In any industry, decisive and efficient decision-making is paramount for project success. Recently, I led a one-day design workshop for a mining company, aiming for a 'directionally correct' concept design for a province of mines. The objective: elicit information to streamline approvals and plan future mining studies.
The workshop started with a structured agenda, a warm welcome, and an engaging icebreaker, fostering collaboration. Emphasizing the workshop's importance in the approvals pathway, we acknowledged the discomfort participants might feel working with estimated data.
Utilising a large laminated map of the province and key deposits, we created a 'mud map' for deposits and infrastructure. The map evolved as we sketched haulage routes and labeled key considerations with sticky notes, providing a shared understanding of the province's layout.
A significant portion focused on a deposit brainstorming session, gathering 'rough and ready' assumptions for key variables. Leveraging participants' expertise resulted in an integrated view, laying the groundwork for mine sequencing and evolving the mud map.
Post-brainstorming, we reflected on conclusions and insights. 'Directionally correct' assumptions enabled proposing mine sequencing, identifying infrastructure requirements, and addressing potential physical constraints.
I compiled a succinct deck outlining key insights and short- to long-term steps, emphasising experts' willingness to make 'directionally correct' assumptions, had enabled us to achieve the desired outcomes in a day.
The workshop showcased collaborative decision-making's power and the efficacy of 'directionally correct' estimates. By navigating through the complexities of the mining landscape in this way, we not only streamlined gathering the information needed for the approvals process but also laid the groundwork for future planning success by identifying questions to be answered and defining shorter and longer term actions.
A New Zealand bank was auto-decisioning less than 1% of business lending applications. That meant almost every application needed a human to review it. Contact centre staff. Credit analysts. Manual touchpoints at every step.
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