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Data & Analytics (DNA)

Capture Greater Value from Your Data

Data is a valuable resource for any organization, yet it is often underutilized. Frequently, organizations possess the necessary data to support strategic decision-making and enhance operational efficiency, but the challenge lies in unlocking its potential. CFGI’s Data and Analytics (DnA) offering is designed to help clients uncover meaningful insights, turning raw information into a business value.
Our DnA team, armed with extensive industry and technical expertise, delivers actionable insights and measurable impact by:
Moreover, our vendor-agnostic approach allows us to collaborate seamlessly with clients, leveraging their preferred technologies and platforms for project success. Regardless of where your company sits along the maturity model, CFGI’s team can provide a customized solution to fit your business needs.

Empowering Better Decisions, Faster

Data enablement and analytics capabilities are integral to any transformation initiative, seamlessly integrating DnA with broader company-wide goals. By aligning strategic vision with tangible results, companies can enhance business outcomes with faster, more effective decision-making, evolving into a data-driven and analytics-centric enterprise.

Data and Analytics Solution

Embark on a transformative journey to establish a truly data-driven company with CFGI’s recommended foundational data and analytics solutions, built on four pillars:
Data Governance, Organization, and Design: Improve the data quality, integrity, and auditability of data to align a single source of truth across systems – as well as providing structure and policies to support the business.
Process Automation: Automate manual and repetitive processes to drive efficiencies and support data integrity, such as joining files, reconciliations, and financial consolidations

Model Automation: Increase scalability and accuracy of models by automating the model build to drive efficiencies, improve data gathering, and capture scenario-based business drivers.

Dashboards & Analytics: Drive real-time business decisions and support decision-making to understand the business drivers through visualizations, data trend identification, and actionable insights.

Data Governance, Organization, and Design

Support strategic business decision-making through data-driven financial modeling:
  • Data Quality Strategy: Develop processes to support monitoring of data integrity
  • Data Quality Assessment: Assess the current state of the data quality and clean the data
  • Data Lineage: Data source mapping and alignment of disparate sources
  • Master Data Management: Develop centralized repository of data and internal data standards to align a single source of truth across systems
  • Center of Excellence Design and Setup: Establish an operating model supporting people, technology, and processes

Process Automation

  • Data Quality – Profiling & Cleansing: Data quality assessment
  • Data Flow and Transformation: Manipulate and convert data into usable formats/structures
  • Data Curation:
  • Data Integration: Develop a centralized repository of data
  • Automated Reporting: Customized and real-time reporting through process automation

Model Automation

  • Define Requirements and Assess Model: Collaborate with stakeholders to define business requirements
  • Data Transformation & Processing: Extraction of data from disparate sources
  • Refine, Build, and Consolidate: Build model based on stakeholder requirements
  • Predictive Analytics: Layer in statistics and modeling techniques
  • Ongoing Support: Provide ongoing support and training to allow management to maintain model

Dashboard & Analytics

  • Data Governance and Integrity: Data quality assessment and implementing reporting checks
  • Data Transformation and Processing: Extract data from disparate sources
  • Data Warehousing: Develop a centralized repository of data
  • Dashboards and Visualization: Data analytics and KPI development
  • Predictive Analytics: Layer in statistics and modeling techniques

Pain Points

The key pain points help inform which offering can best move our client across the maturity process. As your Data and Analytics capabilities mature, the related service offerings address increasingly complex needs.

Data Governance, Organization, and Design

  • Poor data quality
  • Challenging managing data access 
  • Lack of efficiency with inability to reuse processes 
  • No single source of truth for reporting

Process Automation

  • Completing manual or repetitive Excel tasks
  • Manually consolidating files and risking data loss
  • Slow Excel files that crash often
  • Siloed reporting efficiencies

Model Automation

  • Finance team managing multiple large Excel models
  • Complexity of Excel models impedes accuracy
  • Existing models are not iterative and scalable
  • Models require increasing sophistications (e.g., pipeline processes, validation sets)

Dashboard & Analytics

  • Reports lack real-time or actionable insights
  • Reports are static and not dynamic when new data comes in
  • Lack of trust for business decisions
  • Inferior decision support stemming from inconsistent data across organization

An effective data and analytics strategy is crucial for businesses to not only survive — but thrive. If you are contemplating transforming your organization through the use of data and analytics, we would love to hear about your goals and challenges. Contact us today!

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