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The Power of Big Data & Analytics in Supply-Chain Management

Overview

Frequent shocks and disruptions, such as the COVID-19 pandemic and other natural disasters, have a major impact on businesses and tend to expose gaps and vulnerabilities that exist in their global value chain. As a response, leaders across various industries are becoming more aware of their supply-chain processes and are looking to increase resiliency and transparency.

Many organizations are hesitant to invest in digital solutions due to the high cost associated with it. However, integrating digital solutions early on can have long-term and short-term benefits and better prepare organizations and their supply-chains for any disruptions that may occur.

To be successful in today’s hypercompetitive and volatile environment, leaders need to reinvent processes and leverage digital tools to optimize performance. 

Supply-Chain Trends & Challenges

Key trends such as new innovations, shifting consumer demands, evolving business cycles, and the use of big data are reshaping the way supply-chains operate. Leaders must take these into consideration and transform their supply-chains to be more agile, flexible, and resilient to respond and adapt to uncertain environments. Supply-chain resiliency has become the top priority for executives across multiple sectors.

The COVID-19 pandemic highlighted how unprepared businesses were to respond to crises. A study by McKinsey found that 54% of executives surveyed did not have clear visibility into their supply-chain. Lack of visibility due to insufficient data and slow technology adoption amongst other factors can lead to poor decision-making and planning for all stakeholders including manufacturers and retailers.

The use of data and analytics can help overcome these challenges, however, instead of taking a holistic approach, the traditional supply-chain views data in a fragmented manner. This approach prevents stakeholders from determining areas of intersection and neglects the full potential of data analytics on supply-chain management and performance. Often, businesses are left with a large amount of data but lack the capacity to apply it to optimize performance.  

Integrating data analytics, artificial intelligence, and machine learning can help provide more actionable insights to businesses enabling more accurate and timely decisions.

Implications of Big Data

As the world becomes more connected due to the internet and increased adoption of digital devices, a copious amount of data is being produced on a daily basis. It can be challenging for traditional software to process such complex information. Big data solutions are essential to analyze information and determine how it can be applied to various areas of a business to increase efficiency and productivity.

Big data can improve visibility and transparency across the entire supply-chain and enable companies to optimize performance. Through the analysis of big data, executives are able to get a better understanding of consumer preferences and market conditions to create a superior product mix and surpass competitors. Leading fashion brands such as Zara rely on big data and collect and analyze data gathered across thousands of stores to design products that their customers want and will purchase.

Utilizing big data can also enable businesses to offer a more personalized experience and better serve customers. Recently, Amazon gathered a large amount of data on body types and how they evolve over time. This data can be employed by online brands to ensure their customers get correct size and minimize returns.

Big data can have a positive impact on supply-chain management and enable growth. With increased visibility, transparency, and the availability of more accurate information in real-time, stakeholders are able to make better, more informed decisions and take corrective action promptly.

Big Data & Data Analytics in Apparel Industry

Shocks in the environment that impact the supply-chain are a common occurrence and businesses need to be prepared to respond quickly. Technology can play a vital role in how quickly a supply-chain responds and recovers when faced with volatility. Businesses that leverage data across the global value-chain will emerge as leaders while laggards struggle to keep up. A study by McKinsey discovered that 65% of more successful organizations had a clear data strategy that enabled artificial intelligence.

Integrating data and predictive analytics can minimize the damage caused by a shock. During the COVID-19 pandemic, Nike used predictive analytics to decrease production, re-route goods, and reduce prices which put them in a better position than their competitors. Brands are reimagining processes and leveraging data analytics to make key decisions about assortment while offering more personalization to their customers.

Other brands including  Ralph Lauren are integrating predictive analytics into their operations to help determine how changes in factors such as fabric, price, and design are impacting consumer behavior. Based on this information, brands are creating more products that consumers want at a quicker speed and minimizing their risks.

The apparel industry is behind when it comes to leveraging data analytics due to challenges such as poor data quality, dynamic trends, lack of capabilities and a hyper-competitive environment. The apparel industry has not seen the full potential of data analytics due to their fragmented approach. However, analytics can revolutionize the way the industry works by offering more personalization and a tailored assortment for customers. Research conducted by JDA Software discovered that 43% of brands and retailers intended to utilize customer data to create an assortment based on customer preferences.

An integrated and interconnected approach to data analytics can enable brands to create a clear strategy based on customer needs. Retailers utilizing analytics are discovering the benefits. A study by McKinsey found that analytics applications can boost sales and increase earnings by up to 10% and executives will see an increased return on investment.

Advanced analytics can create new insights for businesses and enable better, more informed decision making and improve performance across the value chain.

Conclusion

New technology can transform the way a supply-chain functions and responds to uncertain environments. Businesses need to leverage digital tools and analytics to optimize performance, increase visibility across the supply-chain, and boost top-line and bottom-line growth.

The Power of Big Data & Analytics in Supply-Chain Management
Rijah Mazhar (Product Marketing Executive - Triple Tree Solutions)
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Published 3. May 2021