Working in conjunction with subject matter experts, data scientists can swiftly apply statistical tools and uncover emerging trends. This is extremely valuable for companies trying to operate in a disruption. Not only will executives have an accurate representation of their present situation, but new products & services can be devised from these insights.
Weather has a high impact on operations in many industries, and therefore is of great value to integrate into strategic decision making. Mosaic has roots in aviation research & development, giving us deep expertise in combining weather data streams with planning applications to facilitate efficient resource allocation.
Global external shocks are going to continue to happen, that is a fact of operating a business in today’s environment. As companies embrace data science in their decision-making processes, they are better positioned to deal with these disruptions, allowing them to manage a risk-optimized supply chain.
A leading CPG company wanted to diagnose cannibalization hypotheses using a data-analytics-driven approach.
A leading clothing manufacturer distributor and retailer of clothing realized they needed to fortify their pricing decisions with machine learning insights.
For many pharmaceutical firms, trial recruitment forecasting plays a role in trial recruitment planning. However, these forecasts may be generated with relatively simplistic approaches based on only a small subset of available internal & external data.
Designing and deploying computer vision is a powerful technology that humans can employ to improve their decision making. The only limits to these technologies lie within our ability to think of problems for them to solve.
Gameplay data are a trove of information about how athletes are acting and reacting in real situations, and there are real benefits to be gained by mining this information at every level, from the athlete to the entire team. In the modern age, the team that can measure and understand itself through its own data will have the competitive edge.
Retail executives need to think more like tech companies, using AI and machine learning not to just predict how to stock and staff their stores, but also to dynamically recommend products and set prices at the individual consumer level.
Data Science, specifically machine learning forecasting techniques, enables decision makers across a spectrum of industries to set more effective sales targets and plan profitable customer routes that boost top and bottom line growth.