Too Good to be True

Filters to Protect against Folly

If it seems too good to be true, it probably is!

We will start today’s post with three real-life stories about people who fabricated a reality and convinced the world around them to believe it. You probably know the stories already, so I will keep them short.

All three stories have one common theme. Human Folly.

These are stories of outright fraud. But the objective of highlighting them is not to dissect the perpetrators and how they did it. It is to reveal something important about the outside world, on whom these stories worked for a long time.

Story 1

Elizabeth Holmes founded Theranos in 2003. Her stated mission was to revolutionise diagnostics and democratise healthcare. With a single finger prick and a few drops of blood, her company and its technology could perform hundreds of tests on them. The story was irresistible. Many Private equity funds and star investors invested in it.

Theranos was backed by a star‑studded Board comprising Henry Kissinger (former U.S. Secretary of State), Richard Kovacevich (former CEO of Wells Fargo), William J. Perry (former U.S. Secretary of Defense) and many other luminaries.

With all these factors and the media adoration, the story drove Theranos to a $9 billion valuation.

There was just one problem.

The magic never worked inside the labs of Theranos. The Company’s devices could run only a small fraction of the tests it claimed. Many tests based on finger prick samples were done on hacked Siemens machines, with dilution of the sample, which made them completely unreliable. In practice, most patients ended up giving blood through the conventional method of drawing it from veins. Those samples were processed on ordinary machines bought from other companies. The results from the Company’s devices were inaccurate on most occasions.

As the scrutiny grew, the gap between the narrative and the reality widened. In 2018, Theranos ceased its operations and announced its formal corporate dissolution. In 2022, Holmes was convicted of fraud and conspiracy and sentenced to more than 11 years in prison.

Story 2

People trusted Bernie Madoff for several decades. He provided them steady 10–12% returns in all markets, year after year.

Many wealthy investors and institutions wanted to invest with him. His resume was also impressive. He was a Wall Street veteran, trusted insider and at one time NASDAQ chairman. His reputation smoothened any anomaly that was ever noticed by anyone.

People believed “If he is cheating, then the whole system is broken.” So, they stopped asking questions.

There was just one problem.

Behind the closed doors, there was no real investment strategy for his clients. There were no actual trades done with their funds as promised. It was just a classic Ponzi scheme. Account statements were fabricated and old investors were paid with new investors’ money.

When the financial crisis hit in 2008, markets crashed and investors rushed to withdraw money from everywhere. They were in need of their money placed with Madoff as well.

There was no enough new money to pay these investors and the Ponzi scheme collapsed.

Madoff was arrested, convicted and sentenced to 150 years in prison.

Story 3

Back home in India, a promising home-grown company, Manpasand Beverages, caught the attention of investors on the back of a beverage success story in rural areas. While competitors targeted metro cities, Manpasand focused on tier-2 and tier-3 cities and rural markets. By 2018, the company claimed to have reached hundreds of thousands of retail outlets, multiple plants across India and strong double digit revenue growth.

The annual report shared impressive numbers. The quarterly conference calls shared upbeat commentary on the performance of the Company often stressing that they understood Bharat (rural India) better than the MNCs.

Investors loved it.

There was just one problem.

In 2018, Deloitte resigned as auditors of the Company just before the announcement of results. Questions were raised about GST, quality of revenues & cash flows and the reliability of Company’s numbers.

Investigations later uncovered fake units, bogus GST credits, and manipulated books of account. The grand rural distribution story was, to a large extent, fabricated only on paper whereas on‑ground reality was completely different. As the facts were revealed, the stock collapsed, executives were arrested, and the “India’s next FMCG star” narrative went into dust.

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Whether it was a drop of blood, a steady 10-12% return, or a rural beverage empire, the outside world believed the numbers and the narratives without checking the on-ground reality.

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The Filters Against Folly

Garrett James Hardin was an ecologist and microbiologist. He wrote extensively about human overpopulation and the tragedy of the commons - the idea that innocent, self-serving actions by individuals can inflict massive damage on the environment, leaving society at large to pay the price.

He made another, very important contribution. He provided a very useful mental map to counter human folly. The best part is, this mental map can be applied to almost anything. It acts as a filter against the kind of human folly we just saw in those three stories.

In his 1985 book, “Filters against Folly”, Hardin provides three important filters to protect us from our blind spots. The Literate Filter, The Numerate Filter and what he calls the Ecolate Filter.

I have taken the liberty to slightly adapt what each filter means to fit them universally. They go like this.

The Literate Filter – What are the Narratives?

The Numerate Filter – What are the Numbers?

The Ecolate Filter– “And Then What?” Second Order Effects and the fact that everything is connected to everything else.

Today we are going to focus on the first two. The third, the Ecolate filter, we will reserve for another post.

Possible, Plausible, Probable

To apply these first two filters effectively, I am going to borrow a very smart framework from Professor Aswath Damodaran. He uses this specifically for the valuation of companies, but the idea is so powerful that it can be adapted to test almost any hypothesis.

When combined, the Literate and Numerate filters allow us to test a story using three distinct questions.

Is it impossible?

Is it implausible?

Is it improbable?

Notice the phrasing. We are not asking:

• Is it possible?

• Is it plausible?

• Is it probable?

We are deliberately asking these questions in the negative. Our minds are masters of self-deception. If you ask your brain, ‘Is this possible?’, it will try to find the evidence to confirm what you already want to believe.

By forcing yourself to ask, "Is it impossible?", you change the task. You start hunting for the flaws. You force your mind to work hard to actively seek disconfirming evidence.

Putting the Filters to the Test

Let’s apply these negative filters to our stories.

For the Theranos story, the science for conducting hundreds of tests from a single finger‑prick sample had not been demonstrated anywhere. There was no peer‑reviewed validation of Theranos’s own devices and methods. The regulators later flagged their ‘Nanotainer’ vials as unapproved devices. FDA had approved only one test on their device. The experts had articulated the limits of micro-volume testing. The claim made by Theranos of running hundreds of accurate tests from one finger‑prick sample was practically near‑impossible, or at the least, implausible based on the available evidence.

For Madoff, the returns of 10-12% that he was providing for years were unusually consistent and disconnected from the market trends. He was reporting a consistent return of about 1% a month, i.e., roughly 10-12% per year with almost no losing months. The story was the same even during the major crashes. This was mathematically inconsistent and hence, was implausible. It was absolutely too good to be true.

For Manpasand Beverages, independent market data and channel‑checks on distribution and sales was not in sync with the claims the company was making. Comparing the retailer surveys and physical presence with reported rural penetration and revenue, it was highly improbable that the business was as large in non-metro areas as management communicated.

The Skeptics

It is possible to think that we are trying to fit the solutions of what we now know to the problem, with the benefit of hindsight.

But, these were the same investigations done by skeptics while the stories were still unfolding. They were applying multi‑disciplinary thinking, science, simple arithmetic and on‑ground verification to counter the narratives at the time when they were being told.

In fact, it is intriguing that the stories of Theranos and Madoff continued for so long, when there were multiple instances, where they could have been exposed much earlier. Both Holmes and Madoff, could continue their stories for so long without being questioned due to their personal charisma, their tactful handling of situations, the blind trust of others and in case of Theranos, threats of legal action against any potential whistleblower.

Much before Theranos collapsed, clinical scientists and lab professionals raised the concerns on impracticality of performing large number of blood tests using blood pricked from a finger and lack of evidence to support the claims made by Theranos.

Eventually whistle-blowers like Tyler Shultz and journalist John Carreyrou flagged that the technology was producing erratic and unreliable results, most tests were not actually run on the proprietary devices and the company’s bold claims lacked peer‑reviewed scientific data and FDA backing.

Many years before Madoff was arrested, a financial analyst named Harry Markopolos submitted extensive evidence to the SEC multiple times, proving mathematically that Madoff’s returns were not in sync with the market and they could have been reported only by fraud.

Long before the auditor resigned at Manpasand Beverages, Amit Mantri from 2point2 Capital had already published an extensive research report titled “The Curious Case of Manpasand Beverages,” highlighting the disconnect between Company claims and market data.

All of them possessed the discipline to use the Literate and Numerate filters, asking the hard, negative questions.

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Filters Against Euphoria

Literate and Numerate filters are useful in many other areas, not only fraud. They are equally relevant during the times of euphoria.

Let’s take the case of Suzlon Energy in 2005.

Suzlon was the ideal stock in 2005. The India rising theme was in the air. Climate change was on the agenda. Wind energy was projected as the clean, scalable solution for the future.

Suzlon was a home‑grown turbine maker aiming to spread its wings.

Order book was consistently growing, Capacity was consistently expanding and the stock kept climbing new highs. Investor presentations pointed to its huge potential riding on future installations, new wind corridors and policy support. It all sounded like writing on the wall.

Yet very few people were asking the basic question: “Where will all these turbines be installed?”

To justify the projections and for the valuations to make sense, what was needed was an ample supply of high‑quality wind sites, land, grid, logistics, and execution at a massive scale. The problem was, India’s geography, land use patterns and grid infrastructure imposed significant constraints, making the aggressive projections highly improbable at the pace implied in the valuations.

Unlike Theranos or Manpasand, in Suzlon’s case, the technology worked and the manufacturing of turbines was real. But the expectations priced into the stock were too good to be true.

At the height of the wind euphoria, it was already possible, using capacity and land calculations, to see that Suzlon’s stock price was not factoring the constraints and some very real bottlenecks in land acquisition and grid connectivity.

Eventually, the valuations fell in sync with ground realities. Cost overruns, debt, policy shifts, tightening economics, all played their part.

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The Next Narrative

These filters are not just for investing. Once we see them, we start spotting Literate and Numerate failures everywhere. Health advice, public policy, news headlines, even decisions in our personal life.

A hot crypto story, a get‑rich‑quick scheme, a miracle weight‑loss promise, a “financial freedom” pitch, public trials by media, grand slogans like “Eradicate Poverty” or “Free Food for All.”

Different domains but same pattern. Most of these stories start to fall apart the moment we apply Hardin’s filters and ask:

What is the narrative, really? And what are the numbers, exactly?

In the HBO documentary on Theranos - The Inventor: Out for Blood in Silicon Valley, Dan Ariely, a renowned behavioural economist, explains our vulnerability to good narratives:

“The reality is that data just doesn’t sit in our mind, as much as stories do. It’s almost the glue that takes all of the data. And even more important, stories have emotions that data doesn’t. And emotions get people to do all kinds of things, good and bad. And if you think about the people who invested in her with very little amount of data, it’s about having an emotional appeal and about having trust, and believing the story, and being moved by this, and being able to tell themselves a story.”

Because our brains are wired this way, there will always be a next time. Right now, fresh narratives are building in the markets. Around AI, new energy, or biotech that are already demanding ambitious valuations and hinting at effortless riches.

The next time you find buzzwords like “disruptive,” “democratise,” “pivot,” “flywheel,” or “synergies” in a management presentation, stop and apply the Literate filter. What do these words actually mean? What is the narrative, really?

And when the very next slide shows a “hockey-stick projection,” a “trillion-dollar TAM (Total Addressable Market),” “hyper-growth phase” or “Adjusted EBITDA,” stop and run them through the Numerate filter. What physical world should look like to make these numbers true?

Make sure you do the fact check and math before you believe the next story.

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There is still one important filter we need to explore that Hardin suggested. It is not limited to busting just the too good to be true stories. It is a very useful tool to approach any kind of judgment.

The Ecolate Filter.

Applying that filter has the capability to bust many of the myths which look possible, plausible and probable. In reality, we ignore the most important factor – The Second Order Effects! The fact that everything is connected to everything else!

That is the subject matter of another post.

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Useful resources

Filters Against Folly - Book by Garrett Hardin

Narrative and Numbers: The Value of Stories in Business - Book by Aswath Damodaran

Bad Blood: Secrets and Lies in a Silicon Valley Startup - Book by John Carreyrou

The Inventor: Out for Blood in Silicon Valley - HBO Documentary (Available in India on Jio Hotstar)

Madoff: The Monster of Wall Street - A Netflix Documentary

“A Curious Case of Manpasand Beverages” - A blog post by Amit Mantri on Manpasand Beverages (Click the URL to read the post)

The Man Who Mistook A stock For His Wife - A Blog Post by Prof Sanjay Bakshi on Suzlon (Click the URL to read the post)

Note - The part on Suzlon Energy has been provided for illustration purpose only and deals with the valuation during 2005- 2008. It does not comment or infer any views about the current valuations of the stock or business prospects of the Company.