The Information Age

Information Age Myth 2: Mine operations should be optimised from start to finish to produce the best results.

The Information Age is so labelled due to the advent of powerful computer hardware and software information technology. Myth 1 paradigms understandably were hardcoded by ERP system designers as prevailing business practices. One cost certainty assumption is that savings across all areas are additive, a cent saved in a department is a cent saved to the overall organisation. This belief meant performance targets could be set at the department level. With information readily accessible with a click of a computer button, micro-management has flourished. We’ve seen the budgeting process used to approve and control departments with just enough capacity to run to average demand. Also observed is the setting up of accounting based KPIs using historical budget numbers. This is a dangerous assumption carried over from the Industrial Age – The past repeats and can predict the future.

Systems Thinking in the Information Age has emphasised optimising business processes from a start to finish, end-to-end perspective. However, clashes between process and technology have surfaced. It’s common during implementation to force organisation process changes to suit the “best practices” built into the software structure. After the IT system goes live, making subsequent software coding changes is extremely difficult. User groups are asked to wait patiently for the next “real soon” version. And perhaps pay for the upgrade. It’s intriguing to learn from resourceful employees how their spreadsheet workarounds keep work flowing but are discreetly hidden from prying eyes.

The mix in today’s Yellow Bubble

In Article 1, we noted the global decline in employee engagement as well as the decline in mining productivity, which started 15 years ago. These sobering findings are corroborated by the McKinsey graph[1], which found that global mining productivity overall has decreased by 29% over the last decade. From 2014 to 2016 McKinsey’s Mine Lens reported a 2.8% per annum uptick in overall mining productivity. Two main trends underlie these modest gains: a 3% annual reduction in headcount and tightly controlled capital spending and expenditures for non-labour operations.

Mining technologies are being heavily promoted as today’s solution. Despite great promise in digital advancements, many companies are struggling to embrace tech-enabled transformation. One growing fear is that humans are becoming more and more subservient to technology. Instead of technology enabling humans to perform well, the inverse is occurring.

Let’s take a closer look at the people side of mining. Myth 1, combined with Myth 2, has led to three organisational conflicts:

1. Top Management seeking to achieve “work-as-reported” company performance targets.

2. Centralised administrators trying to optimise a “work-as-imagined” end-to-end process.

3. Operations managers and supervisors attempting to increase local “work-as-done” productivity.

We will address the origins of each conflict and how to resolve by “mining differently.”

1. Classical Management Theory

Besides Frederick Taylor, two other Industrial Age thinkers influenced the running of organisations, Max Weber and Henri Fayol. Together the three pioneers formed what is known as Classical Management Theory.

Max Weber focused at the highest level with his Bureaucracy doctrine. His work addressed the problem of factory work attracting untrained rural farmers to urban cities. The master/apprentice craft model was ill-fitted to handle high demand and volume from technology-driven industrialisation. Company owners and directors welcomed Weber’s solution with open arms.

The impact of his contribution is summed up by Gary Hamel:

“Most of us grew up in and around organisations that fit a common template. Strategy gets set at the top. Power trickles down. Big leaders appoint little leaders. Individuals compete for promotion. Compensation correlates with rank. Tasks are assigned. Managers assess performance. Rules tightly circumscribe discretion. This is the recipe for “bureaucracy,” the 150-year old mashup of military command structures and industrial engineering that constitutes the operating system for virtually every large-scale organisation on the planet.”[2]

French Mining Engineer Henry Fayol gave his attention to the middle layer, the managerial class.  He laid down 14 principles of management for improving overall administration and how managers would control the internal activities of the company. Fayol’s 14 management principles are accepted as a Manager’s approach and the foundation for Administrative Science. In contrast, Taylor’s Scientific Management is termed an Engineer’s perspective oriented on production and operations at the lowest level.

They collectively reinforced the view that organisations were functional machines controlled to deliver efficiency and productivity. Fayol declared there must be a proper place for everything as well as each thing must be in its appointed place. He described how control would be executed.

“An employee will receive orders from one boss only.” (Unity of Command)
“All the organisational units should work for the same objectives through coordinated efforts.” (Unity of Direction)
“Individual or group interest are sacrificed or surrendered for general interest.” (Subordination)

Ultimate accountability flowed hierarchically to the very top characterised by US President Harry Truman’s famous phrase: “The buck stops here.”

Here’s the vertical rub. Top Management sees work-as-reported measured against corporate performance targets typically set by Weber’s bureaucrats. Fayol’s middle managers idealistically plan work-as-imagined using the available resources. Taylor’s operational managers create work-as-prescribed, limited by imposed regulations, standards, rules. The front-line workers perform work-as-done after adapting to daily variability and interdependencies. Operations are sensitive to how their abilities are scrutinised, so what is communicated up the line is work-as-disclosed. Systemic problems multiply and remain unresolved. Eventually, a tipping point is reached, and catastrophic failure occurs. Frequently the CEO is the last one to find out and the first to mutter “Why wasn’t I informed”?

Systems thinking offered a “horizontal” view to describe and understand how organisations work. While the buck stops here, the work flows horizontally. Where best practices prescribed only one right way for efficiency, from systems thinking arose the possibility of more than one correct answer. Choice was a novel idea, and the goal was to find an optimal solution from a range of choices for effectiveness.

Scientific Management evolved into the discipline of Engineering. The paradigm was straightforward. Envision an idealistic future state and design a perfect system working linearly backwards from finish to starting point. Use standardised project and change management practices to build, operate, and maintain the orderly flow through the parts of the system (technology, process, people).  Measure deviations from control norms and fix to get back on track.

It’s not difficult to find companies today operating under Classical Management theory, practising Myth 1, and using system thinking tools developed in the Information Age. They still think their organisations should operate like integrated machines comprised of working parts that fit together seamlessly, like Henry Ford’s Model T automobile.

“In this machine view, organisations should be designed to run like clockwork. Organisational structures should follow rules that determine where resources, power, and authority lie, with clear boundaries for each role and an established hierarchy for oversight. When decisions require collaboration, governance committees should bring together business leaders to share information and to review proposals coming up from the business units. All processes should be designed in a very precise, deliberate way to ensure that the organisation runs as it should and that employees can rely on rules, handbooks, and priorities coming from the hierarchy to execute tasks. Structure, governance, and processes should fit together in a clear, predictable way.”[3]

What should a mining company do? Dispense with their vertical hierarchy and abandon Classical Management theory? No. We suggest thinking differently.

Think of everything cited in the above quote as a system constraint that is either controlling, governing, or enabling. Think of bureaucracy as a system property that emerges from the blending of constraints. A desirable form of bureaucracy is Stability, a machine that is well oiled and humming; the constraints are in the right proportions, and all are working together. On the other hand, stringent command and control rules, goal conflicts, information gaps are examples that enable an undesirable form to emerge – Extreme bureaucracy. Employees are so tightly restricted they become paralysed, fearful of violating a constraint and being punished. During a change initiative, they are told: “If you don’t change, you will be changed.”

Fortunately, there is a Mining Differently alternative to help find an appropriate balance. In the next article, we will describe an anthro-complexity approach that can reveal constraints causing strained relationships and interactions amongst people at all levels in the vertical organisation hierarchy.

2. The Rise of IT systems – Enterprise Resource Planning

Before the advent of IT, local managers faced the problem of making ill-informed decisions. Moving information was paper-based and painstakingly slow. This typically meant that operations managers and supervisors had to try and run as efficiently as possible within their areas. With an online ERP system, they could now access timely information on local cost and resources. But so could others including Weber’s bureaucratic analysts and Fayol’s middle managers.

“If you can’t measure it, you can’t manage it.”

“Under scientific management,” Taylor wrote, “the managers assume … the burden of gathering together all of the traditional knowledge which in the past has been possessed by the workmen and then of classifying, tabulating, and reducing this knowledge to rules, laws, formulae…. Thus all of the planning which under the old system was done by the workmen must of necessity under the new system be done by in accordance with the law of science.”

Reliance on ERP numbers not only gave the impression of scientific expertise based on “hard” evidence, it also replaced intuitive judgment, the lessons learned from previous experiences. Management demanded more data—standardised KPIs, ratios, statistics. And ERP delivered.

Professor Jerry Muller has coined this questionable managerial pattern “metric fixation.”

“When proponents of metrics advocate “accountability” they tacitly combine two meanings of the word. On the one hand, to be accountable means to be responsible. But it can also mean “capable of being counted.” Advocates of “accountability” typically assume that only by counting can institutions be genuinely responsible. Performance is therefore equated with what can be reduced to standardised measurements.” [4]

Muller describes the damage our obsession with metrics is causing. “In our zeal to instil the evaluation process with scientific rigour, we’ve gone from measuring performance to fixating on measuring itself. The result is a tyranny of metrics that threatens the quality of our lives and most important institutions.”

As the Information Age advances into Big Data analytics, there is the digital vision of predictive algorithms replacing the need for human decision-making. What will happen if mining operation algorithms are implemented based on myths and fallacies?

What should a mining company do?  Drop ERP reporting? Eliminate KPIs and performance targets? No. We suggest thinking differently.

ERP data should augment the decisions made by humans. Software packages are a communication and organisation tool. They provide content to answer the “who, what, when, where” queries. But not the “why” question because they are unable to capture context. While it can offer helpful insights into existing work conditions, they can’t capture the non-quantifiable emotional and irrational factors humans use to make decisions. While it seems more straightforward to trust the data, it’s better to trust human judgment.

Wait a minute. Can we trust humans? Well, it depends on the organisation’s system constraints, in this case, performance management. A common practice involves setting annual goals for employees and turning measures into numerical targets to achieve.

Anthropologist Marilyn Strathern’s paraphrasing of Goodhart’s Law is a clear warning of the downside of measures on human behaviour. Be careful what you wish for. Humans are skilled at “gaming” an incentive system to earn monetary (pay-for-performance, safety bonus) or reputational (rankings) rewards. The needs of self can take priority over the needs of the many. Employee stories gathered with an anthro-complexity approach can shed light on unhealthy stress due to metric fixation constraints.

Success or failure is not created nor controllable; it is an emergent outcome of the system. Thinking differently means letting go of holding individuals accountable for results they have no control over. Don’t blame the person; blame fixes nothing. Put the onus on the system. Treat KPIs not as scoreboard targets but as dashboard gauges monitoring progress.

In systems thinking where there is more than one right answer, choosing an optimal solution sounds reasonable. Therefore, it seems perfectly logical to believe Myth 2: “Mine operations should be optimised from start to finish to produce the best results.”  But it’s false. Paradoxically the opposite is true. Eli Goldratt in his Theory of Constraints has mathematically proved:

“The closer you are to a balanced capacity chain, the closer you are to bankruptcy.”
“If you want to make money, most of your resources must be idle from time to time.“

3. The Theory of Constraints

Myth 2 is a violation of the Theory of Constraints. TOC is a management paradigm created by Eli Goldratt. He viewed any manageable system as being limited in achieving more of its goals by a small number of constraints. Constraints include material, equipment, vehicles, people, policies, rules. TOC constraints are typically viewed as restricting/controlling but can also be governing and enabling. For examples, policies can be considered enabling because they reduce the burden of too many choices down to 1 so one can quickly move into action mode.

Envision a mining operation as a chain of links linearly connected. TOC focuses on the “weakest link” in the chain – the bottleneck where in-out capacity is the worst. Other links that are not bottlenecks are permitted to be (and have to be) “underutilised resources.”

Not surprisingly, “underutilised resource” raises red flags. The C-suite and Weber’s bureaucrats are concerned that making such metrics public (transparency) could lead to shareholders questioning how the company is carrying out the mandated mission (accountability). It does take some technical understanding and time to explain TOC theory adequately.

Fayol’s middle managers worry about the optics of poor resource management highlighted by ERP reports. Local operations managers fear being punished for not meeting annual performance targets. So they try to optimise their own productivity and look busy. This exerts more pressure on the bottleneck link, aggravates their situation, and decreases overall chain production flow. As stated earlier, the needs of self can take priority over the needs of the many.

What should a mining company do?  Ignore TOC? Stop ERP reporting? No. Once again, we suggest thinking differently.

Myth 2 infers ERP systems will accentuate TOC violations if incorrectly utilised. Recall what Taylor said: “…all of the planning which under the old system was done by the workmen must of necessity under the new system be done by in accordance with the law of science.” The Theory of Constraints is a law of science. Also be mindful that software packages are tools, not solutions. Therefore, change the ERP business rules to support TOC.  

It’s time that the fighting ceases between central and operational levels. When ERP rules are set for end-to-end optimisation, conflicts with local managers are generated when centralised analysts report less than optimal performance and even idleness. So set the ERP rules to manage the TOC constraint. Adjust ERP rules to realise whatever rate of production can pass the bottleneck constraint is the ultimate rate that can pass through the whole chain.

Goldratt’s Drum, buffer, and rope approach makes TOC a simple system to implement. Use ERP to schedule upstream resources to keep the buffer full using a mix of forward and backward scheduling. Schedule downstream resources always forward from the output of the constraint.[5] If you are confronted with the ERP rules that can’t be modified, insist on changes unless you agree humans should be subordinated to technology.

Engage local Management and workers to determine where the bottleneck is. Develop ERP reports to support optimisation of the bottleneck. Stability of flow of the chain as a whole is the clear objective. We have demonstrated in over 85 interventions with the Productivity Platform (PP) that Stability at a higher level is within reach. In a PP engagement with a large mining company, we opened their eyes by showing them how their planning practice was slowing down production. They were planning their operations on a balanced capacity chain as prescribed by Myth 2. With “just enough of everything”, production output was below target and highly unstable. Their next step was to switch to optimised flow. With the TOC adjustments, they generated more than 20% average output increase of tons mined within four months and without increasing capital expenditures.

PP is a change platform designed around the principle of flow. Workers meet daily in a flow room. They focus on the key resources that determine revenue flow, while the rest of the system is set up with adequate protective capacity and buffers to protect the revenue flow.

The Flow Room provides visual feedback on the processes workers are responsible for and shows them how their actions affect the overall system and the outcomes. It highlights problem areas in these processes and allows for dialogue around these processes. Management and workers simultaneously become aware of problems in the system, and constraining conditions can be addressed on the spot.

PP deploys Agile techniques like Scrum and Kanban. A drift toward Extreme bureaucracy is held in check. The anthro-complexity approach creates a flow room that is psychologically safe for people to speak up and share good and bad experiences.

A considerable benefit is shifting the local manager’s role from being full-time in charge to supporting the team in the background. With time freed up, the manager can attend to working on internal end-to-end collaboration and external social license to operate issues.

It’s time to rethink incentive paradigms and the why, what and how human performance is rewarded by the organisation. Don’t be ruled by the tyrannical mindset that the path to success is quantifying the results and doling out rewards & punishment based on the numbers. Personal success is not created by the individual but emerges from others delivering favourable consequences. Metrics can be beneficial if used to complement rather than replace judgment based on personal relationships and experiences. Put a spotlight on shared learning. Make it deliberate and fun. And don’t screw it up with incentives.

Safety in the Information Age

Classical Management Theory continues to be prominent in shaping safety thinking. Safety-I bureaucracy can grow uncontested, especially with government regulators demanding more auditing and compliance with rules. Safety industry suppliers are cashing in with software dedicated to automating safety inspection processing and reporting.

Human Factors developed as a professional discipline as a response to Classical Management Theory. Business process improvements, coupled with technological advancements, have made operating systems more complicated to manage. And when downtime occurs, it’s challenging to fault human error when there are so many moving parts. As James Reason said in 1990:

“Rather than being the main instigators of an accident, operators tend to be the inheritors of system defects created by poor design, incorrect installation and bad management decisions. Their part is usually that of adding the final garnish to a lethal brew whose ingredients have been long in the cooking.”[6]

What should the mining company do?  Increase bureaucracy to prevent accidents? Find fault, blame and punish when accidents happen? No. You’ve read it before… think differently.

Thankfully, accidents rarely happen. And yet, organisations spend enormous amounts of time, effort, and money on so little data. As a result of this foolishness, a new view called Safety-II has emerged to examine when things go right, which is most of the time.  The idea of ‘performance variability’ was born; a human is not a hazard but a hero who could adapt performance in response to changing conditions in the work environment. A scrum meeting in the PP flow room is an example of local workers adapting successfully to keep the line running. 

Safety professionals in mining companies who don’t perform myth-busting due diligence on new technology proposals are not fulfilling their role. Be proactive and ask if humans are expected to behave perfectly like machines and how the technology allows for human error. Humans are fallible. Even the best people make mistakes. Safety by design means humans enabled by technology, not the other way around.

There have been 6 mining deaths in the past 12 months in Queensland, making it the worst year for mining deaths since 1997. Mines Minister Anthony Lynham announced two reviews into the industry. A review into incidents on coal mines will be expanded to include mineral mines and quarry sites as well as all deaths on mines over the past two decades. A second and separate review is being led by the University of Queensland, which will review state mining health and safety legislation in light of emerging mine technology and practices. Both reviews are expected to be completed by the end of this year and tabled in Parliament. We hope that they will look at the sharp end and not focus primarily on high-level issues at the Blunt End of the safety spear.

Mining companies should focus on the Sharp End, where the workers are. It’s the end with the highest injury potential but the least amount of influence. But let’s make it different. Adopt an anthro-complexity approach to safety, which gives workers significant influence over the system.

Using the power of everyday stories from workers, we have the capacity to detect potential situations before they fail. The early warning system enables a worker to tell a story “Hey! I have a bad feeling about this.” rather than a story “Damn! I knew it was going to happen.”

How management responds matters to workers. To build mutual trust, “sense-making” tools operate in real-time so mitigating action can be taken immediately.  Stories can be collectively analysed to identify system constraints which influence how people behave. The set of stories represents the organisation’s safety culture. If we can shift the type of stories willingly shared (i.e., more stories like “Hey…” and fewer like “Damn…”, then we have a way to change the safety culture positively.

In the next article (Radical Innovation in Mining Management- Article 3), we examine Mining Differently in the Ecology Age. Complexity Thinking takes Mining beyond Systems Thinking. The whole is greater than its parts and includes the social license community. And a culture change myth is born.


  1. Behind the mining productivity upswing: Technology-enabled transformation, McKinsey, 2018.
  2. Bureaucracy Must Die. Gary Hamel, HBR, Dec 2014.
  3. Agility: It Rhymes with Stability. McKinsey Quarterly, Dec 2015
  4. Tyranny of the Metrics, Jerry Z. Muller, 2018.
  5. ERP Software and The Theory of Constraints, Tom Miller, Jan 2014.
  6. Human Error, James Reason, 1990.