Analyzing time series data using statistics and modeling to make predictions and inform strategic decision-making.
Compare the statistical predictions from Predictive Planning against your forecast.
Forecasting the depletion level of stocks in stores, capacity planning, and inventory planning.
Optimize price, discount,and clear inventory based on predicting consumer demand to optimize profit.
Person tweets that they are interested in a certain product or service, text analytics can discover this & feed this info to a sales rep who can then pursue this prospect and convert them into a customer.
Drive optimal strategies in planning, increase inventory productivity in supply chains, decrease operational costs.
Determining the expectations of future results, usually applied in budgeting, capital budgeting and/or valuation
The three main channels where banks can use artificial intelligence to save on costs are front office (conversational banking), middle office (anti-fraud) and back office (underwriting)
When the COVID-19 outbreak became a global pandemic, financial-markets volatility hit its highest level in more than a decade, amid pervasive uncertainty over the long-term economic impact. The transformative impact of AI on all industries is indisputable. Several banks are applying machine learning (ML) to enhance traditional models—for example, by calibrating parameters more efficiently.
Artificial Intelligence (AI) is most commonly applied in manufacturing to improve overall equipment efficiency (OEE) and first-pass yield in production. Over time, manufacturers can use AI to increase uptime, improve quality and consistency, which allows for better forecasting.
The global retail industry, which has grappled with waves of change over the past decade, is facing one of its most dynamic and unpredictable periods to date. Due to the naturally reduced consumer spending during the global pandemic, retailers are required to embrace AI and enjoy its benefits.
Optimize patient care, accelerate research in disease prevention and treatment, accurately forecast staffing and operational needs, while optimizing payer operations — all which saves lives and improves the quality of care for all patients, regardless of socioeconomic status.
Within the telecom industry data science applications are widely used to streamline the operations, to maximize profits, to build effective marketing and business strategies, to visualize data, to perform data transfer and for many other cases.