The use of analytics to deliver greater tangible value is one of the most powerful tools a company has in its arsenal. 幸运的是, organizations already have much of the data they need to support better strategic decision-making, increase organization efficiencies and reduce operational costs – in some cases they just can’t see it.

CFGI’s Data and 分析 (DnA) offering helps clients identify and capture meaningful insights from their data to turn information into a competitive advantage. 我们的DnA团队拥有广泛的行业和技术专长, allowing us to deliver actionable insights and measurable impact for clients by:

  • 将战略愿景与实际成果联系起来.
  • 使用灵活和可伸缩的支持模型来驱动核心计划.
  • Providing ad hoc, deeply transformational and ongoing data and analytics architecture and solutions.

进一步, 我们完全是供应商不可知论者, which enables us to work with our clients’ preferred technologies and platforms to ensure project success. 除了实施和改进工具, 数据和模型, we also focus on building new 功能 to certify that your data and analytics program offers a sustained competitive advantage.



Understanding the difference between data and analytics — and the interconnectedness of these two terms — is paramount for achieving actionable insights.

Data 是基础. 它由定量信息和定性信息组成, 观察, 报告中使用的测量和变量, 推理, 讨论与计算. 没有数据,你就无法获得洞察力.

分析 是动作. 它允许您利用诊断, 描述性的, predictive and prescriptive methodologies to derive actionable insights from data. 工具支持, 分析与解释, analytics provide data-driven discoveries to guide strategic business decisions. Without asking the right questions, you won’t know what kinds of data to capture.  


Data enablement and analytics 功能 are important components of any transformation initiative, 用最有效的策略将DnA与更广泛的, 全公司的目标. 通过将战略愿景与实际结果联系起来, 公司可以更快地推动改进的业务成果, more effective decision-making while evolving into a data-driven and analytics-centric enterprise. 


Creating a truly data-driven company starts with establishing a strong foundation built on an exploration of the untapped value that resides in your data 今天, while at the same time paving the path toward the actionable insights of the future. CFGI’s recommended foundational data ecosystem is composed of six pillars that support continuous data evolution within a company:

Align strategy, culture and 功能 with desired business outcomes

  • 确定哪些数据组件对成功至关重要.
  • Leverage key trends and insights to drive innovation and accelerate change.
  • 促进所需的文化转变,以实现更大的业务影响.
  • 将期望的业务结果与数据驱动的思维方式结合起来.

Support the evolving needs of the business through accurate, trusted data management

  • Drive accountability with agile data governance practices and frameworks.
  • 保护、提升和优化公司价值.
  • Build effective data governance programs to ensure data quality and integrity.
  • Become the single source of truth by establishing the highest standards of ethics and trust.

Deliver best-in-class data architecture and solutions that scale with the business

  • Enable scalable data and analytics infrastructure to flex with the business.
  • Understand the latest trends, and empower teams with the right data and analytics tools.
  • Prioritize investments in information, platforms and solution architecture.
  • Establish master data governance to ensure data quality throughout the company.


  • Construct compelling, interactive dashboards for reporting and analysis.
  • Provide comprehensive flexibility in planning and analytics applications.
  • Enable 功能 for data mining and integrated, cross-functional analysis.
  • Adopt data-driven policies throughout the business without compromising quality, integrity or trust.


对可操作的见解的需求根植于每个职能部门, 角色, process and decision of the business — which means data-driven leaders must understand how to enable their data and operationalize their analytics strategy for the greatest impact. 

Transform data into a perpetual source of value by fueling strategic decisions and actionable insights with powerful analytics, 数据驱动的故事叙述和动态建模

  • Establish, validate and benchmark operating models and business strategies.
  • Enable self-service reporting and analytics to facilitate activity throughout the business.
  • 发现隐藏的模式和趋势.
  • 确保团队能够访问正确的数据和工具.


  • 建立和加强财务和数据模型.
  • Incorporate dynamic variables and “what-if” scenarios to tell a coherent story across the life cycle.
  • 支持兼并和收购, 以及剥离资产的努力, 使用协同识别和捕获模型.
  • Empower teams with centralized reporting and enterprise-wide, self-serviced and actionable insights.
  • 在定义公司范围的需求时探索工具和趋势, 成功部署所需的技能和能力.
  • Understand, measure and qualify the business impact of an advanced analytics program.

Use the right tools, methodologies and best practices for analytics success

  • 了解可用数据的类型, 以及它们的功能, 整个业务的来源和使用.
  • Drive cross-functional collaboration to deliver better, deeper and more impactful operating insights.
  • 实现实时、易于访问的数据 技术堆栈.
  • 简化数据收集、聚合和清理工作.
  • 使用度量阈值激活重复和耗时的任务 亚博电子游戏网站(RPA).
  • Standardize enterprise key performance indicators (KPIs) and reporting to optimize 财务规划和分析(FP&A) 功能.
  • 将分析目标与可用的人才和能力结合起来.
  • 发现, assess and transform operating models while improving business outcomes of strategic initiatives.

An effective data and analytics strategy is crucial for businesses to not only survive — but thrive. 

If you are thinking about transforming your organization through the use of data and analytics, 我们很想听听你的目标和挑战. 电子游戏网站 今天.