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Mining & Minerals
Mine Planning & Design
Capital-intensive extraction and processing programs where safety, regulation, and supply chain complexity define execution.
Maptek
Leica Geosystems
Dassault Systèmes
Micromine
Inside this journey
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Pre-Discovery
Align stakeholders, decision criteria, timelines, and ensure geological data & models are ready for robust benchmarking.
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Stakeholder Alignment
Confirm decision roles, financing and due-diligence requirements, timeline, and what ‘good’ looks like for technical and commercial stakeholders.
Alignment Questions
Tell Us the Story So Far — a quick snapshot
- How would you briefly describe the project stage and the trigger for this review?
- Who will be involved in the decision to move forward on recommended changes?
- What outcome would make this engagement feel worth the effort to your team?
- What is your target timeline for having validated outputs (e.g., lender-ready schedule or revised mine plan)?
- Which mine planning / geological software does your team actively use today?
- Tell us, in one paragraph: what keeps you up at night about the next presentation to investors or lenders?
Where the Money Really Lives — are you leaving value behind?
- Are you confident today that your mine plan captures the majority of recoverable value — or could meaningful NPV be left unrecognized?
- Which elements of your current plan do you suspect are most likely to be suboptimal?
- Have you run any internal or external benchmarking studies previously, and if so what was the measured uplift or gap?
- What target NPV or reserve improvement would justify recommending a change to the current plan to your executive team?
- How do you currently determine cut-off grades and economic pit shells?
- Give an example of a recent planning decision you later questioned — what happened and how did it impact value?
When Plans Break Down — the assumptions lenders and teams challenge first
- Which single assumption in your current plan worries you most because it could cause lenders or investors to reject the plan?
- Which sources of geological uncertainty are most material for your deposit?
- How frequently does your block model get updated and how painful is that process?
- Describe your current approach to modelling uncertainty (e.g., single deterministic model, multiple scenarios, conditional simulation).
- How adequate is your drill-data coverage across the deposit and key domains?
- Tell us about a time geological uncertainty materially changed your plan mid-study—what was the impact on schedule, cost, or reserves?
What Would a Lender-Ready Plan Actually Look Like to You?
- If a lender asked you for the most defensible deliverable, what single thing would you point to as non-negotiable?
- Which outputs must be fully reproducible and auditable for due diligence?
- What validation or acceptance criteria would lenders or your internal governance require (select all that apply)?
- How do you prefer optimization and schedule results to be delivered for sign-off (formats / platforms)?
- What would make you feel emotionally confident handing a plan to lenders rather than anxious?
Computing, Data & The Practicalities — can the tech keep up?
- If compute time or file interoperability failed to match your needs, would that alone block you from accepting optimized outputs?
- Which of these best describes your largest block model today by block count?
- What compute environment do you have available for heavy optimization runs?
- Which block model attributes are essential inputs for your optimization and schedule (select all that apply)?
- How fast do you expect optimization or schedule runs to finish for a realistic largest-case model?
- Describe any data handover or QA checkpoints that must happen before we execute benchmarking (formats, custodians, validation rules).
People, Roles & Governance — who signs, who executes, who worries?
- Who ultimately approves changes to the mine plan and is accountable for risk to schedule and reserves?
- Which team will own day-to-day coordination with our consultants or software team during the engagement?
- How frequently does governance expect project check-ins or milestone reviews for studies like this?
- Who is responsible for data QA and final sign-off on the block model used for optimization?
- What are the biggest people-related risks to delivering the project on time (skill gaps, resourcing, internal politics)?
- Which stakeholders, internal or external, do we need to include early because their buy-in is critical?
A Small First Win — what would convince you to run a pilot now?
- What minimal scope would demonstrate tangible value quickly (select up to three)?
- What budget range would you be comfortable allocating to a focused benchmarking pilot that proves feasibility?
- How quickly would a successful pilot need to show results for you to consider scaling to a full engagement?
- What specific deliverables from a pilot would allow you to make a clear go/no-go recommendation to sponsors or lenders?
- What would prevent you from greenlighting a pilot today (internal approvals, budget, data readiness, other)?
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Data & Model Readiness
Validate block model quality, drill-data coverage, attribute completeness, software interoperability, and compute resource needs for benchmarking.
Model Readiness
Tell Me About Your Model—Start Simple
- What type(s) of block model do you currently maintain and in which file formats?
- How old is the active block model we’d be benchmarking (last full rebuild or major update)?
- Approximately how many blocks are in the model you’d use for benchmarking?
- What is the model’s primary current purpose?
- Who owns and signs off the canonical model in your organization (role/title)?
Is the Model Really Telling the Full Story?
- If an investment committee asked right now ‘how defendable are your reserves?’, what would you say — and where would you hesitate?
- What specific validation tests or diagnostics do you currently run on the block model?
- Which model attributes are present and maintained for every block?
- Are there key attributes or metadata that are missing or inconsistently populated? If so, which and how does that affect decisions?
- How often are attributes refreshed (assays, density, geotech inputs) and by what process?
Where Data Leaves You Holding Your Breath
- Which gaps in your drill data or spatial coverage would make you pause before approving a lender-ready plan?
- How do you currently map and quantify those spatial gaps (heatmaps, interpolation error, buffer analysis, other)?
- Tell us about your assay QA/QC pipeline—what steps flag suspect samples and who investigates them?
- Have you experienced material surprises during drawdown or early production that traced back to model/data gaps? Please give a short example.
- How long have those problematic gaps existed, and what attempts have you made to address them?
What Would It Take to Trust the Numbers?
- If a lender asked for a fully reproducible benchmarking workflow today, what’s the single weakest link that would probably break?
- Which external or internal acceptance criteria must the benchmark meet to be considered ‘bankable’?
- Which stakeholders need to be involved in validation and who has final sign-off?
- Do you maintain runbooks, scripts or containers that allow someone else to reproduce model prep and optimization steps today?
- What documentation or outputs would make you sleep better the night before presenting to lenders?
Are You Losing Value to Software Friction?
- How often do data translation or interoperability issues add delay or risk to your planning work?
- Which systems must our platform interoperate with for a smooth benchmark (select all that apply)?
- Describe any recurring import/export problems you've had (coordinate shifts, missing attributes, units confusion, domain mismatches).
- How important is having the original modelling software present versus translating to a neutral exchange format?
- Do you have licensing or security constraints that restrict third-party access to models or raw data?
Can Your Hardware Keep Up?
- When you run your largest optimization or scheduling job today, what typically happens (e.g., completes in hours, crashes, runs for days)?
- What compute environment do you use for heavy runs?
- What are typical turnaround times you expect (acceptable) for: pit optimization, cut-off optimisation, integrated scheduling?
- Do you use any parallelisation or distributed compute frameworks today (MPI, Spark, Kubernetes)? If yes, which?
- Are storage or data transfer speeds a recurring bottleneck when moving models between systems?
When Would You Call a Benchmark 'Done'?
- If we delivered an optimized plan, what single outcome would convince you it's ready for lenders rather than just an internal study?
- Which deliverables are mandatory for your internal and external reviewers?
- Which reporting standards or templates must deliverables align with?
- How long does your internal review process typically take once the benchmark package is submitted?
- What acceptance tests or checks will you run on the outputs (e.g., rerun optimization, statistical comparisons, independent review)?
If We Fixed One Thing, What Would It Be?
- What single change would most reduce your funding or execution risk on this project?
- How open are you to running a short, focused benchmarking pilot to prove interoperability and runtime on a representative slice of your model?
- What immediate constraints would prevent a pilot from starting (select all that apply)?
- Who should be in the room for a kickoff pilot (roles/titles) and who is the single point of contact?
- What cadence of updates and governance would make you comfortable during a benchmark (choose preferred frequency)?
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Customer Discovery
Clarify project objectives, key constraints, target metrics (NPV, reserve confidence, schedule), and primary geological and operational uncertainties.
Discovery Questions
Kickoff — Tell Me the Short Story
- In one sentence, what single decision are you trying to make with this mine plan?
- Which stage best describes where the project sits today?
- What recent event or trigger prompted this review (e.g., financing request, declining grades, regulator request)?
- Which commercial metrics matter most for the decision right now?
- Who will be the primary user of the outputs we deliver (name/role)?
Are You Comfortable Betting the Mine's Future on Assumptions?
- How confident are you that today’s block model and assumptions reflect reality well enough for a lender to rely on?
- Which specific data issues concern you most right now?
- How often in past projects has a model revision meaningfully changed economics or schedule?
- Describe a recent case where geological surprises forced a rework of plan or budget—what happened and how did it feel to the team?
- Do you have minimum reserve classification or confidence thresholds lenders must see?
What’s the Real Cost of Leaving Value in the Ground?
- If your current plan is suboptimal, what would a realistic NPV uplift need to be for you to justify switching tools or partners?
- How do you currently quantify opportunity cost from pit-shell selection, cut-off choices, or schedule sequencing?
- Which operational constraint most frequently reduces project value: fleet capacity, plant throughput, blending limits, permitting, or capital availability?
- How sensitive is project NPV to commodity price and operating cost swings in your base case?
- If an optimization showed material uplift, what organizational or political barriers might still prevent adoption?
What Are the Unknowns You're Most Afraid To Admit?
- Which geological or operational uncertainties do you think are least well captured in your current plan?
- Approximately what share of your deposit area is supported by direct drill data versus inferred interpolation?
- Which modelling assumptions feel weakest to you and why?
- Have external due-diligence or lenders previously raised technical concerns? If yes, what were the top issues?
- How many scenario or stochastic realizations do you believe are necessary to demonstrate robustness to lenders?
Imagine the Investment Committee Leaves Smiling — What Did We Deliver?
- What specific deliverables would make your plan unequivocally lender-ready?
- Which single output carries the most weight with your lenders or investors?
- What acceptance criteria or thresholds would the committee expect to see before approval?
- Who must sign off internally before the committee sees the result (roles and any non-technical approvers)?
- How will you demonstrably compare our outputs to your incumbent plan (what tests or KPIs will you run)?
Who's Deciding, Who's Watching, and Who Needs to Be Convinced?
- If you had to name the three people whose opinion matters most for project approval, who are they and what do they care about?
- Which stakeholder groups should be included in discovery and review sessions?
- How do external stakeholders (lenders, regulators, community) influence technical scope or schedule?
- What communication rhythm and format keeps your governance comfortable (dashboards, weekly demos, milestone reports)?
- Are there decision-makers who historically resist algorithmic optimizations or external benchmarking? If so, why?
The Practical Bounds: Timeline, Budget, and Compute
- What is your target deadline for delivering a lender-ready plan?
- What budget range has been allocated or is likely available for external optimization, validation, and reporting?
- What is the size/complexity of your largest block model we would need to work with (blocks and attributes)?
- What constraints or preferences exist for compute and data handling (on-prem only, cloud allowed, data residency, VPN requirements)?
- Who will be responsible for data handover, QA, and providing access to models during the engagement?
How Will We Validate — The Proof That Locks the Deal
- What validation evidence would make lenders comfortable signing off (reproducibility, independent audit, sensitivity breadth)?
- Which benchmarking comparisons do you plan to require against your current plan?
- Would you allow a blind benchmarking exercise where we run your model and demonstrate improvement without exposing proprietary assumptions?
- What level of documentation and reproducibility (runbooks, scripts, logs) will your technical reviewers expect?
- Who inside your team will be the day-to-day technical contact for validation and troubleshooting?
Next Step — If We Could Start Tomorrow, What Would That Look Like?
- Assuming alignment today, what would a successful first milestone look like in 30 days?
- What early success signals in the first 60 days would make you confident we're on the right path?
- What risks or blockers must be resolved before work can begin (data access, approvals, budget sign-off)?
- How do you prefer to receive interim results: interactive workshop, written report, live dashboard, or a combination?
- Are there procurement or contracting steps we should expect that typically extend your project start timeline?
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Solution Experience
Use the customer’s models and scenarios to show how optimized pit shells, cut-off grade strategy, and integrated scheduling change NPV, risk, and deliverability.
Experience Meetings
- Solution Experience Alignment
- Model Ingest & Readiness Check
- Benchmark Run — Pit Optimization Proof
- Integrated Scheduling & Deliverability Workshop
- Solution Validation & Decision
- Customer to supply or confirm equipment availability calendars and any contract constraints affecting schedule.
- Demonstrate, using customer data, the delta in NPV and reserves between baseline and optimized pit shells.
- Show how cut-off grade strategy materially shifts throughput, grade, and NPV in customer's scenarios.
- Obtain explicit customer validation of results or a prioritized list of clarifications/adjustments.
- Select 1–3 alternatives to move forward into integrated scheduling for deliverability analysis.
- Seller to deliver NPV comparison package (baseline vs optimized) including data tables and visuals.
- Customer to confirm acceptance/rejection of each optimized alternative and provide feedback within agreed SLA.
- Seller to document any assumption differences flagged during validation and rerun if required.
- Seller to prepare selected alternatives for the integrated scheduling session.
- Recap Selected Alternatives and Goals
- Produce a lender-focused schedule that demonstrates deliverability tied to NPV outcomes.
- Quantify schedule risk and its direct impact on NPV and financing readiness.
- Obtain customer concurrence on a preferred schedule or a prioritized gap list for final remediation.
- Identify any operational assumptions that must change to meet lender acceptance (e.g., ramp rates, contingencies).
- Seller to produce integrated schedule package: Gantt, cashflow, NPV sensitivity, and deliverability/risk dashboard.
- Introductions & Objectives
- Seller to run and deliver requested sensitivity runs flagged during the workshop.
- Customer to confirm which schedule variant will be used for lender-readiness deliverables.
- One-Line Current & Future State Recap
- Customer either signs off that acceptance criteria are met or provides a prioritized list of gaps with owners and deadlines.
- Agree the next commercial milestone (statement of work, pilot, or full engagement) and timeline for Deployment Planning.
- Ensure reproducibility and traceability requirements for lender-ready outputs are documented and owned.
- Establish governance cadence for post-delivery issues and enhancement requests.
- Seller to compile final validation package (reports, model versions, run logs, assumptions, and acceptance checklist).
- Customer to sign off on acceptance items or list gaps with prioritized actions and owners.
- Seller to issue proposed commercial milestone schedule and Statement of Work for next engagement phase.
- Schedule Deployment Planning meeting to allocate compute, owners, and QA checkpoints for execution.
- Produce a single-sentence current-state description that all participants accept.
- Agree and quantify the primary consequences (NPV loss, schedule delay, financing risk) of the current state.
- Define a measurable future-state outcome the Solution Experience must prove.
- Agree on required data, credentials, scenarios, and timeline for the live optimization runs.
- Customer to deliver final block model, baseline mine plan, commodity/cost assumptions, and scenario list to a shared folder.
- Customer to nominate decision owner(s) and lender/finance reviewers for final validation.
- Seller to confirm compute capacity, required software licenses, and a schedule for live runs.
- Seller to prepare a one-page consequence summary (money, schedule, risk) to use during live sessions.
- Pre-work Recap
- Confirm the model passes integrity checks or list precisely what needs fixing.
- Agree the exact baseline and scenarios to be run during the Solution Experience.
- Confirm compute access, runtimes, and file handover procedures to avoid delays during live runs.
- Establish clear 'run-ready' acceptance criteria for the model.
- Customer to remediate and re-upload any missing attributes or corrected coordinate transforms within agreed SLA.
- Seller to provision compute environment and provide access details and run schedule.
- Seller to produce a model readiness report listing any assumptions made for attributes or densities.
- Customer to confirm baseline plan file and mark the single baseline version for comparisons.
- Recap the Agreed Current/Future State & Acceptance Criteria
- Scheduling Inputs & Constraints Review
- Run: Baseline Pit Shell & NPV
- Block Model Integrity Summary
- Consolidated Proof Package Presentation
- Current State Statement (Diagnosis)
- Acceptance Criteria Walkthrough
- Run: Optimized Pit Shells (Diagnosis → Proof)
- Attribute & Domain Completeness
- Live Integrated Scheduling Run
- Consequence Quantification
- Scenario Mapping & Baseline Plan Identification
- Cut-off Grade Strategy Sensitivity
- Sensitivity: Capacity, Ramp-up & Equipment Availability
- Force Validation: Customer Confirmation
- Define Future State (Outcome)
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Solution Scope
Define modules (model review, pit/underground optimization, scheduling, geotech, economics), deliverables, acceptance criteria, and responsibilities.
Scope Configuration
- Import and Clean Geological Block Model
- Conditional Simulation Grade Re-estimation
- Generate Multiple Block Model Realizations
- Optimal Ultimate Pit Shell Generation (NPV)
- Design Multi-stage Pushbacks and Stage Geometry
- Detailed Open-pit Bench and Ramp CAD Export
- Underground Decline and Level Design
- Stope Layout Optimization with Dilution Modeling
- Cut-off Grade Optimization and NPV Sensitivity
- Mineable Reserve Inventory and LOM Export
- Grade Control Block Model and Sampling Plan
- Geotechnical Slope Stability Modeling and FOS Maps
- Processing Blend Optimization and Recovery Forecasts
- Financial Cashflow Model and NPV Forecast
Scope Questions
Import and Clean Geological Block Model
- What file formats do you currently have for the block model and related datasets?
- Approximately how many blocks (order of magnitude) are in the model to be imported?
- Which key block attributes are present and required (select all that apply)?
- Are there known issues with the model that require cleaning (e.g., negative densities, duplicate blocks, inconsistent domains)?
- Do you require coordinate system / projection verification and transformation during import?
- Describe any custom attribute calculations or mappings that must be applied during import (e.g., metallurgical recoveries, dilution rules).
Conditional Simulation Grade Re-estimation
- Is conditional simulation required to update block grades for uncertainty quantification?
- Which variables should be simulated (e.g., gold, copper, recoverable metal, density)?
- What simulation method do you prefer or currently use (SGS, Turning Bands, Sequential Gaussian, Multiple-point)?
- How many realizations are needed for conditional simulation to support risk and optimization?
- Are there specific drillhole or sampling QC issues that must be handled before simulation (e.g., capping, top-cutting, sample length standardization)?
- Please list target statistical outputs required from the simulation (e.g., mean grade maps, coefficient of variation, percentile envelopes).
Generate Multiple Block Model Realizations
- Purpose of realizations (select all that apply)?
- How many realizations will be used operationally in optimization and scheduling?
- Do you require realizations to preserve short-scale variability or large-scale trends?
- Are realizations constrained to specific geologic domains or hard boundaries?
- What computational resources are available/desired for generating realizations (local workstation, cloud nodes, HPC)?
- Specify any timeline constraints for producing realizations (e.g., must be ready for optimization by X date).
Optimal Ultimate Pit Shell Generation (NPV)
- Is the goal to produce a single NPV-optimal pit or a set of candidate shells for stakeholder review?
- What economic parameters must be used or referenced (commodity price, processing recoveries, mining/capital/processing costs)?
- Which optimization engine or constraints are required (e.g., Lerchs-Grossmann, integer programming, slope constraints, ramp access)?
- Are lender or reporting standards prescribing specific pit definitions or strip ratio limits?
- Do you require sensitivity napplication across commodity prices or cost scenarios for the ultimate pit?
- Are pushback shells and their sequencing expected to be integrated with ultimate pit outputs in this module?
Design Multi-stage Pushbacks and Stage Geometry
- Which stage design approach do you require (e.g., equal-stripping, NPV-driven pushbacks, operational constraints-driven)?
- How many pushback stages are anticipated or desired for planning?
- Are there maximum allowable slope angles, bench heights or berm widths that must be respected?
- Do you need stage-specific production targets or stripping ratios defined?
- Should pushback geometry consider phased access (e.g., haulroad gradients, ramp positioning)?
- Provide any site constraints that affect stage geometry (environmental buffers, infrastructure, water management).
Detailed Open-pit Bench and Ramp CAD Export
- Which CAD export formats are required by your downstream teams or contractors?
- What level of bench detail is required (e.g., design centerlines, bench toes/crests, ramp edges, berms)?
- Do you require survey-ready deliverables with coordinate metadata and layer naming conventions?
- Should ramp gradients and cross-sections be included in the CAD export?
- Will CAD deliverables be integrated into a GIS or machine-control fleet (requires specific formats)?
- Provide any drafting standards or templates we should follow for CAD layers and annotation.
Underground Decline and Level Design
- Is the underground design for a greenfield decline or to connect to existing workings?
- What decline parameters are required (gradient, width, support assumptions, ventilation provisions)?
- Which level spacing and access strategy do you prefer (e.g., conventional levels, sub-level caving, longhole stoping)?
- Do you need hydraulic, ventilation or dewatering interfaces considered in decline routing?
- Are 3D CAD or BIM exports required for underground development planning?
- Please list any rock mass or geotechnical input constraints we must observe for underground design.
Stope Layout Optimization with Dilution Modeling
- Which stope optimization method do you require (e.g., integer programming, dynamic programming, heuristic)?
- What dilution and recovery assumptions should be applied (fixed %, variable by domain, selective mining unit-based)?
- What is the minimum mining unit or stope dimension to respect?
- Do you require stope sequencing and extraction schedules integrated with the scheduling engine?
- Are backfill strategies or pillar retention constraints to be modeled?
- Provide any cut-off rules or selective mining criteria that should drive stope selection.
Cut-off Grade Optimization and NPV Sensitivity
- Is cut-off grade optimization required for single-period or dynamic multi-period (LOM) optimization?
- Which economic inputs must be used or varied during sensitivity (prices, exchange rates, processing recoveries, costs)?
- Do you require scenario outputs by probability or percentile (P10/P50/P90) for NPV sensitivity?
- Should cut-off optimization consider processing constraints like mill throughput or blend requirements?
- Do you want recommended operational cut-offs vs. financial (NPV-maximizing) cut-offs documented separately?
- Provide any stakeholder or lender-mandated assumptions for cut-off grade calculations (e.g., conservative recoveries).
Mineable Reserve Inventory and LOM Export
- Which reserve classification standard applies to this project (e.g., JORC, NI 43-101, SAMREC)?
- What output formats are required for inventory and LOM (CSV, XML, database export, reporting tables)?
- Do you need reconciliation and reporting templates for reserve movements and annual reconciliations?
- Should the LOM schedule include material type tagging (ore/waste/low-grade) and monthly/quarterly tonnage and grade?
- Are cut-off rules, mining dilution, and recovery assumptions to be embedded in the LOM export?
- Provide any regulatory or lender validation criteria that inventory exports must meet.
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Mutual Commit
Agree commercial terms, milestones, validation criteria for lender-ready outputs, responsibilities, and governance cadence.
Agreement Modules
- Non-Disclosure Agreement (NDA)
- Master Services Agreement (MSA)
- Statement of Work (SOW)
- Commercial Terms & Pricing Schedule
- Payment Schedule & Milestone Invoicing
- Validation & Acceptance Criteria (Lender-Ready Outputs)
- Data & Model Handover Agreement
- Compute, Environment & Access Agreement
- Responsibilities & RACI Matrix
- Governance & Meeting Cadence
- Change Control / Change Order Agreement
- Compliance & Regulatory Reporting Commitment
- Risk Allocation & Contingency Plan
- Subcontractor and Third-Party Consent
- Final Sign-off & Handover Certificate
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Deployment
Operationalize project execution with readiness checks, compute provisioning, and QA validation.
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Deployment Planning
Allocate compute resources, schedule tasks, assign owners, and set data handover and QA checkpoints for execution.
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Validation Checklist
Verify reproducibility of optimized plans, confirm acceptance criteria, and ensure deliverables meet financing and regulatory reporting standards.
Validation Questions
Start Here: A Quick Snapshot
- Which project best describes why you’re engaging us today?
- What's the single most important decision this mine plan will influence in the next 6–18 months?
- Who on your team will be the primary day-to-day contact for this project (role and responsibility)?
- Which of the following best describes the timing pressure you’re under?
- Roughly how large is your principal block model (number of blocks / approximate file size)?
- Any immediate constraints we should note (budget band, regulator deadline, lender pre-conditions)?
Are We Betting the Bank on the Wrong Plan?
- If the current mine plan goes to investors exactly as-is, what’s the single worst thing that could happen?
- Who must be convinced for a financing approval—what are their top three evidence requirements?
- Have lenders or external reviewers previously flagged weaknesses in your planning work? If so, what were the key concerns?
- How tolerant are your stakeholders to model-driven variance in reserve estimates and production schedules?
- What would count as a deal-stopping finding in an independent benchmarking study?
Where Does Value Hide in Your Model?
- Do you suspect your current plan leaves recoverable value behind—and why might that be true?
- Which modeling or optimization tools do you currently use for pit shells, cut-off grade, and scheduling?
- Can you estimate the NPV uplift you think is realistically recoverable from re-optimization (ballpark percent)?
- Which parts of your block model feel least trusted (select up to three)?
- Tell us about any past re-optimizations—what changed materially and what surprised you?
What’s Really Keeping You Awake at Night?
- Which single operational or technical risk worries you most if the plan underperforms?
- Have unexpected geotechnical or grade surprises occurred during past campaigns? What were the consequences?
- How frequently do actual grades and tonnages meaningfully diverge from your model projections?
- Which stakeholders most amplify your stress when plans shift—finance, operations, board, or others?
- How does it feel internally when a plan is questioned during financing—embarrassing, defensible, urgent to fix, or something else?
If This Went Perfect, What Would You Present to the Investment Committee?
- If you could show one headline to secure financing, what would it be (e.g., X% NPV uplift, reserve increase, de-risked schedule)?
- What minimum NPV uplift or reserve confidence improvement would make the engagement a clear success for you?
- Which deliverables must be lender-ready (select all that apply)?
- What acceptance criteria would your finance or technical reviewers use to sign off on 'bankable' outputs?
- Beyond numbers, what narrative or story must the plan convincingly tell to secure support?
Who Needs to Be Convinced—and How?
- Who are the decision roles that will push back hardest on the revised plan, and why?
- Which evidence types carry the most weight for each stakeholder group (select applicable)?
- How important is reproducibility—do lenders require a repeatable runbook and traceable inputs?
- What format do stakeholders prefer for technical deliverables and review—formal report, interactive dashboard, raw model files, or live walkthrough?
- What governance cadence will be required during the engagement (steering meetings, weekly checkpoints, approvals)?
What Can We Run on Your Data—Right Now?
- If we had access to your block model today, what’s the fastest outcome you’d want to see within two weeks?
- Which file types and systems contain your current models and data (select all that apply)?
- How complete are the attributes we need for benchmarking (grades, densities, domains, recovery, metallurgy)?
- Do you have a preferred sandbox or compute environment we must use, or can we provision our own for heavy runs?
- Any compliance or IP constraints on sharing models and raw data we should know about?
What Would Make You Say Yes Today?
- What’s the single simplest commercial or technical thing we could offer that would remove your biggest hesitation?
- Which of these contracting approaches would make you most comfortable to start quickly?
- What is your internal approval process for vendor engagements—who signs, what thresholds matter, and typical lead time?
- What budget band would realistically allow you to move forward in the next quarter?
- If we delivered an initial, lender-ready benchmark within your timeline, how likely would you be to recommend us internally?
Next Steps & Confidence Check
- On a scale from 1–10, how confident are you that a third‑party re-optimization can materially improve your presented plan?
- What would you like to see on our first joint call to feel progress has been made?
- Who are the three people we should include in the kickoff meeting and why?
- Is there any confidential context, recent change, or sensitivity that would help us tailor our approach (M&A, cost cuts, upcoming audits)?
- Any final concerns or hopes you'd like us to address before we prepare a scoped proposal or pilot?
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Success
Confirm outcomes against success signals, hand over final deliverables, and maintain a shared channel for issues and enhancements.
Success Reviews
- Success Validation Workshop
- Deliverables Handover & Acceptance
- Operational Transition & Knowledge Transfer
- Issues, Enhancements & Support Governance
- Post-Delivery Review & Continuous Improvement Checkpoint
Issues & Enhancements
- Ensure stakeholders know how to report issues and how they will be prioritized and resolved.
- Finance/legal to issue or acknowledge final invoices and sign-off documents.
- Roles & Ownership
- Ensure customer operators can reproduce key runs in their environment without vendor assistance.
- Assign operational owners and confirm a QA/checkpoint cadence for ongoing use.
- Document training needs and schedule supplemental sessions for identified staff.
- Deliver runbooks, environment specs, software versions, and sample command-lines/scripts to the shared channel.
- Customer to complete the hands-on reproducibility run and confirm parity or raise issues within 5 business days.
- Schedule role-based training sessions and assign owner for ongoing QA cadence.
- Shared Channel & Access
- Create a durable, auditable support and enhancement process with clear SLAs and ownership.
- Introductions & Objectives
- Agree on governance cadence and reporting metrics to track outcomes and ROI.
- Project team to create the shared channel, invite stakeholders, and pin the deliverable manifest and runbooks.
- Publish triage rules, severity definitions, and SLA commitments to the channel.
- Open an initial enhancement backlog and schedule the first prioritization workshop within 2 weeks.
- Metric Review: Expected vs Actual
- Verify whether delivered plan is delivering expected value and trigger remediation if not.
- Capture concrete lessons and update model/process artifacts to reduce future variance.
- Agree next steps (remediation, enhancements, further consulting) with owners and timelines.
- Schedule the first checkpoint at 30 days and assign the data owner to provide reconciled production, grade and cost data.
- If variance exceeds agreed thresholds, trigger a remediation analysis and assign owners within 5 business days.
- Document lessons learned, update runbooks and models where required, and publish changes to the shared channel.
- Confirm delivered outputs meet each documented success signal or capture clear exceptions.
- Demonstrate reproducibility of key results using the shared data package and run scripts.
- Obtain formal acceptance or an agreed remediation plan with owners and timelines.
- Customer to provide formal acceptance signature or itemized exception list within 10 business days.
- Project team to publish reproducibility logs, run scripts, and provenance documentation to the shared channel.
- If exceptions exist, schedule remediation activities with owners and target dates in the shared channel.
- Deliverables Inventory
- Ensure the customer has intact, accessible copies of every deliverable in usable formats.
- Complete formal acceptance and record sign-off for contractual closure.
- Clarify any licensing, IP, or regulatory documentation required for financing.
- Publish the final data package and secure links to the agreed shared channel with checksums and file manifest.
- Customer to confirm they can open and validate the core deliverables (block model, optimized pit, schedule, financial model).
- Runbook Walkthrough
- Root-Cause Analysis for Variances
- Triage Process & Severity Definitions
- Access & Integrity Check
- Current State Recap (one-sentence)
- Hands-on Reproducibility Workshop
- Consequence Review
- Lessons Learned & Model Adjustments
- Acceptance Criteria Walkthrough
- Enhancement Intake & Prioritization
- Governance Cadence & Escalation
- Commercial & Legal Closepoints
- Decide on Follow-up Actions
- Review Success Signals & Acceptance Criteria
- Operational QA & Checkpoints
- Reporting & ROI Tracking
- Training & Support Plan
- Reproducibility Demonstration (Proof)
- Record Signatures & Archive
- Traceback: Tie Outputs to Problems
- Validation & Sign-off
- Next Steps & Remediation Plan (if needed)