By Ferdinand Steenkamp
Although hindsight is often 20/20, interpretations of the past are rarely objective or neat.
Take, for instance, the rise of social media. In the mid-2000s, when platforms like Facebook began to emerge, their growth was far from a guaranteed success.
Early reactions were varied: some dismissed these new forms of online social interaction as fleeting fads, while others over-invested, placing undue faith in the endless promises these platforms seemed to offer.
The stark contrast in the potential seen in social media can perhaps be best exemplified by Myspace.
Acquired for just under US$600 million in 2005, Myspace was eventually sold six years later at a staggering 94% loss.
Today, social media undeniably plays a central role in our online experience, but the reality is far different from the early predictions.
This is not to suggest that social media has failed to deliver — it most certainly has — but in ways that few could have predicted.
Social media has become a tool for engagement and connection, not necessarily in the grand, world-changing ways it was once expected to.
This phenomenon is not unique to social media. In the tech world alone, innovations like the Internet of Things, the Metaverse, augmented reality, generative AI, cryptocurrency, and blockchain were all hailed as ‘revolutionary.’
Yet, none of them have truly revolutionised industries as anticipated. Instead, like social media, these technologies have found their place within existing frameworks, often serving as new marketing tools or as fresh coats of paint on established ideas, leaving their full potential largely untapped.
Big Data
Ironically, many of these so-called “disruptive” technologies rely on an idea that itself has become deeply embedded in modern business operations: big data.
As the number of data sources continues to expand, the desire to leverage this wealth of information to better understand the world — whether that’s customers, suppliers, or markets — has intensified.
Yet, like the technologies mentioned before, big data is often seen as either a magic bullet or a necessary evil — something businesses must adopt to avoid being left behind.
As a result, significant time and money are invested in acquiring the best data sources, and, as the term suggests, big data is frequently associated with vast amounts of information drawn from many different sources.
The outcome? Companies now face an overwhelming glut of data.
The average business now relies on five or more data sources, and some even draw from upwards of 20 different databases.
But here’s the catch: more data doesn’t always equate to better insights. This paradox has led to what’s known as data fatigue, which is becoming an increasing challenge for businesses and decision-makers alike.
At its core, data fatigue occurs when the sheer volume of data overwhelms decision-makers, leaving them swamped by irrelevant information and noise. Even when businesses manage to analyze and interpret the data, they often fail to account for the inherent biases in large datasets. For instance, data mining — when data is combined, manipulated, and scrutinized — can yield results that appear statistically significant, but are far removed from any practical or real-world context.
Even if these insights are mathematically sound, they may not be economically, financially, or socially relevant. Making business decisions based on such disconnected insights — cobbled together like a mathematical Frankenstein — inevitably leads to poor outcomes, frustration, and potentially even failure.
Streamlining Decision-Making
Ultimately, data on its own is not inherently valuable. It becomes useful only in the hands of those who know how to harness it effectively. Much like a carpenter with a workshop full of tools, having access to numerous data sets doesn’t guarantee the creation of a functional strategy.
But when the range of tools is streamlined to include only those that are most relevant, the path to success becomes clearer. Similarly, businesses must simplify their decision-making processes, avoiding unnecessary complexity and focusing on the tools that will help them succeed.
In this context, businesses — like skilled carpenters — need not add further layers of complexity by introducing superfluous options that are neither practical nor relevant.
What they require is a focused toolkit that allows them to make decisions swiftly and effectively in response to shifting market conditions and evolving strategies.
Unless you are Amazon, Facebook, or any other large ever-present corporate entity, big data, as you knew it, has been a failure — not as an idea, but in its execution.
We should be adapting big data ideas to our present realities and needs, and not to that of actors operating in different markets and industries.
Data, and its ability to illuminate trends, ideas, and areas of concern remains inherently useful; but without the guided and purposeful curation of our inputs, the outputs will remain inefficient and obstructive.
For businesses in South Africa, there has never been a more critical time to start streamlining. As we look to the near future, companies that have a clear data strategy for 2025 are likely to be the ones that not only avoid the pitfalls of looming erratic decision-making (by those within and beyond our own borders) but also possess the agility to navigate the uncertainties that lie ahead.
Tech trends in business evolve as their uses, advantages, and disadvantages are revealed, often emerging as a more nuanced and powerful tool than what was originally imagined. It is time to stop clinging onto the idealised and outdated idea of big data and take the needed step towards modern and competitive practices.
Ferdinand Steenkamp is a Co-founder of Tregter.
BUSINESS REPORT