t)
Kimbo Bodd
ington Hunt
ly
Kaaim angr
asie
Poços De
Caldas Kindia
Gove
Panchpatm ali
Willowda le
Bread nut Va
lley
Klaverbad
Mort as/Dog
ank uzu
Weipa
Paragom inas Project
Moengo- Coer
motibo Trombeta
s Bok
é
Lelydorp III Los
Pijiguao s
Disco very B
ay
Manche ster P
late au
Schwallenb urgh
Russell Pl ace Suriname mines
1.2 Observations
BMS is currently mining bauxite in Suriname and is part of a joint venture with Alcoa. The joint venture has proven a bauxite reserve of 300 million tonnes in the west of Suriname. As BHPB is responsible for the mining part of the JV it is their task to develop and operate the future Bakhuis mine. The mine design is based on so-called benchmarks that BMS corporate management has set.
As part of the local BMS management team the author of this thesis was confronted with benchmarks that were set based on results of other mines. Also in order to satisfy certain benchmarks this would mean not reaching benchmark performance in other areas.
Analyzing the Suriname situation certain factors are immediately clear. Suriname has:
• A lack of internationally qualified labour force (e.g. welders, train operators, heavy equipment operators, etc.)
• Shallow harbour
• Weak infrastructure
• Mine reserves in nature reserves, etc
It is reasoned that the ultimate performance will be a combination of different targets that are set for the different departments. These targets do not necessarily each represent a “best in class” but in the optimal combination lead to a benchmark mining performance with regard to cost per tonne bauxite mined. Support for this statement can be found in the discussions later in this thesis.
1.3 Scope of research
The research of this thesis has been conducted in the period September 2007 up to March 2008. The study is conducted within the framework of the master thesis project for the Master of Business Administration (MBA) at the FHR Institute of Social Studies in co-operation with Maastricht School of Management, with specialization Corporate Strategy and Economic Policy. The focus of this thesis is on the mining and transport of bauxite to the refinery. The result of this research is a model that will enable BHPB management to identify performance improvement opportunities and set the appropriate targets for the different processes (departments) in order to achieve an overall benchmark performance that should equal or surpass the production cost of the Boddington mine.
1.4 Structure of the paper
This paper follows the following structure:
CHAPTER 1, Introduction describes in general the scope and why the subject was chosen
CHAPTER 2, Research Design discusses the problem statement and research questions CHAPTER 3, Background information, deals with information about the bauxite mining industry in Suriname and in Australia. For the latter the focus is on the Boddington mine
CHAPTER 4, Literature research describes information from the resources used to gain knowledge on the subject matter. It also includes a summary of what was learned out of these resources.
CHAPTER 5, Assesses the criteria needed for designing a mining benchmark model CHAPTER 6 is where a Cost model and a LSB model are being designed.
CHAPTER 7 & 8 deal with the Conclusions & Recommendations
"What are the factors that influence the ability to mine bauxite at a competitive cost per tonne?"
CHAPTER 2 Research Design
2.1 General
In order to arrive at a “location specific benchmark (LSB) model” a research design was made and used as a guide for doing research.
2.2 Problem definition
It is obvious that operating in a country like Suriname is very different from operating in a country like Australia, South Africa or elsewhere in the world. Talking with expatriates that have work experience all over the globe it becomes apparent that :
• Culture of the labour force plays an important role. When operating as a responsible corporate citizen this needs to be taken into account.
• Lack of skilled of labour (and the available training capability) can be an issue. This will determine what you can do with them (with respect. to training) but also the amount of expatriates needed to do the job.
• Consideration must be given to the government, who is making laws and regulations and who normally issues permits etc. Just think of labour laws that limit work hours or that impose rates for overtime, etc.
• Technology in underdeveloped countries is often hard to come by or needs time to allow for adaptation.
• Supporting businesses needed for outsourcing non-core business often are non-existent or not up to standard, thus burdening the company with taking care of support functions such as maintaining housing facilities, transport departments, etc.
The problem that a multinational faces when running a subsidiary in a country as Suriname is to determine what performance is achievable. Hence, the problem definition is:
When these factors are known it is key to know how they rate against the same factors in other
achievable “KPI- level” is under the current circumstances but more important which factors to focus on (read manage) in order to improve the benchmark capability of the mining company in Suriname.
2.3 Research questions
Based on the problem statement and the scope of this thesis the research questions were formulated.
2.3.1 Main research question
Earlier discussions already revealed that for benchmarking it is a prerequisite that the processes being compared are comparable (popularly stated : one must prevent comparing apples with oranges). Therefore determining what to benchmark and then benchmark it to the “comparable”
best in class should be the intent. In the mining industry the most common KPI used is cost per tonne of bauxite. This means that the main research question for this thesis is :
“Which factors affecting the cost per tonne bauxite mined is location specific?”
2.3.2 Central questions
To reach an academic conclusion this research is conducted through the following questions:
1. What determines/ makes up the mining cost of BMS?
2. What determines/ makes up the mining cost of Boddington mine?
3. What is the difference gap between the two?
4. How does this relate to the location (e.g. Suriname/ Australia)?
5. How does the benchmark theory apply to each?
2.3.3 Hypothesis
With mining as the core business, performance of all other (none core) cost contributors should become visible. This because they directly impact it.The hypothesis therefore is:
“Proper benchmarking of the mining industry in Suriname should focus on the core business processes taking into account location specific factors instead of stating “best in class” figures for the key cost contributors.”
2.4 Research objective
The research objective assumes that
• The basic mining, meaning removing ore out of the ground can be seen as pretty standard.
• Location specific aspects influence: availability of equipment, labor, laws, etc, the way the operation is run and how it ultimately performs.
• The requirements of the companies shareholders : zero harm and maximum ROI ( read lowest cost/tonne bauxite mined) are universal.
To make proper business decisions it is imperative for management to make a sound and practical judgment of a mining operations capability and or performance.
Therefore the research objective is:
“Design a model that takes into account location specific factors that influence the operation and allow for comparison to other locations for benchmarking purposes”.
The LSB model should enable BHPB management to get an insight in what processes to improve in order to reach benchmark performances which should result in the most profitable cost per tonne mined.
CHAPTER 3 Background information
3.1 Current Mining at BMS
Currently, Bauxite is being mined by BMS from 3 Mines:
• Coermoribo (CBO). A mine in the north east from Suriname. This is a “depleted mine”.
However the mining team keeps finding pockets of ore suitable for “remnant” mining. CBO has challenges such as (but not limited to)
o Mine is located approx. 150km from the refinery. This means staff has to be housed in a company operated village.
o Ore transport from mine to refinery is done by barge
o Remnant mining entails very scattered operations hence having a negative impact on equipment utilization and employee productivity.
• Kaaimangrasie (KG). This mine is located approx.27 km from the refinery. It is a new mine that only came online in 2006. The challenges for KG are but not limited to:
o Relatively small reserve meaning investment must be depreciated over a very short period, increasing the cost per tonne mined.
o Long haul needed to transport the ore to the refinery. This has demands for equipment numbers as well as safety considerations.
• Klaverblad (KB). This mine is located approximately 12 km from the refinery. It is also a new mine that came online in 2007. The challenges for KB are but not limited to
o Relatively small reserve meaning investment must be depreciated over a very short period, increasing the cost per tonne mined.
o Ore body is next to and partially under the Suriname river. This created a need to build a cofferdam. This means extra cost that needs to be depreciated over a very short period.
o Working under the water level of the Suriname river poses safety risks for which mitigation is very expensive ( e.g. elaborate pumping equipment and schemes).
To illustrate the remarks regarding the depreciation that must be taken into account see the following table (table # 1). Because of confidentiality issues the numbers have been multiplied by a factor.
Table #1 Cost comparison for BMS mines
Name Cash Cost (C1) ($/t) Depreciation ($/t) Full Oper.Cost (C2) ($/t)
Kaaimangrasie 5.9 7.2 13.1
Klaverbad 9.2 14.0 23.2
Moengo-Coermotibo 12.3 1.3 13.5
Looking at table#1 the argument of this thesis is being illustrated. Looking at the full operating cost alone one would tend to classify Klaverblad mine as the most expensive operation. Being 71 % more expensive then Coermotibo. However when we take into account the high depreciation rates that they have to pay and also take into account that Coermotibo is an “old” mine with a low depreciation then the conclusion will be different. Without depreciation it appears that Klaverblad outperforms Coermotibo. The Coermotibo operation in this case is 33% more expensive then the Klaverbald one. Operational wise depreciation can not be influenced and therefore not taken into account when evaluating the operational performance of the mine.
Mining
Mining of course starts with locating the ore and doing studies on the feasibility of mining that ore.
As those cost are normally not carried forward in the later cost / tonne mined it will not be further discussed. As soon as a decision is made that mining the ore is feasible the mine can be built. In Suriname this often means activities in the middle of the jungle that is most of the time hardly accessible (see picture#1 ). This is of course a cost issue as resources in these areas are very scarce and all has to be brought to the field
Figure # 2 : Suriname river – SM project; Coermotibo deepseated; Safety dept BHPB-BMS 2005-2006
The nature of the Amazon rainforest which is typical for Suriname is so demanding that either special equipment is needed or that the used equipment is challenged to the max (See pictures #2).
Note in the pictures below that a normal pickup truck, needed to be fitted with “snow tracks” in order to reach remote areas
Figure # 3 : Rac A Rac SM project; Road to KG; Safety dept BHPB-BMS 2005-2006
And then when you finally manage to get into the jungle you are faced with the wild life (see pictures #3). This poses both a safety risk as well as an environmental risk. Mining nowadays can only be done profitably ( because of image and legal implication) if it is done in an environmentally friendly manner. Elaborate biodiversity, rehab and closure plans are needed to ensure this.
Figure # 4 : Kanknatrie north; Bakhuis camera trapping; Environmental dept BHPB-BMS 2005-2007
When all these challenges are met the miners enter with their equipment and start mining. All mining currently done in Suriname as well as projected for the future is done by a “truck and shovel” operation. This means that after the mine area has been prepared the ore is lifted out of the ground by blasting. The separated ore is then loaded using shovels into trucks that transport it to an intermediate stockpile. Different grades of bauxite are stocked in such a way that blending of grades is possible. Depending on the grade requirements of the refinery “highway trucks” are loaded with the correct grade and transport the ore to the crusher which then crushes the bauxite and feeds it to the refinery. Picture #4 depicts the Mining process as done by BMS
Figure# 5 : Mining at BMS , Info presentation BHPB- BMS CSR dept 2007
3.2 Current Mining at Boddington
Boddington is 123 kilometers south-east of Perth, in Western Australia, and is the nearest town to the Worsley Alumina bauxite mine (see figures 6 & 7).
Figure 6 : Map of Australia (circle and arrow detail location of Boddington) Figure 7 : Overview Map detailing boddington mine location
More than 1200 people are employed at the mine site and refinery. Many more jobs have been created through the employment of sub-contractors and through the support of local businesses and suppliers. The company is also an active supporter of local community projects and programs.
The mine site is 51 km from the refinery and the ore is being transported overland with a conveyor- belt system. Worsley's overland conveyor system is one of the longest of its kind in the world and is a result of a unique engineering approach by Worsley Alumina and the UK company Cable Belt.
The 51km system contains more than 200km of wire rope (drive cable) and approximately 100km of rubber belt. The decision to use a conveyor to transport bauxite from the Boddington mine to the refinery was made after studies of alternative transport costs, energy use, environmental factors and maintenance. The conveyor consists of two flights - the first is 31km from the bauxite mine to a transfer point and the second is a 20km flight to the refinery. The dog-leg shape avoids an area of forest with a high conservation value.
Both flights follow the natural topography as closely as possible, dipping into valleys and crossing rivers. It is also raised in parts to allow native animals to migrate underneath.
The system operates on a continuous basis with planned breaks for maintenance, and travels at a speed of 26km/h. It carries 2700 tonnes of bauxite per hour and conveys 12 million dry tonnes per annum. The belt rests on two 57mm steel cables and the motors at the end of the conveyors drive the cables. The cables pass over 68,000 polyurethane pulleys.
During operating hours the conveyor is patrolled by teams in 4WD vehicles. Their duties include monitoring and reporting on the condition of all components of the system. When the system is not running, the power is shut down to allow maintenance and repairs.
The conveyor is contained within a 35m wide corridor, along the full length. Also confined in this corridor are a sealed service road, power line, optical fiber communication system, 22 tunnels and 10 bridges.(Worsley website accessed Nov 2007)
CHAPTER 4 Literature research
4.1 Benchmarking
The license to operate for any company is its ability to provide it’s stake holders with a profitable return on their investment. In the past businesses could rely on loyalty from shareholders for several reasons such as family ties, being the only investment option, etc. Now however it is the bottom- line and image that are the determining factors. Shareholders invest their money in companies that provide a reasonable return. On top of that shareholders expect companies to uphold a certain image that will not harm them if they are associated with it. Globalization has provided a global arena where they can invest their money. For businesses, staying ahead of competition and meeting demand became a way of live. Staying ahead of competition has become a prerequisite for companies who want to survive. However this is easier said then done. In the past it was just making sure to stay ahead of the local competition. The focus was on customer retention. Because of globalization competitors now may be operating from a location thousands of miles away while at the same time the customer may be right next door to that competitor who’s thousands of miles away. The solution to this situation was easy to think of “be better then the rest”. Businesses now had to identify the best in class and aim at out performing them. This is the basis for
“Benchmarking” as used in this thesis. Note of caution: this does not implicate that
“Benchmarking” and “best in class” are synonyms. This thesis argues that that is not the case.
4.1.1 What is benchmarking
The term 'benchmark' presumably originates from the practice of making dimensional height measurements of an object on a workbench using a gradual scale or similar tool, and using the surface of the workbench as the origin for the measurements.
In surveying, benchmarks are landmarks of reliable, precisely-known altitude, and are often man- made objects, such as features of permanent structures that are unlikely to change, or special- purpose "monuments", which are typically small concrete obelisks, approximately 3 feet tall and 1 foot at the base, set permanently into the earth.( Wikipedia, the free Encyclopedia accessed August 2007)
Thus enabling one to determine whether or not another position (point) is higher or lower then the
Figure # 8: A benchmark
The traditional definition of benchmark in the dictionary(Merriam Webster’s online dictionary): 1. a mark on a permanent object (see picture) indicating
elevation and serving as a reference in topographic surveys and tidal observations
2. a point of reference from which measurements may be made
3. something that serves as a standard by which others may be measured or judged
4. a standardized problem or test that serves as a basis for evaluation or comparison (as of computer system performance)
This thesis defines benchmarking as :
Benchmarking is the process of determining who has the best performance, who sets the standard, and what that standard is (F. John Reh). This is done by a systematic comparison of organizational processes and performance to create new standards or to improve processes.
4.1.2 The History of benchmarking
Benchmark has become a household name in the industry and is associated with performance.
Benchmarking is considered to be a systematic comparison of organizational processes and performance to create new standards or to improve processes. Even though this seems easy enough the challenge lies in what (whom) to use as a benchmark-partner.
This interpretation of Benchmarking dates back to the 1950’s when Japanese engineers went to trade shows and were seen taking notes and pictures. It wasn’t until the 1970’s that the seriousness of this became apparent as the Japanese products started to get universal acceptance and seriously competed with the market leaders of that time.
One of the most quoted examples is that of the Xerox company who had its copiers challenged by those of Canon Inc. In reply Xerox worked on improving its manufacturing techniques to increase their efficiency (productivity). In doing so they used ideas and techniques that originated from their
competitors. Xerox succeeded in determining where their competitors’ strengths lay and then copied and, if needed, improved them. As Xerox achievements got more attention, so did the benchmarking.
It was realized that it was no longer to use “yes but..!!!” as an excuse to explain or deny the reality.
Instead it was needed to find out why , how, where and when the competitor was outperforming.(Presentation, Tony Eltringham)
4.1.3 Why Should Companies benchmark
If the standard is not known you cannot compare yourself against it. You also have to know where your competitors stand. If the company against whom you are competing is able to produce at a lower cost it is easy to see who will be favored by both customers and investors. Both of whom are critical for survival of a business.
A further justification for a benchmarking activity comes from the requirement to keep on improving to match the changes that are occurring. It is in fact probably the most powerful tool for continuous improvement. In the current climate in which businesses are operating today, capital investment in plant and process changes are not likely to be universally popular.
GE’s Jack Welch highlighted the following points in a meeting with his management team:
• Don’t add costs
• Consolidate acquisitions
• Use intellectual capital to replace plant and equipment investment
(Presentation, Tony Eltringham)
Benchmarking is an exercise that will confront the participants with observations or facts that are sometimes unsettling. The basis of benchmarking is the recognition that benchmarking will lead to uncovering of gaps between where we are and where we could be. This will then enable a company to direct its focus to closing those gaps and hence improve its performance.
“Strategies and technologies only deliver promises. People and processes deliver results”
Deloitte & Touche Consulting advertisement
4.1.4 What can be Benchmarked
So now we know that benchmarking is the way forward. We know that we have to choose
with whom we want to benchmark. Thus accepted a ranking of competitors who probably are doing better and we need to find out why and determine how to improve to meet this challenge.
Thus benchmarking can focus on KPI’s (key performance indicators) and or key business processes.
• Benchmark performance indicators, usually expressed in numbers such as : o profit margins
o return on investment o cycle times
o percentage defects o sales per employee
o cost per unit of product or services
• Or you can benchmark business processes which drive performance indicators, such as : o how you develop a new product or service
o how you manage to meet a customer's order or respond to an enquiry o how you produce your product or service
4.1.5 Limitations of Benchmarking
Improving by trying to find out everything yourself is very expensive. A company with a proper view of the benchmarking process should be able to develop disciplined guidelines that will result in desired improvements. However, if the company does not benchmark for the right reasons, benchmarking efforts will ruin it.
The Benchmark process limitations
Benchmarking works because real gaps are identified between where we (our results) are relative to where “others” are. This means that one has to be able to identify (observe) the differences. The better the observation, the clearer and more explicit the metrics (measurements), then the better the information. will be. Thus the benchmarking exercise will be as good as the benchmarking process or model used. Observing the wrong KPI’s or looking at the wrong metrics can lead to wrong deductions and subsequent incorrect improvement plans.
Graph 2 : World_record_progression_100m_men
Benchmark information is perishable.
The most constant thing in the economic global arena is change. Graph 2 depicts the progression of the100m time for men (athletics). If we assume that the world record time represents the best in the world then this graph clearly demonstrates that the “best” time in 1920 will not even earn us a start in position in 2008.
Therefore we must be aware that while we are doing the benchmarking study data may become outdated. Benchmarking is a continues process and not a once off. It is of great importance that one takes this into account when interpreting benchmarking data. Benchmarking data must be kept
Benchmarking used for the wrong reasons
It is easy to get hung on the numbers, Often management thinks that benchmark should be a KPI.
The most common one used in mining is the cost per tonne mined. Cost cutting just to reach a certain financial indicator may result in loss of focus on the real goal of performance improvement.
The goal of benchmarking is to understand the tools and techniques used to reach certain performances. This understanding allows management not only to reach the desired KPI level, but also to develop a vision of how to achieve an even more advanced goal.
To stay with the example of cost-cutting. By focusing on reaching a certain cost per tonne number, some companies may have implemented exercises for downsizing, cutting expenses, remove the infrastructure (people or information systems). They then find that they now lack the capability to sustain or improve.
Organization is not ready for benchmarking
To gain maximum benefits from benchmarking, a company should only conduct a benchmarking exercise after it has attained some level of maturity in the core competency being benchmarked.
Management should have some data about its own process before it can perform meaningful comparison with another company. This is to ensure that there is sufficient data to do a meaningful benchmarking exercise. In such cases management ends up spending (wasting) a lot of resources in visiting other plants and observe a lot of things but lack the information to fully understand their relation to its own performance.
Not every company is ready for benchmarking. However, companies should not avoid benchmarking just because of a previous bad experience or because they have the attitude of “We are already the best” or “We are different than everyone else”. The latter is benchmarking called the
“Yes but “ syndrome. People tend to agree with the good performance of the benchmark partner
“but” always have a good explanation of why they cannot or should not reach the same performance level. Companies in which responsible individuals have such a mindset will have little chance of improving.
Imitating competitors
One of the most common mistakes made in benchmarking is attempting to carbon copy benchmark partners’ activities. As mentioned earlier benchmarking also entails learning how the benchmark partners changed their businesses and what the constraints may be for the own business to adopt the
“new” process. Think of workforce skills, labor unions, local laws en regulations, etc.
4.2 Benchmark focus.
Benchmarking--the research and analysis of quantitative, empirical data--is a way to isolate weaknesses and strengths and to make connections between best practices and performances. Once these connections have been made, determining which practices are appropriate for an organization to adopt becomes a competitive imperative.
(Emma Skogstad, 2003)
Figure #9 Ranking of benchmark partners (Presentation, Tony Eltringham)
It is good to first determine where we are and where we want to be. In other words what is our current benchmark profile and which one do we aspire. One is either a Loser, Survivor or Winner.
This can further be refined into the hierarchy of benchmarking. Thus helping to keep focus in the art of benchmarking. One should focus the next level in the hierarchy (see fig #9). Aiming too high may lead to frustration and ultimately to failure.
• World Class – Managing the business in such a way that it serves as an example for other companies, no matter the industry they are in.
• Country Class –. Managing the business in such a way that it serves as an example for other companies, no matter the industry they are in.
• World Class in Industry – Global recognition by the peers in the same industry.
• Country Class in Industry- Local recognition by the peers in the same industry
• Very Good – Being profitable, providing reasonable return to the shareholders.
• Survivor – Trying to make ends meet marginal profits.
• Fair – Trying to make ends meet.
• Poor – Operating at a loss
• Very Poor / Loser – Company is going out of business sooner or later
4.3 Benchmark process
What steps should be used to insure that a benchmarking process is quantifiable? When the following checklist (Terry Wireman – 2003) is used, it allows for the benchmarking process to be successful. If a disciplined approach is not followed, benchmarking is unlikely to produce any long- term results. Note that this is a summary a more detailed checklist is in appendices C
• Plan for benchmarking. Choose the right parameters to focus on.
• Search for suitable benchmark partners
• Gain knowledge of their processes
• Determine the gap with own processes
• Prepare and implement a plan to close the gaps
• Benchmarking is continues process.
Benchmarking commandments 1. Keep it legal.
2. Respect confidentiality. Keep the information internal.
3. Use benchmarking contacts. Don’t refer without permission.
4. Be prepared from the start. Understand your expectations. Act in accordance with your expectations.
5. Be honest.
6. Follow through with commitments.
In summary, to ensure the process as mentioned above works it should be that:
o There is a thorough understanding of your own situation.
o Suitable benchmark partners are chosen.
o The right KPI’s are benchmarked.
o The right people are involved.
o Benchmark exercise results are turned into practical improvement projects.
o Benchmarking is an ongoing process
4.4 Benchmarking methods
Benchmarking methods are used to determining how well a business unit, division, organization or corporation is performing compared with other similar organizations. A Benchmark is often used for improving communication, professionalizing the organization / processes or for budgetary reasons. Traditionally, performance measures have been compared with previous measures from the same organization at different times. Although this can be a good indication of the rate of improvement within the organization, it could be that although the organization is improving, the competition is improving faster.
There are four benchmarking methods:
1. internal (benchmark within a corporation, for example between business units) 2. competitive (benchmark performance or processes with competitors)
3. functional (benchmark similar processes within an industry) 4. generic (comparing operations between unrelated industries)
1.Internal Benchmarking (Benchmarking against internal operations)
In most large companies there are similar functions in different business units. One of the simplest benchmarking exercises is to compare these internal operations. The objective of internal benchmarking is to identify the internal performance standards of an organization.
The advantages of internal benchmarking are:
First, there is often a significant amount of information sharing accompanying internal benchmarking.
Second, many organizations are able to obtain immediate gains by identifying their best internal practices and transferring those to other parts of the organization. This internal knowledge can become the baseline for later investigation and measurement involving external benchmarking partners.
The disadvantage of internal benchmarking is that it fosters an introverted view. It is all too easy to ignore that other firms have the edge on you if you are concentrating on outperforming internal rivals.
2. Benchmarking against external direct product competitors, called Competitive Benchmarking.
Benchmarking can be done externally against competitors. Direct competitors are the most obvious to benchmark against. The objective is to compare companies in the same markets that have competing products or services or work processes. eg Coca Cola vs Pepsi.
The advantage of competitive benchmarking is that you can see what your related performance is.
The main disadvantage is that information is very hard to obtain, beyond that in the public domain.
3. Benchmarking against external functional best operations or industry leaders, called Industry or Functional Benchmarking.
You can benchmark others in the same industry that may have the same products or services but are not competitors in the same market. Industry benchmarking tends to involve comparisons between firms that share some common technological and market characteristics and to concentrate on
specific functions. For example, Telecom Australia might benchmark its billing process against the billing process of British Telecom.
The big advantage of industry benchmarking is that it is easier to identify willing partners, since the information is not going to a direct competitor. The disadvantages are cost and the fact that the most renowned companies are beginning to feel overwhelmed with benchmarking visits and some are even charging a fee for access.
4. Benchmarking a process in one or several unlike organizations, called Generic or Process Benchmarking.
This type of benchmarking focuses on excellent work processes rather than on the business practices of a particular organization or industry. Some business functions or processes are the same regardless of dissimilarities of the industries.
Generic benchmarking can be very effective even though it is generally the most difficult. It has the potential of revealing the best of best practices. It requires broad conceptualization but careful understanding of the generic process.
Choosing which type of benchmarking to use depends on what you want to benchmark.
(Anne Evans and Margaret Matters, 1999)
Based on the theory above the focus of this thesis will be on Internal benchmarking as this thesis will address the question of how the mines in Suriname can be benchmarked against the mine in Boddingtons, Australia. However, this will be only the first step. This thesis will produce a model that will create questions and identify gaps. When it has been determined what can and cannot be benchmarked with Boddington the next logical question is “what to do with the cannot’s”. This is where competitive, functional and generic benchmarking come in.
4.5 Summary Literature research
All literature and articles reviewed agree on the same basic principles. A benchmark in itself is meaningless unless it is put into context. This paper will focus on the performance processes.
Authors do have their own classification of benchmark models depending on the processes that they benchmark. All describe some forms of internal benchmarking and forms of external benchmarking.
Literature agrees that Benchmarking is a process that starts with gaining knowledge of the own process. Based on the “success” level of the benchmarkers process it is determined which benchmark partner to choose. Each author sums up various do’s and don’ts as he or she sees it.
Despite different formulations the do’s can be summarized in:
• Plan for benchmarking. Choose the right parameters to focus on.
• Search for suitable benchmark partners
• Gain knowledge of their processes
• Determine the gap with own processes
• Prepare and implement a plan to close the gaps
• Benchmarking is continues process.
The don’ts/ limitations can be summarized as:
• Focussing on the wrong KPI’s will lead to wrong results.
• Benchmarking is not to set KPI’s and targets.
• Company must be ready for benchmarking.
• Do not use outdated data for benchmarking purposes.
The above will be used to prepare a model focussing on the mining core business while at the same time taking into account location specific aspects in such a way that it will facilitate the selection of benchmark partners. Upon selection of the benchmark partners, the model will also facilitate the decision making into which processes to benchmark.
CHAPTER 5 Criteria for a mining benchmark model
Research of the literature and discussions regarding benchmark analyses enabled the design of a benchmark model for the mining industry. The designed model assumes that there is agreement on certain issues.
In the mining industry the cost per tonne mined is the accepted overall indicating factor of performance (see graph 1 earlier in this thesis). Benchmarking success will ultimately be judged on the improvement of the cost per tonne mined.
The LSB model assumes that people cannot be benchmarked. This has various reasons of which an important one is culture. Some people because of religious beliefs do not work on Saturdays. This means that if you would compare their productivity to a group that does not share those beliefs and do work on Saturday it would not lead to the correct conclusions with regard to their performance.
The LSB Model also tries to focus on the right cost influencing units. For instance: traditionally productivity is expressed in tonne related to man-hours worked. Since we are interested in the contribution to the ultimate cost per tonne it is better to look at the labor cost per tonne mined. To illustrate the value of this. Traditionally if company A mines 1 tonne of bauxite using 3 employees and company B mines 1 tonne of bauxite with 1 employee it would be concluded that based on productivity the company A would have to improve. However when looking at the goal of benchmarking and looking at the goal of cost per tonne the location specific factors may not allow that. Let’s say that company A is in Suriname with relative low labor cost and company B is in Australia where the cost of labor is four times as high as in Suriname. If one would be looking at the labor cost per tone one would find that the labor cost per tonne in company A is much lower then company B even though they employ 3 times as many employees. The question in this one would be is the traditional “productivity” a good benchmark indicator. In the concept of this thesis it is not.
This leads us to the obvious question of “what should the model take into account”. Mines when designed will have constraints that “limit” their productions. This is a key factor that must be taken
into account when choosing a benchmarking partner and more so when choosing a process as a benchmark. To illustrate: the Escondida copper mine (Chile) is designed with a “truck” constrained while Mount Arthur North, an open pit coal mine, is designed to be shovel constrained. Therefore these two may not be benchmarked against each other as they undergo different pressures. One may see that Escondida will probably have very good utilization numbers on the trucks and less on the shovels while the Mount Arthur North may have the reverse. The current situation in Suriname is that the mines are “refinery constrained” This means that the mines would be able to produce more but their customer; “the refinery” cannot take more.
To illustrate the direction and the focus this model should have, graph#3 was generated.
Graph #3 Brook Hunt “Bauxite and Alumina cost” database. Cost contributors curve
Cost Contributors Curve 2007 ($/t)
Kimb o
Bodd ington
Hunt ly
Kaaim angr
asie
Poços De
Caldas Kindia
Gove
Panchpatm ali
Willowda le
Bread nut Va
lley
Klaverbad
Mort as/Dog
ank uzu
Weipa
Paragom inas Project
Moengo- Coer
motibo Trombeta
s Bok
é
Lelydorp III Los
Pijiguao s
Disco very B
ay
Manche ster P
late au
Schwallenb urgh
Russell Pl ace Diesel ($/t) Labour ($/t) Consumables ($/t) R&M Materials ($/t) Services / Other ($/t)
Suriname mines
Boddington
Compared to the graph #1 it now becomes apparent why this thesis argues for benchmarking instead of just comparing to “best in class”.
To further clarify this the graph was further refined (see graph #4)
Graph #4 Brook Hunt “Bauxite and Alumina cost” database. Cost contributors curve (refined)
Cost contributors $/t
Diesel ($/t) Labour ($/t) Consumables ($/t) R&M Materials ($/t) Services / Other ($/t) Boddington Kaaimangrasie Klaverbad Moengo-Coermotibo
Name Diesel ($/t) Labour
($/t)
Consumables ($/t)
R&M Materials ($/t)
Services / Other ($/t)
Boddington 0.6 0.9 0.8 1.4 0.7
Kaaimangrasie 1.8 1.0 0.8 0.5 0.7
Klaverbad 2.5 2.0 0.8 0.5 1.5
Moengo-Coermotibo 2.0 2.4 1.6 2.0 0.5
If Boddington as a whole would be the benchmark because of their ranking then this thesis argues that would not be correct. The graphs above show that for “consumables” Boddington, KG and KB are on one level while for “R&M materials” KG and KB have far better results. It becomes apparent why in Benchmarking the term partner is used. If the four above mines would be Benchmark
• For Diesel, Boddington
• For Labour Boddington and KG
• For consumables Boddington, KG, KB
• For R&M materials KG, KB
• For Services CBO
By having Benchmark partners the goal is to learn from each other strengths. So benchmarking should be a sharing of information.
Of course the above graph and table alone are not enough. Of great importance is that before even attempting benchmarking, thorough knowledge of your own processes and their respective constraints must be obtained. The thus identified bottlenecks then can be prioritized. Subsequently the search for benchmark partners with a focus on the same type of bottleneck may be started.
This also gives a indication of what can be practically attained. This does not necessarily need to be the “best”. This may seem contradictive. Why not aim for “the best”? Discussions earlier already indicated that companies are not in the business of being the best. The common factor of all businesses is providing shareholders with an attractive return on their investment. For mining this means competitive cost per tonne mined.
Benchmark partners do not necessarily have to be likewise businesses. To illustrate this. An acid plant may cost as much as a Boeing 737. As we all know the airline industry has a high focus on :”zero risk tolerance”. It is also common knowledge that mining companies like BHPB proclaim that they go for “zero harm” (read eliminate all risks). This view point makes it easy to see that a company like BHPB would look at the airline industry for guidance on how to eliminate risk. This is a good example where management is tested on the seriousness of benchmarking.. Training of one airline pilot (read operator) costs approximately 200,000 US$. How much is BHPB willing to spend on the training of one acid plant operator?. It is obvious that the operator will not go trough the same training rigor as the pilot. Even though this may be a good subject for investigation, for the sake of this thesis the following argument is raised. Almost any mistake made by an airline pilot can result in the deaths of tens to hundreds of people at once. An acid plant operator’s mistake in many cases will lead to some down time and/or decreased efficiency (production). Therefore the airline industry because of their business have some additional pressures that justify c.q. pressure them in paying the cost for training of operators (pilots). BHPB management may then select to what extend they deem it practical to train their operators.
The previous example illustrates that determining comparable bottlenecks alone is not enough.
Knowledge of how they tie into the rest of the process is of the utmost importance. Some food for thought. In the mining industry blasting is an area that is often benchmarked. From the type of explosives to the technique of the blasting itself. While investigating this it was clear that improvements were made taking into account the next step in the process, Ore-lifting and hauling.
As long as they were unaffected or improved, the “improvement” in blasting is considered a success. However if the bigger picture is taken into account and interlinks are being observed then one will notice that blasting has a direct influence on the crushing. The coarser the blasted material the more expensive crushing gets. This means that the solution to a crusher “underperformance”
may lie in changing the blasting technique. This is where the LSB model must assist managers with insight. The LSB model takes into account that performances are interlinked.
The above mentioned interlinks are very difficult to spot if one is not very familiar with the local/
practical situation and or circumstances. Workforce “buy in” and appreciation for benchmarking now comes into play. Not only buy in from supervisors but also from operators and other front line staff. They are valuable when determining the proper benchmark parameters. Of course the reliability of the information is also important. This means that when looking for information c.q.
data it is key to ensure what the data represents. A good example was when Highland Copper mine decided that they wanted to benchmark against Escondida. They requested data on production, efficiency and utilization. After analyzing the data they came back and indicated that they thought the reported production figures where 13% too low. This was based on efficiency and utilization of the equipment. Escondida quickly explained that all reported data was correct but that Highland Copper mine had made a wrong assumption. They assumed that Escondida worked 24hrs per day while in fact they only worked 21hrs per day. The 3 hours (13% of 24hrs) explained the differences.
The model will gather this type of data which will enable Surinamese mine to properly gather and analyze data from benchmarking partners. No need to argue that the collected data must be auditable.
The earlier also illustrates why benchmarking entails benchmarking of processes rather then numbers. On the other hand benchmarking for the sake of benchmarking is a waste. Benchmarking
As mentioned earlier benchmarking is a process in which management is able to determine where there is room for performance improvement. The LSB-model designed in this thesis will reveal
“many” opportunities and management will have to decide on prioritization.
Table #1 below indicates how the general benchmarking types relate to focus, cost, workers buy in and speed of implementation
Tabel #2 Benchmark Implementation
Benchmarking Focus Cost/effort Level of
acceptance
Speed of implementation
Internal Reducing
variation low high fast
Competitive /
Functional Closing the Gap medium medium medium
External Generic Presenting
breakthrough high low slow
As mentioned earlier the objective of internal benchmarking is to identify the internal performance standards of an organization. This helps to identify their best internal practices and transferring those to other parts of the organization. In other words it gives them a understanding of how their performance is and what the gap is to where they want to be. Most of the time this will result in a focus on more consistent performance. Because the data is readily available and is easy to share this normally does not cost a lot and the findings can be implemented rather fast. Acceptance is normally high because it is familiar to all involved. Many will claim that they have been knowing it all along but that management has been procrastinating in following it up. This type of benchmarking is where miners benchmark against their best month or best week c.q. performance and try to consistently replicate that.
The next logical step is to compare against your direct competitors. You may think that you are where you need to be but is that true? Just think of the next anecdote.
Two guys are in the forest and come upon a hungry lion. One of them quickly kneels down and starts putting on his sneakers. The other guy shakes his had and says. “Come on, you will never outrun a hungry lion”. At this his friend replies, “I don’t need to. I just need to out run you”.
This illustrates that in order to survive one must know what the competitors are doing. That is where competitive benchmarking comes in. Sometimes it doesn’t even have to be a direct competitor but just someone in the same industry who has proven to have superior performance.
With the knowledge from internal benchmarking as baseline the focus is on identifying the gap between our own performance and that of the “competitors”. This will require effort and may cost money to get the appropriate information from the other companies. This is also where the “yes, but” syndrome kicks in. Employees tend to acknowledge the data collected and can find themselves agreeing with the conclusions. They then will try to justify their performance with “Yes but” and then explain what advantages exist that favor of the other’s better performance or what is preventing them from better performance. This “yes but” syndrome hinders acceptance. And will cost extra time to implement benchmark results/ recommendations.
After the internal and competitive benchmarking it can be assumed that there is sufficient information to go to the next step. This is where the focus is shifted to “excellent work process”.
Here the focus is very wide and also covers industry that is dissimilar from the own. A good example is the investigation technique used by BHPB. BHPB with its focus on ZERO HARM soon became the “best” in the industry. However the statistics were still not at the goal of ZERO HARM.
To further improve they looked outside their industry and found that the airline industry did manage to get good safety statistics. They did this using the Incident Cause Analyses Method (ICAM).
BHPB reviewed this and decided to also adopt this method.
Normally benchmarking progresses from internal benchmarking to competitive and functional and ultimately to external benchmarking. As benchmarking is an ongoing process a company can do a combination or all of the types at ones. This means that some processes may be benchmarked internally while others are being benchmarked externally.
CHAPTER 6 Model design
Because the ultimate indicator is the cost per tonne mined, this research started with the financial reports. As explained earlier this will not be enough and therefore operational data will be used to explain, focus on or draw attention to differences in the performance of the benchmark partners.
Table #3 depicts the items per mine that where found in the BMS cost report.
Table #3 Consolidated Cost report of the BMS mines
(BMS cost report Dec 2007). Note: A enlarged version can be found in the appendices.
Analysing this report reveals that the cost structure of the three mines is different. KG and KB have the same cost structure. Also it becomes clear that CBO has costs allocated that the others have not.
Therefore the cost per tonne for CBO cannot be benchmarked against the cost per tonne of KB or KG as is. Investigating the cost build up of these mines the following questions where researched.
• Why the different cost built up.
• BMS has three mines yet the cost report shows 4 cost reports.
