Defining a Strategic Roadmap for Enterprise-Wide Analytics Transformation

Developed a comprehensive data analytics and BI strategy and roadmap that aligned business priorities, enterprise analytics requirements, and technology architecture, creating a scalable foundation for self-service reporting and data-driven decision-making.

24

Business and IT stakeholders interviewed across global operations

13

Enterprise analytics subject areas identified and designed

3

Implementation phases defined for enterprise analytics transformation

Executive Summary

A leading container leasing company launched a business intelligence initiative to improve reporting, analytics, and decision-making across its global operations. However, fragmented data sources, heavy reliance on IT, and limited cross-functional reporting capabilities created challenges in defining a clear path forward for enterprise analytics adoption.

DiLytics conducted a comprehensive BI Strategy and Roadmap exercise involving executive, business, and IT stakeholders across multiple regions and functions. The engagement defined enterprise analytics requirements, identified key KPIs and reporting needs, designed a scalable data warehouse architecture, evaluated technology options, and developed an analytics strategy roadmap for phased implementation.

The initiative provided a clear analytics vision, reduced implementation risk, aligned BI investments with business priorities, and established the foundation for a successful enterprise-wide analytics transformation.

A leading container leasing company sought to improve reporting, analytics, and decision-making across its global operations but faced challenges due to fragmented data sources and limited reporting capabilities. DiLytics conducted a comprehensive BI Strategy and Roadmap assessment, working with business and IT stakeholders to define analytics requirements, identify key KPIs, design a scalable data architecture, evaluate technology options, and develop a phased implementation plan. The engagement established a clear analytics vision, aligned BI investments with business priorities, reduced implementation risk, and laid the foundation for a successful enterprise-wide analytics transformation.

Submit Your Details to See the Complete Transformation Story 

Transformation Unlocked!

Use the top navigation menu or scroll down to explore the details.

Container Leasing and Fleet Management Analytics

Client Overview

The client is one of the world’s largest intermodal container leasing companies, specializing in the acquisition, leasing, management, and resale of marine cargo containers. With a global fleet exceeding four million twenty-foot equivalent units (TEUs), the company serves customers worldwide and is also a leading reseller of used containers.

Creating a Unified Enterprise Analytics Strategy Across Fragmented Business Systems

Despite launching a business intelligence initiative, the organization continued to face fragmented reporting, siloed operational data, and heavy dependence on IT for business insights. A comprehensive strategy was needed to align business priorities, analytics requirements, and technology investments while reducing implementation risk.

Fragmented Enterprise Data

Fragmented Enterprise Data

Critical data was scattered across multiple systems, limiting cross-functional reporting and enterprise visibility

Heavy Dependence on IT

Heavy Dependence on IT

Business users depended on IT teams for reporting, data access, and analytics, reducing agility and self-service

Limited Cross-Functional Reporting

Limited Cross-Functional Reporting

Disconnected data sources restricted unified reporting across leasing, billing, finance, repairs, and asset management

Lack of a Unified Analytics Roadmap

Lack of a Unified Analytics Roadmap

A structured BI roadmap was needed to align business goals, technology, KPIs, and implementation priorities

Creating a Unified Enterprise Analytics Strategy Across Fragmented Business Systems

Fragmented Enterprise Data

Fragmented Enterprise Data

Critical data was scattered across multiple systems, limiting cross-functional reporting and enterprise visibility

Heavy Dependence on IT

Heavy Dependence on IT

Business users depended on IT teams for reporting, data access, and analytics, reducing agility and self-service

Limited Cross-Functional Reporting

Limited Cross-Functional Reporting

Disconnected data sources restricted unified reporting across leasing, billing, finance, repairs, and asset management

Lack of a Unified Analytics Roadmap

Lack of a Unified Analytics Roadmap

A structured BI roadmap was needed to align business goals, technology, KPIs, and implementation priorities

Enterprise BI Strategy and Roadmap for Scalable Analytics Modernization

DiLytics partnered with the client to conduct a comprehensive Business Intelligence Strategy and Roadmap exercise. The engagement involved executive and stakeholder interviews across multiple business functions and geographies, assessment of existing reporting challenges, identification of enterprise analytics requirements, definition of data warehouse architecture, and development of a phased implementation roadmap for enterprise analytics modernization.

Services Provided
  • Conducted executive, business, and IT stakeholder interviews
  • Assessed existing reporting processes, tools, and analytics challenges
  • Documented enterprise reporting, KPI, metric, and dashboard requirements
  • Defined subject areas, dimensional models, and enterprise data warehouse architecture
  • Evaluated BI, ETL, and data warehouse technology options
  • Developed enterprise analytics strategy and implementation roadmap
  • Provided implementation guidance, sequencing, scope, and cost recommendations
Business Solution

The strategy established analytics requirements across six major business areas:

  • Fleet Operations & Asset Management Analytics: Covering container inventory, utilization, depot operations, repairs, maintenance, storage capacity, and asset performance
  • Leasing & Customer Analytics: Covering lease performance, lease profitability, lease renewals, customer activity, contract management, and customer profitability
  • Sales & Resale Analytics: Covering bookings, opportunities, resale performance, pricing trends, sales effectiveness, and customer purchasing behavior
  • Credit & Risk Analytics: Covering receivables, collections, credit exposure, customer payment behavior, and risk monitoring
  • Financial Performance Analytics: Covering profitability, revenue, costs, depreciation, net operating income, customer operating income, and financial performance
  • Planning & Executive Analytics: Covering enterprise KPIs, performance management, scenario analysis, forecasting, and executive decision support
Technical Solution
  • Assessed data across JD Edwards, TEMS, BATS, FAST, CAPEX, and other operational systems
  • Defined an enterprise data warehouse architecture based on Microsoft SQL Server
  • Designed 13 analytics subject areas and corresponding dimensional models
  • Recommended Microsoft SSIS for data integration and Oracle Analytics for enterprise reporting
  • Defined KPI, metric, hierarchy, security, and metadata standards
  • Developed a three-phase implementation roadmap for enterprise BI adoption

Establishing a Strategic Foundation for Enterprise Analytics Success

The BI Strategy and Roadmap engagement provided a clear vision for enterprise analytics transformation, helping the organization align technology investments with business priorities while reducing implementation risk and enabling future self-service reporting capabilities.

Unified Enterprise Analytics Vision

Established a business-aligned analytics strategy that supported enterprise priorities and operational objectives

Reduced Implementation Risk

Provided a structured business intelligence roadmap and phased implementation approach to guide future BI investments

Enterprise-Wide Reporting Framework

Identified reporting, KPI, and analytics requirements across multiple business functions and operational domains

Scalable Data Architecture

Defined a future-ready enterprise data warehouse architecture as part of a data strategy roadmap designed to support long-term growth

Self-Service Analytics Roadmap

Created a strategy roadmap for reducing IT dependency by enabling business users with self-service reporting capabilities

Informed Technology Investment Decisions

Enabled leadership to make confident decisions regarding technology selection, implementation sequencing, and analytics modernization

Ready to Build Your Enterprise BI Strategy?

Develop a future-ready analytics roadmap that aligns business priorities, technology investments, and enterprise reporting goals while creating a scalable foundation for self-service analytics and data-driven decision-making.