A project, a process or a decision.
I can help.
Need more hands to get a planning cycle over the line? A process that's slower or more fragile than it should be? A big decision that has to hold up when people push back?
I work in your tools, alongside your team, on-site in Brisbane (and further afield when the work needs it).
Three ways to work together
Pick the closest fit. They overlap, and plenty of work starts in one and ends up in another.
Work alongside your team
Extra capacity, working in your models and your process.
- •Planning cycles, from monthly updates to major reforecasts
- •Field development planning, budgeting and integrated activity planning (with 10 years of Enersight behind it)
- •Short projects, or ongoing support
Make your planning faster and better
Add capability to the models, processes and tools you already have.
- •Refreshing and speeding up Enersight models, and adding the functionality your key decisions depend on
- •Redesigning the processes around the model: data flows, ownership, updates, reviews
- •Build fit-for-purpose tools and automations to cut the manual steps between systems
Rethink how you plan and decide
End to end, from framing the problem to a recommendation you can defend.
- •Investment and capital allocation decisions
- •Simulation-based comparison of strategies across scenarios and uncertainties
- •Wuick answes when leadership asks 'what if?'
Something else?
If it involves planning, forecasting or decisions in oil and gas, tell me about it.
If I'm not the right fit, I'll say so.
Who you'd be working with
I'm Mark. Mechanical engineer, MBA, and 10 years with Enersight.
For a decade I've helped clients with field development planning, budgeting and integrated activity planning. The first three years as a consultant. The next seven in product management, as the go-to person for the hardest problems (and training your trainers).
So I've seen planning from both sides: building the plan, and building the tool underneath it. I know what the reconciliation actually costs.
I'm based in Brisbane, happy to work on-site, and can travel when the work needs it.
Before any paperwork, I'm happy to meet, learn about your world and what success looks like for you. If I'm not a good fit, I'll tell you.
How I approach big decisions
Complex decisions don't get solved in one pass. You build a model, find a variable you missed, challenge an assumption, and realise the decision wasn't quite what you started with.
So I treat it as a cycle. Five steps, and you'll usually loop through them more than once.
Clarify the decision
Prevent solving the wrong problem
- •What decisions are actually being made?
- •What does success look like? (a choice, an objective to optimise, constraints to be satisfied?)
- •Who is making the decisions and when do they occur?
Most problems start loosely defined. Tightening the decision space early ensures the model is solving the right problem.
Frame the system
Define the world the decision sits within
- •What are the key performance measures and the boundaries of the system?
- •What uncertainties exist and how do they behave (noise, trends, shock, rare events)?
- •How do variables interact, scale and constrain each other?
- •What ranges and edge cases actually matter for the decision?
This step is about the structure and behaviour of the system.
A model is only as good as the way the problem is framed.
Build the simulation model
Turn the system into something you can explore
- •Represent the key variables, decisions and their relationships
- •Model how the system evolves over time, including staged decisions
- •Incorporate new information as it becomes available
- •Design for ranges, distributions and interactions
The goal is to simulate how the system behaves under different conditions.
Analyse, challenge & evolve
Reveal what matters, and what's missing
- •What actually drives outcomes?
- •How do different strategies perform across scenarios?
- •Where does risk and variability come from?
- •What assumptions break under pressure?
- •What new variables, interactions or decisions emerge?
This is where the model is tested, challenged and refined, and where the insight comes from.
Iterations here often lead to reframing the decision, introducing new variables, and changing how the system is represented.
Each pass improves both the model and the decision.
Communicate the decision
Turn analysis into action
- •What is the recommended path forward?
- •What are the key drivers behind that recommendation?
- •What risks and trade-offs need to be understood?
- •What range of outcomes should the decision-makers expect?
Analysis only matters if people can understand it and act on it.
The goal is a decision that you can explain, and defend when someone pushes back.
Data, processes & systems
Make the model work in practice
- •How is data sourced, validated and kept up to date?
- •What level of trust and transparency exists in the inputs?
- •Who owns the data, the model and the outputs?
- •How are updates, reviews and decisions operationalised?
- •How can we cut the manual effort and disconnected steps?
A good decision model needs reliable inputs and clear ownership, wrapped in a process that repeats.
The aim is a system people trust and keep using.
Clarify the decision
Prevent solving the wrong problem
- •What decisions are actually being made?
- •What does success look like? (a choice, an objective to optimise, constraints to be satisfied?)
- •Who is making the decisions and when do they occur?
Most problems start loosely defined. Tightening the decision space early ensures the model is solving the right problem.
Analyse, challenge & evolve
Reveal what matters, and what's missing
- •What actually drives outcomes?
- •How do different strategies perform across scenarios?
- •Where does risk and variability come from?
- •What assumptions break under pressure?
- •What new variables, interactions or decisions emerge?
This is where the model is tested, challenged and refined, and where the insight comes from.
Iterations here often lead to reframing the decision, introducing new variables, and changing how the system is represented.
Each pass improves both the model and the decision.
Build the simulation model
Turn the system into something you can explore
- •Represent the key variables, decisions and their relationships
- •Model how the system evolves over time, including staged decisions
- •Incorporate new information as it becomes available
- •Design for ranges, distributions and interactions
The goal is to simulate how the system behaves under different conditions.
Frame the system
Define the world the decision sits within
- •What are the key performance measures and the boundaries of the system?
- •What uncertainties exist and how do they behave (noise, trends, shock, rare events)?
- •How do variables interact, scale and constrain each other?
- •What ranges and edge cases actually matter for the decision?
This step is about the structure and behaviour of the system.
A model is only as good as the way the problem is framed.
Data, processes & systems
Make the model work in practice
- •How is data sourced, validated and kept up to date?
- •What level of trust and transparency exists in the inputs?
- •Who owns the data, the model and the outputs?
- •How are updates, reviews and decisions operationalised?
- •How can we cut the manual effort and disconnected steps?
A good decision model needs reliable inputs and clear ownership, wrapped in a process that repeats.
The aim is a system people trust and keep using.
Communicate the decision
Turn analysis into action
- •What is the recommended path forward?
- •What are the key drivers behind that recommendation?
- •What risks and trade-offs need to be understood?
- •What range of outcomes should the decision-makers expect?
Analysis only matters if people can understand it and act on it.
The goal is a decision that you can explain, and defend when someone pushes back.
Tools, if they help
I start with your existing models and tools. Where it makes sense, I can bring in Bear Decisions, my Excel add-in that generates every combination of your decisions and uncertainties and shows you what's driving the results. Or build something new, fit for your purpose and workflow.
Many teams don't need anything new. The decision comes first.