If you don’t stay on top of your supply chain management, you’re leaving your business open to numerous potential problems.
An issue with just one cog in your supply chain can affect the rest of the chain. That can cause delays and unforeseen expensive costs, and lower client and customer satisfaction.
On the other hand, when you use data analytics to access useful information, inspect each element of your supply chain, and predict possible outcomes, you can make much more informed decisions to ensure your supply chain, from the sourcing of raw materials to getting products to end customers, is managed in the best way.
On the surface, data analytics is simple. You need to access data about each component of your supply chain to identify current and potential problems. You can then take steps to manage the supply chain better and gain better results.
But if you look at data for each component separately, such as data about your manufacturer or data about your shipping company, you won’t be able to gain an overall picture. To manage the supply chain better, it’s crucial that you correlate all of the information.
When you use advanced data analytics, you can better understand your supply chain. You’ll gain a broader range of in-depth information to help you make your supply processes more effective and come up with more strategic decisions.
In turn, that means you can improve key metrics, keep your inventory balanced, and gain more value from your assets.
When you access advanced data analytics, you not only gain a clear picture of the current state of your supply chain. You are also able to predict future trends and demands.
When you use supply chain data analytics to access demand forecasts and trends, you can better predict customer demand and potential disruptions to the supply chain.
That enables you to get better control over your operational costs and gain a competitive edge.
Basically, you can produce or store fewer items during times when demand for your product is low and produce or store more when the demand is high.
Although businesses have been adapting to incoming changes in demand for a long time, when data analytics is employed, you can take things a step further.
Predictive analytics use machine learning to foresee changes, helping you to gain more accurate insights in comparison to historical data analysis methods, such as using a simple spreadsheet.
Furthermore, modern data analytics enable you to access real-time data, which means you can reveal trends as they develop.
Businesses around the world realized just how important data analytics is for successful supply chain management after the lockdowns were imposed in 2020 as a result of the Covid-19 pandemic.
While no one could have predicted the pandemic and the chaos it would cause, businesses that were ready with backup plans for their supply chains were able to navigate the difficult situation better.
Solutions could be as simple as having more than one supplier to ensure that, when problems happen with one supplier, you can still use another to get products to your end customers.
Without data analytics, it is far less easy to prepare for emergencies that affect your supply chain. When you use data analytics to make predictions and help you be prepared for disruptions, interruptions, and emergencies that affect the supply chain, you can take the right steps to manage you