This article will delve into the nuances of asset predictive analytics.
Features of Asset Predictive Analytics
The more the data, the better it is, right? That does not have to be the case. According to Dan Fisher, Advisory Principal of KPMG, “It is not about owning the most data, but about gaining the most insight from the data and turning it into a real business advantage”. Hence, regardless of the amount of data one holds, if it is not leveraged to the company’s advantage, a company is unnecessary suffering from issues that could have been avoided. Predictive analytics feeds on different forms of data ranging from statistics, mathematical modelling and simulations, data mining and machine learning. While this is ideal for asset-centric companies that hold enormous amounts of big data, it also works wonders for companies in other sectors. Using all the data it can feed on, asset predictive analytics will analyse historical data to forecast any anomalies in real-time. Asset managers deploy this form of analytics to ensure a company’s assets are reliable. This is especially due to the need to meet the standards of ISO 55000. However, it may be hard to understand how this solution can help asset managers if they do not know what it is and the best way to start implementing it. Hence, here is all you need to know about asset predictive analytics:
Understand the True Potential of Each Asset
Asset predictive analytics emit scientific insights to asset managers, thereby providing extremely reliable data. Unlike those who have a team of scientific data analysts who spend days and weeks trying to assess the performance of an asset, an advanced digital solution has the capacity to automate detailed reports on how the asset is currently performing and can also demonstrate its desired levels of performances. Through this, managers can gain statistics on the productivity level of each asset and ensure that it is used accordingly. Therefore, managers can utilise their existing resources to gain maximum results. Thus, managers can redesign the asset infrastructures to ensure that they are functioning in the best conditions all the time.
Reduces Risks and Assures Safety
Most of the time, an impaired asset hinders business and, most importantly, can be hazardous to people. Whether it is the utility service team or the citizens in the area, failure to attend to an asset’s health has drastic consequences. There could be situations where signs of your asset being sick cannot be witnessed until it completely breaks down. The repair team will blindly enter the premises where the asset lies and will not know what is wrong until they approach it. Moreover, outside factors such as the weather could hinder the team from being deployed. A predictive analytics system allows managers to be aware of problems humans cannot detect and consider the best way to repair an asset with that knowledge. Not only would it highlight any dangerous aspects the asset maintenance teams need to keep in mind, but it could also use data regarding the weather to predict the most suitable period to repair it.
Fewer Expenses, More Cost Effective
Predictive analytics does not require an organisation to make physical space or invest in fancy equipment. While there are hardware components that include predictive analytics, asset managers can reduce expenses whilst gaining the same features as a hardware component would provide and a lot more smart solutions with a cloud-based predictive analytics system. The best part is that no major changes need to be made, nor do existing systems need to be removed, thereby ensuring that no resources are wasted. Managers can simply integrate the software into existing software solutions and share asset data amongst asset custodians and other financial decision-makers. This way, all departments across a company can access data to make the best asset decisions in the country. This includes making financial budgets following forecasts made by the system. As it is cloud-based, this also gives asset managers the option to access data remotely, giving them the ability to take quick decisions in instances of emergency, especially during natural disasters.
Prevent Malfunctions
Traditionally, asset managers face problems in their machinery, and when they face sudden malfunctions, it leads to their services being interrupted. Where utility service providers particularly experience this, it directly leads to not just one but a large number of people in a specific area being inconvenienced. While some issues could be solved in a few hours, there could be situations where a day or more is required to repair or replace the asset. In such cases, consumers expect to be warned prior so that they can schedule their activities accordingly. This is hard to do when asset managers cannot detect the problem in its initial stage and may require time to identify what is wrong with the asset to fix it. Adding predictive analytics, therefore, gives more control to utilities. By knowing potential risks that could occur indefinitely, managers can take measures to prevent them from happening. Alternatively, where maintenance has to be scheduled, utility service providers can quickly inform consumers days or weeks ahead, thereby improving customer satisfaction.
Minimise Service Disruption with Asset Predictive Analytics
Whether you are in the manufacturing industry, are a utility service provider or belong to any other sector, integrating predictive analytics can help you cut your overall expenses. From decreasing downtime to guaranteeing customer satisfaction, you can ensure the safety of your team and your fellow citizens, understand the full potential of your assets and take well-informed decisions, thereby making the best use of your data 24/7.