New financial actors and valuation platforms in education technology markets

Ben Williamson

New financial and investment organizations have become important influences in the education technology sector. Photo by Andreas Klassen on Unsplash

Prepared for the Education/Globalization/Marketization virtual workshop hosted by Malmo University, 9-10 December 2020

Investment in educational technologies has grown fast over the last ten years or so. Investors annually inject billions of dollars into edtech companies, helping fund the technologies that will shape the future practices of schools and universities. However, little is known about these financial and investment actors, the practicalities and materialities of their work, and their potential power to exert influence over education systems and practices.

This post describes some initial digital fieldwork on one new financial actor in the edtech sector. HolonIQ is an education market intelligence agency with a very considerable role in edtech investment, as well as a key source of edtech market information which is cited extensively in the media and published research. I’ve been collecting data from watching HolonIQ online webinars and YouTube presentations; gathering weekly newsletters, its reports and research notes; collecting website content, social media updates on Twitter, Facebook and Pinterest, and staff details from LinkedIn; mapping its organizational relations, and tracing external citations and social media @mentions. This all gives us some glimpses into the professional, technical and practical work of HolonIQ. There is also a lot of potential research data ‘hidden’ behind the annual subscription costs that HolonIQ charges for access to its proprietary platform and other client-only services.

What I want to suggest here is that HolonIQ acts as a ‘meta-edtech’ platform—an educational technology whose central concern is processing data about edtech, or edtech about edtech. As a meta-edtech platform and an emerging financial actor in education, HolonIQ not only catalogues edtech market movements but actively catalyzes future edtech market dynamics. It exemplifies the growing power of new kinds of market and finance actors to influence education, particularly as the edtech sector and its investors seek to capitalize on the ‘catalytic effects’ of the Covid-19 pandemic in 2020.

New financial actors

The role of financial actors has been the subject of previous studies of the ‘global education industry’, and edtech investment is now the subject of emerging political economy studies that have mapped the sprawling networks of edtech investment. Besides the wider political economy of edtech investment, very little research has examined the specific social, economic and technical practices of this new domain of financial work in education. As Janja Komljenovic notes in her research agenda on ‘assetization’ in digitalized education, ‘The opportunity recognised by investors and entrepreneurs lies in calculating the digital share in the global spending on education,’ and edtech’s ‘asset value is constructed in the light of expectations about future returns on investments’. As such, financial and investment actors are significant because they are seeking to shape the direction of edtech development and stimulate market growth, with a view to generating financial returns.

Making sense of edtech investment actors therefore requires some engagement with economic sociology, particularly its emphasis on the practices and devices of all economic activity. To simplify greatly, economic sociology insists, for example, that markets have to be actively made and maintained through specific micropractices and sociotechnical devices. Capitalization is produced through operations that include practices of assetization and valuation—how things get valued for investment based on calculations about their prospective future income. The recognition of market-making and valuation as operations and processes means any inquiry requires description of the actors, relations, settings, and actions of such operations, as well as the databases, technical literature, methodologies, disciplinary standards, and more, that are all involved in turning things into capitalizable assets with future value for investors.

From this perspective, we can approach HolonIQ as an agent of edtech market-making and valuation. It actively prompts edtech markets, is deeply involved in making edtech into objects of investment, and produces valuations that attract investors to the future income available from their investment in edtech. But this approach requires getting up close to those operations—which this post can only begin to identify for future detailed examination.

Capitalization professionals

The first way in to studying HolonIQ is to view it in terms of its organizational history, the professionals who work there, their wider relationships, and their specialized technoeconomic practices and methodologies. As Fabian Muniesa and colleagues argue, capitalization is a kind of job, performed by ‘capitalization professionals’ in particular kinds of organizations within a wider system of professions and geopolitical locations, using specialized techno-economic practices and methodologies.

The history of HolonIQ is very short, only being founded in May 2018, and yet in those few years it has expanded from an office in Sydney to London, San Francisco, New York and Beijing, and a larger network of international research partners. The website appears in two languages, English and standard Chinese, reflecting the geopolitical importance of edtech in China and HolonIQ’s attempt to embed itself in that context. Its founders are on LinkedIn, so we can begin getting some sense of their personal and professional backgrounds too. One co-founder, for example, has an MBA in corporate strategy, finance and management, an online degree in machine learning, and a background in maths, computer science, military strategy and leadership. Another has a background in enterprise education, as well as an MBA and a prestigious ‘global entrepreneur-in-residence’ position at a leading US university. Both worked at a global education services company before co-founding HolonIQ. HolonIQ also runs a virtual Global Innovation Internship Program to train new edtech market professionals.

But HolonIQ is not just a company of human capitalization professionals or embodied technoeconomic practice. A page on its website describes HolonIQ as a ‘trusted global source of market intelligence’. It connects ‘people, ideas and capital’ to support ‘the future of education’ through a ‘global market intelligence platform’ that ‘provides data and analysis’ of ‘global markets’. The platform, it claims, powers ‘governments, institutions, companies and investors by connecting billions of data points’ and by applying ‘machine learning to analyse, evaluate and identify patterns’ for ‘data-driven decisions’. The market professionalism of HolonIQ is partly constituted by its platform algorithms, and by the machine learning techniques it has enrolled to the task of edtech market analysis.

As a platform company, what HolonIQ primarily does is make predictions about the future of education and edtech’s role (and potential share) in it—as its detailed report Education in 2030: Global scenarios indicates. Published just a month after the company’s launch as a statement of its ambition and analytics capacity, the five scenarios were built using natural language processing algorithms and cluster analysis to identify patterns from a very large quantity of texts about the future of education, cross-checked against data and reports from the World Bank, OECD, and UNESCO. As such, the scenarios are the result of a complex methodology of algorithmic futurism.

This is what making objects suitable for investment requires—the identification of trends and circumstances in which an investment made today might multiply in years to come. For HolonIQ this is about forecasting future scenarios and predicting financial returns available from the actualization of those algorithmically-identified futures. So in a sense the HolonIQ 2030 global scenarios are an attempt to ‘de-risk’ investment, by claiming a limited selection of possible futures—in all of which edtech plays a major role–based partly on machine learning analysis. It then enables venture capital firms ‘to easily discover companies that are a strategic fit, ready for funding or primed for acquisition’ in order to ‘price your investments with confidence’.

As an organization constituted of both capitalization professionals and a machine learning platform, then, HolonIQ has positioned itself as a powerful new financial intermediary and source of technoeconomic expertise in education. It is seeking to catalogue the edtech market and its dynamics, but also to catalyze investment and procurement in ways that might realize certain future scenarios of education that promise high return on investment. It also organizes events including global innovation summits, ‘fast-paced and data-packed’ webinars and client-only executive roundtables around the world to create market encounters between edtech founders and investors, where such future prospects can be discussed and investment deals brokered.

Valuation claims and devices

One of HolonIQ’s most significant roles is the production of valuation claims that lubricate these relations. Through its platform, it performs technoeconomic work to calculate the value of edtech markets and their growth as a way of making edtech suitable for investment. It makes these valuation claims through a variety of narratives and representations, such as its 20 year graph of global education stocks. This valuation representation depicts near relentless growth, projecting prospective returns that ascend, literally, off the chart.  

Some of its valuation claims are packaged up in research note narratives featuring very large numbers and supported by eye-catching illustrative charts that ‘explain the Global Education Technology Market’. These include its year-end calculations about $16bn venture capital investment in edtech in 2020 alone–described as ‘funding backing a vision to transform the way the world learns’–and its prediction the global edtech market will reach $404bn by 2025—itself predicted from its in-house economic model and ‘tens of thousands’ of ‘machine learning revenue estimates’. Overall, HolonIQ predicts, the entire ‘Global Education Market’ will be valued at $10trillion by 2030, and argues for greater share of this spending on edtech. And these glossy, persuasive valuation claims travel through its weekly email newsletter to tens of thousands of inboxes each week.

These newsletters and images—as material transmitters of valuation claims—can be considered important market and valuation devices that make the edtech market legible and describable in terms of past, present, and future prospective value. The infographics and interactives HolonIQ produces are especially powerful market valuation devices designed to incite investment interest.

For example, one of its major outputs is the Global Learning Landscape 2021, an infographic and associated report and website, described as ‘An open-source taxonomy for the future of education’. In order to produce the Global Learning Landscape HolonIQ examined 60,000 edtech providers to come up with a global taxonomy of edtech by core functions and individual providers—1,250 are included on this one graphic. This taxonomy is a really catalytic market device—directing both the investor’s gaze and the purchasing decisions of institutions to a selection of the market that HolonIQ has determined to be of most value. Users can easily copy its images to social media too—these are easily tweetable valuation claims designed to incite edtech market excitement and optimism.

The research methodology behind the device is based on data-driven machine learning and artificial intelligence, identifying ‘natural patterns’ and clusters and segmentations in the data that are ‘not biased’ as other established taxonomies of education are. In other words, HolonIQ claims it has found the ‘natural’ shape of the edtech market based on ‘unbiased’ objective AI analysis. Its algorithms perform a significant role in organizing and ordering education into an intelligible shape to which investors as well as customers might then react.

Valuation platforms

So this is where HolonIQ’s proprietary platform comes in. It’s an advanced AI-based valuation platform made up of both human experts from the company’s Intelligence Unit and nonhuman expertise from its Intelligence Platform, which together function as a new form of technoeconomic expertise in the valuation of education. As its homepage indicates, the HolonIQ platform is made up of ‘human and machine learning smarts’ that combine to produce ‘predictive intelligence’. Kean Birch and Fabian Muniesa argue that ‘things become assets’ by being constructed through sociotechnical entanglements of human valuation practices and technoeconomic devices; the HolonIQ platform turns edtech into assets for investment by ascribing them prospective value through predictive technoeconomic machine learning analysis.

An important feature here is that not only is HolonIQ turning edtech into objects for investment with future value. As a for-profit company, the platform and the billions of data points it has indexed are also assets with high valuation potential for HolonIQ itself. It invites clients to ‘rent’ access to the data ‘on demand’ and subscribe to the platform in order to make use of its Analytics Studio, Power Tools, and data visualization studio, for annual costs ranging from $10,000 per year for limited functionality, to $120,000 per year for its full stack of services and support. Subscribing clients get access to interactive tools to model market segments by sector, region, and so on, perform competitor analysis, market mapping, generate market trends, predict VC deals, and more, but only as a paying customer. So HolonIQ also invites its users to share its market intelligence gaze, and to see education in terms of segments, products and valuations that are themselves represented in HolonIQ’s database as millions of data points.

The value of HolonIQ’s valuation platform, then, derives from the prospective value it ascribes to other edtech companies based on its extensive datasets. It even maps the world in edtech. This year HolonIQ has produced top 50 or top 100 compilations of edtech in every global region. It has made education markets internationally intelligible in these graphics, performing a key task of making edtech visible to investors either as single vendors or market clusters with high projected worth. Many of the companies selected for inclusion on the edtech regional maps take to social media to celebrate, or are invited to present their success story at HolonIQ webinars—this isn’t just cataloguing or indexing the world of edtech, but catalysing investment in and reconfiguring the world of edtech.

The maps are produced through a particular apparatus of valuation that HolonIQ calls its Scoring Fingerprint—a methodology that weights the market ‘attractiveness’ of specific edtech segments, rates product quality and team expertise, assesses a company’s financial health and ‘ability to generate or secure funding’, and its momentum, size and market velocity over time, that is, its future prospects for investors. If an edtech company wants to feature on HolonIQ’s maps, it has to ensure its organizational and market fingerprint is strong enough to be measured, scored, and ranked. This is a valuation methodology for prospective market-making as much as retrospective valuation.

Finally, HolonIQ has become a direct edtech investment partner too, mobilizing its valuation platform as an investment device itself. In September it announced a partnership with Rize, a London-based investment company, and the index investing firm Foxberry, to launch an exchange-traded fund dedicated to edtech. Exchange traded funds are like ‘baskets’ of shares that investors then invest in as a whole, rather than in individual companies, with the fund administered by asset management firms. The Rize ETF holds about $5m of edtech assets in 34 companies. HolonIQ’s particular role in this partnership is to translate its global datasets and valuations into the portfolio of companies that the fund invests in, seeking to capitalize on the rapid growth in the value of edtech companies during the Covid-19 pandemic.

Again, the fund is underscored by complex technoeconomic valuation devices. HolonIQ’s Scoring Fingerprint methodology is used to value companies included in the basket, ‘determined using publicly available data provided by the company through its published financial statements, company presentations and/or official earnings conference call transcripts’. The company fingerprint determines whether a company can be included in the ‘Global Education Stock Universe’ first launched by HolonIQ in 2018 (by 2020 it included 250+ edtech companies), from which the basket of companies to be included in the ETF basket is then selected. The result was the production of an Education Technology and Digital Learning Index. It then used one of its ‘core computational engines’, named HUM, to calculate the performance and reach of the top performing edtech organizations in the index. By mapping, indexing and valuing the (future) educational world in these ways, HolonIQ has defined both the ‘stock universe’ and the selected basket that promises the best return on investment. In other words, besides analyzing edtech markets, HolonIQ is itself actively intervening in the world of edtech investment as a new kind of asset-managing financial intermediary in private capital markets.


Overall, as a new financial intermediary and source of technoeconomic expertise in education, HolonIQ itself plays a kind of governing role in the edtech investment ecosystem—shaping and channelling investment towards certain selected futures and associated companies. Its platform may even be considered one of the most powerful educational technologies in the edtech sector. HolonIQ is a meta-edtech platform—edtech about edtech—that taxonomizes the entire global edtech market by various segments, hierarchies and valuations through the deployment of machine learning, and directs funding towards a future vision of education.

Through complex technoeconomic practices and platform algorithms, it makes the edtech field intelligible and attractive to investors, whose investments then shape the fortunes of individual companies and products, subtly shaping practices in the schools where they are used. As a meta-edtech platform with ‘predictive intelligence’ it steers the edtech market towards particular futures that HolonIQ’s experts and algorithms have ascertained to offer high return on investment prospects. In this respect, the HolonIQ meta-edtech platform is itself a highly significant educational technology that is likely to shape educational realities, albeit at a distance from schools or classrooms, to fit prospective market trends that have been predicted with algorithms and machine learning.

These fragments of digital fieldwork surface a number of issues for further study of financial and investment actors in edtech. New studies should seek to examine the practical technoeconomic work of a range of edtech investors and financial intermediaries–from VC firms to portfolio fund asset managers–and the significant market analysis and valuation efforts involved in the edtech industry. Research should more carefully conceptualize how edtech is capitalized and assetized, and how future prospective value is calculated to attract investment by a range of financial professionals, market analysts, asset managers, investors and other intermediaries. Studies might also follow specific investment actions through to the edtech developments they fund–ultimately following the money through to the materialization of edtech products, and on out into concrete practices in schools and universities. Such studies would help to reveal the significant role of financial and market-making organizations to the functioning and fortunes of the edtech sector, and their effects on educational settings and practices.

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