Business intelligence consulting
Define the decisions, reporting requirements, and tools that should guide your analytics work.
- Business questions and reporting priorities
- Data source and tool assessment
- Analytics roadmap and implementation scope
Data analytics
Turn business data into actionable insights.
Combine business intelligence, predictive analytics, and applied machine learning to understand performance and support planning. Develop reports, forecasts, and models around defined business decisions.
What we do
Analytics for reporting, planning, and decision support.
Define the business question, prepare the relevant data, and select the analytical approach. We develop and validate outputs with assumptions and limitations made clear.
Predictive analytics
Use historical data and models to examine likely outcomes and support planning decisions.
- Data preparation and feature analysis
- Forecasting or prediction models
- Validation and interpretation of results
Prescriptive analytics
Compare possible actions using optimization or simulation around an agreed business decision.
- Decision constraints and objectives
- Scenario analysis and optimization
- Recommendations with assumptions explained
Customer analytics
Examine behavior, purchasing patterns, and engagement to inform product, marketing, and retention decisions.
- Customer segmentation and behavior analysis
- Journey and engagement reporting
- Insights for targeted improvements
Text and sentiment analysis
Find themes and sentiment in text sources such as surveys, reviews, and customer feedback.
- Text preparation and classification
- Theme and sentiment analysis
- Reporting on recurring patterns
Applied machine learning
Develop analytical models for specific tasks, such as recommendations, anomaly detection, or predictive maintenance.
- Task and data assessment
- Model development and validation
- Integration requirements for using results
What you get
Consistent reporting and decision support.
Bring reporting, analysis, and relevant models closer to the decisions your business needs to make.
A shared view of the measures that matter.
Bring relevant data sources and metric definitions together in reports or dashboards that teams can use to understand business performance.
- Prepared data and agreed calculations
- Reports or dashboards around business questions
- Clear metric definitions and refresh guidance
Evidence to support the next business decision.
Examine trends, forecast scenarios, or compare possible actions using assumptions that planning teams can review.
- Analysis grounded in available business data
- Forecasts or scenarios where appropriate
- Findings with assumptions and limitations explained
Validated models for defined analytical tasks.
Use suitable models to explore recommendations, anomalies, sentiment, or other defined tasks, with results checked against the business context.
- Models developed for an agreed analytical task
- Validation and interpretation of results
- Integration requirements for using the outputs
How we work
From business questions to validated analysis.
Agree on the decision and measures, assess data quality, and develop reports or models. Validate the results with your team and define how the outputs will be used and updated.
Define the decision
Agree on the question, the users, and the measures that matter.
Prepare the data
Review sources and resolve the quality issues relevant to the analysis.
Build and validate
Develop reports or models and check results against the business context.
Put insights to use
Walk teams through the outputs and plan updates as needs change.
Why it matters
Make decisions with a consistent view of the data.
Analytics connects business questions to reporting, forecasts, and models that teams can interpret and evaluate.
Decision support
Compare trends and scenarios using documented measures and assumptions.
Operational insights
Analyze bottlenecks, resource use, and performance to prioritize improvements.
Customer understanding
Examine behavior and engagement to inform product, marketing, and retention decisions.
Opportunity identification
Explore market and business patterns to identify areas for further investigation.
Where to start
Choose the decision your data needs to support.
Begin with a reporting gap, a planning question, or an operational decision that needs a clearer view of the data.
Forecast inventory demand
Use sales history and demand patterns to inform stock planning and replenishment.
Understand production bottlenecks
Examine operational data to identify delays, resource constraints, and improvement priorities.
Improve financial planning
Explore trends and forecast scenarios with assumptions that planning teams can review.
Bring reporting into one view
Align data sources and metric definitions so teams can work from consistent reporting.
Questions
Planning your analytics engagement.
Answers about scope, existing systems, and delivery requirements.
What types of data can you analyze?
Structured data from databases, unstructured text, and semi-structured formats such as XML or JSON can all be part of an analytics project. The sources and quality of the data shape the approach.
How do you handle data privacy and compliance?
We plan data access, governance, and handling around the information involved and the requirements that apply to your organization, including relevant data protection obligations.
How is data kept secure?
Security measures can include access controls, encryption, and review of the data flow. The controls are defined for the systems, data, and risks involved in the project.
Which industries can use data analytics?
Analytics can support retail, financial services, healthcare, manufacturing, and other sectors. The questions and available data differ by industry.
What happens after implementation?
Support can include troubleshooting, updates, and optimization as data and business requirements change. The support period and responsibilities are agreed in the engagement scope.
Next steps
Make your data more valuable to the business.
Tell us which decisions you need to support and where the relevant data sits. We can define the reporting or analysis required.