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Data-Driven Supply Chain Strategies for the Evolving Retail Landscape
Customers' shopping behavior has permanently changed due to the pandemic. Online shopping is part of everyday life. Home deliveries and pick-up points are replacing or complementing traditional shop visits. Furthermore, product preferences have shifted, and customers are accustomed to a wider product offering due to past availability issues. These changes have driven retail companies to strengthen their supply chain management. They need to analyze their operations closely and identify cost reduction opportunities.
Leverage data for a competitive advantage in retail supply chain management
Online stores have made it easier for customers to compare different products, features, prices, and associated services. This has led to increased price awareness and intense competition, putting pressure on profit margins. Significant investments are required to adapt store logistics for new needs. It creates pressure to reduce operational costs from every level, from product purchase, to marketing, sales, and delivery.
Tightening competitive situations forces retail companies to have a better and more real-time understanding of how the competitors work and what kind of changes are happening in the product ranges. It is not enough anymore to analyze the data from your own company only.
You have to be able to combine data from different data sources and analyze that data in real-time.
It is not possible to respond to these challenges and build an overall and real-time picture of the situation without a comprehensive use of information systems and centralized data warehouses. Because of this change, retail companies had to put more power on Supply Chain Management, they had to analyze it more carefully and they had to find ways to reduce costs.
Utilizing AI and machine learning for real-time insights in supply chain management
The competitive landscape demands a deeper understanding of competitor strategies and product range changes. Analyzing just your own company's data is no longer sufficient. Retailers need to combine data from various sources and perform real-time analysis.
Managing a large amount of data and analyzing it are demanding and time-consuming tasks if you use traditional data processing methods. That is why retail information systems are first in line when utilizing actively the new possibilities of AI, machine learning, and efficient new data processing methods. When the big picture to be analyzed is getting more and more complicated, only AI and machine learning can allow us to compare countless numbers of different variables at the same time, realize the connections between them, and define exact actions to be used for optimal results on supply chain management and cost optimization.
Learn how you can benefit from selecting the right supply chain management system >
5 benefits of using a comprehensive supply chain management system
The supply chain management system provides you with a holistic view of your entire retail ecosystem. This real-time visibility allows you to:
Gain a unified view: Get a comprehensive overview of your entire store network and online channels, understanding how they operate as a whole.
Track change impact: See how adjustments you make affect both individual functions and the overall performance of your business.
Boost customer satisfaction: Improve customer satisfaction by offering well-targeted assortments, efficiently utilizing store space for a better shopping experience, and maintaining competitive pricing.
Simplify in-store operations: Manage all in-store services within one system, including online store deliveries, shop-in-shop stores, restaurants, cafes, and their material flows. This eliminates unnecessary waste and streamlines processes.
Leverage AI for smarter decisions: Take advantage of artificial intelligence to analyze data and its changes more accurately. AI can generate decision proposals and automate tasks within your retail supply chain management, leading to improved efficiency.
