Data analytics enables people to better understand how their supply chain operates and recognize the source of problems. This information can help companies reduce costs by better targeting areas of their supply chain that need improvement, increasing profits by tracking efficiency, and saving time by uncovering risk.
Understanding Data Analytics
For many businesses, data analytics is the key to understanding their supply chain. In addition, the data analytics process can help companies know where to allocate resources for efficiency, identify vulnerabilities, and better understand customers.
What is Data Analytics?
Data analytics is a toolset and process for extracting meaning from data, typically large data sets. Data analytics usually includes data mining and statistical analysis but can extend to other disciplines, including time series analysis, machine learning, and predictive analytics.
Data Analytics Can Help Improve Your Supply Chain
Data analytics is the key to understanding the supply chain. Inefficiencies, delays, and underperforming parts of the supply chain are made easy to recognize. You have a choice of many powerful analytical tools for this purpose. Blackstone+Cullen prides itself on having a predictive and prescriptive tool in Glimpse which does the heavy lifting with your data to output clear, concise, and actionable analyses giving you competitive advantage.
How Do I Use Data Analytics to Improve My Supply Chain?
As businesses grow, they need to face the impossible task of managing the ever-increasing amount of collected data. Data analysis makes this task more manageable, enabling companies to identify patterns and opportunities to improve productivity. Data analytics tools help to organize and manage the data. The tools make it possible to build data pipelines that extend from ERP systems, ordering systems, the truck dock, and the warehouse floor to management dashboards. These data pipelines help expose all parts of the supply chain and assess performance for each supply chain link in real-time.
With data analytics in place, you don’t have to make changes to every variable in your business to improve supply chain performance and achieve a positive ROI. Instead, you only need to find the variable that most impacts your company’s performance and make changes that deliver the largest supply chain performance improvement.
For example, you may be selling a product that is doing well. However, suppose that the product is only selling well in certain countries. The most important analytics for this company could help identify the countries where this product is most profitable, identify the best-selling channels, and surface the customer characteristics that could help explain sub-par sales in some locales.
Here are some practical ways you might use data analytics:
- Notify your suppliers of the items that are most frequently out of stock on your shelves
- Find out which of your team members are the most productive
- Discover which stores are under-performing and which stores are successful
- Determine the best location for your next store
- Predict stockouts so that you can plan for alternate sources or replacement products
- Identify best-selling replacement products to cover stockouts
- Find out which items you need to put on sale for a higher customer turnout
Data analytics tools have been around for a while now, and they’ve been proving to be quite valuable in various fields – such as supply chain management. For example, businesses like yours can identify and monitor risk factors in their supply chain, such as lead times, demand fluctuations, and production issues. With analytics on hand, you can make better-educated decisions.
Data analytics allow businesses to monitor their supply chain, identify risks or problems in advance, and take corrective measures to ensure the supply chain runs smoothly.
The best way you can use data analytics in supply chain management is to use technology and predictive modeling to identify what to buy, when to buy it, and how much to buy with each order to have an optimal level of inventory.
So What Next?
The data you need to help you with supply chain interruption and disruption recovery planning is available in your systems. To sum up, analytics are easy to assemble, visualize, and interpret with a powerful analytics tool like Glimpse.SX.
In the White Paper we’ll take a deeper dive into the valuable assortment of analytical tools that would help identify significant supply chain dependencies. In addition, we’ll show how we can quickly configure Glimpse.SX tools to gather, cleanse, and transform data from any number of MRP, ERP, CRM, or WMS systems. Intelligent business rules implemented as microservices in the cloud bring data into Glimpse visualizations.