Planning for uncertainty with simulation and optimization
How companies can move beyond point forecasts by combining scenarios, predictive models and optimization to improve decisions under volatile conditions.
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Analytics, data and decision systems
Turn data, analytics and decision systems into clearer insight, stronger choices and more effective execution.
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Articles
From dashboards to decision systems
Why the next frontier in analytics is not more reporting but better decisions�supported by integrated data, explicit decision logic and continuous performance feedback.
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Who is the customer for your data?
A data product becomes meaningful when its consumers, recurring needs and expected outcomes are clearer than the technology used to deliver it.
What is actually driving the number?
Advanced analytics should separate the factors behind performance rather than provide increasingly sophisticated descriptions of the outcome.
Strategic challenges
The best prediction may not produce the best decision
Small improvements in forecast accuracy can matter less than correctly representing operational constraints, costs and available actions.
Enterprises produce data faster than they create information value
Large data estates can continue expanding while important users still recreate datasets and struggle to find reliable information.
POV
Scenarios are not forecasts with different numbers
Their purpose is to challenge the expected future and expose decisions that remain robust when the world develops differently.
A decision model should expose disagreement, not hide it
When stakeholders disagree, the model should reveal whether the difference comes from evidence, assumptions, probabilities or values.
Strategic impact
Shared meaning makes data more reusable
Clear definitions, metadata and relationships allow the same information to travel across systems and use cases without losing context.
New signals can change the analytical picture
Combining external conditions with internal performance can expose relationships that neither dataset makes visible independently.
What we observe
Data roadmaps often start with the technology estate
We frequently see platform replacement prioritised before the business has determined which information capabilities actually need to change.
The model often begins after the decision has been framed badly
We frequently see sophisticated analysis applied to alternatives, objectives or assumptions that were never challenged at the outset.