Key uses of advanced analytics platforms
While we have talked about advanced analytics platforms in the past, we have yet to discuss their application in data analytics operations. As mentioned before, advanced analytics can do far more than the standard analytics software because of technology like AI. This sets the groundwork for more advanced analytical methods like machine learning, sentiment analysis, and cluster analysis.
These advanced functions are invaluable for most organisations because it expands the functionality of data collection and analysis. With this in mind, we are going to discuss the key applications for advanced analytics platforms.
Key applications for advanced analytics platforms
Advanced data analytics has the technology to implement transformative processes for organisations.
Here are some of the options.
Analytics for the Agile-Lean model (also known as the Lean-Agile model)
Advanced analytics comes with several advanced features like reporting, forecasting, and process enhancement. This means analytics platforms can lay the groundwork for potentially transformative business operations, like the Agile-Lean model.
The Agile-Lean model refers to a business-oriented model where organisations are better placed to respond to unexpected exogenous events. By using the power of predictive analysis models, organisations can create a more flexible supply chain that is better placed to respond to external events. For example, supply chain planners can create a supply model that can respond to unforeseen or complicated events while maintaining a consistent production line that delivers on time, despite the exogenous shocks.
Optimised demand planning capabilities
Most firms with a global supply chain have complex planning procedures and processes. For most organisations, this is a rather inefficient process. One that takes up a ton of time, drives up costs, and takes valuable time away from productive work.
Advanced data analytics can help alleviate some of the issues that come with planning and coordination by bringing visibility to the entire supply chain. Greater visibility in the supply chain allows organisations to optimise procedures. It’s much easier to identify where procedures are going wrong and take action to rectify them.
This advanced analytics allows organisations to act more proactively when dealing with unexpected occurrences, like stormy weather.
Advanced analytics can automate decision making
While professionals are still an integral part of the decision-making process, advanced analytics is reducing the burden that professionals normally have to deal with. The analytics platform comes with several features that include artificial intelligence, which allows organisations to automate part of their processes.
One example is inventory management. The process of replenishing certain parts or components is usually a manual process. A process that consumes time and resources. Advanced data analytics can automate most repetitive functions like inventory analysis. This allows organisations to cut operating costs and reallocate resources to more pivotal areas.
Bring new products and services to market
The process of bringing a new product or service to the market is not an easy one due to external and internal factors. Organisations need a thorough understanding of the market. They need to know what their consumers want, what their pain points are, and how they are looking to deal with their problems.
Similarly, organisations need to understand their competition, what they are doing, and how they are reaching out to their customers. This leads to a complex business process that involves marketing and research.
Advanced analytics platforms allow organisations to make this process far more efficient than before. Data analytics helps organisations access real-time data, which gives organisations a better understanding of their supply chain. Furthermore, with the use of machine learning, organisations can learn the market and even predict where the industry is heading—making it easier to anticipate market trends and act accordingly.
It is also important to note that machine learning can be used to optimise company functions, eliminating inefficiencies, reducing operating costs, and bringing products to the market faster.
Using advanced analytics to maximise operational efficiency
Advanced analytics have a potentially transformative impact on organisations. Most companies are struggling to deal with an assortment of problems ranging from complex supply chains to inefficient, bureaucratic red tape.
Data analytics platforms can provide the insight most organisations need to fix the underlying problems in their processes. By fixing these problems, organisations can attain new heights in operational efficiency, allowing them to reduce costs and bring innovations to the market at a faster rate. These are the key applications of advanced analytics.
Visit Selerity to know more about advanced analytics platforms.