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数据治理在转变 CPG 行业中的关键作用

信息技术2024-01-01VMLf***

AI智能总结

Data Governance in Transforming the CPG Industry

Data Governance is a critical framework comprising policies, processes, and standards that ensure high data quality, integrity, and security across an organization. In the CPG industry, where vast amounts of consumer data, supply chain information, and market insights are generated daily, effective Data Governance is indispensable for several reasons.

Key Benefits of Data Governance

Data Quality and Accuracy
- Description: CPG companies deal with intricate supply chains, diverse product portfolios, and numerous customer touchpoints. Reliable data forms the foundation for accurate decision-making, product development, and marketing strategies.
- Impact: Data Governance ensures that the information driving these processes is consistent, accurate, and trustworthy.
Compliance and Risk Mitigation
- Description: With increasing emphasis on data privacy regulations like GDPR and CCPA, CPG companies must adhere to strict compliance standards.
- Impact: Data Governance provides the necessary structure to manage and protect sensitive information, reducing the risk of regulatory fines and reputational damage.
Operational Efficiency
- Description: The CPG industry thrives on agility and responsiveness. Streamlined operations are crucial.
- Impact: Effective Data Governance enhances operational efficiency by providing a clear understanding of data workflows, reducing redundancies, and ensuring that decision-makers have access to the right information at the right time.
Informed Decision-Making
- Description: Data-driven decision-making is the cornerstone of success in the CPG sector.
- Impact: Data Governance ensures that decision-makers have access to relevant, timely, and accurate information, enabling strategic planning, effective resource allocation, and swift responses to market changes.
Maturity, Measurement, Continuous Improvement
- Description: Establishing metrics and maturity levels helps assess the impact and effectiveness of the Data Governance framework.
- Impact: These metrics enable functions to strive towards specific goals or states of maturity, providing a structured pathway for continuous improvement.

The Evolving Role of Data Governance

While traditionally focused on ensuring 'high-quality data' to unlock innovation and drive business success, Data Governance now extends to ensuring end-to-end assurance of data, particularly in the context of consumer experiences. This includes:

Empowering End Consumers: Data Governance serves as a pivotal mechanism through which CPG companies can assure individuals that engaging with and sharing their data will yield personalized value.
Managing AI and Data Applications: Addressing the imperative of managing the surge of AI and the use of data in AI applications.

Key Roles in Data Governance

Data Steward
- Description: Responsible for overseeing the quality, security, and proper use of data.
- Impact: Ensures data is accurate, accessible, and aligned with organizational policies.
Data Custodian
- Description: Tasked with the technical implementation of Data Governance policies.
- Impact: Manages data infrastructure, oversees data storage, and implements security measures to protect sensitive information.
Data Governance Committee
- Description: Comprised of representatives from various departments, responsible for developing and enforcing Data Governance policies.
- Impact: Provides strategic oversight, reviews policy effectiveness, and addresses challenges related to data management.

Foundational Pillars of Data Governance

Data Quality Management
- Description: Ensuring the accuracy, consistency, and reliability of data through measures like data profiling, validation, and cleansing.
Data Security and Privacy
- Description: Implementing measures to safeguard sensitive information, comply with data protection regulations, and protect against unauthorized access.
Data Lifecycle Management
- Description: Managing data from creation to retirement, ensuring its relevance, accuracy, and proper handling throughout its lifecycle.
Metadata Management
- Description: Cataloging and managing metadata to provide context and understanding of data, supporting effective data discovery and utilization.

Support for Data Governance

Data Governance Software
- Description: Specialized software designed to facilitate the implementation of Data Governance policies, automate workflows, and provide insights into data quality and usage.
Training and Education
- Description: Ongoing training programs to educate employees about the importance of Data Governance, their roles within the framework, and best practices for data management.
Consulting Services
- Description: External consultants or experts who provide guidance, conduct assessments, and offer recommendations for optimizing Data Governance strategies.
Documentation and Communication Tools
- Description: Platforms for documenting and communicating Data Governance policies, procedures, and updates to ensure transparency and alignment across the organization.

Conclusion

In the fast-paced and data-rich environment of the CPG industry, Data Governance emerges as a strategic imperative. By ensuring data quality, compliance, operational efficiency, and informed decision-making, Data Governance becomes a catalyst for innovation and sustainable growth. A robust Data Governance framework serves

数据治理在转变CPG行业中的关键作用尽管传统的数据治理角色主要集中在确保“高质量数据”以解锁创新并推动业务成功，但不断变化的数字和AIlandscape已将数据治理的范围扩展到确保端到端的数据保障，尤其是在消费者体验的背景下。除了维护数据完整性，数据治理现在还扩展其功能以赋能终端消费者。它作为关键机制，使消费品公司能够向个人保证，与公司互动并分享数据将获得个性化价值。这一转变也应对了管理人工智能激增及在AI应用中使用数据的迫切需求。数据治理的双重责任不仅在于保障信息质量，还在于成为促进信任和为那些向组织交付数据的人提供定制化利益的催化剂。为什么数据治理对组织如此重要？数据治理是一套框架，包括政策、流程和标准，确保组织内部数据的质量、完整性和安全性。在快消品（CPG）行业中，每天都会产生大量的消费者数据、供应链信息和市场洞察，有效的数据治理对于以下几个原因至关重要。 1.数据质量和准确性：消费品公司应对复杂的供应链、多样的产品组合以及众多的客户接触点。可靠的数据是准确决策、产品研发和营销策略的基础。数据治理确保驱动这些过程的信息是一致、准确且可信赖的。至关重要。有效的数据治理通过提供对数据工作流程的清晰理解、减少冗余并确保决策者能够及时获取所需信息来提升运营效率。 4.知情决策：数据驱动的决策是消费品行业成功的基础。数据治理确保决策者能够获取相关、及时且准确的信息。这进而enables战略规划、有效资源分配以及迅速应对市场变化。 2.合规性和风险缓解：随着对数据隐私法规（如GDPR和CCPA）重视程度的增加，消费品公司需要遵守严格的合规标准。数据治理提供了必要的结构来管理和保护敏感信息，从而降低违规罚款和声誉损害的风险。 3.运营效率：在一个以敏捷性和响应性、简化运营为动力的行业中 5.成熟、计量、持续改进：为了建立对数据治理框架、标准和控制影响与有效性的信心，建立指标和成熟度水平是至关重要的。这些指标使功能能够朝着特定目标或成熟状态努力。成熟度通过数据保护、数据管理以及数据利用等关键维度进行衡量。这种方法不仅确保了对数据治理生态系统进行全面评估，还为持续改进提供了结构化的途径。数据治理的3个关键角色数据治理的四大支柱成功的数据治理依赖于组织内部明确定义的角色和职责。以下是三个关键角色，对于数据治理的有效性至关重要：有效的数据治理建立在四个基础支柱上，每个支柱在创建强大的框架方面都发挥着至关重要的作用： 1.数据管家:数据steward负责监督数据的质量、安全以及恰当使用。他们在确保数据准确、可访问并与组织政策保持一致方面发挥着积极的作用。 ■数据质量管理：确保通过数据profiling、验证和清洗等措施实现数据的准确、一致性和可靠性。 ■数据安全和隐私：实施措施以保护敏感信息、遵守数据保护法规并防止未授权访问。 2.数据托管人：数据托管方负责实施数据治理政策的技术层面。他们管理数据基础设施、监督数据存储，并实施安全措施以保护敏感信息。 ■数据生命周期管理：从创建到退役管理数据，确保其在整个生命周期中的相关性、准确性和适当的处理。 3.数据治理委员会：这个委员会通常由各部门代表组成，负责制定和执行数据治理政策。他们提供战略监督，审查 ■元数据管理：cataloging和管理元数据以提供数据的背政策有效性，并解决任何与数据管理相关的问题。景和理解，支持有效的数据发现和利用。什么是数据治理支持? 数据治理支持指的是帮助组织实施和维护有效数据治理实践的资源、工具和技术。这包括： 1.数据治理软件：专为实施数据治理政策、自动化工作流程以及提供数据质量和使用情况洞察而设计的专项软件。 2.培训和教育：持续开展培训项目，教育员工关于数据治理的重要性、他们在框架中的角色以及数据管理的最佳实践。 3.咨询服务：外部咨询顾问或专家为优化数据治理策略提供指导、开展评估并提出建议。 5.文档和通信工具：用于记录和沟通数据治理政策、程序及更新的平台，以确保组织内部的透明度和一致性。 Conclusion 在快节奏且数据丰富的消费品行业（CPG）环境中，数据治理成为一种战略性的紧迫需求。通过确保数据质量、合规性、运营效率以及基于数据的决策制定，数据治理成为推动创新和可持续增长的催化剂。当消费品公司navigating复杂的数字景观时，一个坚实的数据治理框架充当着指南针的角色，引领它们在不断变化的市场中取得成功。与作者联系如果你希望获得关于导航消费品数字landscape复杂性的指导或讨论，请联系YannGautier，全球消费品行业负责人，VML。 YannGautier 全球行业领先-CPGVMLyan.gautier@vml.com 关于VML VML是一家领先的创意公司，结合品牌体验、客户体验和商业活动，创造连接的品牌以推动增长。VML以其为宝洁、高露洁-棕榄、戴尔、福特、英特尔、微软、雀巢、可口可乐公司和温迪快餐等蓝筹客户合作伙伴提供的创新且获奖的工作而闻名。该机构因其在ForresterWave™报告中被列为商业服务、全球数字体验服务、全球营销服务以及最近的营销测量与优化领域的“领导者”而受到认可。VML的全球网络由分布在60多个市场的30,000名才华横溢的人才驱动，主要办事处位于堪萨斯城、纽约、底特律、伦敦、圣保罗、上海、新加坡和悉尼。 VML是WPP代理机构(NYSE:WPP)。有关更多信息，请访问www.vml.com，并跟随Instagram,LinkedIn,andX.#WeAreVML 与我们联系 T:+44(0)2038580061 E:yan.gautier@vml.com

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