Understanding the future .
It is a forward looking approach that has the capability to predict “what might happen”. This is an analytics approach that understands the future and provides actionable insights to the companies based on the data analysed. This statistical algorithm just like any other data estimates the likelihood of a future outcome but can’t give 100% certainty. It is a great tool to forecast the future outcomes.
This is an analytics approach that depends on probabilities where errors might happen. We have to find the missing links by filling the gaps with best guesses. Historic data is collaborated from different sources such as ERP, CRM, POS and HR systems to identify patterns in data. Then the data is processed with statistical methods and algorithms to capture relationship between various data forms. We as an analytics company performs predictive analytics throughout the organization, right from forecasting customer behaviour and purchasing patterns to forecasting demands for inputs from supply chain, inventory and operations to identifying sales trends. Additionally, we produce a credit score that are used to determine the probability of customers making future credit payments on time. This is a great help to the financial service providers for designing better future.
Predictive Analytics Methods .
Predictive analytics helps businesses reliably forecast future trends and behaviours. It focuses primarily on data analysis and manipulation of variables in order to pick up forecasting capabilities from the existing data. A variety of statistical modelling approaches are involved in predictive analytics that predict the behaviour of key variables that are unknown but have a significant impact on the performance of the business.
Predictive analytics rely on various elements including measurable variables and manipulating metrics that predict future outcomes effectively. Other than predicting demand that includes volume and prices in various forms, few additional factors are considered such as input prices, currency movements and risk that is directly or indirectly affected by weather or other variables. Furthermore, predictive models help in analyzing information patterns to support tactical analytics, such as online marketing or fraud detection. Predictive analytics modelling yields functional results once its causal drivers and their past behaviour is identified and their relationship to the main variable forecasted becomes stable. This process becomes more challenging when there are a lot of random elements or there are significant discrete events.
Activities involved .
We at Intellectyx use predictive analytics whenever we need to know about the future or fill the gaps in the given data. This is how we proceed:
- Offer this forward looking approach for better business prospects
- Focuses on non-discrete predictions of future relationship, conditions and patterns
- Introduces key product documentation
- Review configuration for identified issues and provide comparisons for usage patterns
- Gathers longitudinal data from across the organization
- Use insights from ongoing support case
- Describe prediction result set probability distributions and likelihoods
- Provide error sources, estimates, and bounds as an contextual output
- Perform non-discrete forecasting
- Model application for better performance