Insight
A four part series on the significant opportunities big data provides to increase agility, efficiency and customer-centricity in supply chains.
More than ever before, organizations are faced with streams of data flooding in from various channels at an accelerating rate. Data overwhelm can hamper an organization’s ability to keep up with data inflows and derive valuable insights.
It is becoming increasingly apparent that supply chains must learn to harness the power of the data sources that benefit it significantly. Leveraging the advantages of advanced analytics, supply chains can become more responsive, demand-driven and customer-centric.
Competitive dynamics are quickly shifting towards having capability to mine and analyze real-time data.
Yatish Desai, Managing Director, Supply Chain and Operations Advisory, KPMG
In our four-part big data series for supply chains, we aim to present an in-depth exploration of the world of big data and the significant opportunities it provides to increase agility and efficiency.
Part 1: Differentiating big and small data, and how to avoid paralysis by analysis
In part one, we discuss key concepts, issues, and applications of big data principles in supply chains.
Read it to gain insight on:
- big versus small data
- how to avoid paralysis by analysis in your supply chain
- how big data is being applied in supply chain operations
- identifying value-creating big data sources in supply chains
- capabilities of future big data practitioners.
Part 2: The main tools, platforms and methods currently used to analyze large portions of data
The nature of big data calls for a multi-disciplinary approach, spanning skills and expertise in computer science, applied mathematics, statistical analysis and economics to faciitate the analysis of large and various sets of data. Current tools and techniques developed for this are abundant and some even context-specific.
Read part two to gain insight on:
- big data enablement in your supply chain
- analytic techniques to best serve your data
- a case study of advanced analytics in retail forecasting.
Part 3: Becoming more agile, responsive, demand-driven and customer-centric
In part three, we investigate supply chains of the future and how we believe they will utilize the power of data to become more agile, responsive, demand-driven and customer-centric. Furthermore, we discuss supply chain risk management and resilience enhancement practices and illustrate how these practices are being used to benefit from big data solutions to deliver more effective operational results.
Read it to gain insight on:
- how big data drives scalable change in supply chains
- how to achieve superior financial and operational performance through embedding big data analytics and capabilities
- the role of big data in assuring global supply chains and support trade
- a case study of supply chain risk modeling.
Part 4: The role of IoT, machine learning and blockchain in transforming supply chains
Manufacturing industries and service sectors alike are increasingly investing in disruptive technologies to enhance their operational efficiencies and improve customer experiences.
Read part four to gain insight on:
- increasing operational efficiency and control through data
- applications for the Internet of Things (IoT) in supply chains
- blockchain for supply chain data security transparency
- the views of Bruce How, Vice President, JDA, on the future of supply chains
- highlights of how DHL applies big data analytics across its clients' global supply chains
- potential roadblocks to big data solutions in your supply chain.
For the progressive supply chains already investing in advancing their data and analytics capabilities, KPMG sees a bright future. For the supply chains yet to embrace the power of big data, we encourage them to consider the significant contributions it can make in achieving excellence in supply chain management.
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