Category Archives: Sense-making

Cynefin® & Safety

Last month we celebrated 21 years of Cynefin. In the new book Cynefin® – weaving sense-making into the fabric of our world, Dave Snowden describes how the framework has evolved and it’s wonderfully illustrated by research artist Sue Borchardt.

The message is that to remain relevant and useful, models, frameworks, and maps change in response to the arrival of new information and learnings. We’ve certainly witnessed that in the world of Safety. Some argue that the proliferation of new models is doing damage by confusing people. I personally welcome diverse thinking as a healthy recognition that life isn’t clean, straight-forward, and fits nicely in a 2×2 table; life is fuzzy, messy, non-linear, and entangled. Very much like the bramble bush background that Sue used to connect the emerging Cynefin versions.

Our anthro-complexity view of safety is different from the traditional view held by industry leaders and executives. It has been strongly influenced and supported by the Cynefin Framework. Safety in organizations is not produced or manufactured. Safety is an emergent property of many interacting forces, such as employees, policies, incentive systems, and regulatory requirements in a complex adaptive system: an organization.

In 2 online panel conversations held last month, I and fellow safety colleagues reminisced about the evolution of safety. We also shared how we can use the Cynefin Framework and Narrative to see new possibilities for designing and improving safety in companies.

Click here to watch the two webinar videos.

Release of new Cynefin® book

For the past 4 months I and Cognitive Edge VP Michael Cheveldave have been writing a chapter in a new book CYNEFIN: Weaving Sense-making into the Fabric of our World. Our chapter is titled: “A Cynefin Approach to Leading Safety in Organizations.”

We’re just 1 of 46 chapters showing how powerful Cynefin® is for making sense of the real world. In ~ 3,000 words, we did our best to describe the anthro-complexity approach to improving Safety in organizations.

We believe that all organizations are complex adaptive systems. Safety is an an emergent property of a complex adaptive system. We explain 3 keypoints to enable safety to emerge:

  1. Work with the system as a whole.
  2. Work from your present state.
  3. Work with small actions to create conditions for big improvements.

Printed and Kindle versions are available at Amazon. Click here If you would like a special copy signed by Dave Snowden.

Black Elephants in our Safety Systems

COVID-19 is a black elephant. A black elephant is a cross between a black swan and the proverbial elephant in the room. The black elephant is a problem that is actually visible to everyone, but no one wants to deal with it, and so they pretend it is not there. When it blows up as a problem, we all feign surprise and shock, behaving as if it were a black swan [1].

Nicholas Nassim Taleb popularized the black swan metaphor to describe an event that is rare, unexpected, and has a large negative, game-changing impact. COVID-19 is an infectious disease that waited for the right conditions to emerge. Like an accident just waiting to happen. It reminds me of Todd’s Conklin’s statement: “Workers don’t cause failures. Workers trigger latent conditions that lie dormant in organizations waiting for this specific moment in time.”

Taleb also noted that a black swan event is often inappropriately rationalized after the fact with the benefit of hindsight. This should ring a bell for those with accident investigation experience. It’s the counterfactual argument when work-as-imagined is compared to work-as-done. What’s ignored is the normal variability adjustments the victim had to make due to unexpected changes in the environment.

The emergence of COVID-19 is not a black swan. We shouldn’t have been surprised but we were. There have been 11 pandemics from the Plague of Justinian (541 – 750 AD) to Ebola (2014-2016).[2] In 2015, Bill Gates warned all nations that we have invested very little in a system to stop an epidemic.[3] In the October 2019 Event 201 global pandemic exercise, a call to action was outlined in seven recommendations.[4] Some countries have acted while others have chosen to ignore the peril for political-economic reasons deemed higher priority.

Those that acted installed seemingly robust fail-safe disaster response systems. Scarred by the SARS epidemic that erupted in 2002, China thought they had an airtight response process free from political meddling in place. However, Wuhan local health bureaucrats not wanting to raise an alarm and cause embarrassment suppressed automatic reporting. This fear kept Beijing in the dark and delayed the response. In our words, their fail-safe system failed. [5]

The real surprise is finding out in a painful way how intricately connected we are globally. Our ground, air, water transportation systems made it easy for the COVID-19 disease to spread exponentially. “Going viral” has sickened and killed thousands, crumpled economies, and plunged societal life into a fearful limbo with no easily discernible end in sight. Tightly coupled supply chains we take for granted are disrupted. Westerners are feeling what “made in China” means when local store shelves remain empty. Everyone is having a firsthand excruciating experience of surviving in a complex adaptive system (CAS).

Every organization is a CAS. Every industry is a CAS. So is every state, country, nation. Civilization is a CAS. We are many complex adaptive systems entangled to form one mega CAS called planet Earth. That idea was reinforced seeing Blue Marble, the image of the Earth from Apollo 17. Boomers felt that when Disney showcased It’s a Small World at the 1964 World’s Fair. (Now that we’ve mentioned it, is the tune streaming in your head too? Sorry about that.)

In the spirit of Safety Differently, let’s ask our 3 fundamental questions: Why? What? How? and pose different, non-traditional responses.

WHY… will we face more Black Elephants?

The emphasis in a CAS is on relationships between agents. Besides humans, other agents are machines, events, and ideas. Relationships are typically non-linear, not if-then causal, strengthened or weakened by fast feedback interactions. The Butterfly effect is a small initial change which can yield a huge impact if a tipping point is reached. Non-linear relationships are exponential like the COVID-19 spread. Many relationships in the real world follow a Pareto distribution, a logarithmic power law. Catastrophes like Black Elephants are rare in frequency but huge in severity. These are also called outliers, as they lie outside the realm of regular expectations of the Gaussian world. So it’s not if they will happen but a matter of when.

The level of complexity increases exponentially every time a new relationship is formed. For humans it could be the simple act of friending on Facebook or accepting a LinkedIn invitation. Or a person you don’t know choosing to follow you on Twitter. Annoying outcomes from new connections are more spam emails and unsolicited ads. More disconcerting is computer programmed machines interacting with other smart parts sometimes in hidden ways. When algorithms collide, no one really knows what will happen. Flash market crashes. Non-ethical AI. Boeing 737 Max 8. Or in one hypothesis, the cutting down of rain forests which allowed once-contained diseases like COVID-19 to infect wild animals. Hmm, workers trigger latent conditions that lie dormant

Realistically organizations are unable to develop emergency plans for every disaster identified. Even if they had unlimited time and money, there’s no guarantee that the recovery solutions will be successful. And by definition, we can’t plan for unknowables and unimaginables.

WHAT…can we do Today?

The starting point is understanding the present situation of the CAS. The Cynefin Framework has been widely around the world in contexts as diverse as the boardrooms of international fashion houses, militaries, NGOs, and SWAT teams on city streets. For a brief explanation of the sense-making framework, check out Jennifer Garvey Berger’s YouTube video.

The above graphic maps the type of safety decisions made and actions executed in each Cynefin domain. No domain is better than any other. The body of knowledge that Safety-I has provided is clearly in the Obvious and Complicated domains. Much of Safety-II advancements reside in the Complicated domain as experts wrestle with new processes and tools. Whether these can be made easy for anyone to use and thus moved into the Obvious domain remains to be seen. A major accomplishment would be shifting the front-line worker mindset to include what goes right when planning a job.

Now let’s apply sense-making in our battle with COVID-19. Be aware this is a dynamic exercise with relationships, events, and ideas constantly changing or emerging. Also note that the Cynefin Framework is a work-in-progress. The Obvious domain is being renamed as the Clear domain.

Self-isolation is in the Clear domain; you haven’t been tested so avoid others as a precautionary measure. Self-quarantine means you have tested positive; your act is to monitor your conditions and respond as you get better or worse.

Conspiracy theorists are in the far corner of the Clear domain. They believe their ordered life mindset has been deliberately disrupted. Strongly held beliefs range from political party subterfuge to willingness to risk death to save the economy to blaming 5G.

At the time of this writing, experts have not agreed if the mandatory wearing of masks will help or hinder the COVID-19 battle. Two resistance movements are shown. Both reside in the Cynefin Complex domain near the Chaotic border. Not all Coronavirus challenges hoping to go viral have been positive. Licking toilet seats may have garnered lots of social media attention for the challenge creator. But it has plunged one follower into the Chaotic domain with his testing positive.[6] Some who attended parties with a feeling of invincibility have also fallen into the Chaotic domain.[7]

The Disorder domain is associated with confusion and not knowing what to do. Many myths, hoaxes, and fake news include expert quotes and references. When eventually exposed as fiction and not fact, they can up the level of personal frustration and anxiety.

One fact is that your overarching safety strategy hasn’t changed: strengthen Robustness + build Resilience. As this article is about surviving change, let’s focus our attention on 3 capabilities of a resilient organization.

With the COVID-19 battle still raging, the chances of doing a fast recovery and returning to the original operating point [A] are practically slim to none.

If we know that we have black elephants, then we have an early detection system in place [C]. Being caught with our pants down simply means the messenger doesn’t have enough trust and respect or the organization bureaucracy is too dominant and overbearing. Path [B] is shaping the “new normalcy” for the organization. This entails asking key questions and exploring options. Change Management specialist Peter Hadas has posed a set of questions:

  • If we suddenly had to double our capacity, could we do it?”
  • Are our systems well connected to suddenly handle a spike in capacity?”
  • If I had to scale back to just 20% of my employees that I would absolutely need to rebuild my company from scratch, who would that be?”
  • Of the remaining 80% of your staff, who has mission-critical information in their heads that is not written down anywhere?

In his blog Peter cites case studies where a downturn was perceived not as a calamity but an opportunity. In terms of safety, let’s ask:

  • What black elephants will be unleashed when our organization changes to the new normalcy?
  • What existing latent conditions will enable safety or danger to emerge due to a new tipping point in the new normalcy?
  • When we return to work or if we need new recruits, what will be different in our safety induction and orientation programs in the new normalcy?
  • What human-imposed constraints such as safety policies, standards, rules, procedures need to adapt in the new normalcy?

HOW…can we operationalize the What?

Top Management is under fire to demonstrate leadership and take charge in a time of crisis. First step: Stop the bleeding to get out of the Cynefin Chaotic domain. Now what? Craft an idealistic vision of the new normalcy? Direct subordinates to “make it so”? Well, this would be a Complicated domain approach. Since the future is uncertain and unpredictable, developing the new normalcy happens in the Cynefin Complex domain. Instead we manage the evolutionary potential of the Present and shape the new normalcy on a different scaffold. Classical economics? Evonomics? Doughnut Economics? How about Narrative economics?

One of the principles of Safety Differently is: Safety is not defined by the absence of accidents, but by the presence of capacity. Adaptive Safety means building adaptive capacity. When working in the Complex domain, one capacity is possessing useful heuristics to cope with uncertainty. Heuristics are simple, efficient rules we use to form judgments and made decisions. These are mental shortcuts developed on past successful experiences. The upside is they can be hard measures of performance if used correctly (i.e., not abstract and no gamification). The downside is that heuristics can blind us or may not work in novel situations. So don’t get locked into a trusty but rusty heuristic and be willing to adapt.

To operationalize the What, let’s apply 3 simple rules drilled into US soldiers to improve the chances of survival in war: Keep moving, stay in communication, and head to higher ground.

Keep moving

Okay, we’ve stopped the bleeding. We, however, can’t sit still hoping to wait until things settle out. Nor go into paralysis analysis looking at a multitude of options. We don’t want to be an easy target or prey for a competitive predator. Let’s speedily move into the Complex domain and head towards this new normalcy.

Before we move, we need a couple of tools – a compass and a map to plot our path [B]. As shown by Palladio’s Amber Compass, a complexity thinking compass is different. In our backpack will be tools to probe the system (mine detector?), launch experiments (flares?), and that map not only to plot our direction but monitor our progress.

In the military world, each soldier on the battlefield is equipped with a GPS device. This capacity enables the Command centre to monitor the movement of troops in real-time on a visual screen. How might we build a similar map of movement towards a new normalcy?

Stay in Communication

In the battle against COVID-19 to stop the bleeding, numerous organizations immediately enacted an age-old heuristic: terminate, layoff, stand down. This action is akin to removing soldiers from the battlefield for financial reasons. The policy is based on the traditional reductionistic paradigm of treating people as replaceable parts of a mechanistic system. It reinforces a Classical Management theory of treating humans as expenses not assets. (Suggestion: Organizations that state Our people are our greatest resource should update to our greatest expendable resource.)

In novel times like today, perhaps it calls for a different heuristic. Denmark as a nation CAS leader decided to “Freeze the Economy.”[8] The Danish government told private companies hit by the effects of the pandemic that it would pay 75% of their employees’ salaries to avoid mass layoffs. The idea is to enable companies to preserve their relationship with their workers. It’s going to be harder to have a strong recovery if companies have to spend time hiring back workers that have been fired. Other countries like Canada [9] and the US [10] are following Denmark’s lead and launching modified experiments. From a complexity perspective, this is a holistic paradigm where the whole is greater than the sum of its parts.

No matter what employee policy has been invoked, cutting payroll costs does not necessarily mean disengaging. Along the same lines, practicing social distancing does not mean social disconnecting. One can stay in communication. But let’s communicate differently. Ron Gantt wrote that it’s time for an anthropological approach. We agree. Let’s become physically-distanced storytellers and ethnographers.

Cognitive Edge is offering the adaptive capacity of SenseMaker® for COVID-19  to collect real-life stories from employees working remotely plus temporarily removed from the battlefield. It’s an opportunity to show empathy, sense wellbeing, and build early detection capability [C]. Most of all, we can use stories to generate our map of movement towards a new normalcy.

Head to higher ground

This is a story-generated 2D contour map from Safety Pulse. Each dot is a story that can be read by clicking on it. The red X marks a large cluster of undesirable stories – rules are being bent to get a low amount of work done. In our military analogy, we have soldiers on a hill but it’s the wrong high ground.

For illustrative purposes, the higher ground or new normalcy is the green checkmark where quality work is being completed on-time, on-budget, and within the safety rules. Thanks to the map, we now have our compass heading. The question is how do we make it easy to head to the higher ground? In other words, how might we get fewer stories at red X and more stories like green checkmark?

The challenge is the ground to be traversed is an entanglement of work-as-imagined safety policies, standards, rules, procedures and work-as-done practices. W-A-I is created by the Blunt end and W-A-D by the Sharp end of the safety spear. Another twisted layer is the formal vertical hierarchy and informal horizontal networks. Entanglement implies that any new normalcy thinking ought to include everyone and shines a different light on Diversity.

Heading in a Top-down only route to a new normalcy could cause inadvertent harm since it is clueless on how work really gets done in the organization. Read Peter’s firsthand experience of a company letting go of people with mission-critical tacit knowledge. Similarly a Bottom-up only route may fail to consider PESTLE tensions that impact the entire safety spear.

Shaping the new normalcy is not a change initiative with an authoritative few making a huge Ego bet. Think carefully about consultants recommending a huge disruptive transformation change. People are in a fragile state trying to personally survive COVID-19. Think the opposite. It’s Eco and empowering all in the CAS. Think not about doing it to people but doing it with people.

The Executive’s role is to mobilize diverse learning teams and act as central coordinator. These would not be large teams subjected to Order system linear forming -> storming ->norming ->performing crapola. Teams would be 3 people (trio) with the capacity of diverse knowledge and empowered to make decisions within their coherent unit. A cardinal rule would be a trio must inform Central what decisions they have made. Diversity is not necessarily the typical demographic lines of gender, age, geographic location but body of knowledge and informal network relationships. For example, a trio could be comprised of a senior executive, a new employee fresh out of college, and a front-line tradesperson. Another could be an IT specialist, a mechanic, and a public relations coordinator.

Each trio would have the skillset to design safe-to-fail experiments. But before launching, they would engage the Unintended Consequences trio. Good candidates for the UC trio would be the CFO, a risk analyst, and the  person with the reputation of being the noisiest complainer in the organization. Using a process like Ritual Dissent or Red Teaming, the UC trio has the task of pointing out the risks and any harm that a safe-to-fail experiment might unleash. Their role isn’t to kill but improve the proposal.

Central would have the capacity to navigate using a near real-time dashboard with maps generated by stories. All trios would have access to the maps to learn how their experiments are enabling desirable aspects of a new normalcy to emerge.

Informed by authentic voices (i.e, click on a map dot and read its story), Central would make the strategic choice what will be in or out of the new normalcy. Trios or more probably combinations would form innovation teams to implement.

Innovation teams would carry on resilient path [B] and move into the Complicated domain and apply project management practices. Key activities would be document, adapt constraints (i.e., policies, standards, rules, procedures), and train the workforce in the patterns of the new normalcy.

The continuous flow of stories is required for the dashboard and maps to maintain their near real-time value to manage the PM portfolio.  Establishing a human sensor network would also fuel the Early Detection capability [C]. Imagine being able to respond to “I’ve got a bad feeling about this” attitudinal stories well before they turn into “We wouldn’t be in this mess if someone had listened to me.”

In the new normalcy, everything would be up for scrutiny by trios including venerable best practices, sacred cows and of course, black elephants. Small, simple changes such as replacing weekly reports and entering stories whenever (24/7/365) and wherever (office/field/home) can go a long way.

Act now. Act quickly. Act differently.

References:

  1. The Black Elephant Challenge for Governments. Peter Ho, former head of civil service for the city of Singapore. 2017.
  2. Pandemics that Changed the Course of Human History. Business Insider. 2020-Mar-20.
  3. The next outbreak? We’re not ready. Bill Gates. TED Talk. 2015-04-03.
  4. Public-private cooperation for pandemic preparedness and response. Event 201 recommendations. 2019-10.
  5. China Created a Fail-Safe System to Track Contagions. It Failed. The New York Times. 2020-03-29.
  6. ‘Corona Challenge’: Man Tests Positive For COVID-19 Days After Licking Toilet Bowl. 2020-03-26.
  7. Florida college students test positive for coronavirus after going on spring break. CBS News. 2020-03-23.
  8. Denmark’s Idea Could Help the World Avoid a Great Depression. The Atlantic. 2020-03-21.
  9. Trudeau promises 75% wage subsidy for businesses hit by coronavirus pandemic. Global News. 2020-03-27.
  10. The government will now pay businesses to keep workers on payrolls (and hire back ones they laid off). Fast Company. 2020-04-02.

Adaptive Safety Masterclass interview

Southpac International who sponsored my Adaptive Safety HOPLAB Masterclass has published 2 YouTube videos on my interview with CEO Andy Shone.


https://youtu.be/RHz1SWp6cbo
00:16 – Why are we talking about complexity-based approaches
01:25 – VUCA world and why are we using these terms more frequently?
03:27 – We have mostly a hierarchy system, who is really in charge of a complex adaptive system?
04:33 – What is the Cyenfin Framework?
07:00 – Explain the costs for treating everything as an order system


https://youtu.be/rua4PKPXw0w
00:15 – In the complexity domain of the Cynefin Framework, why are stories so valuable?
04:29 – Explain vectoring in Cynefin Framework
07:47 – What are the implications for safety practice?
10:35 – What is storytelling to you?

Adaptive Safety: HOP Masterclass

On November 6&7 I had the immense pleasure to deliver our Adaptive  Safety workshop as part of Southpac Human & Organizational Performance (HOP) Masterclass series. The location couldn’t have been better at the Swiss Belhotel in Brisbane, Australia.

Course notes were provided. I presented some slides that were not in the handouts. Class participants can click here for the extras. Included is the Cynefin Mapping method to generate action plans for each domain.

The Vector theory of change applies the change intervention question: “How might we get more stores like these and fewer like those?” In the last exercise we made the link to the 5 HOP principles. As safety ethnographers, we can search and listen for stories that either support or violate the principles.

Consider this story: “It was a rush job and in a hurry I dropped my hammer and dented what I was working on.” What happened next? How did people respond? Was it “You idiot! It’s your fault if  we don’t meet the deadline. Get your act together!” Or was it “Okay. Let’s reset. What can we change to make the deadline? If we can’t, I’ll find out how hard the deadline really is.”

If a friend asks you: “My  son is thinking of applying for a job where you work. What’s it like working there?” Instead of replying yes or no, tell your friend your version of the story about dropping the hammer. He’ll understand.

Radical Innovation in Mining Management Article 3: The Ecology Age – Stability + Agility

The following article was published on 2019 Sep 04 at http://www.austmine.com.au/Events/category/articles-editorials/radical-innovation-in-mining-management-article-3-the-ecology-age-stability-agility

In the last two editions we discussed how yesterday’s solutions have led to 2 myths that control current mining thinking.

Myth 1: The best way to run a mine is to focus on cost certainty and manage people as if they are parts of a machine.

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

In this article we examine Mining Differently in the Ecology Age. Complexity Thinking takes Mining beyond Systems Thinking.

This lengthy article may be covering a lot of new ground for readers. So here’s a quick summary:

1.       Open both eyes to see the real world.

2.       The secret sauce is Stability + Agility.

3.       Forget about creating culture, social license to operate and safety; all are emergent properties of a complex adaptive system.

4.       Shape your mining operations by doing what comes naturally – storytelling.

Today we are coming out of the second “yellow bubble”, a mix of Classical Management theory from the Industrial Age and Systems Thinking with the notion we can engineer technology-process-people linear systems from start to finish. Now stir into the mix an ecological perspective vociferously highlighting why some problems remain unresolved and are causing to new ones to emerge. For example, with a cradle-to-grave mindset what does Social license to operate really mean? Does sustainability have a chance? Is a circular economy[1] in mining viable or will the concept be duly crushed by short-term profit seekers? These are higher-level industry questions that won’t go away. For this third article, we’ll examine them at the mining operations level.

Three Systems in the Real World

To understand what’s going on requires “opening both eyes” to see three systems: Order, Complex, and Chaos. 

With only one eye open in the Industrial and Information ages we saw machines and humans behaving in stable, repeatable, predictable environments. Exploiting the idea of Reductionism, a system could be reduced into process, technology, and people parts, root cause and effect relationships found, parts fixed, and the whole re-assembled. We strive for Stability with operations running smoothly like clockwork in a sea of calmness. Best Practices and Optimization are primary drivers in the Order system. Looking in the rear-view mirror, one can comprehend how Myths 1 and 2 seized an opportunity to dictate in the Order System. We have explained though by thinking differently how organizations can overcome the myths and even reap more benefits from a stable production flow.

Chaos is very dynamic and volatile. Everything is random and cause & effect relationships don’t exist. Entering the Chaotic system is typically accidental; it’s an unexpected surprise like falling off a cliff, the Edge of Chaos. We strive to escape as quickly as possible by returning to the Order system (Recovery) or moving into the Complex system (Exploration). Being in Chaos is temporal – you do not stay there for any length of time. If you don’t act immediately, somebody or something else will and the situation will change.

Unlike the Order system, the future is unpredictable in the Complex system. It feels like Chaos with confusion and uncertainty but with one important difference: Some semblance of Order may exist in the form of underlying patterns. Complex patterns in nature have been discovered in clouds, coastlines, beaches, trees, leaves, seashells. We can recognize likenesses across a complex system and come to some understanding of the whole without dividing it into its parts.

We are interested in a special type of complex system – a complex adaptivesystem (CAS). A tornado is a complex system; eventually all energy dissipates and it naturally dies out. In contrast, a CAS adapts to survive changing conditions. Birds flock, fish swarm, ants colonize by following simple rules to survive. Humans form tribes and gangs. After a company restructuring that breaks up silos, it’s common to observe informal networks like cliques, coffee clubs, meetups later reappearing, a complexity phenomenon called self-organization. The mining industry is a CAS interconnecting companies, customers, suppliers, agencies, communities and each is a CAS in its own right.

In the Complex system, we strive for Agility to make sense of dilemmas, paradoxes, and conflicts so that we can decide and take action. In the Ecology Age it’s not Stability or Agility but both/and.

“Agility is the ability of an organization to renew itself, adapt, change quickly, and succeed in a rapidly changing, ambiguous, turbulent environment. Agility is not incompatible with stability—quite the contrary. Agility requires stability for most companies.

Agility needs two things. One is a dynamic capability, the ability to move fast—speed, nimbleness, responsiveness. And agility requires stability, a stable foundation—a platform, if you will—of things that don’t change. It’s this stable backbone that becomes a springboard for the company, an anchor point that doesn’t change while a whole bunch of other things are changing constantly.”[2]

Agility in the Complex system involves launching small trial & error experiments to learn, monitor consequences, and adapt the social license.

“Authors in the field of complexity in the public sphere “identify common themes such as the impossibility of prediction and therefore the need to adopt more experimental approaches to intervention based on the assumption that there will be new phenomena (unknown unknowns) likely to emerge endogenously.”[3]

One more key point about Complexity. We do not create stability nor agility. They are emergent properties of a CAS. What we create are the conditions that enable them to emerge.

“Agility is an ‘outcome and not a goal’. If you focus on ‘doing’ agile you’ll miss the whole point of delivering value to your customer more effectively, and if you fail to become agile as an organization, you’ll fail to address the reasons you are not agile to begin with.”
             Nigel Thurlow, Chief of Agile – Toyota Connected

And as we learned from the myths, the wrong conditions like extreme bureaucracy can be harmful and allow instability and paralysis to emerge.

Culture Change in the Order system

In the Order system the constraints are so fixed that all behaviour is predictable. Causal relationships exist. In the Information age, several mindsets have persevered: Culture is the way people behave around here (when Management isn’t looking). Culture can be created. Only Top Management can modify their organization’s culture. Senior leaders craft ‘value statements’ that outline how they want people to behave. Focus on individual habits. Change culture one person at a time.

A scene frequently played is a company transformation program launched with culture change leading the way forward. The change hypothesis is: If we can change worker behaviour then we will achieve the desired results. Culture change requires defining an ideal future state, designing a roadmap, setting explicit milestones, and aligning people to close the gap. Scaling means if the desired behaviour changes works in one context, then it will work in another. Aggregation is the corollary of reductionism. Copy. Paste. Integrate.

The Order system assumptions have led to the third myth:

Myth 3: We can achieve social licence acceptance and safety aims within our current management paradigm by pursuing effective culture change.

Culture, social license acceptance and safety are complex issues; all are emergent properties of a CAS. It’s not a simple matter of closing the gap between a predicted future and the present. In the Ecology age, evolving the present to construct a new direction is more important than creating false expectations about how things could be in the future. You make sense of your current situation and see what you can change. You define an exploratory path and a speed of travel, not outcome-based targets.

Social License to Operate

The Productivity Platform described in the previous article creates the conditions that enables Stability to emerge. It frees up time for managers to pursue Social License to Operate issues with Agility. And it couldn’t come at a better time. According to Ernst & Young:[4]

The Productivity Platform described in the previous article creates the conditions that enables Stability to emerge. It frees up time for managers to pursue Social License to Operate issues with Agility. And it couldn’t come at a better time. According to Ernst & Young:[4]

“Surveying over 250 sector participants from around the world, we have seen ‘License to operate’ rocket to first position, with over half of our respondents nominating it as the No. 1 risk.

  • It is the key risk that CEOs and boards are discussing because the current approach is not broad enough, the stakeholder landscape is changing and miners need to adapt.
  • We have seen the advance of nationalism globally.
  • The necessity of digital transformation highlights the need for a stronger license to operate.
  • The sector is working to redefine its image as a sustainable and responsible source of the world’s minerals. But while many in the industry are saying all the right things, their actions do not follow their words, and the many stakeholders are not fooled.
  • License to operate has evolved beyond the narrow focus on social and environmental issues. There are now increasing expectations of true shared value outcomes from mining projects. Any misstep can impact the ability to access capital or even result in a total loss of license.
  • Mining and metals companies need to transform their business models to remain more competitive and bring all their stakeholders along on the journey. A new approach is required, and license to operate needs to quickly become part of a mining company’s DNA in the same way as safety is.’

The stakeholder landscape is shifting. There is more information, bigger platforms and more at stake than ever before. Underestimating the power of each and every single stakeholder would be a mistake.”

Look no further than the social and environmental controversy over bringing the Adani Carmichael coal mine project on line. It highlights the political divide in Australia in mitigating climate change. Carmichael is seen as the thin edge of the wedge. Adani would blaze a trail for six other potential mines in Queensland’s Galilee Basin.

Social License problems can dramatically impact mines in production. Dozens of people were injured in clashes between local residents and workers from a Chinese company at a gold mine in Kyrgyzstan’s Naryn province.[6] About 500 local residents gathered near the mine on August 5 and entered the construction site attempting to seize several trucks belonging to the company. The locals blamed the Chinese company for the mass death of livestock, saying the mining firm has contaminated the local environment. The Prime Minister of Kyrgyzstan released the following statement:

“The problems that exist in the field of the mining industry today have accumulated over the years and require serious rethinking and decisive actions. I want to stress: if investors violate the requirements and rights of our citizens, we will take appropriate measures against them. But everything should be within the law. If people demand to close the enterprises because of each such incident, then all investors will turn away from us. The actions of individuals who want to take advantage of this incident instantly jeopardize what we have achieved through great efforts.”

We totally agree the current approach is not broad enough, the stakeholder landscape is changing, and miners need to adapt. But not an approach engrained in the Order system.

You don’t manage Social License to Operate. You don’t make a list of activities, establish KPIs, and measure performance. You do more than listen to the loudest and most important voices; you listen to them all. You don’t make promises you can’t control and then assign blame or find excuses when not delivered.

“The Social License has been defined as existing when a project has the ongoing approval within the local community and other stakeholders, ongoing approval or broad social acceptance and, most frequently, as ongoing acceptance.

…Social License is rooted in the beliefs, perceptions and opinions held by the local population and other stakeholders.

…Social License has to be earned and then maintained.”[5]

Could a mine in Australia be nearing a Social License tipping point? Whether you agree or deny, you won’t really know until you fall over the Edge of Chaos. Human tipping points can’t be seen. Clearly the aim is to proactively avoid plunging into the Chaotic system. A new approach will require thinking differently. It starts by not giving Social Licence to Operate lip service as one more business risk to be avoided but as an emergent property of a CAS.

An Anthro-complexity approach

Traditional techniques such as Likert surveys and questionnaires do not function well in the perpetually changing Complex system. The length of cycle time does not pass the Agility test. Professional time is needed designing the survey instrument, obtaining approvals, collecting, analyzing, and reporting data. Information is predominantly numerical with bar charts and pie graphs. It’s difficult to explain “what a composite 3.7 score out of 5” really means. Comments submitted may shed some light.

Interviewing involves considerably more time. To manage costs, the number conducted is limited to a selected few; who decides on the sample size can become a point of contention. Interviewers unconsciously (or deliberately) inject their own cognitive biases when preparing the set of questions to be asked. Will the findings truly reflect what was said or simply be an exercise to validate pre-determined conclusions? How is accuracy affected since data is filtered by an analyst’s interpretation? Is there sufficient information in the snapshot-in-time report for decision-makers to act upon? If a month or two have passed, is it still valid especially if new events have occurred?

The writing practice is to include a few respondent comments and quotes in reports. Because they add qualitative depth and meaning, considerable weight is given to them during discussions. However, there’s a risk when decision-makers are restricted to what biased analysts pick and choose as worthy information. And the risks are ominous – taking ill-fated action predicated on a misunderstanding of community feelings, creating an unintended uproar, further damaging social license trust.

Fortunately, there is a better way.  One that has been used globally by military, government, non-profits, private companies for the past decade. The Narrative SenseMaker® tool and process developed by Cognitive Edge[7] uses design principles based on natural science, complexity thinking, and from anthropology a branch called ethnography.

A story is an event that a person experienced first-hand or heard about. A narrative is how that story is shared. Humans are natural storytellers and narratives are ideal for making sense of complexity because they include context. Narratives can be collected from anyone located anywhere who is willing to share good and bad experiences about mining operations.

The approach enables storytellers to self-interpret their experiences, giving them the power to tell us what those narratives mean, rather than handing over that power to researchers or computer algorithms. Data visualization tools input stories as data points to generate 2D contour maps called “narrative landscapes.” In the sample map shown, decision-makers can see the direction heading (top-right corner) and navigate on the social license journey. If a question arises about the location of a data point, a simple click pops open the story for reading. This feature is called “disintermediation” and provides a direct line-of-sight connection between storytellers and decision-makers. You can’t beat this for authenticity.

There are resilient organizations who use Narrative Sense-making on a real-time 24/7/365 basis to monitor shifting customer, employee, investor, supplier, stakeholder dispositions. One company does continuous mapping of unarticulated customer needs on the lookout for clusters. They put prototyping teams to work on a cluster to see if it is worth addressing the need discovered. Resilient means anticipating and proactively getting in front of the situation. In today’s reality diverse social media events on Twitter, Facebook can go viral as they are fueled by the Internet’s fast feedback loops. People are attracted and self-organize into advocacy and protest groups. Actions are irreversible. – you can’t take them back like you can in the Order system. These are all phenomena of complexity.

Culture change in the Complex system

Unlike the Order system, the future is unpredictable in the Complex system. That includes human behaviour. People are not logical, information-processing machines. We are irrational, emotionally-charged pattern recognizers. Each of us in varying degrees is mentally infected by over 100 cognitive biases and physically by inattentional blindness – we do not see what we do not expect to see.

Think about the last time you heard a presentation announcing a new change initiative. From Cognitive Science research on inattentional blindness people hear about 5% of what was just said. Brains autonomically begin comparing against the most recent experiences. While still processing, you hear: “If we do this, then in x year’s time look at how wonderful life will be! Any questions?” After answering a few queries emanating from “first-fit” pattern matches, leaders exit feeling confident the big launch was a success. But actually people are still processing, searching for a “best-fit” match. First-fit pattern recognition is “Thinking Fast” while Best-fit is “Thinking Slow”, two modes of thought analyzed by Nobel Memorial Prize in Economic Sciences laureate Daniel Kahneman.[8]

Thinking Slow happens when people later meet to chew over the new initiative and share stories. As a survival mechanism, the brain is naturally geared towards recalling stories of failure and bad experiences. Feedback loops tend to amplify negative feelings into powerful forces. They can range from “No way we can do this!” anger to “Here we go again” resignation. The ethnographic practice called Appreciation Inquiry is a noble effort to balance the overwhelming negativity with positive stories about good memories. With the anthro-complexity approach, it is what it is. Negative plus the positive. Whatever is in the Yellow Bubble.

We shape behaviour from a natural science perspective. We focus on the system, not humans. We pay attention to system relationships and interactions. Dialogue shifts from unpredictable human behaviour to predictable system conditions humans face every day. As noted by James Reason: “You cannot change the human condition, but you can change the conditions in which humans work.”[9]

Conditions include business policies, standards, processes, rules, and so on that impact humans. Reinforcing or relaxing constraints will influence relationships and interactions and thus behaviour. Stories provide the context why a person decided to behave in a particular way. Because narratives are emotional experiences, they offer insights into attitudes and mindsets, the core centre of personal change.

We can view Culture as the emergent set of stories acted out every day. A 2D narrative landscape produced from stories is a partial representation of the culture. Because it’s a complex system, we can recognize likenesses and come to some understanding of the whole without dividing it into its parts.

The intervention question now becomes: What system constraint might we change to get more stories like these and fewer like those?  It is much easier to say “it’s like one of these” than to articulate the specific qualities of a problem.

Safety in the Ecology Age

Safety maps can be easily generated using the accustomed Narrative Sense-making tools in place for Social License to Operate. In this example, one cluster (brown area) requires immediate attention. Why are workers getting the job done but not following the rules. Is it workarounds? Shortcuts? Clicking on a dot and reading a story in a cluster provides contextual information.

Because attention is on the system and constraints, storytellers feel psychologically safe to participate without any fear of reprisal.

Safety is an ethical responsibility. There is the belief that the only ethically and morally acceptable accident goal is: Zero; that is, one absolutely cannot allow harm, injury, or disease. On the other hand, how realistic is it to demand perfection from fallible humans, machines and systems? Known as Vision Zero, other labels frequently used are Zero Accident Vision (ZAV), Zero Harm, No Harm.

Professor Rob Long laments: “No other concept in safety has ever caused more divide, debate and long term damage to safety than that of Zero Harm.” [10] There are, however, some merits about Zero as stated by Sidney Dekker “…in a complex, dynamic, resource-constrained and goal-conflicted world, zero is not an achievable target, but a zero commitment may be worth some encouragement.”[11]

We can take the air out of the controversy by viewing Safety as an emergent property of a CAS. The Vision Zero debate is avoided because safety isn’t measured using accidents as Safety KPIs. In its place is the ongoing monitoring of conditions that enable safety to emerge. The green area on this particular narrative landscape displays the vector direction towards Zero Vision. Progress is denoted by the visual shifting of clusters with more stories here, fewer there.

The End of the Beginning

As one of over 3,000 readers following the series, thanks and we hope you’ve enjoyed the ride in our attempt to explain how we got to Now. Hopefully we have been able to weave together the importance of history and making connections to one’s roots. We’ve probably missed a few stitches and made some mistakes but in the Age of Ecology, we accept people aren’t perfect machines. We are fallible and will make errors.

As one of over 3,000 readers following the series, thanks and we hope you’ve enjoyed the ride in our attempt to explain how we got to Now. Hopefully we have been able to weave together the importance of history and making connections to one’s roots. We’ve probably missed a few stitches and made some mistakes but in the Age of Ecology, we accept people aren’t perfect machines. We are fallible and will make errors.

By examining the Mining Industry’s historical patterns, we have a better understanding what the deep value streams are in what we do today, what we need to preserve for the future, and what we must let go from the past. What remains become the foundation on which new ideas will be born.

Mining has had its share of successes and failures. One thing we can say with certainty about an unpredictable future is that the “2 steps forward, 1 step backwards” learning pattern will continue. We are learning how to learn, experientially.

We have no idea how long the Age of Ecology will last. All that we know is something better will eventually come over the horizon. So stay focused managing the evolutionary potential of the Present and keep an open mind to detect the emergence of the next Age.

Upcoming webinars and workshops

A video recording of the 1-hour Mining Differently webinar delivered on August 29 will be posted on the stratflow.com.au website and YouTube. Hendrik Lourens and Jason Eagleton identified the fundamental constraint shackling employee and mine performance. The good news was this has been overcome in more than 90+ mine interventions.

We will host our second Mining Differently webinar on September 25. This one will deal with Ecology age issues: social licence to operate, safety and cultural aspects that are rising in importance.

We are also conducting 1-day Mining Differently workshops on October 31 (note change to Melbourne) and November 8 (Brisbane). The workshops will include exercises to practice the Theory of Constraints and Complexity thinking. To be added to our invitation list, please contact Hendrik Lourens at hendrik@stratflow.com.au.

For readers with a particular interest in safety, Gary Wong will be delivering 2-day Adaptive Safety workshops in Brisbane (Nov 6 & 7) and Auckland (Nov 10 & 11). Please contact Gary Wong at GaryWong@gswong.com for registration information.

Written by Gary Wong and Hendrik Lourens

References

1. What is Circular Economy? http://bit.ly/2YsOD5Z
2. Agility: It Rhymes with Stability. McKinsey Quarterly, Dec 2015
3. Top 10 Business Risks facing Mining and Metals in 2019-20. Ernst & Young, 2019. https://go.ey.com/2YrMlEd 
4. Complexity theory and Public Management: a ‘becoming’ field. E. A. Eppel and M. L. Rhodes, Public Management Review, vol. 20, no. 7, pp. 949-959, 2018
5. Kyrgyzstan: Locals clash with Chinese mining company workers. http://bit.ly/2T8UwnV
6. What is the Social License? http://bit.ly/2YvdAOf
7. Disclaimer: Gary Wong is associated with Cognitive Edge as a Cynefin trainer but not as an employee. https://cognitive-edge.com
8. Thinking, Fast and Slow. Daniel Kahneman. 2011
9. Managing Maintenance Error: A Practical Guide. James Reason & Alan Hobbs. 2003
10.For The Love of Zero: Human Fallibility and Risk. Rob Long. 2012. http://bit.ly/2TcbVMA
11. Zero vision and a Western salvation narrative. Sidney Dekker, Robert Long, Jean-Luc Wybo. 2015 http://bit.ly/2TeT3fF

Radical Innovation in Mining Management: The Information Age – Myth 1 Reinforcement and Myth 2 Domination

The following article was published on 2019 July 24 at  http://www.austmine.com.au/News/radical-innovation-in-mining-management-article-2-the-information-age-myth-1-reinforcement-and-myth-2-domination

Austmine is the leading industry body for the Australian Mining, Equipment, Technology and Services (METS) sector. 

In the last two editions, we discussed how yesterday’s solutions have led to three myths that control current mining thinking.

Myth 1: The best way to run a mine is to focus on cost certainty and manage people as if they are parts of a machine.

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

Myth 3: We can achieve social licence acceptance and safety aims within our current management paradigm by pursuing effective culture change.

This article explains the second “yellow bubble” we find ourselves in today.

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.

Thank you for the feedback and enthusiastic show of support. A 1-hour webinar titled Mining Differently is scheduled for August 29. This webinar will illustrate the practical problems caused by Myths 1 and 2 and how mines have successfully dealt with them.

Planned for September 25 is a follow-up Webinar – Mining Differently Part 2. This will deal with Ecology age issues: social licence to operate, safety and cultural aspects that are rising in importance.

We are also conducting 1-day Mining Differently workshops on October 31 (Sydney) and November 8 (Brisbane). To be added to our invitation list, please contact Hendrik Lourens at hendrik@stratflow.com.au.

Written by Gary Wong and Hendrik Lourens

References

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. http://bit.ly/2XU3few
6. Human Error, James Reason, 1990.


Radical Innovation in Mining Management: The Industrial Age fuelled by Myth 1

The following article was published on 2019 June 27 at http://www.austmine.com.au/news/radical-innovation-in-mining-management-1  Austmine is the leading industry body for the Australian Mining, Equipment, Technology and Services (METS) sector. 

In the last edition we introduced how yesterday’s solutions have led to three myths that control current mining thinking.

Myth 1: The best way to run a mine is to focus on cost certainty and manage people as if they are parts of a machine.

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

Myth 3: We can achieve social licence acceptance and safety aims within our current management paradigm by pursuing effective culture change.

Each myth began as a solution for a specific era of time.

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A myth follows a life-cycle S-curve pattern. It slowly begins as a new idea in the embryonic stage. A growth spurt occurs when people embrace the idea; the adoption rate rapidly increases. A myth can perpetuate for many years, decades, centuries. As time passes and the myth matures, it succumbs to changes in society, technology, and environment. Methods founded on the myth struggle to solve prevailing problems. Different solutions emerge, some based on research breakthroughs and some unfortunately based on pseudoscience. This crisis period is pictorialised by the “yellow bubble.” As the myth is still the dominant paradigm, myth protectors attempt to maintain the status quo by denying, challenging or crushing the rise of disruptive ideas.

It sounds wise for organisations which are generating big profits to show reluctance to change. Everyone has heard the story about Kodak whose managers didn’t recognise soon enough that digital technology would decimate its traditional business. According to these managers, it’s a myth. They were very aware of the new technology. The failure was not convincing Kodak executives to provide R&D funding. The finance decision-makers did not want anything to disrupt the flow of money coming from film.[1]

For consultants who have created a lucrative business, it’s reasonable to keep “milking the cow.” After all, the myth has not reached the peak yet. Enticing spinoff solutions are sold to clients such as “train the trainer” to institutionalise the myth and strengthen the consulting relationship. Late maturity is often marked by a professional certification program with stepped levels of knowledge attainment. Learn all there is to know and earn a badge. But it’s also a signal the declining stage of the S-curve is nearing.

Others realise earlier in the life-cycle the ground beneath is dramatically shifted. They appreciate the myth’s thinking has been valuable and still delivering results. However, they also know why clients are staying awake at night thinking about unresolvable problems. As Peter Senge said: “Today’s problems come from yesterday’s solutions.” It’s time to “jump the S-curve” and explore what the next Age and its solutions has to offer.

Our intent is to not criticise the past by searching for root cause, blaming someone, but learning from it. We have the pleasure of hindsight bias. In this article we will turn back the clock to see what made logical sense as the Industrial Age unfolded. We delve deeper into Myth 1 and the problems it creates today.

Industrial Age Myth: The best way to run a mine is to focus on cost certainty and manage people as if they are parts of a machine.  

The Industrial Age was a golden period of growth, expansion and productivity increase. The big idea in the early 20th century was Frederick Taylor’s Scientific Management principles of productivity.

Two quotes from Taylor illustrate the managerial thinking at the time.

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Order, structure, and discipline emanated from Taylor’s beliefs. Industrial giants like Henry Ford implemented the machine assembly line and production flow concepts into manufacturing. In line with this thinking was Ford’s “You can have any colour of car as long as it is black.” Certainty meant dealing with “known knowns” and working with proven cause & effect relationships.

The Industrial Age birthed statistics and statistical theory. The first control chart appeared in 1924. People schooled in Scientific Management developed the new method of statistical process control (SPC). However, it wasn’t successfully implemented in a business setting until the 1950s. Other cost certainty methods that followed included cost accounting, activity-based costing, inventory management, zero-based budgeting, material requirements planning (MRP).

Academic professors turned consultants chimed in with business research applying a case study approach. It didn’t take long before project managers were writing a business case complete with a benefit-cost analysis.

In conjunction with improving assembly line operations was the formal organisation of people. Academics and big consulting firms introduced an idea dating as far back as Plato – Division of Labour. A managerial class would separate decision making from the doing of work, a strategy visible in the institutions of church and military at the time. The schema took root and easily spread in a relatively stable, repeatable, and predictable work environment.[2]

An early adopter was General Motors who implemented the divisional organisation in response to the car market demanding greater variety and choice. Cost accounting was used to calculate transfer pricing and keep the system coherent. This made sense because 85-90% of the value of an item sold could be attributed to variable costs (direct labour and raw material).[3]  As engineering, financial and marketing functions grew to satisfy the evolving market, by the late 1990s only 30-40% of costs were truly variable. However, management thinking stayed the same and fixed overhead costs were allocated by various means. This started to skew decision making, but few noticed.

To keep the assembly line running smoothly, engineers, accountants, and process analysts closely tracked what went wrong. Control was about minimalising deviations and stoppages like machine breakdowns, equipment failures, supply shortages. Failure analysis extended to the treatment of front-line workers. Processes were designed with humans performing “perfectly” without errors. Mistakes and absenteeism were not tolerated and often led to loss of pay punishment or outright dismissal.

In 1936 Charlie Chaplin wrote and directed the film “Modern Times.” While billed as a comedy, the film captured the painful working conditions shaped by the efficiencies of modern industrialisation.

The rise of unions

Counterbalancing the heavy-handed treatment of workers was the rise of labour unions. Work stoppage was the economic weapon. Not all strikes were confined to internal struggles between workers and management; politicians and even military troops were drawn into the picture. In Australia the 1949 coal miners strike saw 23,000 workers withdraw their labour between June 27 and August 15 of that year[4]. The dispute dominated Australian politics at the time and saw elements of revolution and counter-revolution which had been a rarity on Australian soil. Labour unrest shook the once stable work environment. The assumption that humans behaved in a predictable manner like machines was thrown into doubt.

The non-union managerial class was also subjected to command & control. HR produced job descriptions which included new terms such as roles & responsibilities, accountability, transparency, blameworthiness. Management by Objectives (MBO) was popularised by Peter Drucker in his 1954 book The Practice of Management. It surfaced as a system to measure managerial performance. Pressure was applied by setting annual KPI targets and stretch objectives for individuals aspiring to climb the corporate ladder.

TQM and PM

During this crisis period in the Industrial Age humans strengthened by union solidarity reacted to being poorly treated as cogs of a cost-driven industrial machine and demanded changes in working conditions.

Total Quality Management emerged as one “yellow bubble” solution. Pioneers Edwards Deming, Joe Juran, and Phil Crosby led the advancement of TQM. They are also credited for developing Project Management as a discipline. Progressive companies adopted TQM as their way of overseeing all activities and tasks needed to maintain a desired level of excellence. Instead of mainly looking inward for efficiency improvements, TQM promoted the idea of looking outward and achieving customer satisfaction.

Themes in Deming’ s PDCA cycle were continuous improvement, waste reduction, and customer loyalty. Quality was measured in financial terms. Improvements in waste management, production control, and increased sales from happy customers were calculated in terms of budgetary impact.

Juran applied the 80/20 Pareto Principle to prioritise quality issues. A major contribution was highlighting the human side of TQM. He stressed the importance of education, training, and understanding resistance to change.

Crosby’s philosophy was “do it right the first time”. He coined the term Zero Defects. Eliminate errors. Avoid time-consuming and costly failure fixes.

Many organisations did not get excited about TQM and saw it as a passing fad. They chose to remain entrenched in cost certainty mode and placed attention on finding more ways to reduce expenses.  Consultants were more than willing to help and offered innovations such as unbundling, outsourcing,  replacing labour with automation, and optimising supply chains.

Not everyone was in favour of Zero Defects. Detractors deemed the assumption human error is avoidable as unrealistic and unattainable. In the safety industry a similar assumption is that all injuries are preventable. The worry is putting a strain on worker performance and morale.

Not everyone was in favour of focusing on the customer. In 1976 a controversial idea that shareholders owned the firm and the true purpose of management was to maximise shareholder value. SVA[5] became the rallying cry for CEOs and financial markets who would benefit most from the paradigm. A major player was Jack Welch while CEO at General Electric. Not quite calling it a myth, upon reflection in 2011 he called SVA “the dumbest idea in the world.” [6] He questioned why do CEOs and their top managers receive massive incentives to focus most of their attention on the expectations market, rather than the real job of running the company producing real products and services.

Lessons learned from the Industrial Age

Behind all ideas are good intentions. But so are unintended negative consequences. What results have been accomplished? What have we discovered and learned from the Industrial Age?

Mining Productivity

Australian mining experienced a resource boom in the Industrial Age. In the early 1960s, discoveries of new metals led to a resurgence of interest in Australia’s mineral resources. Production also increased and Australia became a major raw materials exporter, especially to Japan and Europe.

Today Australia is one of the world’s leading mineral resources nations. It is the world’s largest refiner of bauxite, producer of gem and industrial diamonds, lead and tantalum, and the mineral sands ilmenite, rutile and zircon. Other world rankings in production are: zinc (2nd); gold, iron ore and manganese ore (3rd); nickel, aluminium (4th); copper, silver, black coal (5th). [7]

It seems odd that Australia’s enviable position has been accomplished with productivity levels that have been trending downwards. According to Ernst & Young[8] capital productivity in Australia has fallen 45% since 2000. Perhaps it’s because Australia hasn’t been alone in the worldwide decline. E&Y reported labour productivity in the South African gold sector dropping by 35% since 2007.

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These sobering findings are corroborated by McKinsey [9] which found that global mining productivity overall has decreased by 29% over the last decade. From 2014 to 2016 McKinsey’s Mine Lens shows a 2.8% per annum uptick in productivity, but productivity is still far below the level 15 years ago.[10]

Employee engagement

Organisations consider employee engagement an important indicator of company health. Engaged employees offer their talents and energy to work efficiently and effectively. Actively disengaged workers, on the other hand, look around for ways to ignore or damage the best interests of the organisation. Galluphas been measuring employee engagement across the world for many decades.

“Worldwide, the percentage of adults who work full time for an employer and are engaged at work — they are highly involved in and enthusiastic about their work and workplace — is just 15%.

“They imply a stunning amount of wasted potential, given that business units in the top quartile of Gallup’s global employee engagement database are 17% more productive and 21% more profitable than those in the bottom quartile”.

For Australia/New Zealand the 2013 report identifies 24% or workers as highly engaged and 16% actively disengaged.[11] In the 2017 survey the highly engaged number dropped to 19%.[12] 

Compounding the employee engagement problem is anecdotal evidence that millennials do not see mining as a promising career. Jake Klein, CEO of Evolution Mining stunned many attending the 2019 Future of Mining Conference in Sydney by informing there are only 25 mining engineers enrolled in Australian Universities[13]. He sees the biggest challenge is making mining an attractive industry for young people.

Klein’s concern reinforces a view expressed by the World Economic Forum (WEF).[14]Business leaders say that attracting, managing and retaining a skilled workforce is their number one business challenge in the next five years. WEF research showed better benefits, more accessible savings plans, and guidance and technology tailored to individual needs would have a very positive impact on a workforce.

Despite the clear message, Myth 1 continues to be played out today. Permanent employee levels are contained or shrunk by using contracted labour and outsourcing (parts of a machine). Financial actions such as switching employer-employee shared pension plans from defined benefits to market-based enhance cost-certainty and shift the risk of retirements fund sufficiency from the company to the individual. When workers opt out on corporate buy-out and early retirement programs, the labour cost savings are highlighted but neglected are the non-monetary losses in tacit knowledge and experience.

Implications of running mines according to Myth 1

History has taught us that Myth 1 has created “wicked” problems for the mining industry. Wicked problems are difficult or impossible to solve because of incomplete, contradictory, and changing requirements that are often difficult to recognise. [15] 

Some industry pundits believe that poor productivity and employee engagement are two sides of the same coin. Measuring systemic productivity while enforcing individual accountability injects disharmony into the organisation and reaps diminishing returns.  How does this happen? Boston Consulting group partner Yves Morieux[16] explains: 

“…this drive for clarity and accountability triggers a counterproductive multiplication of interfaces, middle offices, coordinators that do not only mobilise people and resources, but that also add obstacles. And the more complicated the organisation, the more difficult it is to understand what is really happening. So we need summaries, proxies, reports, key performance indicators, metrics. So people put their energy in what can get measured, at the expense of cooperation. And as performance deteriorates, we add even more structure, process, systems. People spend their time in meetings, writing reports they have to do, undo and redo. Based on our analysis, teams in these organisations spend between 40 and 80 percent of their time wasting their time, but working harder and harder, longer and longer, on less and less value-adding activities. This is what is killing productivity, what makes people suffer at work. 

We need employees to cooperate, to trust their coworkers and managers. It is to take a risk, because you sacrifice the ultimate protection granted by objectively measurable individual performance. It is to make a super difference in the performance of others, with whom we are compared. It takes being stupid to cooperate, then. And people are not stupid; they don’t cooperate.” 

Safety in the Industrial Age

Ever wonder why Safety is a cost item in a budget? We hear platitudes that an organisation’s greatest asset is its employees. Yet instead of an investment, they are entered as expenses on the Profit & Loss statement. No different than a replaceable part in a machine.

“Safety-I” was coined by Erik Hollnagel[17] to reflect the mechanistic treatment of humans in the Industrial Age. Safety is defined as the absence of negative events. Humans are error prone, focus on what goes wrong, and the ideal target is Zero Harm, a logical extension of Zero Defects thinking.

Surrounded by scientific management principles, the beginnings of Safety as a practice intuitively mirrored the patterns of business and the avoidance of human failure. In 1931 Herbert Heinrich published his book “Industrial Accident Prevention, a Scientific Approach.” [18]  The book cited 88 percent of all workplace accidents and injuries/illnesses are caused by “man-failure.” More famous is Heinrich’s Law: that in a workplace, for every accident that causes a major injury, there are 29 accidents that cause minor injuries and 300 accidents that cause no injuries. Alas, Fred Manuele disclosed in his 2011 review, it’s a myth.[19]

Learning to let go

The Y-axis of the Life-cycle diagram is labelled “Utility of the Paradigm” for a good reason. A subsequent age doesn’t start from zero but is elevated by the previous age. That means we carry forward the valuable lessons and practices and adapt them to the next emerging Age. And just as important, we let go of the myths and fallacies of the old Age.

In the next article we examine the radical thinking in the Information Age. Scientific Management yields to Systems Thinking. An Engineering paradigm emerges. And a new myth is born.

Thank you for the feedback and enthusiastic show of support. In response to the interest, we are conducting 1-day Radical Innovation in Mining Management workshops on October 31 (Sydney) and November 8 (Brisbane). To be added to our invitation list, please contact Hendrik Lourens at hendrik@stratflow.com.au .

Written by Gary Wong and Hendrik Lourens

References

[1]       The Real Lessons From Kodak’s Decline, MITSloan Management Review Magazine: Summer 2016.

[2]       Freedom from command and control, John Seddon, Productivity Press, Kindle, 2005.

[3]       Profitability with no boundaries, Reza M. Pirashteh and Robert Fox, American Society for

Quality, 2011.

[4]       Australian Coal Strike https://en.wikipedia.org/wiki/1949_Australian_coal_strike

[5]       Theory of the Firm: Managerial Behavior, Agency Cost and Ownership Structure, Michael Jensen and William Meckling, Journal of Financial Economics, 1976.

[6]       The Dumbest Idea In The World: Maximising Shareholder Value, Steve Deming, Forbes, Nov 2011.

[7]       History of Australia’s Minerals Industry. http://www.australianminesatlas.gov.au/history/index.html

[8]       Productivity in Mining: Now comes the hard part, Ernst & Young, 2016.

[9]       Productivity in Mining Operations: Reversing the downward trend, McKinsey, 2015.

[10]   Behind the mining productivity upswing: Technology enabled transformation, McKinsey, 2018.

[11]   State of the Global Workplace, Gallup, 2017.

[12]   State of the Global Workplace, Gallup, 2013.

[13]   Future of Mining Australia 2019, Jake Klein. https://www.youtube.com/watch?v=0cw0V30gmyk

[14]   Is this the secret to happy and engaged employees? WEF 2018.

[15]   Wicked Problem, Wikipedia.

[16]   Smart Rules: Six ways to get people to solve problems without you, Yves Morieux, Harvard Business Review, September 2011.

[17]   Safety I and Safety II: The Past and Future of Safety Management, Erik Hollnagel, 2014.

[18]   Industrial accident prevention, H.W. Heinrich, McGraw Hill, 1931

[19]   Reviewing Heinrich: Dislodging Two Myths From the Practice of Safety, Fred Manuele, Oct 2011, Professional Safety, www.asse.org

Radical Innovation in Mining Management: Introduction

2020-04-30 Update

I was informed this week that this article in Austmine magazine has over 14,000 clicks. Perhaps the COVID-19 crisis is presenting the opportunity for organizations to unshackable themselves from the 3 myths and look at the new normalcy through a complexity perspective.

The following article was published on 2019 May 06 at http://www.austmine.com.au/news/radical-innovation-in-mining-management-1  Austmine is the leading industry body for the Australian Mining, Equipment, Technology and Services (METS) sector. 

Introduction

Social license, Digital transformation, Safety, and Profitability – four issues that seem to be caught in a perpetual trade-off. Spend more time on one, and it reduces the attention given to the others. It’s a problem that impacts everyone in the organisation:

  • As an executive, you’re frustrated with events that unexpectedly emerge to disrupt production.
  • As a manager, you’re angry when corporate performance statistics don’t reflect the tireless effort required to keep things running locally.
  • As a supervisor, you’re frustrated with fault finding in people and blaming individuals for mediocre results that are beyond their control.
  • As an engineer, you’re disillusioned by past innovative programs that started with a bang and then either withered away or had the budget pulled. 
  • As a tradesperson, you can sense worsening mine conditions but feel powerless in voicing your concerns.

Have we reached a plateau in our ability to improve on each of these issues individually as well as collectively? Peter Senge claimed: “Today’s problems come from yesterday’s solutions”. In this first article, we introduce how yesterday’s solutions have led to three myths that control current mining thinking. In the following months, we will delve deeper into each myth and the problems they create today.

Based on 15 years of consulting experience we believe that radical innovation is essential to disrupt myth domination. “Radical” does not necessarily mean painful and agonising. It means being enlightened that the world has radically changed and the Mining industry needs to catch up.

Three myths that destroy mining innovation

Myth 1: The best way to run a mine is to focus on cost certainty and manage people as if they are parts of a machine.

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

Myth 3: We can achieve social licence acceptance and safety aims within our current management paradigm by pursuing effective culture change.

Each myth began as a solution for a specific era of time. Besides introducing new thinking, an Age carries the best of the previous ages forward while dispensing myths and fallacies with facts and evidence.

The evolution and implications of different Ages

The Industrial and Information Ages

The Industrial Age growth mindset in the early 20th century was fuelled by Scientific Management principles of productivity. The work environment was stable, certain, and predictable. However, it couldn’t last forever when humans revolted over their treatment as mere cogs in a machine. A crisis point was reached resulting in declines in capital, labour, and material productivity.

Systems thinking and Human Factors boosted by computer technology offered new and improved alternatives. A popular solution called Business Process Reengineering succinctly captures the dominant engineering paradigm. This is the Information Age with people, process, and technology as parts of a system. “The whole is equal to the sum of its parts.” Industry rally behind “Faster, better, cheaper” in the pursuit of optimised efficiency. However, all is not well. We observe promising Information Age digital tools yielding negative impacts and making operations extremely complicated. As consultants, we have seen many attempts to optimise across the entire system to achieve efficiency. Some software packages are coded on this premise. However, systems thinkers like Russell Ackoff argue that system capability decreases. Eli Goldratt in his Theory of Constraints mathematically supports Ackoff’s claim.

Figure 1: The development of the Industrial, Information and Ecological Ages.

Figure 1: The development of the Industrial, Information and Ecological Ages.

Implementation of new technologies has not been easy. In 2016 strategic business & technology advisor and internationally best-selling author Bernard Marr wrote in Forbes.com that 25% of technology projects fail outright; 20-25% don’t show any Return on Investment, and 50% need massive re-working by the time they’re finished. From his experience, many projects failed not due to tech problems.  In fact, 54 % of IT project failures were attributed to poor management.

Change Management programs are often deployed as the lever to execute implementation because they focus on changing culture. The belief is cause & effect relationships will apply to people as they do for mechanistic processes and technologies. Great, if valid. However, consulting firms (McKinsey, Connor, Kotter) have reported a dismal 70% failure rate of change management programs. Once again we’ve reached a crisis period and the decline of an Age.

The Ecological Age

In the Ecology Age, confusing dilemmas, ambiguous paradoxes, diverse conflicts are natural occurrences. Mining has become a complex adaptive system. The unexpected emergence of new things means “the whole is greater than the sum of its parts”. For example, when “hot water is poured over dry coffee grinds, aroma as a new thing emerges”. The interaction of two ingredients creates something new. A deeper example happens inside our heads. “Billions of neurons in our brain interact in ways that we cannot fully understand to create a stream of consciousness.” People are no longer viewed as predictable cause & effect machines but are illogical, emotional decision makers. Culture is not a lever but emerges as an outcome of people, process, and technology interacting.

The evolution of Safety through the Ages

Safety has gone through similar paradigm changes. In the Industrial Age, safety was defined as the absence of negative events. Humans are error prone, focus on what goes wrong, and the ideal target is zero harm. The term “Safety-I” was coined by Erik Hollnagel to describe this thinking, one which many organisations still follow.

In the Information Age, new schools of safety sprung to life. One posed humans as problems in a system that could be managed using safety policies, standards, rules and compliance inspections. In the “Safety-II” view, humans are solutions, able to adapt performance due to varying conditions in the work environment.

In the Ecology Age, we accept it’s human nature to be fallible; mistakes will be made.  Less emphasis is given to changing the behaviours of illogical, emotional decision-makers. Instead, emphasis is placed on influencing relationships and interactions and designing systems for imperfect humans. Like culture, safety is an emergent property of a complex adaptive system. Workers don’t create safety. They create the conditions that enable safety to emerge; they can also create the conditions that enable danger to emerge.

Social Licence as an Ecological problem

We can add Social Licence to Operate as another emergent property of a complex adaptive system. SLO involves not just the community in which the mine is situated, it also involves employees, government (through regulation) and societal attitudes at large. In our conversations with mining managers, we hear the lament they cannot free up the time to deal with ecological issues. They are also aware in the Ecology Age the Internet with fast feedback loops empowers people to socially connect and voice their concerns. Failure to place sufficient attention may lead to a tense issue “going viral”. What do we do?

Dealing with Ecological problems

We need to create the conditions where we are able to free up time and high-level manpower to embark on new ways of doing to deal with these ecological issues. To do this we need to understand the myths holding us back, to stop doing much of what is considered best practice and start doing differently. Management’s role in this endeavour is critical.

Based on 15 years of experience and more than 85 mining interventions we believe this is possible.

We look forward to offering our Information and Ecology Age ideas and thoughts in the series of upcoming articles. We shall put Einstein’s quote to the challenge: “We cannot solve our problems at the level of thinking that caused them in the first place.”

Written by:

Gary Wong and Hendrik Lourens – Stratflow

Evolution of Safety

Yesterday I was pleased to speak at the Canadian Society of Safety Engineering (CSSE)  Fraser Valley branch dinner.  I chose to change the title from the Future of to the Evolution of Safety.  Slides are available in the Downloads or click here.  The key messages in the four takeaways are listed below.

1. Treat workers not as problems to be managed but solutions to be harnessed.

Many systems have been designed with the expectation  humans will perform perfectly like machines. It’s a consequence of the Systems Thinking era based on an Engineering paradigm. Because humans are error prone, we must be managed so that we don’t mess up the ideal flow of processes using technologies we are trained to operate.

Human & Organizational Performance (HOP) Principle #1 acknowledges people are fallible. Even the best will make mistakes. Despite the perception humans are the “weakest link in the chain”,  harnessing our human intelligence will be critical for system resilience, the capacity to either detect or quickly recover from negative surprises.

As noted in the MIT Technology Review, “we’re seeing the rise of machines with agency, machines that are actors making decisions and taking actions autonomously…” That means things are going to get a lot more complex with machines driven by artificial intelligence algorithms. Smart devices behaving in isolation will create conflicting conditions that enable danger to emerge. Failure will occur when a tipping point is passed.

MIT Professor Nancy Leveson believes technology has advanced to such a point that the routine problem-solving methods engineers had long relied upon no longer suffice.  As complexity increases within a system, linear root cause analysis approaches lose their effectiveness. Things can go catastrophically wrong even when every individual component is working precisely as its designers imagined. “It’s a matter of unsafe interactions among components,” she says. “We need stronger tools to keep up with the amount of complexity we want to build into our systems.” Leveson developed her insights into an approach called system theoretic process analysis (STPA), which has rapidly spread through private industries and the military. It would be prudent for Boeing to apply STPA in its 737 Max 8 investigation. 

So why is it imperative that workers be seen as resourceful solutions?  Because complex systems will require controls that use the  immense power of the human brain to quickly recognize hazard patterns, make sense of bad situations created by ill-behaving machines, and  swiftly apply heuristics to prevent plunging into the Cynefin Chaotic domain.

2. When investigating, focus on the learning gap between normal deviation / hazard and avoid the blaming counterfactual.

If you read or hear someone say:
“they shouldn’t have…”
“they could have…”
“they failed to…”
“if only they had…”
it’s a counterfactual. In safety, counterfactuals are huge distractions because they focus what didn’t happen. As Todd Conklin explains, it’s the gap between the  black line (work-as-imagined) and the blue line (work-as-done). The wavy blue line indicates that a worker must adapt performance in response to varying conditions. The changes hopefully enable safety to emerge so that the job can successfully completed. In the Safety-II view, this is deemed normal deviation. Our attention should not be on “what if” but “what” did.

The counterfactual provides an easy path for assigning blame. “If only Jose had done it this way, then the accident wouldn’t have happened.”  Note to safety professionals engaged in accident investigations: Don’t give decision makers bullets to blame but information to learn. The learning from failure lessons are in the gap between the blue line and the hazard line.

3. Be a storylistener and ask storytellers:
How can we get more safety stories like these, fewer stories like those?

I described the ability to generate 2D contour maps from safety stories told by the workforce.  The WOW factor is we now can visually see safety culture as an attitudinal map. We can plot a direction towards a safety vision and monitor our progress.  Click here for more details.

Stories are powerful. Giving the worker a voice to be heard is an effective form of employee engagement. How safety professionals use the map to solve safety issues is another matter. Will it be Ego or Eco? It depends. Ego says I must find the answer. Eco says we can find the answer.

Ego thrives in hierarchy, an organizational  structure adopted from the Church and Military. It works in the Order system, the Obvious and Complicated domains of the Cynefin Framework. Just do it. Or get a bunch of experts together and direct them to come up with viable options. Then make your choice.

Safety culture resides in the Cynefin Complex domain. No one person is in charge. Culture emerges from the relationships and interactions between people, ideas, events, and as noted above, machines driven by AI algorithms. Eco thrives on diversity, collaboration, and co-evolution of the system.

An emerging role for safety professionals is helping Ego-driven decision makers understand they cannot control human behaviour in a complex adaptive system. What they control are the system constraints imposed as safety policies, standards, rules. They also set direction when expressing they want to hear “more safety stories like these, fewer stories like those.”

And less we forget, it’s not all about the workers at the front line. Decision makers and safety professionals are also storytellers. What safety stories are you willing to share? Where would your stories appear as dots on the safety culture map?

Better to be a chef and not a recipe follower.

If Safety had a cookbook, it would be full of Safety Science recipes and an accumulation of hints and tips gathered over a century of practice. It would be a mix of still useful, questionable (pseudoscience), emerging, and recipes given myth status by Carsten Busch.

In the Cynefin Complex and Chaotic domains, there are no recipes to follow. So we rely on heuristics to make decisions. Some are intuitive and based on past successes – “It’s worked before so I’ll do it again.” Until they don’t because conditions that existed in the past no longer hold true. More resilient heuristics are backed by natural science laws and principles so they withstand the test of time.

By knowing  the art and principles of cooking, a chef accepts the challenge of ambiguity and can adapt to unanticipated conditions such as missing ingredients, wrong equipment, last-minute diet restrictions, and so on.

It seems logical that safety professionals would want to be chefs. That’s why I’m curious in the study An ethnography of the safety professional’s dilemma: Safety work or the safety of work?  a highlight is “Safety professionals do not leverage safety science to inform their practice.”
Is it worth having a conversation about, even collecting a few stories? Or are safety professionals too time-strapped doing safety work?