Business Intelligence | Alternative Path

What This Practice Covers

The reporting environment senior teams actually use.

Business Intelligence covers the disciplines that make leadership decisions defensible: executive and board reporting, operating dashboards across the business, reporting automation, embedded analytics for software firms, and ongoing BI managed services. Every piece of this practice is designed around one question: what decisions does the senior team need to make, and what is the most trustworthy information environment we can build to support them? We start with the decisions. The dashboards follow.

Executive & Board Reporting

Structured reporting designed for the highest-stakes audiences in the firm: the executive team, the board, and (for asset managers) the LP base.

Coverage: Monthly operating reviews. Quarterly board materials. Annual reporting cycles. Single source of truth across previously divergent reporting tracks. Definitional consistency on the metrics leadership actually uses.
Engagement shapes: Reporting cadence design, metric framework authorship, end-to-end ownership of board reporting cycles, partnership with the CFO or COO on what to report and how.

Operating Dashboards

Decision-ready dashboards across the business domains where executive teams have ongoing questions: revenue, sales, operations, finance, product.

Coverage: Custom dashboard and reporting build. Self-service reporting environments. Performance tuning. The data-modelling discipline that sits beneath every credible dashboard.
Tooling: Vendor-neutral by design. Tableau, Power BI, Looker, ThoughtSpot, and open-source alternatives, anchored to your team, your data, and your budget.

Reporting Automation

The replacement of manual reporting workflows with automated, audit-trailed pipelines that compress cycle time and remove human error from the reporting process.

Coverage: Finance, operations, and revenue reporting cadences. Audit-trail design for compliance and review. Integration with the underlying data platform. Continuous improvement of the automation surface as new reports are added.
Engagement shapes: Project-based automation of a defined reporting cycle (typically monthly close, board reporting, or investor reporting). Managed services for ongoing report maintenance and new build requests.

Embedded Analytics

For software firms, the design and build of customer-facing analytics surfaces that turn your product's data into a feature.

Coverage: Customer-facing dashboards inside the product. Self-service analytics for end users. Performance and scale considerations for embedded surfaces. Integration with the data pipeline that feeds them.
Engagement shapes: Project-based build of embedded analytics for a SaaS product. Ongoing maintenance and extension of the analytics surface as the product evolves.

BI Managed Services

Ongoing ownership of the BI function, designed for organisations where the analytical environment is now business-critical and needs to be operated to a service-level standard.

Coverage: Dashboard maintenance. New build requests against an agreed backlog. Performance tuning. Continuous improvement of the data-modelling layer. Quarterly capability reviews with the senior data or finance leadership.

Strategic Counsel

Reporting strategy before reporting build.

The most expensive BI investments are the ones built before the strategic question is settled. The Consulting Practice partners with senior leaders on the questions that determine whether a BI environment changes decisions or simply produces dashboards.

Reporting & Analytics Diagnostic

An assessment of where decisions are being made today, what information they rest on, and where the analytical environment is failing to support them. Output: a prioritised roadmap.

Executive & Board Reporting Design

Structured design of the reporting cadence and information architecture for senior leadership, including the metric definition framework and lineage documentation that make the system defensible.

BI Platform & Tooling Strategy

Vendor-neutral assessment of the BI tooling landscape, anchored to your team, your data, and your budget. We do not resell tools. We do not take referral fees.

Outcomes

Outcomes our clients see.

Monthly reporting cycle time reduced from days to hours

Single source of truth across functions previously running parallel reporting tracks

Executive reporting confidence (measured by leadership reliance on the environment) meaningfully increased

Definitional consistency across previously divergent metrics

BI function shifted from request-response to insight-generation

Case Studies

The work, in practice.

Business Intelligence engagements often pair with Data Ops, because trustworthy reporting depends on a trustworthy data layer. Two engagements illustrate the practice.

Modern Data Platform & BI for a Global Asset Manager

Re-engineering of the firm's data and analytics layer, including ETL development on SQL, Python, and Pandas, cloud-based data warehouse design (Redshift, Snowflake), and OLAP and reporting-ready data modelling for executive and portfolio analytics.

See case study

Alternative Data Operations for a Data-First Hedge Fund

Beyond the alternative-data engineering work, the engagement includes custom SQL-based deliverables, reports, and enriched data products for investment teams, plus KPI and QA methodology design that sits inside the BI discipline.

See case study

Pairs Well With

Where this practice connects.

Data Ops

BI is only as trustworthy as the data layer beneath it. Most BI engagements draw on Data Ops capacity directly.

Finance

When the BI work is in service of CFO-level reporting, fund reporting, or management reporting cycles.

Consulting Practice

When a reporting strategy or metric framework decision precedes the build.

Decision-grade information, designed for executives.