A A Frame mewor ork for or Ad Adaptive Ri Risk Management for Mi Mini ning ng Capi pital Projects ts Craig Rice, The University of British Columbia W. Scott Dunbar, The University of British Columbia
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Idea in brief. Adaptive (Risk) Management. Classical Project Risk Management. New Perspectives on Risk. The Adaptive Risk Management Framework. Key Takeaways.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. A method to analyze, observe, and respond to unforeseen emerging risks with high uncertainties . No clear best resolution option. Pursue multiple competing options. Which options are worth pursuing? How do we arrive at a best option? Improving the knowledge domain. Iterations, simulations, modelling.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. An Example – The Underperforming SAG Mill
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Minin Min ing Ca Capit ital l Project cts. How do we fix it? What do we do? Reduce material feed size? Pursue easiest, cheapest, or Crusher performance. fastest options first? ROM material. SAG Mill modifications? Do a bunch of things and see Grate size/spacing. what happens? Ball charge. Crusher modifications? What options are worth Larger crusher. pursuing? Additional crusher. Additional SAG Mill? BTW – We’re losing money.
A Framework A k for Ada Adaptiv ive Ris Risk k Mana nagement in in Minin Min ing Ca Capit ital l Project cts. Adaptive Management 1. Structured and iterative approach. 2. Well developed system model. 3. Pursue multiple completing resolution options. 4. Observe and learn through iterations. 5. Repeat until best option identified.
A Framework A k for Ada Adaptiv ive Ris Risk k Mana nagement in in Minin Min ing Ca Capit ital l Project cts. My Research: Adaptive project risk management Using new perspectives in risk Risks with economic impacts Valuing options within the adaptive framework.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Why is this important?
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. 65% of projects fail to meet their objectives. (Merrow, 2011) Project fail at an astonishingly high rate.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. No, we just don’t We’re terrible at know how to estimating costs and manage uncertainty planning projects! in projects! Flyvbjerg (2008) Ward and Chapman (2003)
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Planning does not eliminate uncertainty. You can’t predict everything that will go wrong.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Minin Min ing Ca Capit ital l Project cts. Classical Approaches to Project Risk Management: Predict – Quantify – Plan - Monitor (ISO, AACEI, PMI) 𝑆𝑗𝑡𝑙 = < 𝑡 ' , 𝑞 ' , 𝑦 ' > 𝑗 = 1,2, … 𝑂. 𝑡 ' = 𝑡𝑑𝑓𝑜𝑏𝑠𝑗𝑝 𝑝𝑠 𝑓𝑤𝑓𝑜𝑢 𝑞 ' = 𝑞𝑠𝑝𝑐𝑏𝑐𝑗𝑚𝑗𝑢𝑧 𝑝𝑔 𝑢ℎ𝑏𝑢 𝑡𝑑𝑓𝑜𝑏𝑠𝑗𝑝𝑠 𝑝𝑑𝑑𝑣𝑠𝑠𝑗𝑜 𝑦 ' = 𝑑𝑝𝑜𝑡𝑓𝑟𝑣𝑓𝑜𝑑𝑓𝑡 𝑝𝑔 𝑢ℎ𝑏𝑢 𝑡𝑑𝑓𝑜𝑏𝑠𝑗𝑝 (Kaplan and Garrick, 1981)
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Classical approach only suitable for risks that are known/knowable and can be identified in advance. What about the others?
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Known Unknown Knowns Knowns Knowability Unknown Known Unknowns Unknowns Known/unknown status
A Framework A k for Ada Adaptiv ive Ris Risk k Mana nagement in in Minin Min ing Ca Capit ital l Project cts. What about risks you can identify, but can’t characterize or quantify? Identifiable but extremely rare… Conjunction of rare but possible events… Aleatory vs. epistemic uncertainty... Probability as a degree-of-belief... (Pate-Cornell, 2012)
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. New Perspectives on Risk (Aven, 2012) 𝑆𝑗𝑡𝑙 = 𝐵, 𝐷, 𝑉 = 𝐵, 𝐷, 𝑅, 𝐿 𝐵 = 𝑡𝑑𝑓𝑜𝑏𝑠𝑗𝑝 𝑝𝑠 𝑓𝑤𝑓𝑜𝑢; 𝐷 = 𝑑𝑝𝑜𝑡𝑓𝑟𝑣𝑓𝑜𝑑𝑓𝑡 𝑝𝑔 𝐵 𝑉 = 𝑣𝑜𝑑𝑓𝑠𝑢𝑏𝑗𝑜𝑢𝑧 𝑏𝑐𝑝𝑣𝑢 𝐵 𝑏𝑜𝑒 𝐷 𝑅 = 𝑛𝑓𝑏𝑡𝑣𝑠𝑓 𝑢𝑝 𝑠𝑓𝑞𝑠𝑓𝑡𝑓𝑜𝑢 𝑣𝑜𝑑𝑓𝑠𝑢𝑏𝑗𝑜𝑢𝑧 𝑉 𝐿 = 𝑐𝑏𝑑𝑙𝑠𝑝𝑣𝑜𝑒 𝑗𝑜𝑔𝑝𝑠𝑛𝑏𝑢𝑗𝑝𝑜 𝑏𝑜𝑒 𝑙𝑜𝑝𝑥𝑚𝑓𝑒𝑓 𝑅 𝑗𝑡 𝑐𝑏𝑡𝑓𝑒 𝑝𝑜 Strong focus on uncertainty/knowledge and fluidity of these parameters.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Whew. Let’s recap so far. Traditional approaches are insufficient. Unknown/unknowable risks? Benefits of new perspectives.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Adaptive Risk Management: Responding to surprise risks that you didn’t predict. Responding in a way that minimizes consequences.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Adaptive Risk Management: Key Point #1: Analyze risk according to new perspectives.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Adaptive Risk Management: Key Point #2: Use analysis to highlight uncertainty and potential improvements in knowledge (ie – information gathering.)
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Adaptive Risk Management: Key Point #3: Develop multiple completing mitigating options for resolution.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Adaptive Risk Management: Key Point #4: Model options to determine value/cost to be paid (ie – “is this option worth pursuing right now.”)
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Adaptive Risk Management: Key Point #5: Pursue your options and gather information. If risk not resolved, perform additional iteration with additional knowledge.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Adaptive Project Risk Management Framework Step 1: Identify emergent risk. Step 2a: Analyze/characterize risk. Step 2b: Identify objectives Step 3a: Develop options. Step 3b: Structure information gathering. Step 4: Develop system model. Step 5: Run model. Step 6: Select options for “nth” iteration. Step 7: Execute “nth” iteration. Step 8: Analyze results, learn, and return to Steps 2-5
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Modelling and Simulation Schedule reduction Time-cost trade-off Base-case comparison Multiple iterations shown. Optimize effort in each iteration.
A A Framework k for Ada Adaptiv ive Ris Risk k Mana nagement in in Min Minin ing Ca Capit ital l Project cts. Model and simulation answers the question “Which management options should we pursue?” Probabilistic continuous DCF model with cost, activities, and duration of each option/iteration as probabilistic parameters. 𝑊𝑏𝑚𝑣𝑓 𝑝𝑔 𝑃𝑞𝑢𝑗𝑝𝑜 = 𝑄 ' (𝑂𝑄𝑊 O P − 𝑂𝑄𝑊 R P ) 𝑄 ' = 𝑄𝑠𝑝𝑐𝑏𝑐𝑗𝑚𝑗𝑢𝑧 (𝑠𝑏𝑜𝑓) 𝑢ℎ𝑏𝑢 𝑝𝑞𝑢𝑗𝑝𝑜 𝑗 𝑥𝑗𝑚𝑚 𝑐𝑓 𝑢ℎ𝑓 𝑡𝑓𝑚𝑓𝑑𝑢𝑓𝑒 𝑝𝑞𝑢𝑗𝑝𝑜 𝑂𝑄𝑊 O P = 𝑂𝑄𝑊 𝑝𝑔 𝑜𝑝𝑜 − 𝑏𝑒𝑏𝑞𝑢𝑗𝑤𝑓 𝑠𝑓𝑡𝑞𝑝𝑜𝑡𝑓 𝑔𝑝𝑠 𝑝𝑞𝑢𝑗𝑝𝑜 𝑗 𝑂𝑄𝑊 R P = 𝑂𝑄𝑊 𝑝𝑔 𝑏𝑒𝑏𝑞𝑢𝑗𝑤𝑓 𝑠𝑓𝑡𝑞𝑝𝑜𝑡𝑓 𝑔𝑝𝑠 𝑝𝑞𝑢𝑗𝑝𝑜 𝑗
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