By: Kapil Nagpal | February 08, 2023 | Supply Chain | Analytics
In today's fast-paced business world, companies face a complex network of suppliers, partners, and customers that need to work together to deliver goods and services to consumers. Supply chain management (SCM) has become a critical area of focus for businesses that want to increase efficiency, reduce costs, and enhance the customer experience. To achieve these goals, companies are leveraging data and analytics to optimize their supply chains and make better decisions.
What is the role of data and analytics in supply chain management?
Supply chain data refers to the vast amounts of information generated by the various components of a supply chain, such as suppliers, transportation, warehousing, and distribution. This data can include information on inventory levels, production schedules, shipping times, and customer orders. Analytics is the process of analyzing this data to identify patterns, trends, and insights that can help organizations make informed decisions.
Supply chain data and analytics play a crucial role in helping companies make better decisions about their operations.
For example, using data to track inventory levels can help organizations identify areas where they need to improve their stock management processes. Analytics can also help companies understand their customers' behavior and preferences, allowing them to tailor their offerings and improve customer satisfaction.
In addition, supply chain data and analytics can help companies identify bottlenecks and inefficiencies in their operations.
For example, they can help identify areas where there are long wait times or high levels of waste, allowing organizations to make changes that improve the efficiency of their supply chain processes.
How do analytics help companies make better decisions?
There are many different ways that companies use supply chain data and analytics to optimize their operations. Some of the most common applications include:
Inventory Management: Companies use data and analytics to track inventory levels, predict future demand, and manage stock levels to ensure they have the right products in the right place at the right time.
Logistics and Transportation: Analytics can be used to optimize the routing of shipments, track delivery times, and identify areas where transportation processes can be improved.
Customer Relationship Management: Supply chain data can be used to better understand customers' behavior and preferences, allowing companies to tailor their offerings and improve customer satisfaction.
Supply Chain Risk Management: Companies can use data and analytics to identify potential risks in their supply chain, such as disruptions due to natural disasters or supply chain disruptions. This allows organizations to proactively mitigate these risks and ensure business continuity.
While the volume of data generated by supply chains continues to grow, the role of storytelling in supply chain management is critical to make informed decisions. There are situations where less is more.
How much data is sufficient to tell a meaningful story about your supply chain?
The balancing act: The amount of data required to generate meaningful supply chain analytics can vary depending on the specific business needs and goals. The generally held notion is that the more data that is available, the more accurate and meaningful the analytics will be. But how much data is sufficient?
For example, if a company wants to track inventory levels and optimize stock management processes, a larger dataset of inventory data would be necessary to generate meaningful insights. This would allow the company to track inventory levels over a longer period of time and identify trends and patterns that may not be immediately visible with a smaller dataset.
On the other hand, if the company wants to analyze logistics and transportation processes, a smaller dataset of delivery times and shipment routing information may be sufficient to generate meaningful insights.
Ultimately, the amount of data needed to generate meaningful supply chain analytics will depend on the complexity of the supply chain, the specific goals and objectives of the analysis, and the accuracy and granularity of the data. Generally, companies try to gather as much data as possible to increase the chances of generating accurate and actionable insights. While this is one approach, it does not factor in the cost of not making timely decisions.
Hence, we recommend that our clients start with relatively small amounts of relevant and high-quality data to start telling a story. We follow an incremental approach so that our clients can see the benefits sooner. Perfection is the enemy of good in this case.
How we help clients find a balance between data and storytelling
Learn how you can transform your analytics with Laminar for Business to tell meaningful stories about your business and get actionable insights. We build business dashboards that bring Fortune 500 best practices to our clients. Our dashboards offer compelling stories and measurable results, disciplined decision-making, and automated reports that help you focus on growing the business.
Learn how we help clients in supply chain & operations.