We are all on a quest to understand more, guided by our curiosities and driven to seek answers about the world around us. Data drives human ingenuity. We pursue data to uncover the narratives within our surroundings, predict outcomes, analyze patterns, and provide guidance on the unknown. Data collection has always been a standard for decision-making. What was once simply a practice of so-called “hunting and gathering” of information has now evolved into the core pillar of innovation within research landscapes.
If you read our piece, The Complete Guide to Synthetic Data Applied to Research, you already have some context about the evolution of data collection under your belt. And if by chance you haven’t… we think it would be worth your time to dive into the world of synthetic data.
But let’s shift our focus back to the subject at hand. Understanding the history of where data collection traces back to, allows us to grow our appreciation for its profound influence over our society. Spanning from ancient times to the rise of modern data science and machine learning, we are here to guide you on the breakthroughs of this domain and how it informs our choices.
When did data collection first emerge?
The earliest signs of data collection can be traced back to about 20,000 BCE to the mathematical treasures behind the Ishango bone. Our Paleolithic ancestors utilized a baboon tool to mark notches onto bones, sticks, or clay to record trading activity. These numerical record-keeping practices allowed them to perform calculations and make predictions about time, food supplies, harvests, and trade, amongst other purposes. These prehistoric examples of storing and analyzing data uncover the fundamental instincts humans have to gather it to comprehend the world or preserve information for pragmatic reasons.
The next monumental events in data collection history can be found around 2,400 BCE in Babylon. In comes the abacus, the first device specifically used for arithmetic calculations. An instrument compromised of beads and wires, this tool allowed movement of the beads across a frame to record and count decimals. Additionally noteworthy, the inception of the first libraries coincided with this period. These institutions served as markers of our ongoing progress in the significance and value we place on storing vast amounts of data.
Turning points of modern data collection
1660s- The Founding Father of Human Demography
In the latter part of the 17th century, the field of statistics emerged, revolutionizing data collection practices. John Graunt, based in London during the 1660s, pioneered the application of statistical analysis to data. The devastation wrought by the bubonic plague stressed the necessity to probe into numerical data and demographics. Investigating the reasons behind mortality rates across different age groups, Graunt broke new ground. He was now able to forecast life expectancies, offering new insights into gender-based death rates and developing early warning systems for plague outbreaks. His demographic studies, documented in his publications, laid the groundwork for modern demographic research. Moreover, it solidified statistical analysis as a fundamental element in decision-making and predictive modeling based on existing data, advancing the field to a higher level of sophistication.
1800s- Hollerith’s Machine Transform Census Sampling
Prompted by the US Census Bureau, a surge of technological advancement in data processing emerged. Populations were expanding rapidly, and the challenge of conducting the census was congruently complex. With projections suggesting it would require nearly a decade to analyze the data gathered every ten years, it became apparent that conventional data processing methods would become obsolete by the century’s turn.
Herman Hollerith, a German-American engineer employed by the bureau in the 1880s, drew inspiration for a tabulation machine from the practice of train conductors punching tickets for passengers. Expanding on a punch card machine model devised by Joseph Jacquard, Hollerith invented the Hollerith Tabulating Machine. This machine punched holes in specific locations on sturdy paper cards and allowed brass rods to electronically record the data as it moved through it. This groundbreaking innovation condensed a decade’s worth of work into just a few months. Widely regarded as the father of modern automated computation, Hollerith later established IBM, setting a benchmark for the advancement of modern computing technologies. Early computers adopted his concepts of binary code and punch cards, reshaping not only data collection but also propelling computerizing technology into a new era.
Shifting from ancient data-gathering techniques to the collective understanding and valuation of mass data storage to transitioning into a technologically-driven era dominated by computing, we have established, as humans, a drive for information. Whether trivial record-keeping of daily activities or extensive research into mass societal events, this practice is not only instilled within us, but has also characterized the realities of our modern research spaces.
Having established a physical capacity to record data massively and recognized it as a tool for mastering vast amounts of information to study, we entered a new era at the turn of the century. Advancements in both methodology and technological applications of data collection marked this period.
1900s- Consumer insights industry evolves from in-person interviews to phone calls
George Gallup, a journalism professor and marketing expert, tapped into the realm of surveying, eventually pioneering the methodology of phone sampling. Amidst the economic and political instability of 1930s America– the Great Depression– new communication channels emerged through which public opinion found expression. Radio broadcasts, magazines, newspapers, and films mirrored prevailing despair. With an eye for societal connections and public sentiment, Gallup recognized an opportunity to utilize face-to-face interviews as means of investigating these predominating trends. Prioritizing unbiased research, Gallup transformed such practices by laying the foundation for objective inquiry. Refusing to engage in sponsored polling, his authentic findings via face-to-face interviews enabled him to accurately forecast Franklin Roosevelt’s victory over Alfred Landon in the 1936 presidential election. Around the 1980s, Gallup adapted to contemporary trends by embracing the telephone, the latest technological tool. With telephones becoming prevalent in American households, conducting national surveys became significantly easier, enabling widespread access to information. Through his nonpartisan, representative, and precise surveying, Gallup solidified his legacy and became a household name in the realm of research. Setting a new standard for consumer research, Gallup stimulated the industry’s profitability.
2000s- Emergence of the Internet and online sampling
Transforming the modern data collection landscape, the vision for digital connectivity via expansive online platforms materialized. The birth of the Internet in the 1990s quickly became instrumental in optimizing data collection processes. Moving away from conventional approaches that had defined research, the Internet rapidly gained traction as a dominant means of gathering data.
Setting a foundation for scalable data collection, online surveys were primarily extensive text-based web pages in their early stages. Recognizing the vast potential to reach a global audience instantly, researchers and organizations quickly saw the opportunity. Online surveys revolutionized data collection by bringing public opinion, consumer preferences, and social trends to our fingertips with just a click. The diverse respondent pool, ease of distribution, anonymity, and cost-effectiveness were significant advantages of this new method. As the Internet evolved, new features like checkboxes, drop-down menus, images, and videos were introduced, enhancing user experience and engagement. This increased interactivity and the modern medium of the Internet boosted response rates and enabled comprehensive data collection.
Suddenly, online surveys became an adaptable and indispensable tool for tapping into public opinion. Government agencies, researchers, organizations, and businesses could tailor these surveys to diverse industries or niche topics to gain valuable insights. Online surveys democratized modern market research by streamlining survey creation and analysis through technological solutions. As data analysis tools became more sophisticated, another game-changing phase emerged with the rapid rise of mobile devices. Surveys became accessible anytime, anywhere, allowing respondents to participate with greater ease.
This shift to mobile accessibility expanded the reach to new demographics and improved response rates. Data collection advanced as communication spread, geographical barriers diminished, and consumer research adapted to the evolving digital lifestyle of the early 2000s.
2020s - Artificial Intelligence– where we are today and what the future holds
Despite these immense technological advancements, an even bigger innovation was on the horizon. The relentless technological pursuit led to the emergence of artificial intelligence (AI) and machine learning (ML). These technologies revolutionized data insights, enabling features such as interpretations, text mining, streamlined analysis, pattern recognition, and future trend predictions. AI and ML algorithms extracted actionable insights from vast amounts of data, giving researchers a competitive edge. Building on this foundation, generative AI brought a new dimension to surveys, enhancing their creation and analysis, and amplifying respondent interaction through synthetic data.
As we stand on the brink of this new frontier, synthetic data is being harnessed to dive deeper into complex segments and uncover insights previously out of reach. In the qualitative realm, virtual agents and audiences are delivering insights at unprecedented speeds, with numerous new vendors entering the market. In the quantitative realm, where statistical guarantees are crucial, Fairgen is a pioneer, offering predictive synthetic respondents with statistical assurances. Our synthetic sample boosters at Fairgen have proven to show, on average, that they are worth three times the amount of real respondents; check out our foundational white paper to understand more.
This breakthrough in artificial intelligence has been reinventing the market research industry, business strategies, and product development processes. Synthetic data introduces unparalleled levels of efficiency, creativity, and competitiveness, both as a research assistant and synthetic respondent. Generative AI platforms enhance the research process by aiding in survey ideation, generating hypotheses, testing scenarios, and planning complex methodologies faster and more creatively than before. Additionally, these AI-driven research agents manage interviews, virtual focus groups, and data processing tasks such as translation, summarization, data visualization, or other analysis functions. GenAI technology facilitates the creation of near-real synthetic respondents, offering significant value to the market research industry, which often grapples with low-quality, fraudulent respondents and scarce data in niche areas. Despite the ongoing debate and mixed opinions on synthetic data, this field is closely monitored as the next significant technological advancement.
We will leave you with this…
The evolution of data collection reflects the changing needs and behaviors of humans. From the simple record-keeping of hunting and trading activities with the Ishango bone to the sophisticated realms of generative AI, the landscape of insights has dramatically transformed. By embracing trust, transparency, control, and education, we can collectively advance into the next chapter of history.
