Collecting data is part of what makes the big players like Google and Facebook so successful. The amount of time that users spend on Facebook declined by 50 million hours a day, according to company founder, Mark Zuckerberg. This could prove problematic for the social media giant, because every lost hour on the platform is a lost opportunity to collect more data about its users. That being said, these companies are not simply collecting data just to possess it. In order to achieve success, they use data intelligently. Artificial intelligence and machine learning play a big role in this context as they present more opportunities to manage data and achieve better results for operational processes. This is also the case with supply chain management; both machine learning and artificial intelligence can help companies make the best use out of the data they are collecting.
Artificial intelligence algorithms are adaptive. Therefore, the results improve as the amount of information available increases. This is why the principle “the more, the better” applies. Corporations, both large and small, are collecting data and feed artificial intelligence with it to train the system and increase their ability to make decisions. The handling of our data by Facebook and Google may raise some concerns on a personal level, but the idea behind the use makes perfect sense.
Procurement on the platform
So, why don´t we use this method – in an assiduous and secure way – to make purchasing processes more reliable, more stable and more lucrative? To realize this vision, an instrument like a digital platform is necessary. A specialized platform can compile data concerning the procurement of raw materials, spare parts or other goods from several companies and gain better results for each of them. Here´s an example: There are big retail and wholesale sectors where every single company deals with similar products and the same questions every day. For example, how many packages of cleaning sponges will the customer order tomorrow?
Well-known forecasting methods work out reliable calculations for the future demand based on historic data. In cases of disruptions, however, these forecasting methods reach their limits. As soon as unknown procurement or stock situations appear – such as new supplier conditions or the rise of e-commerce – forecasting requires more data in order to deliver reliable results. This is where artificial intelligence sets in. We already know that artificial intelligence needs a vast data set to learn how to propose the best decision in a disruptive situation.
For this reason, a procurement-forecasting platform could be a helpful solution. To stay with the example: As soon as more than one wholesaler from the same sector enters his data concerning the demand of cleaning sponges and its sales orders, the algorithm can calculate better results for each of these companies as it knows numerous situations and learns from good or bad decisions. Yet again, the principle applies: the more, the better.
Think bigger – and share
A platform represents one form of data sharing. However, sharing data can consist of several levels. In supply chain management, integrating internal processes as well as stepping into a closer collaboration with suppliers is a growing strategy. The results are extremely efficient: when a supplier gets the information from the wholesalers’ demand plan, they can also plan better. In the end, this leads to a stabilization of the entire supply chain. Nevertheless, there are disruptive situations that come up in operative purchasing and supply chain processes on a regular base. This is where a platform-based business model can lead to safer and more efficient processes.
If you “think bigger” and share your data at such a high level with hundreds or thousands of participants, in addition to implementing innovative technologies such as machine-learning methods, you can attain better results for procurement decisions within your own business operations.
Would you share the procurement information of your business within a digital platform?
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