Data is the new oil. As I write this on a humid July day in New York City, a heat wave is blowing in from the west. But that’s not what’s making me indoors. What I’m really here to discuss is all of the data that is being generated by our global supply chains and how it’s reshaping the way we do business.
This data has the potential to transform every industry from manufacturing to agriculture and everything between.
What is Supply Chain Management?
In an increasingly data-driven business world, supply chain management is an important part of almost every company’s operation. Companies are collecting vast amounts of data about their supply chain partners, customers, and their products. They’re analyzing this data to make sure things are running smoothly, and they’re making more informed purchasing decisions as a result.
The supply chain is like a giant web of interconnected boxes. Every time a box is filled with products, that entire web is being indexed, or “indexed and searched,” in the supply chain system. Every product that comes into contact with that web of boxes is “indexed,” meaning that a computer uses that data to create a profile that identifies that product as coming from a specific factory or supplier.
Having this level of insight into the movement of goods allows companies to spot problems almost before they occur. For example, a manufacturer might notice that 74% of their merchandise is being lost in the supply chain. By using big data analysis, they can identify the causes of this problem and come up with ways to prevent it in the future.
The Need for Data in the Modern Supply Chain
No matter how technology is used, data is always going to be used to make decision. Before companies collect data from their supply chain partners, they have to ask themselves: “What does the data tell me?” This is the first step in analyzing data and making decisions based on facts.
After this, companies have to put the data into context. This context is what data scientists call “shininess,” or the level of scrutiny a company must apply to the data. Companies are free to ignore data that isn’t shiny enough to be interesting, but they should pay attention to data that is.
At the same time, companies shouldn’t rely on shiny data to make decisions. They should use data that is fully understood and has been validated. Data is just data, and it can be used in many different ways. Companies should use the data they collect to inform decisions they make on products, service, and employees.
Cloud and Big Data – What’s the Difference?
While big data may sound like a magic bullet for all of the ills of the business world, it can actually have the opposite effect. Big data may produce lots of data, but if the way that data is collected, stored, and analyzed is substandard, then the information produced by big data is of very little value.
For example, if a manufacturer has a lot of inventory that they want to keep track of but don’t have the staff to monitor, they could try using big data to track inventory transactions across dozens of different departments within the company. Unfortunately, this solution only works well if each department records the same data. If data is fragmented or incomplete, then this solution falls apart.
Who Will Use Big Data?
Many companies are using big data to make purchasing decisions that include forged signatures, stolen goods, and other nefarious activities. If a company discovers that their big data is being misused, they have the ability to revoke the trustworthiness of every single supplier through a process called “black listed” goods.
This actually happened to Toys R Us in 2017, when the retailer discovered that the data it was using to blacklist certain toys was being used by other retailers to order toys that were actually under fire from the US Consumer Product Safety Commission.
Benefits of Big Data in the Supply Chain
Big data is not only beneficial for companies that collect it, but for everyone involved in the supply chain. For example, in order to reduce the risk of robbery or physical violence, manufacturers often use “injection security” to keep their products from being tampered with.
This is a fancy term for using injection-molded parts to secure toys and other goods in the supply chain. In addition to security, big data can also be used to improve the customer experience. For example, the European Commission is currently beta-testing a new online platform that will let customers check the safety and quality of products on the internet without visiting a store or having to pay for it.
Using Big Data to Improve Customer Experience
Big data can also be used to make buying decisions that improve the customer experience. For example, companies are increasingly using big data to show consumers what other people are buying. This allows companies to personalize their offers, guides, and websites, making them more engaging and relevant to the customer.
This also has the potential to free up customer service resources that could be used to support more urgent issues.
With so much data now being generated by our global supply chains, businesses have a multitude of ways to analyze it. These analyses range from product identification to supplier due diligence. By conducting analyses in real time, businesses can make informed purchasing decisions that are based on the most up-to-date data.
This can help businesses avoid costly mistakes and save time and money. Big data is only as valuable as the data that goes into it. In order to be most valuable, companies must collect data like there’s no tomorrow. Then they must analyze that data and make informed, judicious purchasing decisions based on facts.