Healthcare And Pharmaceutical Industry
Retail And E Commerce Industry
Travel And Transportation Industry
Predictive Modeling is the process of creating a model whose primary goal is to achieve high levels of accuracy.
It is a situation where we are concerned with making the best possible prediction on an individual data instance.
ORMAE and its consultants have deep insights into this domain. The team can consult clients on the effective use of these advanced modeling techniques in its business operations. Management can take proactive decisions knowing future trends and risks involved.
Many industries use predictive modeling approaches to determine a decision to be made. Usage of these models is varied across all industries and domains.
Usage across industries:
1. Predicting Plane delays, travel times etc.
2. Predictive demand forecast - Efficient demand forecasting, which predicts future demand for products and parts based on past events and prevailing trends, is a key component of after-sales service success. With an accurate picture of demand, manufacturers can improve service after the initial sale of a product without having to raise costs.
3. Predictive Pricing - When using predictive algorithms to set prices for service parts, manufacturers need to be mindful of the different factors that can affect sales, including part location, seasonality, weather, and demand. With predictive capabilities, manufacturers can incorporate all these factors and others to automatically adjust prices based on what the market will bear.
4. Predictive Maintenance - With IoT and predictive analytics, smart parts and sensors will detect when a part is about to fail so the manufacturer can determine when and where parts are needed, proactively routing them to a dealer or repair center instead of storing them in stocking locations around the world. This enables manufacturers to reduce excess inventory and costs, improve part fill rates, avoid the cost and disruption of unscheduled downtime, and, ultimately, maximize customer loyalty.
5. Spam Detection - The most accurate prediction that minimizes false positives and eliminates spam
6. Sentiment Analysis - Every organization wants to preserve their brand value and reputation. So this kind of analysis across social media is effectively done to understand what are customers expectations and convey the core ones to the management
7. Sale price of property in real estate market - Predict the demand and supply and estimate the correct sale price with the accurate predictors for current environment
8. Detecting Fraud - Combining multiple analytics methods can improve pattern detection and prevent criminal behavior. This is used widely across banking and finance, and also in large scale organizations who would like to have a good governance and compliance on its operations
A mathematical algorithm with use of machine learning and data science helps quickly find the predictors and provide insight to management of making quick decisions to help businesses steer growth in right directions and avoid the potential risks.
ORMAE has skills and has served customers to develop customized solutions in this space which has helped clients to make quick decisions and effectively use these in operational optimization.
Predictive Models using Machine Learning and Data Science techniques
Varied solutions across industries and domains
Forecasting demand with high accuracy
Use of predictive results in operational optimization
More and more organizations are turning to predictive analytics to increase their bottom line and competitive advantage.
Growing volumes and types of data, and more interest in using data to produce valuable insights.
Faster, cheaper computers.
Tougher economic conditions and a need for competitive differentiation.