TP PICS vs Allocate3M

TP PICS is an application for taking and classifying pictures. The pictures are then synchronised directly with the photo management in CDE ENTERPRISE. You can classify pictures by using free text fields and you can also utilise lists and set values for editing purposes (short lists). EXIF information, e.g. date and GPS data, is automatically saved with the photo files. You can work offline without an Internet connection. Afterwards all pictures and content will be uploaded to think project! once the Internet becomes available again. Important prerequisite: The user must have access to a minimum of one project from the main system CDE ENTERPRISE, and this project must be configured to operate together with the photo application. Mobile photo management on-site: • Mobile access with the ability to upload directly to the project platform • Work offline and then upload pictures once the Internet is available again • Take and classify pictures comfortably and efficiently • Automatically tag and transfer exif information such as date and GPS data • Create and directly import photos from your camera or import them from an existing gallery • Classify photos with tags from default lists to create a high standard of photo management • Classify photos using free text fields for specific accompanying information • Spontaneous documentation on-site delivers a high level of photo management for your project • Immediate availability of pictures for all members in CDE ENTERPRISE

Machine learning and data analytics are increasingly being used for resource allocation, increasing growth rates or reducing volatility by allocating limited financial, human, technological, time, or natural resources to the tasks and projects that need them most. The “Mean-Variance” Model is the most classic resource allocation model and is widely used in various industries. Common application scenarios: 1. Seeking the allocation weights with the highest growth rate under a specific level of volatility. For example, you can allocate resources based on historical sales data from 500 European retail stores. The “Mean-Variance” model uses the Monte Carlo method to find a set of allocation weights that have the optimal sales growth rate. 2. Weights are assigned based on volatility in order to seek stability. For example, you can allocate your procurement budget based on the historical raw material prices of 300 suppliers in the Asia-Pacific region. The “Risk-Parity” model uses Newton's method to find a set of allocation weights with equal volatility to reduce the risk of raw material price fluctuations. Allocate3M combines three models: “Mean-Variance”, “Black-Litterman”, and “Risk-Parity”, to help you optimize resource allocation results from different perspectives.