Datanomics: [ˈdeɪtənɒmɪks]
the science of creating value from data
Move beyond guesswork.
Develop a data strategy that informs your investment decisions
Understanding Datanomics
The core question for datanomics is “how does value accumulate around data?” and “what are the effects of my decisions on that value?”.
At MadeWithData our goal is to help the world use data to open up the value creation process for firms, for people, and across markets.
This opportunity plays out in a number of different dimensions:
- What are the ‘ingredients’ that are required to create value from data and do I have them all?
- What happens when I ‘work on data’ and can I use hard science to improve it?
- How much should I invest in data and can I measure the returns using a metric like IRR or NPV?
- What does it look like to sell data, and if I am, is there an ideal amount I should trade?
- When my team works with data traders, is there a danger in just ‘going with the flow’ and doing what’s right for me?
Contact us for a white paper that unpacks each question.
Getting started with Datanomics
Understanding Data Assets
What are the ‘ingredients’ that are required to create value from data and do I have them all?
Data Assets inside Business
How much – and how often – should I invest in data?
Trading Data Assets
If I have to share data with my analysts, is there an ideal amount of data to share?
Discover how MadeWithData can open up the value of your data.
Datanomics - The Full Nerd
We all trade data but never stop to consider what the terms of that trade are.
Datanomics brings science to data management by establishing a strategic, theoretically robust perspective that focuses on data as a key driver of economic value. Rooted in platform economics, information theory, and management science datanomics explains how data can play the dual role of both a production factor inside a firm and an exchangeable service across markets. This means data is less like a product (eg. a sandwich or even an idea) and more like an intangible service (eg. a firm’s reputation or its social license).
Open, transparent, long-tail, collaboration is what creates value from data. That relies on trust and stakeholders’ collective efforts to amplify data’s value.
This persistent collaboration is a paradigm shift that challenges enterprises to foster environments where data acts as a conduit for shared goals, driving mutual benefits across a network of internal and external participants. It’s a call to move away from the competitive hoarding of data towards a more open, participatory economic culture.
Viewing data as a long-tail service, and not a transactional product changes the way you see technologies like Gen AI. Prompts become data exchanges that enable insight and agility within a data sharing ecosystem. This approach not only enhances operational efficiencies and competitive differentiation but also opens new avenues for innovation and growth. When scaled together, this view of data can be scaffolded into first a qualitative framework that is useful for identifying pockets of value, and then a quantitative framework for targeting specific, marginal investment. This insight benefits all stakeholders in both the short- and long-term.
Our aim is simple: we want to open up the world’s data economy through empowering people with a detailed understanding and exploration of the value of data around them. As the original data economists, we publish, research and share. Connect with us to discover the untapped potential of your data.