Optimizing Wind Farm Operations and Maintenance with Discrete-Event Simulation

AGM, a globally operating digital marketing agency, develops advertising strategies and executes online marketing campaigns for its customers from a broad range of sectors. Their challenge was to determine the best possible allocation of marketing funds among multiple online channels, optimizing the overall effectiveness and return of investment of its marketing campaigns.

Each of the online channels, from search engines to video-sharing and social platforms, provided analytics data in different formats and at different time intervals. In order to implement a data-driven solution that spans all channels, Wolfram Consulting Group’s first task was to build a fully automated data acquisition pipeline and normalize the available information into a representation suitable for computation.

Then, using a multivariate time-series forecasting algorithm tailored for the kind of data AGM provided from their previous campaigns, we developed and tested a tool that could accurately and reliably predict the evolution of the outcomes of the different channels. During the course of an ongoing campaign, this tool was used to propose reallocation of spending over different channels so AGM could dynamically optimize the overall return on investment.

Finally, we extended the algorithm so AGM could either calculate the budget necessary to achieve a chosen outcome KPI or, alternatively, forecast the outcome for a given budget.

Wolfram experts provided AGM with an easy-to-use graphical user interface to explore “what-if” questions and visualize a wide range of scenarios. Our solution for AGM attracted new clients who were seeking cutting-edge approaches to managing their digital campaigns.

From the beginning, the founders of the biotechnology startup Emerald Therapeutics wanted to develop an ideal research platform that would allow for lab and process automation during experiments as well as easy communication of their findings.

Mathematica provides all the tools the Emerald founders needed to carry out their vision, while Wolfram Language powers Emerald Cloud Laboratory, a web-based life science lab.

Regarding the decision to use Mathematica, Emerald cofounder and co-CEO Brian Frezza says, “It struck the perfect balance of being powerful enough and versatile enough to allow our engineering team to develop sophisticated software within, yet the language is easy enough to learn that it’s accessible to our chemists and biologists to use as a primary means of keeping a daily lab notebook.”

Emerald’s team of scientists and engineers have a shared code base in Mathematica, which allows them to use one platform to carry out all the tasks in their antiviral research workflow—from developing functions to processing and storing data, designing and managing experiments, presenting findings, even controlling lab instruments.

Having Mathematica as the core platform means the Emerald team can trust the repeatability and accuracy of its results and rapidly grow its experiment base. “We can keep handling larger experiments and we can do more complicated things each day because we’re building on a base that is incredibly reliable and precise… You need that level of reproducibility in biology. You need something that can handle all the quantitative detail in a way that’s still accessible and manipulatable to the scientists.”

For Frezza, having one language that both the engineers and scientists can share and perfect is extremely valuable, especially for a startup in the pharmaceutical industry. “The way in which we’re able to build is just incredible. Our burn rate is incredibly low for a startup because the number of people we need to do what we’re doing, which is incredibly ambitious, it scales incredibly well when you have a tool like that.”

A major US-based pharmacy chain needed to reliably automate the process of converting doctors’ prescriptions to standardized printed labels that are attached to customers’ prescription medicines. The doctors’ notes, written in expert English abundant with idioms and conventions used in medical practice, amounted to more than 100 million unique strings of text to be processed as a data stream with minimal latency at tens of transactions per second.

The requirements were to accurately determine the true intent of each prescription and translate its often hastily written and confusing language into clear textual and visual instructions for the consumer. To guarantee absolute patient safety, a custom-built knowledge system had to be deployed for validating dosage recommendations, checking for potential cross-interactions as well as minimizing potential risks arising from common misunderstandings. A warning and feedback workflow with human experts in the loop was implemented to resolve ambiguous cases, resulting in 100% accuracy for all accepted prescriptions.

The solution Wolfram Consulting Group delivered to the pharmacy chain was architected on the basis of Wolfram|Alpha, which provided a domain-specific knowledgebase and a natural language processing (NLP) framework that could be extended to master this unusual and complex task. Wolfram Consulting also curated additional proprietary data and incorporated it into the business process. This solution was delivered through an API that could be easily integrated into the client’s existing infrastructure. The solution greatly reduced the cost and time needed to generate prescription labels while ensuring the client’s highest standards for patient safety.