Imagine how smooth could your journey be had you been able to predict all or at least most of your roadblocks ahead of time? So, you could prepare for it and had your handbook ready for action anytime!
Predictive monitoring is one such magic for your business. It is one application of process mining that is transforming industries today. It has gone a step ahead to prove itself to be one of the most vital concepts surrounding which entire businesses are being built these days. To be able to know beyond the present day is a boon if you know how to utilize it effectively.
So, let us probe a little deep into what can really be predicted by this approach and how exactly it can coexist within the existing organizational structures.
Predictive monitoring takes the companies one step ahead of its time by monitoring how their data points behave and thereby analyzing the same over a certain period via remote asset monitoring. Doing so helps in predicting and deciding the successive big step, and here comes the role of Artificial Intelligence (AI). Whenever any changing pattern is noticed in the data behavior, this monitoring system alerts the business right away. It comes up with an action to be taken by analyzing the same data.
In contrast to predictive monitoring, predictive maintenance is all about consuming specific algorithms and data for giving out the best time for carrying out any sort of obligatory maintenance works.
When used in the manufacturing industry, predictive maintenance takes up past performance data together with present maintenance regularity. With all these accumulated data, predictive maintenance disapproves of sticking to the preset schedules only; instead, it helps the organizations to drive better control over its maintenance works. It again helps an organization in making better decisions and thereby reduces its costs too.
How do predictive monitoring and maintenance benefit your organization?
Predictive monitoring is meant to identify the occurrence of an event before it has occurred. Some human expertise, as well as Artificial Intelligence, comes into action to yield a barrage of insights. It’s just that the system needs to be trained well for every likely scenario. Even if it fails to prevent a downtime once, it’s the same approach that accelerates uptime too.
IT leaders are in a mode of constant learning about predictive monitoring and how it can bring value to the businesses. Its rate of acceptance has been rising rapidly, as data continues to rule over most of the futuristic models of business. It goes way beyond the traditional network monitoring and use of Supervisory Control and Data Acquisition (SCADA) architectures, and it is doing a fantastic job in delivering reliability and preparedness.
Key Takeaways –
- Discloses system downtime to the organization before its occurrence
- Tracks the real-time system or application health
- Identifies the grounds for an all-inclusive performance of a system
As data and insights continue to dictate futuristic business models, it is now the right time for you to introduce predictive analytics into your business processes.