With a digitally transformed and fast-paced business landscape nowadays, it is simply not only enough for businesses to focus on their present goal, they also need to be enlightened on how they can go further and enhance their business operations in the future. Most companies and businesses are now encouraged to go beyond descriptive analytics and discover the things that might or might not work in the future and see how these can be improved. For business leaders and analysts, these insights can only be derived by using a specific data tool that provides an assessment of what will happen in the future. This is called predictive analytics.
But what precisely is predictive analytics and how does it help businesses grow? Simply put, predictive analytics uses data, statistical algorithms, and machine learning techniques to come up with predictions about future outcomes. Based on historical and present data, predictive analytics can generate future insights to increase bottom line and competitive advantage in the market. Though it generally gives insights and predict what might happen in the future based on existing data, predictive analytics helps companies and organizations strengthen their overall analytics strategy.
Companies across various industries benefit from using this technology. Most businesses use predictive analytics to reduce risks, optimize operations, and ultimately increase their revenue in the future. Here are some ways predictive analytics can be a useful tool for any industry’s growth.
Retail, Merchandising, & Marketing
- Sales and revenue forecast
- Demand forecast
- Predicting the best retail location
- Maximize target campaigns
Hospitals and Healthcare
- Predicting patient utilization patterns
- Identifying the prevalence of disease to a patient-based health condition
- Identifying the trend of occurrence of a disease over time
Banking and Finance
- Detecting insurance fraud
- Predicting the approval of loans and credit cards
- Credit scoring and risk assessment
- Trend of insurance claims
Logistics and Supply Chain
- Inventory management
- Routine optimization
Alteryx for Businesses
Realizing the need to adapt with technology to reliably forecast future trends and behaviours of the consuming market, many companies around the globe consider using Alteryx, an American computer software that creates powerful code-free workflows for statistical, predictive, and spatial modelling. Unlike any other computer software, Alteryx is the only quick-to-implement, self-service data science and analytics platform that allows both citizen data scientists and trained statisticians to break the barriers to insight so everyone can experience the thrill of getting to the answer faster. It is an easy to use end-to-end data manipulation and analysis tool which can be integrated with the Qlik platform.
Stages of Data Analytics
Organizations benefit well from solutions like Alteryx in helping them overcome challenges and discover new opportunities for future growth. But since predictive analytics is a branch of advanced analytics, organizations need to realize that there are prior stages before one can make predictions about unknown future events. The Gartner’s graph is an accurate illustration on the stages of data analytcis in a company. The first one is the descriptive analytics which basically answers the question what happened. This stage enables organizations summarize their data and transform them into visualizations such as bar charts, pie charts, excel reports, among others. The data are raw at this stage, and it is up to the organization on how to interpret and drill it down to specific details using the second stage of data analytics which is the diagnostic analytics. This stage correlates the data from the first stage thus answering the question why it happened. Most organizations nowadays are only dealing with the past and present conditions; however, it would be more beneficial if they go beyond the first two stages and deal with predictive analytics which answers the question what will happen. Like mentioned earlier, this stage uses historical data, statistical operations, and algorithms to give predictions for the future. No data is given yet, however, predictions are used to prepare and align future actions. Last stage would be the prescriptive analytics which answers the questions how we can make it happen. More than just predicting what will happen in the future, prescriptive analytics tweaks certain variables such as quantity of products to achieve the best possible outcome, and then prescribes that in order to achieve this we may increase the quantity for this month and so on.
As a partner of Alteryx in the Philippines, Micropinnacle Technology Corporation ensures that these stages are carefully thought out and planned in the Alteryx Designer for various clients across different industries. MTC’s approach to analytics and data science is comprehensive, making sure that clients get a clear insight and overview on how to do their business well in the future.
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dashboard screenshot from www.alteryx.com