Like our two previous infographics (we’ve reposted those below this article & if you click each one it will go to the respective article), this article continues to examine the American manufacturing industry. This article will focus on the proliferation of manufacturing data available in the industry, and how this data can improve business decisions.
A growing trend across all industries has been the application of big data, with the use of algorithms and the hiring of data scientists becoming commonplace. As businesses collect and store an ever-increasing amount of data, the algorithms required to make sense of this data will become even more valuable. This is due to the fact that algorithms can take any number of factors into account and provide unbiased insights into variation.
In order for manufacturing data to be used in the decision-making process, companies must ensure that they are using high-quality data in their analysis. Prudent companies should utilize a process for correcting, and removing, errors and inaccuracies from data sets as well as addressing any recurring data issues. This process is referred to as ‘data cleansing.’ Once your data is clean, the true impact of algorithms can be felt, as algorithms “make it easier for us to see the invisible” says Jim McGinness, regional head of Panalpina.
While many businesses embrace data analytics as a valuable, strategic asset, others are unsure of how analytics can transform their processes. Looking at the manufacturing industry, manufacturing data can be used to improve business decisions. For example, choosing which suppliers are the best, most valuable partners. Currently, when managers look to work with suppliers, they have many choices available, but not a lot of information about these choices. This leads managers to select suppliers on a host of factors that may not best align with their business needs. Managers need a variety of choices, as well as unbiased information to make the best business decisions.
Data analysis is the key to unlocking valuable information that can improve business decisions. However, it is not always clear which manufacturing data to collect and examine. We’ve provided some examples below of useful data to collect when evaluating a new supplier. It’s important to remember the data doesn’t have to be complex, but rather should provide a holistic view of your supplier.
First, it’s important to make sure the supplier you’re evaluating is capable of meeting your needs. This means collecting data on their pricing options, understanding their work schedule and future projects, and ensuring they have the necessary equipment and personnel. You can’t work with a supplier that isn’t capable of meeting your business’ needs. Therefore, it’s crucial to collect and analyze this data before choosing future suppliers.
Next, you need to ensure your potential supplier is reliable. Examine any available safety and financial data. What is their safety record, and do they have appropriate insurance coverage? Based on their financial data, what percentage of their revenue is derived from your business? It’s never smart to be too large of a piece in another business. Finally, collect any information you can from references or recommendations as to whether the potential supplier will be a good fit for your business.
Finally, assess your future supplier on the factors that will make them a valuable addition to your business. What technological capabilities do they have? Are they leading the way with cutting-edge machinery, software, or processes? How is their customer service? Will working with this potential supplier in the future cause you headaches or be a pleasant experience?
In conclusion, the amount of data available across all industries is growing at a staggering rate. The American manufacturing industry is no exception. With high volumes of manufacturing data available, managers can now unlock valuable information when making important business decisions.
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