In this article we are going to tell 4 of the main advantages of applying techniques based on Artificial Intelligence and Advanced Data Analytics in business operations and processes.
Regardless of the sector, organizations currently have a great opportunity to use their data sets to extract knowledge and value from them, and make better business decisions. For example, using Machine Learning models (predictive analytics) to know future demand and plan their resources based on it.
According to a recent McKinsey study, 55% of companies use AI in at least one function, and 27% attribute at least 5% of gross profits to this technology, much of it as cost savings. Following the same line we find the Boston Consulting Group (BCG) and MIT Sloan Management Review (MIT SMR) report, ‘The Cultural Benefits of Artificial Intelligence in the Enterprise’. According to the report, more than 75% of company executives who have integrated AI into their processes say that they have improved decision-making and team efficiency.
These powerful tools are available to any company and their main advantages include:
1. Improved decision making
One of the main advantages of this technology is the help and improvement it brings to the decision making process. Artificial Intelligence and Advanced Analytics use real data as a basis for analysis and value extraction, providing past and real-time information on the performance of the company (descriptive analytics), predicting what will happen in the future (predictive analytics) or telling us what would be the best decision to make knowing all the above (prescriptive analytics). Undoubtedly a decision support that can make the difference between just getting by and standing out.
2. Increased agility
Another of the benefits most reported by companies after the implementation of AI-based systems is the agility in the execution of processes. For example, the automation of an online documentation verification process through text and image recognition systems. It saves a lot of time and increases the speed of response to the customer in an unprecedented way. Previously, the customer had to scan and print a copy of their ID, send it by mail and wait for an operator to review and accept the documentation as valid, which could take days or weeks. Now the customer only has to take pictures of their ID from an app, the system verifies it in a few minutes and notifies the customer about the acceptance.
3. Improved customer experience
The application of this type of technology is also noticeable in customer experiences. In the example shown in the previous point, we can see the difference in the effort and time spent by the customer and the speed of response in each of the cases. In an increasingly immediate world with more and more demanding customers, this advantage in ease and speed of response of AI, together with the personalization it provides, becomes extremely important.
4. Operational cost savings
Another application of this technology is mathematical optimization for efficient planning of resources and operations. In this case, we would have, for example, an optimal planning of production activities in which stock, waste, and the amount of machinery used are minimized. With its corresponding savings in material costs, storage, etc.
To continue with the same example as above, in the automation of the documentation verification process, there would also be a significant cost saving as not so many operators would be needed to review physical documentation.
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