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Facing the tyranny of metrics

13 June 2019 Myra Knoesen

The obsession with quantifying human performance threatens business, medicine, education, government, and the quality of our lives.

At the recently held Investment Forum Leonard Kruger, Portfolio Manager at Allan Gray, talked about the threats that exist when making investment decisions in the face of a tyranny of metrics.

Accountability and transparency

“It is a welcome trend that not everything that can be counted counts, and not everything that counts can be countable,” said Kruger.

“If we know that something is being measured, it affects how we behave. So, if I am told that I will be measured solely on my investment performance and returns as a manager, I might be inclined of the risks I am going to take of achieving this outcome,” continued Kruger.

“In the real world, the fixation on numbers and metrics can be detrimental. However, metrics are here to stay and are increasing in numbers, we just need to be aware of the pitfalls,” he said.

Kruger then went on to give an example of how a fixation on numbers can be detrimental.

The McNamara fallacy

The McNamara fallacy is named after Robert McNamara, the President of Ford and former Defense Secretary of the United States during the early years of the Vietnam War.

His strategy for fighting the war was based on what he developed at Ford where everything was measured and quantified. He argued that, “Things you can count, you ought to count”, including body count.

“The authorities only measured what could be measured. The McNamara fallacy is when a decision is based solely on numbers (e.g. metrics or statistics) and all qualitative factors are ignored. Blindly following, it makes us blind to what is really going on. We need a rationality filter,” emphasised Kruger.

Common pitfalls when fixated

The following, Kruger said, are the pitfalls when you are too fixated on metrics:

  • Short-termism - an excessive focus on short-term rather than long-term performance;
  • Guidance reliance - too focused on metrics for guidance;
  • Attribution substitution - when an individual has to make a judgment (of a target attribute) that is computationally complex, and instead substitutes a more easily calculated heuristic attribute.
  • Abstract versus tacit knowledge - Abstract knowledge is observable, recorded, communicated, etc. and tacit knowledge is knowledge embedded in the human mind through experience etc.
  • You are prone to data mistakes - The data mistakes include cherry picking (the more data you have available, the more likely you are to cherry pick), data dredging (you have data and you just add in things to this data), survivorship bias, false causality (when two things happen at the same time, you make an assumption they are related), gamblers fallacy and overfitting (the more data there is, the more you over fit it to get to a possible solution).

“Investment results are more dependent on investor behavior than on fund performance. Do not become over fixated on metrics in the short-term but focus on what it is you are trying to achieve, as a manager or adviser, for long-term wealth creation for your clients,” highlighted Kruger.

Making sense of large data sets

“Technology and algorithms are changing our lives and how we use these to invest. Data holds the potential to create an information advantage. In 60 seconds, online, there are 156 million emails sent, 87 000 hours of Netflix videos watched, 350 000 tweets sent, 29 million Whatsapp messages sent, 243 000 photos uploaded to Facebook and 3.8 million Google searches,” said Javier Rodriguez, Managing Director and Head of EMEA Client Portfolio Management at Goldman Sachs Asset Management.

“Algorithms are critical to making sense of large data sets, but only 2% is analyzed and 98% is not analyzed. Consider a Google search. There are 130 trillion webpages on Google. Only to go through the titles would take 12 000 000 years,” he added.

Data-driven investment decisions

“Behind the algorithms and computers are people researching and testing fundamentally based, economically motivated signals that drive investment strategies. Quantinomics gives a behind-the-scenes look into how technology can be leveraged and apply human judgement to make data-driven investment decisions,” said Rodriguez.

“Systematic processes start and end with a human. Researchers search for economically motivated datasets that are predictive of future stock returns,” said Rodriguez.

“A disciplined data driven approach can uncover investment opportunities. Through data analysis, companies that have consistent revenue streams, sustainable business models and are well-governed (multiple forms of alternative data can serve as early indicators of earnings and sales growth) can be identified. Alternative data sources can be used to analyze market themes and trends,” he concluded.

Editor’s Thoughts:
As Kruger mentioned, metrics are here to stay and are increasing in numbers, we just need to be aware of the pitfalls. We are also reminded that multiple alternative data sources can uncover investment opportunities. Do you believe the fixation on numbers and metrics can be detrimental? Please comment below, interact with us on Twitter at @fanews_online or email me your thoughts myra@fanews.co.za.

 

Comments

Added by Paul Reed, 13 Jun 2019
A good article indeed.
Nothing worse than a blind quant or bean counter either.
Possibility exists however for a qualitative extract from a quantitative result be it a metric or data pool.
Guess we are not quite there yet.
As in AI,is emotive intelligence possible?



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