Data as a reusable enterprise product
How stronger data foundations, governance and product thinking can turn fragmented information into a scalable source of decision advantage.
Read articleRelated macro
Analytics, data and decision systems
Turn data, analytics and decision systems into clearer insight, stronger choices and more effective execution.
Discover the macroEditorial overview
Articles
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.
Read articleFocus
Is your data ready for the ambition placed on it?
Readiness depends on whether critical information can support the actual decisions, analytics and AI workloads the enterprise intends to pursue.
What will you do differently if the forecast is right?
Prediction creates business value only when the organisation knows which decisions and actions should change as expected outcomes change.
Strategic challenges
One forecast can hide the decision that matters
Expected outcomes can obscure tail risks, thresholds and alternative conditions that would require a fundamentally different response.
Data complexity compounds quietly
Every new source, transformation and point-to-point integration can increase dependencies faster than the architecture can absorb them.
POV
Alternative data should have to earn its place
If an external signal does not materially improve understanding or prediction, its novelty is irrelevant and its complexity is a cost.
Sector expertise should change the model, not decorate the presentation
If industry knowledge does not alter variables, assumptions or interpretation, the analysis is still generic.
Strategic impact
Domain knowledge improves analytical specification
Understanding the sector helps identify relevant variables, relationships and constraints before statistical methods are applied.
Explanation changes the value of business data
Knowing which variables influence an outcome makes analysis more useful for decisions than simply knowing that the outcome changed.
What we observe
Complex models often answer simple questions badly
We frequently see analytical sophistication increase while the business question, assumptions and intended decision remain poorly defined.
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.