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Cognition

A 2021 look back and 2022 preview

A lot happened at Nextmv in 2021. Here’s a 5-minute rundown of all the goodness the team dispatched and a mini preview of what’s to come in 2022.

Decisions as code

We love a good polyhedral representation with a side of matrix math, but we know they're not for everyone. So we're creating decision optimization tooling that allows developers to work with decisions as code.

Testing...testing...1, 2, 3

At Nextmv, we help companies make the best decisions in the time they have. But how do you know what’s better or even good? Let’s talk about testing decisions.

Exploring new frontiers in decision optimization with GPU acceleration

NVIDIA GPU-accelerated decision optimization has elevated the conversation around decision intelligence. Join a live Q&A with the NVIDIA cuOpt team to learn more.

Building stakeholder trust and confidence in decision intelligence

“I wouldn’t pair these products.” “How much better is this optimized schedule than mine?” Human review and feedback is part of any decision workflow...

Lessons lived and learned: Project success and failure in decision science

Historian and philosopher Hannah Arendt once said, “Storytelling reveals meaning without committing the error of defining it.” While good stories of operations research and data science can come from practitioners of all kinds...

Open source in OR: Q&A with Pyomo and HiGHS

The operations research and decision science space has a diverse portfolio of open source projects, including Pyomo and HiGHS. Recently, new momentum is building around project adoption...

The path to production: Exploring the software interface with OR

“I’d like help deploying this decision model. Does this .ipynb work? Or would you prefer .zip?” If you work on decision science projects, it is possible you’ve asked or been asked this question...

Move fast and show value: Agility in decision intelligence via DecisionOps

Good. Fast. Cheap. Pick two, they say. But (true to form) decision intelligence teams strive to maximize for all three — project success often hinges on it. Balancing these objectives often comes down to a team’s agility ability. What does this look like? And how is it put into practice?

What to know about practicing operations research and decision science in industry

Two operations research PhDs with varied real-world experiences explore skillsets, actions, and considerations for entering into and practicing in OR and decision science in industry analytics settings.

Building end-to-end decision workflows: Develop, deploy, test, and enhance

Integrated, holistic optimization approaches are critical for long-term success — without them your project will fail. Learn what these workflows look like through a batch production scheduling example.

AI/ML + mathematical optimization: Overview, benefits, case studies, and protips

“What is your AI strategy? How are you investing in AI? Where are you incorporating AI into your everyday workflows?” Before you think “GenAI” and “LLMs”, have you considered optimization?

Decision maturity roadmap

Learn how to leverage data and AI for better operational decisions.

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.

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.

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.