Live Decision Intelligence Model Sample Gallery

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Tree Donation for Climate

Interactive game-like 2D/3D UI demonstration
Type: front end demonstrator, qualitative model
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Benefits of book marketing

UI demonstration of agent-based model.


Type: front end demonstrator, qualitative model
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Carbon Tax

UI demonstration of moving-bars 3D paradigm. Type: Fully functional qualitative model
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Simulating the effects of aid provided to a justice system

UI demonstration of agent-based model.


Type: front end demonstrator, qualitative model
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Training course investment

A simple model showing how investment in a training course produces ROI under different circumstances.
Type: Front end demonstrator, quantitative model with auto text generation
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Covid-19 CDD Diagram

A Causal Decision Diagram (aka Decision Model) showing how a building manager might make covid-19 decisions.
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How much is enough to donate to trees?

This user interface demonstration shows how you can integrate a decision on the left-hand side with outcomes shown on the right as well as dynamically generated in the 3-D diagram. Move the levers in the upper left to experiment with the model.

Type: front end demonstrator, qualitative model

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Simulating the effects of aid provided to the Liberian justice system



A foundation wishes to grant financial aid to the country of Liberia to improve the justice system.  How big should the aid package be, and how should the funds be allocated between:

  • legal infrastructure,

  • police, and

  • development of community paralegal services?

Agent-based model simulating influence of marketing and network effects on purchasing behavior

This is an agent-based simulation, which means that it shows a population of simulated people and their changing and interacting behavior

This demonstration projects how marketing activities and network recommender effects change the purchasing characteristics of a population.  In the model, the purchasing cycle is represented by three stages:

  • Impression (does the potential buyer becomes aware of the product?)

  • Evaluation (does the potential buyer like the product?)

  • Purchase (does the potential buyer purchase the product?))

The initial population is modeled as 4 segments:

  • Resistant: biased against purchasing the product

  • Receptive: Neutral towards to product and open to persuasion

  • Sympathetic: biased towards the product

  • Active: Already aware of the product and positively disposed to purchasing it.

As the model runs, network recommender effects of those who have purchased feed back to change the purchase propensity of the population who have not yet made a purchasing decision.

Type: front end demonstrator, qualitative model

How investing in a training course produces ROI under different circumstances

This web-based demonstration shows how you can integrate a decision with different outcomes, and is dynamically generated in the 3-D diagram. Move the levers to experiment with the model.

Type: front end demonstrator, qualitative model

How to invest in clean emissions equipment when subject to carbon tax?

This user interface demonstration shows how you can integrate a decision on the left-hand side with outcomes shown on the right as well as dynamically generated in the 3-D diagram. Move the levers in the upper left to experiment with the model.

Type: front end demonstrator, qualitative model

Causal Decision Diagram (CDD) showing how a building manager might choose how to keep people safe in the midst of a pandemic

This CDD shows levers (yellow) and externals (red) on the left, outcomes on the right, and a CDD structure in between. Dependency links are labeled in some cases with different kinds of technology that supports forward simulation. Contact us to learn more about this decision model, or read about it in the Decision Intelligence Handbook.

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