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Simply reacting to the ever-changing situation on the market is no longer a valid business strategy – you have to switch to predicting future outcomes, as a single drawback can leave you far behind the competition. Thus, data mining, analytics, and predictive modelling have become a crucial part of formulating successful business strategies, as preparing for possible outcomes is far more beneficial than simply reacting to them when they happen. That’s where predictive analytics comes into play. Let’s take a closer look at what it is and how your organisation can benefit from its implementation.
Predictive analytics is an umbrella term for various business intelligence (BI) technologies used for predicting events and behaviours based on patterns and relationships uncovered from the so-called Big Data (large volumes of data surrounding an organisation). In short – predictive analytics uses past data collected over a given period of time to anticipate future events or identify any unknown explanatory variable from the past, present, or future. The accuracy of predictive analytics depends greatly on the level of data analysis and the quality of gathered data and formulated assumptions.
Some of the most commonly used predictive analytics tools include data mining, AI, machine learning and deep learning algorithms, and data modelling.
The essence of this process is combining multiple variables into a predictive model which can reliably assess future probabilities. To put it simply – predictive analytics software makes forecasts based on the historical data you’ve fed it with. Though the principals are simple, the process itself is multilevel, uses sophisticated tools and advanced algorithms (such as time series analysis, logistic regression analysis models, and decision trees), and can take a lot of time. Collecting sufficient data may take months or even years, depending on the volume needed. PA shouldn’t be rushed, though – using the wrong gathering tools or inaccurate/outdated data will significantly lower the accuracy and value of resulting predictions.
The development of a predictive analytics process consists of 5 distinct stages:
As already mentioned, predictive models and data analytics are crucial in securing and maintaining a solid grasp on the market and preparing for possible events and occurrences that could affect a company’s position.
Thanks to the historical and transactional data and predictive modelling techniques, you won’t get surprised by events that could disrupt your company’s position/activity. You can easily identify risks and deal with them quickly by utilising the data-driven strategy formulated beforehand. To make sure your strategy is impeccable, consider hiring expert help, e.g., board advisory.
Without predictive analysis you could be set back for years, lose your edge over your competitors, or even completely fall off the market, depending on the severity of unpredicted events that occurred.
The use of predictive analytics can benefit many aspects of business actions, such as:
Businesses can use predictive analytics for, e.g., determining buying patterns via analysis of customer behaviour, predicting potential failures of industrial equipment parts, choosing the most promising investments, flagging potential frauds in financial transactions, or even identifying patients with higher risk of developing certain medical conditions.
The exact benefits you can get out of predictive analytics depends on your business’s characteristics – predictive models can be tailored to individual needs.
Predicting possible future trends is an integral part of leading a successful business in today’s market. Thanks to predictive analytics you’ll be able to, e.g., prepare more successful marketing campaigns, assess potential risks, and make better, data-driven decisions that will help your business’s growth. If you require help in conducting your own predictive analytics, be sure to contact us – here at Silicon Cities we can provide you with various data and business specialists, whose skills and advice will help your business achieve new heights.
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