Predictive Analytics Consulting
Look ahead.
Understand the uncertainty.
Assess whether your data can support a useful prediction for a business decision. We define the question, review data suitability and compare analytical approaches with a meaningful baseline, explaining assumptions and uncertainty so your team can judge how to use the findings.
Decision definition / Data assessment / Evaluation and interpretation
Somerset West, Cape Town Working globally
A few of the brands we’ve worked with
Start with the decision
A useful prediction
needs a clear purpose.
The value of a prediction depends on the decision it helps someone make. The information available at that point, the quality of the data and the consequences of being wrong all shape the work.
We assess those conditions before recommending an approach, then explain what the results can reasonably tell your team.
Assess the analytical opportunity
From available data
to considered decisions.
A feasibility review may be the useful first phase. Further analysis depends on whether the information and evaluation method can support the question you want to answer.
01
Problem definition
We clarify the decision a prediction would support and when that decision is made. This identifies the information actually available at the time and gives the analysis a concrete purpose.
Decision and prediction brief / Available-information boundary / Evaluation objective
02
Data assessment
We review relevant data for completeness, consistency and suitability for the question. The findings identify gaps and limitations before your team commits to an analytical approach that the information may not support.
Data-quality review / Suitability assessment / Evidence gaps
03
Modelling and evaluation
We compare candidate approaches with an appropriate baseline and assess performance using held-out data where feasible. The evaluation examines whether the approach adds useful information for the decision under review.
Analytical approach comparison / Baseline evaluation / Performance findings
04
Business interpretation
We explain the assumptions, uncertainty and practical limits around the findings. This helps the people responsible for the decision understand how the analysis could contribute and where judgement remains important.
Interpretation of findings / Assumptions and uncertainty / Recommendations for use
Working together
A clear way
to work together.
The people making the decision help define what would be useful. We connect their context to a review of the data and a practical evaluation approach.
01
Understand the context
Discuss what you want to anticipate, the decision involved and the information available today.
02
Plan the project
Agree the feasibility work, data access, evaluation method and responsibilities for interpreting the result.
03
Build together
Assess the data and develop the agreed analysis, reviewing assumptions and limitations with your team.
04
Review what comes next
Discuss what the evaluation establishes and whether further data, refinement or use is justified.
The wider picture
Connect the plan
to the work.
Predictive work depends on dependable measurement and an understanding of the wider business process. Digital analytics can help clarify the data foundations before a predictive approach is considered.
Explore related services
A useful question about the future
Which decision needs
a better view ahead?
Tell us what you want to anticipate and what information you have. We’ll discuss whether predictive analysis is practical and what it could establish.
A 30-minute conversation to explore your priorities and agree the next step. No finished brief needed.