Carolyn Mooney

Co-Founder & CEO
Carolyn Mooney began her career running large scale ballistic missile simulations at Lockheed Martin. She adapted her skills to meal delivery in Decision Engineering at Zoomer, then led Grubhub's Systems Engineering team, consulting on projects from ETA improvements to scheduling and market management. Carolyn has a BSE in Systems Engineering from the University of Pennsylvania and coaches volleyball when she's not founding companies.‍
Simulate “what if” questions for decision models with scenario testing and Nextmv

What if order volume increases 4x? What if I changed shift length? What’s the best model formulation? Efficiently play out different scenarios under realistic conditions before committing to a plan using Nextmv’s scenario testing capabilities.

A 2023 look back and 2024 preview of what’s next with DecisionOps and decision science

Last year, we focused on accelerating deployment and testing for decision models. 2024 looks to focus on operating and monitoring models with more platform integrations and greater visibility and control across your development lifecycle.

Nextmv 1.0: Accelerate decision model development with a DecisionOps platform

Our first major version has landed – merging tools for building, testing, deploying, and managing decision models into one platform. Ship more models, rapidly iterate and improve, and make greater operational impacts with Nextmv.

Reflecting on one year of the Nextmv platform

It’s been one year since we launched the new and improved Nextmv platform. That was just the start of an exciting dash to arrive at the product we have today. We’ve come a long way, and there's so much more to come.

The road to production is paved with testing and experimentation

Do you launch decision model A or B? What happens if an operator makes a manual override? How does a new optimization model perform against real-world data? Testing and experimentation has the answers, but getting them has traditionally been a challenge.

The what, why, and how of DecisionOps: Accelerating time to value for optimization

How do optimization teams get decision models live into business processes faster as managed services? We explore this through the lens of dedicated DecisionOps workflows.

Uncertainty, ML + OR, and stochastic optimization: Demo and Q&A with Seeker creator

What approaches are available to decision scientists and operations researchers to incorporate more randomness and uncertainty into their models? We explore this, ML + OR, and stochastic optimization with Nextmv and Seeker.

How to perform a scenario test for decision models

Simulate scenarios to answer "what if" questions with your decision model.

How to bring your custom Python decision model to Nextmv

In this step-by-step video, we’ll walk you through deploying a Python OR-Tools traveling salesperson problem (TSP) model using the Nextmv Python template.

Getting started with DecisionOps – Live Nextmv workshop

In this hands-on workshop designed for operations researchers (decision scientists), developers, and data scientists, participants will get a guided introduction to DecisionOps via the Nextmv platform.

Shift scheduling algorithm comparison: Optimizing for shift coverage

See how to test two shift scheduling algorithms. One algorithm increases the time between shifts to account for new labor laws compared to the other algorithm that does not. How do schedule overages change across the two?

Order fulfillment and carrier selection experiment: Comparing handling costs

Test two order fulfillment algorithms that consider costs for distribution center handling costs and carrier selection. A new algorithm introduces a change to account for inventory capacity at a distribution center to increase efficiency and decrease food waste. How will costs change compared to the algorithm that does not?

Vehicle routing (VRP) algorithm test: Comparing a mixed fleet to a homogenous fleet

See how to test two VRP decision algorithms (one that has a homogenous fleet of cold chain-ready vehicles and one that is a mixed fleet with cold chain and non-cold chain vehicles) that looks to compare total time on road values and other KPIs.

In conversation with Ox and The Rounds: Circular logistics and human-centered automation

The CEOs and founders of two startups sit down with Carolyn Mooney to discuss logistics and automation, navigating the evolving world of AI technology, and the benefits of efficiency and sustainability.

Decision model testing for routing, assignment, order fulfillment, and shift scheduling

Four decision algorithms, multiple experiments, one platform. Explore recently released batch testing capabilities for evaluating model changes to compare output metrics, KPIs, and prepare for acceptance and scenario tests.

Build decision models with confidence: Working with testing in optimization

Optimization model testing plays a key role in ensuring smooth yet improving business operations. But the testing universe is big and sometimes unwieldy. Learn how to get started with a unified decision model testing framework.

In conversation with Dr. Karla Hoffman about optimization and operations research

Is optimization a solved problem? How does it fit into modern business models such as on-demand delivery? What does it mean to model like an operator? We’ll ask Dr. Hoffman these questions and more.

Getting started with Nextmv

Build and run complete decision optimization models in minutes for vehicle routing, scheduling, packing, and Sudoku. With a few commands, you're ready to solve.

From zero to customizable decision model in minutes with Nextmv

Register to watch a presentation, demo, and AMA time with the Nextmv team. Get an overview of the newly released custom decision optimization platform, see it in action, and check out a preview of our multi-solver capabilities.

Decisions as code: Systems thinking, operations research, and computer science

From vehicle routing problems (VRPs) to scheduling staff and workers, there is a multitude of decisions ripe for automation. In this talk, Carolyn Mooney, CEO of Nextmv, talks about her vision for shifting from traditional decision workflows to decision automation where any developer can work with decisions as code.