What truly sets humans apart? We are masters of pattern recognition, a skill distinguishing us from much of the animal kingdom. Compared to other apes and most animals, we might seem like feeble, hairless creatures. We're not exceptional climbers, we're not particularly agile, nor are we the strongest of our distant relatives. Yet, our capacity to detect and interpret patterns is extraordinary. We like to believe that our causal reasoning is unparalleled, but even we can stumble into the pitfalls of some confusing correlation must mean causation fallacies. Our minds often perform intricate gymnastics, filling in gaps and sometimes wilfully ignoring our own biases.
Pictured : Adam de Waal, Quantitative Analyst at Prescient Investment Management
![Unravelling the Patterns: The Essence of Data Science](/media/n5vi1xvd/adam-de-waal.webp)
Recognising and understanding our biases and the weights we attach to the factors we deem important (or less important) in aiding our decisions are not too dissimilar to the steps we take to develop our models. This awareness can enhance our comprehension of others' biases and, consequently, their actions. Systematic thinking is central to this awareness, but it means different things to different people. It’s more than just a collection of tools and methods for analysing data; it’s a philosophy that can be applied to every aspect of life, from personal choices to business decisions. People are quick to disassociate when they hear certain terms— ‘data,’ ‘quantitative,’ ‘science,’ ‘AI.’ Terms too abstract to personally associate and visualise. But if you forget about the connotation of what you associate with these otherwise abstract words, you quickly realise that each action, thought, view, opinion, and worldview is the same process. Since the day you came into existence, you started practicing as a data scientist—the only difference is that you have been doing it so long it has become second nature. Subject to the same biases, overweight on certain views and values or underweight on other views and values.
Systems thinking takes us even further. It progresses from merely observing events or data to identifying behaviour patterns over time and uncovering the underlying structures driving those events and patterns. By understanding and modifying structures that do not serve us well—including our mental models and perceptions—we can expand our choices and create more satisfying, long-term solutions to chronic problems. By being mindful of our biases and weights it allows us to approach problems from a more reassured and stoic perspective.
This perspective requires curiosity, clarity, compassion, choice, and courage. It embodies a stoic approach to problem identification and resolution, demanding a willingness to see situations more fully and recognise our interrelatedness and the interconnectedness of elements within our systems. It involves acknowledging that there are often multiple interventions to a problem and championing solutions that may not be popular but are based on sound reasoning and understanding. Through this lens, we can better navigate the complexities of our world, finding patterns and pathways that lead to more effective and enduring outcomes.
The simplistic nature of models and the power of selected features
In any system where outcomes aren't certain, a model is usually a simpler version of real life. We should always be aware that there can be uncertainty. However, you might be surprised that by selecting the right features, a seemingly complex system can often be explained by just a few factors. This principle is vividly illustrated in Prescient’s development of the Prescient Economic Indicator (PEI), a Dynamic Factor Model designed to nowcast GDP.
Economic data, well known for its complexity, arrives with irregular lags and frequencies, often burdened by noise, measurement errors, and subsequent revisions. Almost surprisingly, empirical evidence supports the notion that numerous time series share common dynamics driven by a small set of unobservable factors evolving over time. We can effectively address these challenges through comprehensive data filtration, enabling real-time tracking of the economic state via nowcasting. This approach allows us to extract a trend, which constitutes the basis of what we refer to as the Prescient Economic Indicator.
Drawing Parallel: Systems thinking in daily life
Just as our PEI model filters through vast amounts of economic data to uncover underlying trends, each person engages in a form of data science in their daily life. We observe events, identify patterns, and try to understand the underlying causes of those patterns. When making decisions—whether in our personal lives or business—we are essentially building models based on the data we have, filtering out noise, and seeking meaningful insights.
Like the PEI, we must be aware of the biases that can distort our understanding. Acknowledging and adjusting for these biases can improve our decision-making processes. This systematic approach is akin to how our model aggregates various data points to provide a clearer picture of economic trends.
Furthermore, just as the PEI offers a higher-frequency view of the real economy, providing timely insights, we, too, can strive to be more responsive and adaptive in our lives. We can make more informed and timely decisions by regularly updating our mental models and staying attuned to new information.
Transparency and attribution are also key elements in our PEI model. Understanding the components that drive our decisions and tracing back the influences help ensure that our conclusions are robust and well-founded. This translates to being clear about our thought processes and the factors that influence our choices in our personal and professional lives.
We are all Data Scientists
Every person engages in a form of data science in daily life. Whether recognising patterns in behaviour, making informed decisions based on past experiences, or systematically thinking through problems, we all use data science principles. The PEI is just one sophisticated example of this innate human ability to find patterns, interpret data, and make predictions. By embracing systematic thinking and acknowledging our biases, we can all become better at understanding and navigating the complexities of our world, turning data into actionable insights and informed decisions.
Disclaimer
- Prescient Investment Management (Pty) Ltd is an authorised Financial Services Provider (FSP 612).
Collective Investment Schemes in Securities (CIS) should be considered as medium to long-term investments. - The value may go up as well as down and past performance is not necessarily a guide to future performance.
- CISs are traded at the ruling price and can engage in script lending and borrowing.
- A schedule of fees, charges and maximum commissions is available on request from the Manager.
- A CIS may be closed to new investors in order for it to be managed more efficiently in accordance with its mandate.
- This document is for information purposes only and does not constitute or form part of any offer to issue or sell or any solicitation of any offer to subscribe for or purchase any particular investments. Opinions expressed in this document may be changed without notice at any time after publication. We therefore disclaim any liability for any loss, liability, damage (whether direct or consequential) or expense of any nature whatsoever which may be suffered as a result of or which may be attributable directly or indirectly to the use of or reliance upon the information. For more information visit www.prescient.co.za