Data Analytics Team Assessment & Transformation Action Plan

Client Context

A fast-growing fintech organization operating at scale relied heavily on analytics to support operations, finance, risk, and strategic decision-making. Despite significant investment in data platforms and reporting, senior leadership observed that analytics outputs were not consistently driving decisions or delivering proportional business value.

The analytics function had evolved organically, resulting in fragmented products, high manual effort, and a growing disconnect between business needs and analytical outputs. Leadership commissioned a data analytics team assessment and transformation plan to reposition analytics as a decision-centric, scalable capability aligned with the company’s growth ambitions.

Key Challenges Identified

Limited Decision Impact

Dashboards and reports were largely descriptive and static, lacking:

• Clear linkage to decision points

• Actionable controls, targets, and alerts

• Differentiation between strategic, tactical, and analytical use cases

This resulted in “noise-heavy” reporting and low stakeholder adoption.

Inefficient Delivery Model

• High share of recurring manual reporting (≈65–70%)

• Debugging dominated the delivery pipeline

• Analytics backlog driven by unclear requirements and rework

The team spent disproportionate time maintaining outputs rather than generating insights.

Fragmented Analytics Landscape

• Inconsistent metric definitions and undocumented methodologies

• Parallel tooling (e.g., Alteryx workflows) increasing technical debt

• Lack of a unified data modeling and instrumentation architecture

Skills & Operating Model Gaps

• No standardized role definitions or skill expectations

• Limited structured learning and knowledge sharing

• Capacity allocation tied to departments rather than project needs

Transformation Objective

To transition the analytics function from report production to decision support, delivering scalable, trusted, and business-aligned analytics products.

The target state emphasized:

• Decision-centric analytics

• Self-served, validated, and noise-free dashboards

• Strong governance, documentation, and validation

• A motivated, skilled analytics squad operating under a clear delivery model

Transformation Approach

The transformation plan was structured around four coordinated pillars: Products, Services, Process, and People, supported by a unified data platform.

Analytics Products – Rebuild

• Full inventory and assessment of existing dashboards and metrics

• Redesign and prioritization of analytics products based on business decision needs

• Creation of a Data Products Manual (DPM) documenting metric definitions, methodologies, use cases, and ownership

• Delivery of standardized tactical scorecards and analytical dashboards

• Validation and enhancement of cost, profitability, and process-performance models

Analytics Services – Revamp

• Introduction of structured stakeholder engagement (monthly satisfaction surveys and cadence meetings)

• Simplified intake and assignment categorization to reduce waste

• Regular analytics release notes highlighting changes, new products, and risks

• Launch of Business Case Support (BCS) services providing prescriptive, decision-oriented analysis

• Periodic insights reports replacing static operational reporting

Analytics Processes – Redesign

• Implementation of time tracking and workload planning to improve transparency and prioritization

• Elimination of redundant manual reporting (target: ≈90%)

• Migration to a single data modeling platform (Snowflake) and retirement of legacy tooling

• Introduction of standardized SOPs for requirements analysis, data validation, and model testing

• Formal documentation of analytics methodologies and conceptual frameworks

People & Capability Development

• Definition of clear role profiles across three analyst levels (Associate, Specialist, Senior)

• Minimum skill expectations across SQL, modeling, and visualization

• Structured internal training and knowledge-sharing sessions

• Individual scorecards to track productivity, skill growth, and contribution

• Shift from fixed departmental assignment to demand-driven capacity allocation

Business Impact

More effective and Scalable Analytics

• Analytics outputs can now support complex strategic, tactical, and operational decisions.

• The analytics team can support growth without linear increases in headcount or technical complexity.

• Analytics evolved from a reactive reporting function into a proactive advisory partner

Higher Productivity & Reduced Waste

• Significant reduction in recurring manual reporting

• Lower debugging backlog through better upfront requirements and validation

• Faster delivery cycles with fewer rework loops

Stronger Governance & Data Integrity

• Standardized metric definitions and validation processes

• Improved auditability and confidence in reported numbers

This analytics assessment and transformation program repositioned the fintech’s analytics function as a decision-centric, scalable capability.

By aligning products, services, processes, and people around clearly articulated business decisions—and grounding execution in strong governance and a unified data platform—the organization laid the foundation for analytics that consistently delivers measurable business value rather than volume-driven outputs.

Deliverable Excerpts (Not Exhaustive)