How can you manage decision model versions on Nextmv? Let us count the ways… An overview of approaches for managing model versions for testing, roll out, roll back, and provisioning by geographic region, client, or development environment in the context of DecisionOps.

How can you manage decision model versions on Nextmv? 🤔 Let us count the ways... 🧐

Tour examples that manage model versions by dev environment, geographic region, client/customer, and shadow mode: www.nextmv.io/blog/how-can...

#orms #decisionOps #decisionscience #datascience

⏳ Early registration for #SMDM26 coming soon! Connect with leading researchers, clinicians, and policymakers shaping the future of medical decision making in Oslo this summer. #HealthPolicy #DecisionScience #PublicHealth

Decisioning at the Edge: Policy Matching at Scale | Towards Data Science Policy-to-Agency Optimization with PuLP

Real-time decisions don’t always require complex AI. Sometimes a well-designed optimization model is enough. #Optimization #DecisionScience #InsurTech #MachineLearning #MLOps #EdgeComputing #LinearProgramming #OptimizationAtScale #towardsdatascience
towardsdatascience.com/decisioning-...

Huge shoutout to my lab mates Zheng Li, Hassan Andrabi, and Hoang Long Nguyen who did an absolutely stellar job delivering their (first?) conference talks! 👏

Big thanks to the organisers, especially Cloudy, for a fantastic event.

#MathPsych #CogSci #Ageing #AcademicSky #DecisionScience #AMPC2026

DecisionOps and reflections on the road ahead The future of operations research and decision science hinges on DecisionOps infrastructure, systems of record, and an integrated ecosystem.

As you think about the year ahead, do you want to spend time building (and maintaining) tools to build models? Or do you want to spend time building (and improving) models that deliver value to your business? hubs.la/Q044Qfxr0

#decisionOps #orms #decisionscience #logistics #supplychain

Prediction is useful. Understanding *why* things happen is powerful. Causal machine learning helps move beyond correlation to real insight, supporting smarter, more ethical decisions across industries. #CausalML #MachineLearning #DataScience #ExplainableAI #DecisionScience

Getting optimization solutions into the hands of stakeholders faster at Grubhub How Grubhub’s data science team uses Nextmv to accelerate model development, ship models as microservices, and build trust with business users.

Learn how Grubhub’s data science team uses Nextmv to accelerate model development, ship models as microservices, and build trust with business users: hubs.ly/Q043PF4d0

#orms #foodlogistics #delivery #datascience #decisionscience #DecisionOps

Tracking the Most Intoxicating Data: A Conversation With Eric LeVine An interview with Eric LeVine by Xiao-Li Meng and Liberty Vittert Capito.

The hardest part of analytics isn’t modeling.
It’s translation.

Curious how others are thinking about this gap between evidence and action especially in complex, regulated environments like healthcare.

buff.ly/75TZbmh

#HealthcareAnalytics #ValueBasedCare #DecisionScience #HealthEconomics

Decision Optimization with GPU acceleration: In conversation with the NVIDIA cuOpt team How can GPUs improve decision optimization workflows? In what ways will solving optimization problems change? How does this change the way technology leaders think about their AI strategies? We spoke ...

→ How can GPUs improve optimization workflows?
→ How will solving optimization problems change?
→ How should tech leaders rethink their AI strategies?

Read the discussion about the NVIDIA cuOpt decision engine and what’s next: hubs.la/Q042Jv840

#DecisionOps #DecisionScience #orms #cuOpt #nvidia

Yeah Y'all know what this is.

#Zajey #Science #Research #ScientificMethod #SystemsThinking #Causality #CausalInference #DecisionScience #ComplexityScience #ComplexSystems #NonlinearDynamics #ChaosTheory #Probability #Statistics #Uncertainty #RiskAnalysis #Modeling #Inference
2/2

Previsit Preparation for Shared Decision-Making in Lung Cancer Screening in Primary Care Using a Paper Decision Aid and an Automated Text Messaging Program: Quasi-Experimental Pilot Study Background: Patient-provider discussions and shared decision-making (SDM) are essential for tailoring lung cancer screening (LCS) decisions to individual patients. However, implementation of SDM in primary care settings is challenging. Innovative approaches are needed to reach patients eligible for LCS and help them prepare for LCS discussions in primary care settings and to increase the uptake of LCS. Objective: We piloted pre-visit preparation comparing two strategies: a paper decision aid (DA) (DA group), and an enhanced comparator strategy consisting of the paper DA plus an automated text message program (DA+TM group) designed to promote patient-provider LCS discussions. We explored feasibility and gathered preliminary data on its potential effects on LCS discussions, decision-making, and LCS uptake in primary care settings. Methods: In a sequential quasi-experimental pilot, we recruited patients who were eligible for LCS in a single academic healthcare system. Prior to an upcoming visit, participants in both groups received a paper-based DA by mail. In the DA+TM group, participants also received a series of automated text messages to help them prepare for their LCS discussions. We monitored participant recruitment and retention, and patient engagement in DA and text messages. In exploratory analyses, we assessed patient-provider discussion of LCS, SDM, patient knowledge, decision conflict at baseline and in follow-up telephone surveys, and LCS completion measured by electronic health records. Results: We enrolled 49 participants (DA group = 19, DA+TM group = 30). Participants were predominantly White, with a median age of 61.0 (IQR, 57.0-65.0), and 58.3% were female. Engagement in both groups was high. LCS knowledge significantly improved in the DA+TM group (4.5 baseline vs. 6.0 follow-up; P=.003), versus no change in the DA group (5.0 baseline vs. 5.0 follow-up, P=.23). Median LCS knowledge change from baseline to follow-up was 0.5 (IQR -1.0-2.5) in the DA group, and 1.5 (IQR 0-3.0) in the DA+TM group (P=.24). Decision conflict in both groups significantly decreased (DA group: 37.5 baseline vs. 0 follow-up, P<.001; DA+TM group: 50.0 baseline vs. 20.0 follow-up, P=.003). The median SDM process score (a measure of SDM) was 3.0 in the DA group and 2.0 in the DA+TM group (P=.11). The LCS completion rates were 5.3% in the DA group and 31.0% in the DA+TM group at 3 months (P=.07), and 26.3% in the DA group, and 34.5% in the DA+TM group at 6 months (P=.75). Conclusions: We showed that pre-visit preparation was feasible in primary care settings. The enhanced strategy utilizing text messaging not only reduced decisional conflict but also improved LCS knowledge. An enhanced, text message-based strategy has the potential to reach and engage broader LCS-eligible populations and prepare patients for LCS discussions with their primary care providers, which may ultimately improve informed decision-making and LCS uptake.

How else can automated text messages educate medical patients?

Adding automated text messages to a paper-based decision aid program improved lung #cancer screening knowledge and screening rates.

doi.org/10.2196/69044

#medicine #edu #decisionScience #healthScreening #oncology

Why join Data Science Connects? 
To learn from peers, build meaningful professional connections, and stay at the forefront of data-driven decision-making. 
 
Find out more: 
https://f.mtr.cool/uaysquiopc 

#DataScience #CareerDevelopment #DecisionScience

#DecisionScience #Leadership #MythBuster #FactCheck #Debunked #ScienceBehindIt #ResearchReveals #EvidenceBased #CriticalThinking #LogicWins #TruthHurts #RealityCheck (3/3)

Our January 2026 OPTIMA Outreach Newsletter is now live.

Read the January edition here:

mailchi.mp/optima.org.a...

#OPTIMA #OPTIMAOutreach #OperationsResearch #Optimisation #Analytics #DecisionScience #STEM #ResearchImpact #IndustryEngagement #Newsletter

Founders and leaders: If you want to influence decisions, focus on how minds work, not just spreadsheets.
#MythBusting #FactCheck #Debunked #Neuroscience #Research #Evidence #DecisionScience #CriticalThinking #Facts #Reality (3/3)

Oncology Launch Curve Forecaster dashboard Executive Brief showing key metrics: 10 analogs selected, $4.3B base case peak (P50) with range $2.4B-$5.2B, $244M revenue at risk (Year 1) under 2-quarter delay scenario, 20 quarters to peak. Shows start of Launch Trajectory Scenarios section.

Built an oncology launch curve forecaster. The insight? Stop asking "what will happen" and start asking "what does this assumption cost if we're wrong?"
.
🔗 tinyurl.com/5cx9s4ye
.
#rstats | #shiny | #pharma | #commercialanalytics | #decisionscience

PhilSciDec ABOUT Philosophy of Science of Decision Making is an online research seminar run by Dr James Grayot of the Mind, Language, and Action Group (MLAG) of the University of Porto, Institute of Philosophy. ...

The latest #PhilosophyOfScience of #DecisionMaking seminar is starting!

This week: Malvina Ongaro, who will present her paper, “Decision-making for the management of natural risks”

More about the series: sites.google.com/view/philsci...

#PhilSciDec #Philosophy #Psychology #DecisionScience #CogSci

Stressed and rushed? Your decisions might suffer New University of Melbourne research reveals how the combination of stress and time pressure can wreak havoc on our ability to make good choices

Excited to see our research on stress and decision-making featured in Pursuit today 😁

It's great to see these findings reaching a wider audience and I hope people find it interesting!

Read the full story here: pursuit.unimelb.edu.au/articles/str...

#DecisionScience #Stress #Psychology #SciComm

@harvard.edu @utoronto.ca

#BehavioralEconomics #ChoiceArchitecture #NudgeTheory #CognitivePsychology #DecisionScience #PublicPolicy #BehavioralInsights #SystemsThinking #LibertarianPaternalism #CassSunstein

Opinion | The Idea That Once Held America Together Died in 2025

If the West is "blowing up process", where does that leave planning? Are there ways planners can reinvent design and policy analysis to support a renewal of belief in process in our countries? #rationality #DecisionScience #creativedestruction

www.nytimes.com/2025/12/24/o...

6/ The practical takeaway:

Benefits alone rarely move decisions. Framing matters.

Make the costs of standing still explicit. Show how risk is contained.

#PublicSector #Leadership #DecisionScience #Management

CHANGE GAINS TRACTION WHEN THE STATUS QUO STARTS TO FEEL LIKE THE BIGGER RISK.

🎉 SMDM and ISPOR are co-developing a shared Frontiers in Modeling session for both Annual Meetings. At #SMDM26 in Oslo, the focus is Frontiers in Causal Modeling. More details soon — submit your abstract now!

#ISPOR #CausalModeling #HEOR #DecisionScience

“Analytics will never replace thinking. But it helps you think better.”
Use data to sharpen your intuition—not replace it.
#ThinkSmarter #GoAnalytics #DecisionScience

Nextmv Platform adds support for NVIDIA cuOpt GPU-accelerated solver Say 👋 hello to Nextmv support for NVIDIA’s cuOpt optimization engine and NVIDIA GPU-enabled compute on the Nextmv DecisionOps platform.

Say 👋 hello to Nextmv support for NVIDIA’s cuOpt optimization engine and NVIDIA GPU-enabled compute on the Nextmv DecisionOps platform: hubs.la/Q03Vcntx0

#nvidiaAI #nvidiacuOpt #decisionOps #orms #nvidia #decisionintelligence #decisionscience #vehiclerouting #operationsresearch

Join us for DecisionFest Tune into DecisionFest to hear from industry practitioners from organizations such as IKEA, Walmart, Carvana, Toyota, and more!

🪅🎉Join us for DecisionFest, a series of sessions exploring practitioner insights on successfully operationalizing decision models in industry. Learn more: hubs.la/Q03TMbzL0

#decisionOps #decisionscience #operationsresearch #orms #datascience #decisionfest

Fear of wasting money hides fear of wasting yourself. This week’s feature helps you make calmer, data-backed spending calls. Read or listen here : buff.ly/tvMnqvW

#EntrepreneurWisdom #DecisionScience #SixCatalysts

🔈 Our edited volume "Decision Making: Fundamentals and Applications", co-edited with @ulrichettinger.bsky.social and Bert Heinrichs, is out.

url.au.m.mimecastprotect.com/s/9P5mCROAEn...

#DecisionScience #DecisionMaking #Psychology #Psychiatry #Neuroscience #Philosophy

Connect your Pyomo model to Nextmv for DecisionOps: A step-by-step guide Developing, testing, or managing Pyomo models? Connect your Pyomo model to the Nextmv platform for streamlined development, simple deployment, built-in testing, and collaboration.

Working with Pyomo models? Follow this guide for streamlined development, simple deployment, built-in testing, and collaboration on the Nextmv platform. #orms #python #pyomo #decisionscience #datascience #decisionintelligence #operationsresearch

Get started here ➡️ hubs.la/Q03RzzK-0

“Right data” isn’t the most data... it’s the signal tied to a specific decision. Define the decision, pick one metric, audit bias, pre-commit actions. If nothing changes, it wasn’t the right data.

questionclass.com/how-do-you-e...

#DataStrategy #RightData #DecisionScience #alignment #questionclass

Cognitive Bias Is the New Technical Debt in Marketing | HackerNoon AI amplifies cognitive bias in marketing. Learn the Cognitive KPI framework to track and resolve problems that scale.

Full playbook, metrics, and real examples of the Cognitive KPI Stack:
👉 hackernoon.com/cognitive-bi...
If you work in data, marketing, or AI ops — this one’s for you.
#AI #Analytics #MarketingStrategy #DecisionScience #Hackernoon @hackernoon.com