This article is focused on business process automation and IT automation. We’ll discuss the types of automation based on their level of complexity, and see which strategies are used for optimising their performance.
IT automation involves creating software to replace repetitive operations that once relied on human intervention. It speeds up the delivery of IT resources and applications, saving time and freeing up IT staff from manual work. IT automation is essential for helping IT teams deliver results with greater speed and security.
In today’s modern IT environment, it’s all about the speed, and time required to achieve results, and that’s where automation comes in. Thanks to automation, a broad range of operations in data centres and the cloud are realised faster.
With the rise of cloud services and the complexity of IT operations, which require rapid and difficult work, it could be too much even for a large professional team to handle. With IT automation, such teams can operate well, even if they need, for example, to set up and configure thousands of servers.
The benefits of IT automation for enterprises are:
Several leading international cloud surveys have identified that 35% of the money invested in the cloud is going up in smoke each month. And the reasons for this are simple: clients are growing rapidly into the cloud, and enterprises don’t have time to optimise their post-migration processes. Additionally, millions of new workloads are created and added to the cloud every year.
To help with this problem, cloud optimisation services offer detailed views to measure how resources are utilised, how resources are consumed, and how to unlock hidden savings to help bring cloud expenses under control.
These three main strategies help simplify decisions and unlock hidden savings:
Artificial intelligence and machine learning go hand in hand, it’s when algorithms learn from data to become better at predicting certain outcomes through patterns, that humans struggle to identify.
Businesses can implement machine learning algorithms in cases where the outcome is influenced by thousands of factors that the human mind will struggle to compete with. Machine learning algorithms can analyse all factors at once to better predict an outcome.
While artificial intelligence is a technology that makes it possible for machines to simulate human behaviour, machine learning is a part of AI that allows a machine to instantly learn from past data without programming for a specific case, it’s so interesting that it can often be seen in movies.
To give an example, some of the common applications that use machine learning are: image recognition, speech recognition, medical diagnoses, statistical arbitrage (buying an asset at a lower price in one market and simultaneously selling it at a higher price in another market), and predictive analytics.
With the process of machine learning automation, those without a theoretical and practical background in machine learning, can participate in the development of AI. The demand for expert-level knowledge in machine learning is growing faster than the number of specialists in that field.
To solve this problem, this automation has given rise to simple and user-friendly machine learning software, that anyone with basic technical knowledge could use. Automated machine learning has the following benefits: efficiency, scalability, and error reduction.
In order to make their existing processes more efficient, productive, and cost-effective, businesses are implementing optimisation. Typically, it involves leveraging existing resources or combining multiple tools, into a single, more cost-effective tool, to simplify operations and increase savings.
Use this business process optimisation structure to get started:
Benefits from optimisation are visible through: enhanced effectiveness of your business; faster assistance for your customers; more clarity in the organisation; and your business becoming easier to improve and grow.
Following are some of the examples of very useful automation: