Ben and Jerry\u27s: When Subsidiaries Fight Back

Ben and Jerry’s is a world-leader in the premium ice cream market, having a very well-established brand known for high quality ice cream and unique flavors. Additionally, they are known for a large emphasis on economic and social equity, standing fast in their values and being very outspoken about their stances on prominent current events. After being acquired by Unilever, a global consumer goods company, Ben and Jerry’s came face to face with the reality that their company values will sometimes clash with their parent company’s after putting out a statement regarding the Israeli-Palestinian conflict that Unilever quickly denounced. While navigating this conflict that eventually resulted in a private settlement out of court, Ben and Jerry’s was forced to reconsider how to best maintain their own brand and mission, while simultaneously being a subsidiary

Talent Marketplace

The Center for People is a nonprofit organization that works to provide services and programs to the low-income that address their basic needs and help them achieve economic independence. One such program connects participants with work training and potential employment opportunities. Previously, the Center for People had no platform to connect their trainees and employers. To combat this problem, the Design Studio team has created a “reverse job fair” web application that allows businesses to search for qualified participants that have been through training at the Center for People. Center for People Administrators can invite both employers and participants to the system, where they can create profile pages. For employers, their page has an “about” section, a profile picture, and information on which job types they are currently hiring. Participant profiles include an “about” section, a list of soft skills, jobs of interest, and their previous job experience. Employers can find potential employees on their discover page, where they can filter employees by the job types they prefer, as well as their soft skills. From the discover page, they can navigate to participant profile pages, and send participants an email through the system to let the participant know they are interested in them for an employment opportunity. The employer can then navigate back to their discover page to see the list of participants they have shown interest in. Participants can then see that the company has reached out to them on their home page. As a result of the platform, employers can now connect with Center for People participants with ease

Building Efficiency Platform Phase II

The Olsson Building Use Efficiency Platform Phase II builds off of last year’s Olsson Design Studio project. The Building Use Efficiency Platform is a way for Olsson to study and analyze how buildings are used and to provide solutions for using space more efficiently and cutting costs. In short, the product consists of a sensor hub and a web application. The hub collects building data from sensors and uploads it to a database so it can be viewed on the Building Use Efficiency dashboard website. The problems that Olsson presented the team with this year were that the device required internet to function, the website did not have many administrative features, and the data visualization could be improved. The Design Studio team this year set out to solve these problems to enhance the product for Olsson. Development was split into three main areas: hardware/offline usage, administrative features, and data visualization improvement. Throughout the year, all the team members worked on different aspects of these problems, but each member had a defining feature that they took ownership of. Through the past two semesters of development and frequent communication with Olsson, the team created a new version of the product that satisfies all of the problems presented by Olsson

AIOps: Predictive Analytics with Mutual of Omaha Servers

This project involved building and using an ARIMA model to process error logs from Mutual’s servers (a few days’ worth of data at a time for any one server or set of related servers) and predict whether the machine(s) error levels are going spike in the next 24 hours. If there’s a predicted spike, our system creates an alert that fits the same standards and model of Mutual’s other alert systems, providing machine names, predicted error times, and some baseline information about the potentially endangered machine so that engineers can mitigate quickly and effectively – stopping outages before they happen

AIOps: Predictive Analytics with Mutual of Omaha Servers

This project involved building and using an ARIMA model to process error logs from Mutual’s servers (a few days’ worth of data at a time for any one server or set of related servers) and predict whether the machine(s) error levels are going spike in the next 24 hours. If there’s a predicted spike, our system creates an alert that fits the same standards and model of Mutual’s other alert systems, providing machine names, predicted error times, and some baseline information about the potentially endangered machine so that engineers can mitigate quickly and effectively – stopping outages before they happen