Financial Services
There has been an explosion in the velocity, variety and volume of financial data. Social media interactions, mobile and web usage in e-commerce, server logs, real-time market feeds, customer service records, transaction details,– there’s no end to the flood.
To make sense of these enormous data sets, companies are increasingly turning to data science and machine learning for answers. Some of the services we can help with are:
- Compliance analytics including fraud and/or risk prevention
- Customer level behavior modeling
- Automated risk credit management analytics
- Pricing analytics
Healthcare
In 2012, the authors of How Data Science Is Transforming Health Care: Solving the Wanamaker Dilemma reported that the U.S. was spending over $2.6 trillion on health care each year; $600 billion of those costs include treatments that either do not help or actually cause harm. It’s apparent that U.S. health care industry is an overpriced, inefficient mess.
Despite a lot of changes, healthcare costs are on the rise and the quality is on the decline. Health care expenses represented 17.6% of the GDP in 2013, $600 billion of which are consumed by waste and fraud. By 2020, this figure is estimated to rise to nearly 20%. The country ranks 37th out of developed economies in life expectancy and other measures of health.
This puts data scientists in a position to make a difference. Used wisely, big data has the potential to help the healthcare industry make better decisions across the board – from personalized treatments to preventive care while slashing costs. Some of the many things we can help you accomplish are:
- Patient sentiment analysis
- Predictive analysis in the areas of behavior, risk and fraud
- Predictive best-treatment analysis and personalized medicine
- Scheduling Optimization and usage analysis
Retail and Consumer
Retail data is increasing exponentially in volume, variety, velocity and value with every sale. Leading retailers are aware that each one of these transaction holds the vital data that can uncover potential for profit.
How much profit?. In a 2011 report, Big data: The next frontier for innovation, competition, and productivity, McKinsey suggested that retailers using big data analytics could raise their operating margins by as much as 60 percent.
- Sales demand forecasting and asset manageme
- Portfolio allocation optimization
- Store layout optimization
- Loyalty program analytics and maximizing customer lifetime value
- Marketing mix optimization
Manufacturing
As Travis Korte points out in Data Scientists Should Be the New Factory Workers, “the increasing success of machine learning in applications such as computer vision, object manipulation and automated movement has made data science an increasingly relevant factor on the factory floor.”
Large manufacturers such as automotive companies or small businesses are collecting and analyzing huge sums of data from internal and external sources and the results are astonishing. Data Science is helping to reduce energy costs, improve efficiencies and boost the bottom line. Learn how we can help your business with these services:
- Predictive modeling for equipment failure
- Inventory level management and optimization
- Sensor placement analytics
- Demand forecasting and inventory replenishment optimization
- Predictive supply chain management
Transportation and Logistics
For a long time businesses have struggled with how to place their assets around in the most efficient way to boost the bottom line. This industry has unique problems that cry out for help from the data science field due to the amount of variables encountered in solving each problem. There is no shortage of data collected by this industry only shortage of ideas and a partner to bridge the gap between data and wisdom to make meaningful decisions.
Data scientists are able to apply advanced mathematics and statistics to solve many of these business problems which provide the wisdom to management necessary to maximize return on assets. Some of the services we can help you with to be more efficient:
- Route planning and optimization
- Inventory optimization levels
- LEAN supply chain optimization
- Truly personalized offers for customers