How an engineer brings clarity to complex pension decisions
hannah
For Tom Wilkinson, an engineer and now Chair of the Alberta Refrigeration Pension Plan, thinking in systems has always been second nature. After decades in engineering and leadership roles, he’s used to dealing with complexity. But even with experience, some problems don’t get simpler—especially when they involve uncertainty, trade-offs, and long-term consequences.
Facing a complex problem with too many variables
Recently, Tom has been working on a challenging question: how to handle surplus funds in a pension plan. On paper, it’s a financial and governance problem—but in practice, it quickly becomes much more complex.
He is dealing with:
multiple possible options and trade-offs
different scenarios that need to be evaluated
forecasting models based on Monte Carlo simulations
Each adjustment to the model requires time and iteration, making it difficult to explore ideas freely.
At some point, the issue wasn’t just about finding the right answer—it was about making sense of the possibilities in a way that a group could discuss and align on.
Using Xmind to explore and structure ideas
Tom has been using mind maps for years. Some of his most effective learning experiences—like an accounting course he once took—were built entirely around them.
When he recently looked for a tool again, he found that older software like Novamind was no longer available on modern devices. After checking recommendations, he came across Xmind.
With multiple machines across different systems—Mac, Windows, tablets, and more—being able to access it easily made a difference. But more importantly, it allowed him to approach the problem in a way that felt natural: starting without structure, and shaping ideas over time.
He began mapping out the pension-related questions by:
capturing key elements and assumptions
listing possible directions and decision paths
gradually reorganizing them into a clearer structure
Instead of jumping straight into simulations, he could first lay out the thinking visually—exploring options before committing to detailed analysis.
Bringing clarity, focus, and alignment to complex work
As the maps evolved, they started to play a role beyond personal thinking.
Instead of repeatedly adjusting simulation models, Tom and his subcommittee could first narrow down their thinking visually. The maps helped them:
focus on what really matters before deeper analysis
reduce unnecessary iterations in simulations
create a shared understanding across the group
Discussions became more efficient, and decisions more grounded.
This approach also reflects how Tom has used mind mapping in the past. Earlier in his career, while rolling out a safety manual, he faced a similar challenge—too much detail, and not enough clarity.
Training sessions would often:
drift into unnecessary detail
lose focus on the main ideas
become difficult to complete on time
By creating mind maps that summarized each chapter, he helped instructors stay aligned with the key points—making it possible to deliver complex material efficiently without losing direction.
Continuing to refine how he works
Tom is still refining how he uses Xmind today. There are practical aspects he’s working through—like condensing maps into a readable format or preparing them for sharing.
But the core value is already clear.
For him, Xmind doesn’t introduce a new way of thinking. It supports a way of working that has always made sense—starting with complexity, and gradually shaping it into something structured, visible, and easier to share.
He sees Xmind as a useful addition to his toolkit—one that helps turn complex, evolving problems into something more manageable. Whether working through pension decisions or summarizing dense material, it provides a way to focus thinking, support discussion, and move forward with greater clarity.
