Strategies for Optimising Automation Performance and Reliability

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.

What is IT Automation?

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. 

Benefits of IT Automation

The benefits of IT automation for enterprises are:

• Savings on cost: Besides shortening the labour hours of staff required to finish routine tasks, IT automation increases productivity, reduces infrastructure costs, and reduces costs related to human error. 
• Time savings: Through the automation of tasks that are repetitive and time-consuming, IT staff can allocate their time to more advanced responsibilities.
• Fewer errors: Consistency on a large scale is ensured by automation, which is sometimes impossible to achieve by individuals, completing work manually.
• Better security: Automated processes ensure the safety of sensitive information because they require fewer human interventions.
• Speed: AI automation speeds up operations, thus reducing service and resource delivery times significantly. 

Why is Cloud Optimisation Important?

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.

Main Strategies of Cloud Optimisation

These three main strategies help simplify decisions and unlock hidden savings:

1. Operations: Finding unnecessary and unallocated resources for computing, network, storage, and database.
2. Architecture: Consists of reducing and eliminating unnecessary network costs, taking advantage of multi-cloud opportunities, and accessing areas where security issues are driving costs.
3. Policy: Including governance, disaster recovery, and reporting.

What is ‌Machine Learning?

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.

Automated Machine Learning

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. 

Business Process Optimisation 

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.  

Strategies for optimising business processes

Use this business process optimisation structure to get started: 

1. Identify and analyse the process that needs optimisation. Once you’ve identified the process that needs to be optimised, it’s time to determine the expected results. This means understanding what is lacking in your process and making changes that will make it work better.
2. Set the key performance indicators (KPIs). By establishing KPIs you’ll understand whether the optimisation is giving the desired outcomes. This helps to monitor the progress of optimization.
3. Keep track and measure. Based on the KPIs made in the previous step, it’s time to monitor and track those optimisations that are being made. That way you can see if the optimisation has been successful.

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.

Automation Examples

Following are some ‌of the examples of very useful automation:

1. Power backup devices. If the regular power source goes off, backup devices directly connect us to the backup power. It’s quite convenient to prevent power being cut off.
2. User electronics. We depend on a lot of electronic devices nowadays, some of our electronic devices are equipped with microcontrollers that are programmed based on consumer requirements. For example, the washing machine stops after a decided time, without the need for manually turning it off. Automated electronic devices, such as the LabJack DAQ device, provide precise data acquisition capabilities to a wide range of users.
3. Healthcare. Medical appointment scheduling, for example, is now more efficient, along with patient registration and appointment reminders. Automated collection of data from patients is done much faster than by humans, which means doctors can focus on more important tasks while intelligent programs will collect all the data.
4. Warehouse. As a part of supply-chain automation, it refers to the optimised transportation system that connects to all parts of the warehouse which is done by robotics, and ensures quick and safe transportation.
5. Self-driving cars. Those cars use AI, cameras, and technology to drive. Although they are not completely without the risk of crashing, they can be set up to a high level of safety, and help human drivers who get tired or are making mistakes.
6. Telephone operators. Rather than speaking to a human operator, you are given different choices to say or write on your phone. This is done by voice-recognition software, and pre-programmed options.
7. Translator. Everyone’s using an automated translator, google translate, rather than an actual translator.