Welcome, Kellogg Students, to the info page for Analytical and AI Consulting Lab (MECN-615), taught by me, Prof. Joel Shapiro.

Winter 2026 application is available here: https://reg.kellogg.northwestern.edu/experientiallearning/

Deadline: For Winter Q 2026, you must complete your application by 8:00 AM on Monday, Oct 20. If you are applying as a team, EACH team member must complete an individual application by the deadline. Admission decisions will be shared prior to the start of FT bidding later that week.

If you are admitted to ACL, I will do my best to assign you to a project that you would really like. However, especially with sports clients, demand is often higher than supply. I recommend that you apply to ACL only if multiple projects sound interesting to you.

Please note: “Analytical and AI consulting” isn’t just about statistical analysis and ML model-building around large datasets. Many companies already have data science teams for that. What they often lack, but truly value, are business-minded experts who can help them think differently about how to use data and AI. In some of the below projects, the real value (and often, the real fun) lies in uncovering new ways to solve business problems using existing data: reframing challenges, surfacing hidden opportunities, and shaping innovative use cases.

Most ACL projects fall into one of the following categories:

  • Empirical analysis of a data set to generate recommendations - sometimes these projects might require building ML models and sophisticated model diagnostics, while others might involve simpler “insight generation”

  • Helping clients map out how data can be useful to a particular goal, like “personalization for revenue generation.” These projects are a bit more about creating a strategy to use data to achieve a business goal, rather than conducting primary empirical work.

  • Helping clients map out how generative AI tools / LLMs can be used to achieve specific business goals. Given the early stage of industry’s use of gen AI, these projects tend to be more open-ended and require significant self-direction by the student team.

Project / clients for Winter 2026 will likely include the following. Check back regularly for more details, as I will update this page as details are finalized.

Generative AI / LLM projects:

  • Exploring generative AI opportunities with the world’s largest equity derivatives clearning organization. The client is evaluating a wide range of potential applications, from automating manual processes, to enhancing existing models, to replacing contractor tasks with agent-based workflows, but lacks a clear framework for prioritization. Students will work directly with senior leaders to assess the landscape of possibilities, define the criteria that matter most for business impact, and weigh trade-offs and opportunity costs. The goal is to deliver structured guidance that helps the organization focus its generative AI investments where they can drive the greatest value. Note: This project is focused entirely on generative AI and large language models. It is not about analyzing existing datasets, but about exploring how LLMs can be applied to solve real business problems. Students will draw on their understanding of these technologies, less on the technical mechanics, more on their practical applications, to identify where they can create meaningful impact.

Data science / analytics projects:

  • Subscriber analytics with a new direct-to-consumer sports network. With a growing base of fans streaming games through its app, this new network wants Kellogg students to help them understand what’s working, what’s not, and how to accelerate growth. Students will analyze subscriber cohorts, trial effectiveness, churn patterns, and engagement behaviors across multiple payment platforms to identify activation and retention levers. This project offers the chance to work hands-on with real DTC subscription and viewing data, helping a fast-scaling startup sharpen its growth strategy in a highly competitive sports media landscape.

  • Fan-facing soccer insights with a sports data company (spun out of a well-known parent org). The client is building a distinctive position as an authority on soccer analytics, with products already in development for both teams and fans. Their data sets capture detailed aspects of player performance and match activity. Students will use these data sets to surface new metrics, analyses, or visualizations that could engage fans in powerful ways. The goal is to generate fresh, fan-facing insights that highlight the richness of the data and inspire both fan engagement and future product opportunities. Knowledge of soccer is helpful but not required, as the client is especially interested in approaches that make the sport more accessible to new or casual fans. Director of strategy is a Kellogg alum.

  • A major consumer brand is seeking fresh insights into the effectiveness and ROI of its sports sponsorship investments. This project will explore how fandom, fan engagement, and live event attendance connect to brand perception and purchasing behavior.

  • Sales and revenue analytics with a U.S. leader in home improvement, offering students a chance to dive deep into revenue strategy and customer behavior with a large home service / flooring company. The business has tens of thousands of customer interactions every month—each an opportunity to better understand conversion drivers, channel performance, and how pricing and promotions shape outcomes. Students will work closely with the firm’s executive team to uncover ways to optimize the sales funnel, drive profitable growth, and inform pricing strategy using real-world data. This is a uniquely hands-on opportunity to apply revenue and customer analytics to affect meaningful revenue drivers. Client sponsor is a Kellogg alum.

  • Health care analytics, with a pharmacy benefits company aiming to help employers better understand and manage their true prescription drug costs—especially for expensive, high-rebate drugs like Ozempic. The project’s goal is to build a data-driven tool that can take in an employer’s claims file, estimate current PMPM costs, and simulate how cost changes if coverage decisions are adjusted. This approach gives the client a predictive advantage to compete with larger players in the market. This project offers students a rare opportunity to work with large-scale real-world healthcare claims data to build predictive, decision-support tools that directly shape pricing strategy and competitive positioning in a multibillion-dollar industry. CEO is a Kellogg alum.

    Other sports and non-sports organizations are likely to participate as well.

Email me here with questions - happy to help!

What is ACL?

ACL is a 10-week experiential course where you and your team work on a real project for a real company with real data challenges. We have periodic meetings during the quarter. I also work with your team as needed / desired.

How to enroll?

You must apply and be accepted to ACL.

I HIGHLY recommend that you enroll in ACL as part of a team of 4-5. Your chances of getting into the class are much improved if you apply as a team. Each team member must apply separately, are admitted separately, and all must meet the minimum qualifications.

FAQs

How often is ACL being offered this year? Currently, ACL is being offered every Fall, Winter, and Spring quarter.

What are the pre-reqs for ACL? You must have completed Business Analytics II or the equivalent. Greater analytics expertise is strongly preferred, but not required. The key to ACL success is that you know how to apply quant or computational methods to solve business problems.