登录查看更多内容

Last updated on 2024年6月9日

全部

What are the top data analytics platforms for optimizing supply chain operations?

由人工智能和领英社区提供技术支持

In the fast-paced world of supply chain management, leveraging data analytics is crucial for optimizing operations. Data analytics platforms help in forecasting demand, managing inventory, and ensuring efficient logistics. These platforms process large volumes of data to provide insights that can lead to cost reduction, improved customer service, and increased agility in the supply chain. Understanding which platforms can best serve your supply chain needs is key to staying competitive in today's market.

本文章的要点总结

Predictive analytics:

This approach to data analysis uses historical data to forecast future trends and demands, allowing you to proactively adjust your supply chain strategies.
AI-driven insights:

Artificial intelligence in supply chain analytics identifies improvement areas by analyzing existing data, leading to cost-effective and efficient operations.

本摘要由 AI 和以下专家提供支持

Kunle IJAYA

Monitoring and Evaluation Officer @…
Padmanaban Srinivasan

Scientist at NATIONAL INSTITUTE OF…

1 Core Features

When exploring data analytics platforms for supply chain optimization, look for core features that address real-time data processing, predictive analytics, and integration capabilities. Real-time data processing allows for immediate insights into supply chain activities, enabling quick decision-making. Predictive analytics use historical data to forecast future demand and identify potential disruptions. Integration capabilities ensure that the platform can seamlessly connect with existing systems, such as Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) software, to consolidate data for a comprehensive analysis.

添加您的观点

Kunle IJAYA

Monitoring and Evaluation Officer @ World Health Organization | Data Analytics
举报内容
Deloitte Supply Chain Solutions: Known for its predictive analytics capabilities, this platform helps supply chain managers make strategic decisions based on real-time data. ThroughPut AI: This AI-powered supply chain intelligence software leverages existing data to diagnose improvements within the supply chain, providing real-time insights and simulations for root cause analysis. SAP Supply Chain Analytics Software: A robust platform that provides real-time visibility, predictive analytics, and scenario planning to enhance supply chain efficiency and decision-making. Tableau: A data visualization platform that helps supply chain professionals analyze and present complex data to inform strategic decisions.

已翻译

赞
Padmanaban Srinivasan

Scientist at NATIONAL INSTITUTE OF RESEARCH IN TUBERCULOSIS (NIRT), ICMR, CHENNAI-31
举报内容
Supply chain analytics software combines powerful algorithms, data, and the latest technologies like Artificial Intelligence and Machine Learning to address the most elusive challenges in the supply chain right now – visibility and control. Think of supply chain analytics as your strategic advantage, like catching that perfect wave early in the surfing game. In the ever-changing business landscape, those who get in on the action before the crowd can claim a competitive edge. And that’s precisely what’s on the horizon for supply chain analytics. Given that the supply chain is an industry characterized by constant flux, surprises, and an intricate web of moving parts – supply chain analytics steps in as the all-powerful enabler.

已翻译

赞
Prashant Bhadauria

CISCP/CISCM | Supply Chain Management | Strategy & Operations Consulting | Digital Transformation | Supply Chain Analytics | Gen AI Enthusiast
举报内容
There are plethora of options when we think about Data Anlaytics tools to optimize with Supply Chains. It all depends on the kind of problem you are trying to solve. The tool can be as simple as MS Excel to advanced Data Anlaytics suites that integrate with ERPs, WMSs, CRMs etc. One needs to identify the problem and THEN try to fit the tool which meets their needs the best

已翻译

赞
Sahar Ejaz

Data Analyst | UX Designer
举报内容
From my experience, optimising supply chain operations requires leveraging top data analytics platforms. Tableau excels in data visualisation, creating interactive dashboards with deep performance insights. SAP Analytics Cloud offers seamless integration with SAP products for comprehensive analysis and real-time decisions. IBM Watson Supply Chain Insights provides AI-driven analytics to predict disruptions and optimise operations. Microsoft Power BI is user-friendly with strong Microsoft integration for detailed reporting. Qlik Sense features associative data indexing, enabling exploration of data relationships. Together, these platforms enhance efficiency and effectiveness in supply chain management.

已翻译

赞
Zia Ibn Hasan

Digital Marketer | Data Analyst | R | Content Creator | #Opentowork
举报内容
In my overall journey, I'd like to say that when exploring data analytics platforms for supply chain optimization, look for core features that address real-time data processing, predictive analytics, and integration capabilities. Real-time processing enables quick decision-making. Predictive analytics forecast future demand and identify disruptions. Integration with ERP and CRM systems consolidates data for comprehensive analysis. ????

已翻译

赞

加载更多内容

2 Usability Concerns

Ease of use is a critical factor when selecting a data analytics platform. You want a user interface that is intuitive and doesn't require extensive training to navigate. Platforms that offer customizable dashboards and visualizations empower teams to access and interpret data without needing specialized skills. Additionally, consider the level of customer support provided, as responsive technical assistance can significantly reduce downtime and enhance user experience.

添加您的观点

Zia Ibn Hasan

Digital Marketer | Data Analyst | R | Content Creator | #Opentowork
举报内容
In my overall journey, I'd like to say that: 1. **Prioritize Ease of Use**: Choose a data analytics platform with an intuitive interface. It should be easy to navigate without extensive training. 2. **Customizable Dashboards**: Look for platforms offering customizable dashboards and visualizations. They empower teams to access and interpret data effortlessly. 3. **Responsive Support Matters**: Consider the level of customer support provided. Responsive technical assistance reduces downtime and enhances user experience.??

已翻译

赞

3 Scalability Potential

As your business grows, so does the volume of data and the complexity of your supply chain. A scalable data analytics platform can handle increased data loads and more complex analyses without compromising performance. This means the platform should offer flexible storage options and computing power to accommodate future growth. It's also beneficial if the platform can adapt to new data sources and emerging technologies to maintain its effectiveness over time.

添加您的观点

Priyanka Kalpattu Vasudevan

Senior Logistics Consultant @ Cardinal Health | Designing healthcare supply chain
举报内容
Choosing the right data analytics platform is crucial for supply chain optimization. For instance, SAP Analytics Cloud offers robust capabilities in data visualization and predictive analytics. Tableau provides intuitive interface and powerful analytics features. IBM Watson Analytics excels in AI-driven insights, while Oracle Analytics Cloud offers comprehensive solutions. Investing in a scalable platform ensures adaptability to evolving market dynamics and drives sustainable growth.

已翻译

赞
Zia Ibn Hasan

Digital Marketer | Data Analyst | R | Content Creator | #Opentowork
举报内容
In my overall journey, I'd like to say that: 1. Scalable data analytics platforms are crucial for growing businesses ??. 2. Look for platforms with flexible storage and computing power ??. 3. Adaptability to new data sources and tech ensures long-term effectiveness ??. 4. Prioritize platforms that can handle increased data loads and complex analyses without performance issues ??.

已翻译

赞

4 Security Measures

Data security is paramount, especially when dealing with sensitive supply chain information. A top-notch platform must have robust security measures in place, such as encryption, access controls, and regular security audits. These features protect against data breaches and ensure compliance with industry regulations. Moreover, consider the platform's data backup and recovery protocols to safeguard against data loss in the event of a system failure or cyberattack.

添加您的观点

5 Analytical Depth

The depth of analysis provided by a data analytics platform can be a game-changer for supply chain operations. Look for platforms that offer a range of analytical tools, including descriptive, diagnostic, predictive, and prescriptive analytics. Descriptive analytics help you understand what has happened in your supply chain, while diagnostic analytics focus on why it happened. Predictive analytics forecast what might happen, and prescriptive analytics suggest actions to achieve desired outcomes.

添加您的观点

Yogabalaji G

Google & IBM Certified Data Enthusiast ?? Padma Shri Award Nominee ?? Data for Good Mentor ?? Google Certified PM Professional ?? Crossroads Emerging Leader ?? Honarary Doctorate in Social Innovation ?? UNESCO Awardee
举报内容
SAS Viya Supply Chain Analytics: Offers a comprehensive suite of analytics tools tailored for supply chain management. Provides advanced capabilities for forecasting, risk management, and optimization. Oracle Analytics Cloud: A cloud-based platform with robust data visualization and machine learning functionalities. Enables real-time supply chain monitoring and predictive analytics. Logility Voyager Solutions: Focuses on supply chain visibility and planning. Offers features for demand forecasting, inventory optimization, and transportation management.

已翻译

赞

6 Integration Ecosystem

A platform's ability to integrate with other tools and services is crucial for a holistic approach to supply chain management. The best data analytics platforms offer APIs (Application Programming Interfaces) and connectors for easy integration with various data sources, third-party applications, and IoT (Internet of Things) devices. This interoperability facilitates the flow of information across different areas of the supply chain, ensuring that all stakeholders have access to relevant, actionable insights.

添加您的观点

加载更多内容

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

添加您的观点

Data Analytics

+ 关注

给文章评分

我们借助人工智能创建了此文章。您认为这篇文章怎么样？

很棒不太好

举报此文章

What are the top data analytics platforms for optimizing supply chain operations?

1

2

3

4

5

6

7

1 Core Features

2 Usability Concerns

3 Scalability Potential

4 Security Measures

5 Analytical Depth

6 Integration Ecosystem

7 Here’s what else to consider

Data Analytics

给文章评分

感谢您的反馈

更多Data Analytics相关文章

更多相关阅读内容