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Let us begin by remembering what the datafication promise was: productivity, efficiency, and transparency with the help of tools that transform organizations into “data-driven enterprises.” Datafication was all about making better decisions based on aggregated information.
But enough time has passed since this concept’s launch in 2013 that we can sit down and talk about whether it delivered on these promises. Is datafication just another buzzword, or does it still create viable investment opportunities?
Let’s take a look at datafication, where it stands today, and the challenge of finding new investment opportunities before we get into the weeds of what types of technology and startups investors should be looking for.
What is datafication?
According to Technopedia:
“Datafication refers to the collective tools, technologies and processes used to transform an organization to a data-driven enterprise… an organizational trend of defining the key to core business operations through a global reliance on data and its related infrastructure.”
But datafication is also a process of turning certain workflows and business aspects into data. With the entrance of big data, data analytics, and AI, today's business landscape requires that decisions and strategies are data-driven, and datafication tools can help companies process mounds of information and receive actionable insights and predictive analytics. The term “datafied” refers to an organization that has implemented datafication in its operations.
Datafication in 2022
The truth is that datafication isn’t magic. Like anything else, it can work wonders in one context but be underwhelming in another. Let us give an example of the latter. In their noteworthy article exploring the impact of datafication on Danish healthcare workers, Klaus Hoeyer and Sarah Wadmann reveal that datafied organizations in this sector have proven to be problematic. According to their findings, Danish physicians felt that datafication in healthcare took away from patient care, professional judgment, and goal orientation.
The main issue with this sector becoming "datafied," it seems, was that “Danish healthcare organizations have produced a data assemblage where data can operate as symbols of knowledge (rather than pathways to knowledge).” And this is a common “danger” with any technology - losing sight of its purpose. Datafication is indeed powerful, but only when employed correctly and as a tool rather than a symbol of knowledge.
Still, datafication and investment opportunities in datafied tech are, in fact, auspicious - in the appropriate context, with the right approach, and with tools that are suitable for the job. After all, in the same article, Hoeyer and Wadmann argue that there is no ontological difference between “meaningful” and “meaningless” work, in this case referring to datafication and the accompanying bureaucracy. Rather, they say that– “What is considered meaningless in one place or situation is typically considered meaningful for others or in other situations and places.”
This is also true of datafication - despite this case study, there are tons of successful datafication examples. Of course, when investors are finding investment opportunities, they need to consider the technology, the industry, and the context. Essentially, the answer to the titular question is in the hands of the actors and how they wield the power of datafication.
Challenges and business investment opportunities in datafication
For investors, finding investment opportunities in the field of datafication can be tricky. Data is precious capital, but we already saw that it doesn’t always work, so how can an investor find a company that harvests the true potential of datafication and applies these processes successfully?
Discovering the best business investment opportunities is a long and arduous process– going through startups, checking the founders’ backgrounds, and future-proofing the technologies they offer. Due diligence takes time, and acquisition targets are aplenty.
For investors to stay ahead in the market, they need a competitive edge. They need a method that brings in a consistent flow of new investment opportunities that are of high quality. So how can they find new investment opportunities with better accuracy and less effort?
We won’t tell you; we’ll show you. As we go through different datafication technologies, we’ll also share some startups that we found using various features offered by Valuer.
Datafication technologies and new investment opportunities
Investing in AI and ML
Without AI, datafication is just data without meaning, and without data, there’s no ML - data feeds machine learning processes. That’s why investment in AI development is a big part of turning companies into datafied entities. All prominent datafication examples - Netflix, Amazon, Uber, Fitbit - combine the resourcefulness of big data with the power of AI to provide users with products that are smart and reliable. And a company doesn’t need to be a unicorn to flourish, thanks to the efficiency these two technologies combined can provide.
Needless to say, investing in AI is the first go-to solution for datafication. AI is not just a thing of the future, and it most definitely isn’t just another buzzword. Both long-standing companies and promising AI startups are prime business investment opportunities for companies looking to become datafied or investors looking to diversify their portfolios. Big data and AI are both future-proof components of automation.
AI companies to invest in
To discover AI companies to invest in that fall under the auspice of datafication, we used the "Explore Industries" feature. From there, we selected the Data & Analytics industry. This feature helps you to visualize the landscape of a particular industry by placing all startups belonging to one of its sub-industries on a cluster map. The startups are color-coded based on the sub-industry and clustered together or spread apart based on how similar their descriptions are.
Once inside the Data & Analytics industry cluster, we selected “Artificial Intelligence” to see only the AI startups that use data to uncover trends, predictive analytics, deep learning, diagnoses, or whatever else in datafication processes.
Here are some AI startups we found:
In your own search, you could apply filters that suit your needs. For instance, you can adjust the stage of the company, the year founded, team size, location, funding amount, and so on.
Investing in sustainability and environmental data
First things first - what is sustainable investing? Sustainable investing, or ESG investing, is when the investor considers ESG factors (environmental, social, corporate governance) before funding a startup or business venture.
Sustainable investing is closely connected to responsible product management, which includes sustainability metrics. With sustainable investing, a firm is evaluated based on its efforts to make a positive contribution to the world, as human activity has brought the environment to the point of crisis. But even beyond ethical investing, sustainability is profitable. Increasing numbers of governmental bodies are likely to impose more regulations regarding sustainability practices. So it’s safe to say that sustainable investing will give investors and companies an edge when it comes to complying with existing and upcoming regulations.
What’s more, consumers are demanding sustainable products and services. So in several aspects - environmental care, consumer interest, and long-term financial gain - sustainable investing is a great business investment opportunity.
But how does datafication fit in the picture? Datafied organizations can use environmental data to measure their eco-impact, find ways to reduce their carbon footprint, and become more efficient overall. Let’s take a look at some startups that help companies integrate environmental data to "SDG up" their business strategies, materials, and outcomes, as well as how you can use our platform to do the same.
Green companies to invest in
We used the "Discover companies using specific technologies" feature to find green companies to invest in. This feature allows users to type in the exact sort of company or solution they're looking for right into the search. The platform then uses NLP to understand the search input and return relevant results.
Since we wanted to find datafication companies that help businesses collect data about their effect on the environment to boost sustainability, we simply type this into the search feature.
Then, we were given the option to add more context by selecting relevant industries. We chose “Data & Analytics,” “Information Technology,” and “Sustainability.” Some of the companies returned include:
Big data investments
There’s no getting around big data - and datafication not only makes use but also makes sense of big data in datafied organizations. As early as 2013, Mark Lycett cites big data as both an underlying resource and the impetus for business intelligence. All those unicorn examples we talked about in our AI section - Fitbit, Netflix, etc. - rely on big data to customize the user experience, something that’s played a huge role in their success.
But big data is everywhere - it’s become crucial in sectors such as automated manufacturing, entertainment, social media platforms, education, healthcare, banking and securities, retail, transportation, and energy. These are only some of the sectors where for a business or organization to be adequately datafied, it needs to rely on the giant pool of information that’s offered by big data companies. Far from being a "techy" buzzword, big data has been the key to success for businesses across industries.
[Related Article - The Top Big Data Startups in Europe]
In essence, big data investments are not a question of whether we should, but rather a question of who we should give our money to. So let’s take a look at the big data companies that our platform discovered.
Big data companies to invest in
First, we went back to the “Explore Industries” feature, then chose Data & Analytics, and selected only Big Data companies. Some of the results included:
This time, we also took a spin with the "Discover look-alikes" feature to discover even more companies. This feature can be particularly useful for investment professionals that need to easily spot new investment opportunities. What this feature allows you to do is find startups that are similar to a particular company, and by similar we mean that it uses or develops a similar technology and or solution, or its within the same industry and sub-industry.
So, we used one of the big data companies we discovered in our previous step to find similar startups to the company Massive Analytic. Here are some of the results:
Is datafication still creating new investment opportunities?
The datafication promise holds, and as you can see, the market offers many new investment opportunities. But, as we cautioned initially, it’s important to implement datafication in the right place and in the right way. Just being datafied isn’t enough - what matters is making the most of it. The sector is essential, and the method is important, as well as the way you employ and integrate the tool.
We gave some datafication examples that covered popular branches in the field. Investing in AI and ML, sustainable investing, and big data investments all have a lot to bring to the table, not to mention that these technologies and directions grow more powerful every day. Hopefully, with the help of our platform, you’ll be able to find startups that help datafication deliver on its promise.
