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About The Education Market Taxonomy ​
HolonIQ’s Global Learning Landscape is an open-source Market Taxonomy for education innovation. The taxonomy offers a granular, structured classification system to categorize and organize the education market, providing a common structure and language for identifying, tracking and making sense of the education market broadly defined, including traditional forms of service and delivery, as well as capturing new models, technologies and solutions.
The taxonomy is structured as a three-tiered hierarchical framework. The uppermost tier consists of the four accepted Sector categories of Early Childhood Education, K-12 Education, Post-Secondary Education, and Workforce Training & Development. The 20 Sub-Sectors across these categories capture the core functions of the market such as delivery, content and services. Each Sub-Sector is further segmented into ‘Market Clusters’ which identify the specific functions, technologies, activities within the sub-sector.
Data on the HolonIQ Market Intelligence Platform is segmented using this Market Taxonomy, including all organizations, market activities, and capital flows, enabling ease of sizing and comparison across categories or over time. By segmenting the education market using this robust framework, HolonIQ is able to support customers’ needs in areas such as market analysis, competitive intelligence, product development, and sales strategies. Licensed under Creative Commons and as an open-source project, the taxonomy is available for anyone to support their own work in strategy and innovation.
Methodology ​
The Global Learning Landscape embraces two classical approaches to data, analytics and design. ‘Bottom Up’ analysis powered by our Global Intelligence Platform leveraging powerful machine learning and artificial intelligence, augmenting ‘Top Down’ analysis driven by HolonIQ’s Education Intelligence Unit and our global network of experts.
Bottom Up - Machine Learning ​
In order to support the development of the taxonomy, we initially undertook ‘bottom-up’ analysis using HolonIQ’s proprietary machine learning and artificial intelligence to analyze 60,000+ education organizations worldwide. The analysis identified natural patterns in the data using uses 'Unsupervised Learning' to explore new approaches to clustering and segmentation that are not anchored or biased by the more established and traditional taxonomies of education. The vizualisation on the right-hand side of the page for example is exploring the network of organizations in a single country. Organizations that are similar in how they support learners, parents, schools and institutions are clustered together based on the segments they service and the models and technologies they employ.
Top Down - Human Expertise ​
HolonIQ’s Education Intelligence Unit and our global network of experts from early childhood to lifelong learning bring deep expertise to our ‘top-down’ approach. The top-down analysis draws on the data-driven foundations of the bottom-up analysis to interpret patterns that the machine learning and artificial intelligence process produced. Considerations include context, history, purpose, business model, technologies and ecosystem relationships to add depth and interpretive understanding to the process. This also enables validation of findings against the models and innovations found in education today or expected in the future.
Who we are ​
HolonIQ is a globally unique education market intelligence firm. Our mission is to connect the world with the technology, skills and capital to transform education through access to the most comprehensive education innovation dataset, intelligence tools and global network of people and ideas.
We help companies, institutions, governments and investors power growth and innovation by connecting billions of data points about education startups, technologies, deal flow, schools, universities, jobs, skills, research and patents and apply machine learning to analyze, evaluate and identify patterns, generating insights that help clients make data-driven decisions and answer strategic questions.
With billions of data-points connected in just a few short months, we have already helped governments, institutions, companies and entrepreneurs in North America, Europe, Asia and Australia answer strategic questions about market trends, growth strategies, investment focus, business performance and benchmarking.
Holon (ὅλον) ​
In systems theory, a Holon (ὅλον) is an evolving and self-organizing system. Each holon has integrity and identity on its own, but is simultaneously part of a larger system. We consider education to be an holonic system, where holons (learners, teachers, academics, schools, startups, universities, national systems) are simultaneously autonomous and co-operative.
Holonic systems are complex systems, efficient in the use of resources, highly resilient to disturbances yet adaptable to change, preserving the stability of a hierarchy while providÂing the dynamic flexibility of an adaptive system.
This is how we think about innovation in education. Not top-down, technology-led but rather innovating from within the system - constantly learning, cooperating and adapting. Enabled and empowered with new models that the network evolves and organizes around, maintaining a constant focus on the learner.
Why we did this ​
Education is a complex sector, combining important social, economic, cultural, intellectual and personal factors and operating at global, national, local and personal levels. However, information and data about education and the innovation that is occuring throughout the system is fragmented and anchored in its local environment, making cooperation across contexts difficult, thus hindering material innovation in the sector.
We have been building, investing and mapping innovation in education for decades and have had the opportunity to work with entrepreneurs, educators, institutions and governments globally. One of the constant themes arising from our engagements and conversations with each of these stakeholders is the difficulty in accessing, understanding and learning from innovations undertaken elsewhere.
The Global Learning Landscape provides common structure and language for identifying, tracking and making sense of the complexity and volume of innovation happening in education all around the world by providing a well-defined, robust, accessible and community enabled taxonomy.
Using a common framework will support the discovery of, and access to innovation initiatives, provide opportunities for collaboration and benchmarking, reduce barriers to innovation and allow analysis and trend mapping within or across innovation clusters. Licenced under Creative Commons and as an open source project, the taxonomy is available for anyone to support their own work in education innovation. The global community can track and contribute to the taxonomy’s ongoing development via GitHub.