Most organisations treat decision-making like a meeting, not a system.

You book a room, invite the usual suspects, argue a bit, and hope the mix of people and perspectives is “good enough”.

Wizer flips that.

By combining Decision Profiles, Panel Strength, and a Recommendation Engine, you get something very close to a decision scientist sitting beside you for every important call — quietly asking:

Below is how the three layers work together, and how teams can use them in minutes—not months.

1. Decision Profiles: Making Decision Styles Visible

What they do Decision Profiles reveal how people tend to make decisions, not whether they’re “good” or “bad” at them.

They’re built on decision science and aligned with research like Dr Juliet Bourke’s work on six core decision lenses (outcomes, options, people, process, evidence, risk). Instead of personality labels, Wizer focuses on the decision style patterns that show up when things are uncertain, political, or high-stakes.

Each person gets a primary Decision Profile (e.g. Achiever, Guardian, Collaborator, Visionary, Analyzer, Deliverer, Explorer) that reflects:

• What they pay attention to first (results, risk, people, process, evidence, new options)

• How they typically move a decision forward (push, protect, explore, structure, connect)

• Where they add value — and where they may create blind spots
  

Why it matters scientifically

Research on diversity of thought and decision quality shows that high-performing teams don’t just differ demographically — they differ in how they frame problems and evaluate options. Bourke’s work has shown that when teams systematically widen their lenses (options, evidence, risk, people, etc.), they generate better ideas and avoid predictable misses.

Decision Profiles give you:}

• A map of cognitive/decision diversity, instead of vague assumptions

• A shared language: “We’re heavy on Achievers and Visionaries; light on Guardians and Analyzers”

• A way to connect individual behaviour to systemic patterns in decisions

This is the raw material. Everything else in Wizer builds on it.

2. Panel Strength: Testing the Quality of the Group Before You Decide

Once you can see individual decision styles, you can ask the real question:

That’s what Panel Strength measures.

How Panel Strength works

For any decision, you define the group who will actually influence the outcome — your panel. Wizer then analyses that group across three lenses:

1. Decision Styles

   • Are certain styles overrepresented? (e.g. outcomes and ideas)

   • Are others missing? (e.g. risk, evidence, delivery, people-focused lenses)

2. Experience & Role Mix

   • Do you have a spread of strategic, operational, and frontline experience?

   • Are the people most affected by the decision represented indirectly or directly?

3. Diversity Signals

   • Is the group overly homogeneous in age, gender, or background?

   • Are you unintentionally replicating the same perspective under different job titles?
     

Panel Strength doesn’t tell you “good vs bad”. It shows:

• Where the panel is strong (e.g. creativity and speed)

• Where it’s exposed (e.g. underweight on risk and implementation)

• How closely the group’s profile matches the type of decision (high risk vs low risk, strategic vs operational, people impact vs financial)

Why this matters scientifically

Decades of research into “wise crowds” shows that the quality of a group’s decision depends on:

• Diversity of perspectives

• Relative independence of views

• A way to aggregate those views

Panel Strength is a live diagnostic of the first part: diversity of decision styles and perspectives at the moment you’re about to decide.

Instead of discovering bias or blind spots after the rollout, you can see:

• “We’re making a long-term risk decision with almost no risk-focused or evidence-focused profiles.”

• “We’re designing something for younger staff with zero younger voices in the panel.”

And you see it before you lock the decision in.

3. Recommendation Engine: Who’s Missing, Specifically?

Once you know the panel is skewed, you face the hard part:

The Recommendation Engine answers that question.

How the Recommendation Engine works

Under the hood, Wizer takes three inputs:

1. The decision you’re making

   • Nature of the decision (strategic, operational, people, risk-heavy, innovation, etc.)

   • Who it affects (employees, customers, community, partners)

2. The current Panel Strength

   • Which Decision Profiles are present or missing

   • Which kinds of experience are present or missing

   • Where diversity is low or one-dimensional

3. The broader stakeholder pool

   • Everyone who has a Decision Profile and basic tags in your organisation (function, level, geography, lived experience, etc.)

It then suggests:

• Named individuals who would add missing decision styles

• People with relevant experience (e.g. frontline, implementation, customer-facing, policy)

• Stakeholders who provide outward-facing diversity that matches the impact of the decision (e.g. regional staff, younger employees, under-represented groups)

In practice, the output looks less like an abstract report and more like:

The engine doesn’t replace judgement. It surfaces intelligent, data-backed suggestions so humans can make faster, better calls about who should be in the room.

4. How They Work Together in Real Time

Think of it as a three-step loop that can happen in minutes:

1. Profiles create the raw decision data

   • Everyone completes their Decision Profile once

   • The organisation now has a live map of decision styles and experience

2. Panel Strength checks the quality of each group

   • For any important decision, you define the panel

   • Wizer instantly shows where you’re strong and where you’re exposed

3. The Recommendation Engine adjusts the mix

   • Wizer recommends specific people to invite to balance the panel

   • You adjust the group and re-check Panel Strength if needed

Then you run the decision — with a panel designed deliberately, not accidentally.

The effect is:

• Fewer blind spots

• Less over-reliance on the same 5–10 voices

• More systematic inclusion of people whose perspective is critical but often missing

• A repeatable way to design decision groups, not just hope you’ve got the mix right

5. Why This Is “Like Having a Decision Scientist in the Room”

A good decision scientist would:

• Ask what kind of decision you’re making

• Look at who’s in the room and what they each bring

• Flag the biases and gaps that are likely to show up

• Suggest who else you should invite before you lock anything in

Wizer does exactly that, but:

• At scale (across teams, business units, and stakeholder groups)

• On demand (for every decision where it matters)

• With memory (re-using what it learns about how your organisation decides)

You still own the judgement.The system just makes sure the conditions for good judgement are there: the right mix of styles, experience and diversity, for the right decision, at the right time.

6. How Quickly Can Decision Intelligence be Used?

This isn’t a multi-year transformation project. In most organisations:

• Profiles are completed once (often in under 15 minutes per person)

• After that, Panel Strength and Recommendations can be used in real time, whenever a meaningful decision is coming up

  
  

Typical fast-use examples:

• Designing the panel for a new strategy, product, or program

• Shaping the group for a funding decision or major investment

• Setting up stakeholder panels for community or customer decisions

• Balancing internal steering groups that keep stalling or going in circles

The pattern is always the same:

7. The Strategic Payoff - Start With Your Decision Profiles

When Decision Profiles, Panel Strength and the Recommendation Engine are used together, leaders get:

• A live view of decision capability across the organisation

• Fewer blind spots and “how did we miss that?” moments

• Better use of internal talent, not just the same familiar names

• Stronger stakeholder engagement, because the right people are involved up front

• A decision process that is explainable, auditable and improvable

And that’s the real shift: decision-making moves from being a black box to a designed system — one that gets smarter every time you use it. Start with your Decision Profile: https://www.wizer.business/decision-profiles