In Defence of a Silo

About a month ago, you may have read a couple articles I posted that reviewed opinions on why projects fail - these were the result of some online research and a number of interviews I held late last year. At the end of my post, I asked your opinion - did you agree, disagree, and if so, what did you think were primary reasons?

There were some great responses, where some were in agreement to the findings, and others offered more in-depth and technically specific reasons, from their perspective. Many of these factors revolved around poor geological or mineralogical understanding and interpretation. Many suggested poor process design, and yet others named social pressures and objections. There were more than a few comments regarding interdependent and complex, compounding issues - something I think we can all recognize for our mining projects. It was great engagement, and I appreciate your input!

To kick this article off, I'd like to dig into the geologic aspect a little more, because it is our primary starting point of a mine anyways, but more particularly because I've recently read a number of articles that have pointed the finger solely at resource and reserve estimations as the cause of failure of many mine development projects.

However, I'd rather not spend time debating how well or poorly some of these geologic interpretations may have been.

Personally, I think this activity is one of the most difficult exercises required for mine developments, and it's a bit unfair to place blame on a single set of practitioners who are always, and I mean ALWAYS, working with an incomplete set of data to do their work. I mean, really, how can anyone truly figure out what's inside of a solid heterogeneous mass simply by poking some needles through it? Could you?

Never mind the fact that the data they have the ability to collect is solely dependent on how much money an owner is willing to invest in the first place...in my opinion, blaming only this role for failures is just - well, not just!

Instead, what I'd like to spend some time debating is what I feel are the real culprits.

Amongst the responses, I heard a common theme. In my mind, there emerged two questions. Were the failures in fact caused by any one particular silo - by those discipline-specific issues suggested? Or, were they caused by invisible barriers - breakdowns in communication and poor information transfers between the parties collecting, interpreting, and then utilizing the resultant data for planning and design?

It would seem to me that some of the technical-related problems with projects stem from:

  • Poor data, and insufficient data collection, relative to the type and level of work required for each design component, at each project phase. 
  • Poor assumptions, and compounding assumptions. Guesses, educated or not, can still cause serious issues if they are wrong.
  • A lack of identification of associated risks, or lack of recognition of the severity of said risks, for either of the above.
  • Not having an appropriate risk management strategy to take care of each risk.
  • Poor transfer and storage, communication, and/or recipient's understanding of information regarding all of the above.

I would also suggest that most of these problems and related impacts to projects arise during the critical, between-phase transitions within a project's lifecycle:

  • When data and results of previous work passes hands.
  • When teams often change in personnel, size, and focus.
  • When management-types make decisions about next-phase scopes of work.

We've all heard the saying - bad data in, bad data out.

It's the truth, impacting analyses, design, and decisions. And unless you win the crap shoot and all your guesses were right, or the market skyrockets and it doesn't really matter anyways, a project or process based on this, at any stage, will take a significant hit. 

Wouldn't you agree?

On not pointing a finger at only the beginning, let's go back to the case of a failed resource estimation example. 

If you asked the person who did the modelling and reconciliation with the field data, would they believed they did anything wrong?

If one talked to the geologists who managed the drilling programs, would they say they had been able to collect enough information for said evaluation?

If you asked these same people whether they believed the information they provided to others had been used appropriately, and within the bounds of its assumptions and limitations?

And now, if you asked the recipients whether they utilized the data they were provided appropriately, would they believe they did anything wrong?

I would guess their responses to all of these would simply be NO.

You see, developing an understanding of nature is a complex and progressive thing, particularly when it comes to the subsurface, where you can't just see all of it with your own eyes. It takes a lot of time, energy, and unfortunately, money, to collect various types of information, with a number of tools, from a variety of sources and from different aspects.

And then, you somehow need to interpret each data piece, bring all of the information together, test for simple correlations vs. causes and effects, and then project what that might mean when it is all put together.

By the way, this is also the case for planning and design of mine development options, processing, and the management of residual wastes from these actions - and any other area of engineering to support these project components.

Assumptions are required, and the less concrete data that we have, the greater risks and impacts those assumptions may have.

When it comes to reporting reserves and resources, there are definitely rules around what and how much information is required for different stages of development. Reporting rules are clear, and qualified professionals (QPs) are well trained and experienced people who take this very seriously when evaluating projects.

Similarly, engineers also follow rules - for assessment, design, review and reporting. And again, this is the case for environmental assessment practitioners who are assessing and reporting on potential risks to the environment for any particular development. 

To not take things seriously, to blatantly lie, or to omit to do what is required, can result in jail time and serious fines, and the reputations of all of these people are on the line. 

So to simply say a specific task has been done poorly is maybe inappropriate. Most people will do the best that they can - with the information that they receive, and as they understand it.

Instead, maybe we should focus on the amount and detail of the data obtained, and the assumptions used as indicated and conveyed within reporting and data transfers, as well as be clear with our communications between teams. We should be asking more questions, and they should be easily answered:

  • at what stage of exploration or evaluation is the property?
  • has enough data actually been collected?
  • how well defined is the ore-body AND the geology around it?
  • how much do we know about the geochemistry and the potential for processing the ore, for managing the wastes?
  • what do we know about the local fault/fold structures and alterations associated with the deposit?
  • what do we know about the encompassing hydrogeology of the deposit and site?
  • geographically speaking, where is the deposit and what are the characteristics of it's surrounding environment - i.e. might there be risks associated with development in that environment?
  • what primary risks can we expect to face with development and processing, and have we taken these into account for our design and management plans?
  • what assumptions have been made?
  • what limitations are associated with the data, and the assumptions?
  • what level of risk, and what are the potential consequences, associated with the assumptions made?
  • and so on...

These are but a few questions we should be asking at early stages, while we are in this iterative, progressive state of learning all there is to know about our sites. 

The reality is that we need to understand what we can absolutely be sure of before we go into design and development. And we need to know what we absolutely can NOT depend on, so that the planning and design for those aspects can be made more flexible and accommodating - if we cannot learn more. With the alternate option of not proceeding with design until we DO know more.

So, how can we improve our outcomes?

How about starting with an open exchange... 

If you have been involved with geologic interpretation of reserves and resources, and you know that planners and designers will be taking and using the information you have derived to develop that ore-body and process its ores,

WHAT are the most critical aspects and assumptions of your reports and communications that they should gain better clarity around to understand the level of risk associated with using the data?

If you are on the receiving end of said information, for development of the deposit, or for designing process options for the ore, 

WHAT are the things that you absolutely need to know before you can proceed? 

And consider this - if you know there is insufficient information for you to realistically remove the risk of a future failure - that the risk is too high to proceed without further investigation,

How would you ensure that risk is well known - to all stakeholders? How could you ensure that the communication of said risk does not get lost or fall by the wayside during times of transition?

What other questions would you ask?