Decision Sciences: Marketing
@RobbMacDonald
The “Decision Sciences: Marketing” blog offers an evolving exploration into how decision sciences enhance strategic decision-making #decisionscience
Solving the Last-Mile Problem in Analytics: Introducing the Decision Science Pre-Analysis Framework #DataScience #DecisionScience #bizML #Marketing wp.me/pfJJ4p-18h
ROAS and the Flaws of Linear Thinking in Marketing Spend Decisions #DataScience #bizML #Marketing wp.me/pfJJ4p-Y9
“Data Helps, People Deliver”: Reflecting on My Last 10 Years as a Data Scientist—and Looking Ahead to the Next 10 #DataScience #bizML #Marketing wp.me/pfJJ4p-L1
The Economy of Insights in a GenAI-Driven World: A Decision Scientist’s Perspective #DataScience #bizML #Marketing #DecisionSciences wp.me/pfJJ4p-Ur
The Executive Decision Series (Post 4): Avoiding Risks with Monte Carlo Simulations in Marketing #DataScience #bizML #Marketing wp.me/pfJJ4p-IN
From Insights to “Out-of-Sights”: How Decision Sciences and GenAI Help Drive Consistency #DataScience #bizML #Marketing wp.me/pfJJ4p-n9
The Executive Decision Series (Post 3): Transforming Decile Tables into ROI Powerhouses #DataScience #Marketing #bizML wp.me/pfJJ4p-Fu
The Executive Decision Series (Post 2): How to Read a Decile Table for Response Optimization #DataScience #Marketing #bizML wp.me/pfJJ4p-Ck
Drawing on HBR’s ‘Where Data-Driven Decision-Making Can Go Wrong,’ this post connects insights from the article to the ideas of ‘impact paths,’ ‘decision black holes,’ and ‘data ‘shoehorning.’ #DataScience #bizML #Marketing wp.me/pfJJ4p-wb
“500 Cats” or one “Tiger”? The promise versus the reality of data analysis and its role in driving actionable decision-making within today’s organizations. #DataScience #bizML #Marketing wp.me/pfJJ4p-Bv
“The Executive Decision” is a new series I’ve launched to bridge the gap between advanced analytics and actionable decision-making. Each post spotlights a new conceptand shows how it empowers smarter decisions #DataScience #bizML #Marketing wp.me/pfJJ4p-xx
My latest blog post explores the concept of impact paths—structured, traceable frameworks designed to connect data-driven insights to explicit business decisions and measurable outcomes. #DataScience #bizML #MarketingStrategy wp.me/pfJJ4p-pA
decisionsciences.blog
Decision Sciences: Why Data Science Needs Clearer Impact Paths
In today’s data-driven landscape, many data scientists face the frustration of their hard work disappearing into the “decision black hole,” where insights fail to translate into measurable outcomes....
In my latest blog, I explore the ‘data veneer’—how surface-level insights and confirmation bias undermine data-driven decisions #DataScience #bizML #Marketing wp.me/pfJJ4p-pn
decisionsciences.blog
Beyond the Data Veneer: A Decision Sciences Call-to-Action for 2025
In today’s data-driven world, it’s not enough to simply include charts and metrics in business presentations. The true test of data-driven decision-making lies not in the presence of numbers on a...
"You don’t have to be great to start, but you have to start to be great.” CC: Visual Growth
“From Meaningful Data Science to Impactful Decisions: The Importance of Being Causally Prescriptive.” A must-read for data scientists aiming to establish a new framework in decision sciences #DataScience #bizML #DecisionScience datascience.codata.org/articles/10.53…
What's the difference between model explainability, interpretability, and observability? Jason Zhong's debut TDS article outlines the nuanced distinctions you should be aware of. buff.ly/3LbvGiZ
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