Startup Professionals Musings: 5 Strategies For Startup Partnering To Win Long Term

via Startup Professionals Musings: 5 Strategies For Startup Partnering To Win Long Term

Wisdom Quotes

To get success you have to get started.
The secret of getting ahead is getting started. (Mark Twain)
There’s only one you in the entire world, so don’t try to be somebody else.
Today you are you! That is truer than true! There is no one alive who is you-er than you! (Dr. Seuss)

When a Man Took a Joke in a Pepsi Ad Seriously, Chaos Ensued


When a Man Took a Joke in a Pepsi Ad Seriously, Chaos Ensued

This speaks to what can happen when we don’t do a reasonable check on the math. Also a good example of arbitrage.

“In 1995 Pepsi ran a promotion where people could collect Pepsi Points and then trade them in for Pepsi Stuff. A T‑shirt was 75 points, sunglasses were 175 points, and there was even a leather jacket for 1,450 points … Apparently, this military aircraft could be yours for 7 million Pepsi Points.”

What I’m Thinking About

Listening is difficult because it involves suppressing your ego long enough to consider what is being said before you respond.

In a world where few people listen, good listeners stand out. So what is it so hard?

When someone starts talking, our minds listen for:

  1. Reasonably guess what they are going to say. (E.g., “I know what you are going to say.”)
  2. Identify a pattern. (E.g., “I know where you are going with this.”)
  3. Something we disagree with (E.g., “That’s wrong.”)

When one of those things happens, we stop listening and our mind starts preparing our response. At the moment, the conversation becomes about us. When the other person does the same, gold becomes lead.

Instead of making the conversation about you, work to understand the other person’s perspective as well as they do. You don’t have to agree. You do have an obligation to understand. A conversation is not a race to make a point, but rather an exploration of someone’s mind.

via :  BrainFood Newsletter

Loose Nuts- FAscinating News via PNUTs Newsletter I subscribe and recommend

Training To Be Fired

  • “Outskilling” is a new trend hitting workers across the country, but experts are not sure if this is the solution to the “automation takeover.” Programs are being developed and implemented to help workers prepare for potential layoffs by providing them skills and training to further their careers in an automated world, but no one is sure how successful this system will be.
  • Executives and upper-level white collar workers have long enjoyed the services of similar programs for decades, but it is a new exit strategy for blue collar workers and the “Everyday Joe.” Reports and studies have noted that less than half the country’s workforce is fully equipped to handle middle-skill jobs, despite those same workers taking up a majority of the labor market.
  • Outskilling could help those in low-wage positions commonly viewed as temporary CV-builders, such as jobs in kitchens or restaurants, which bodes will for large chain franchises such as McDonald’s, but there is a lot of doubt circulating on the cost-effectiveness of these training sessions and programs. Until further studies investigate deeper into the new phenomenon, it is hard to say whether it’s just another trend of the decade or it will be the solution to the age of automation. (BBC)

Interesting Quotes

“It’s always too early to quit.”

via Today’s Quote

“There’s only one way to have a happy marriage and as soon as I learn what it is I’ll get married again.”

via Funny Quote of the Day

“The artist must bow to the monster of his own imagination.”

via Art Quote of the Day

“Only through art can we emerge from ourselves and know what another person sees.”

via Art Quote of the Day

“Love the giver more than the gift.”

via Today’s Quote

Cupid’s Capitalist: Meet Esther Howland, Creator Of The Modern Valentine

China’s Box Office Sales Dropped From $1.5 Billion To $3.9 Million Amid Coronavirus Panic

Check this out from The Times of India

Ficci: Some drugs may not last beyond Feb because of virus crisis
Download the TOI app now:

10 things eft’s been reading this week | eft – Supply Chain & Logistics Business Intelligence

How a Singaporean gourmet snack maker made salted egg snacks a global sensation | DHL Logistics of Things

Random Books recommended this month

  1. Wild Swans: Three Daughters of China
    by Jung Chang
  2. Holes (Holes, #1)
    by Louis Sachar
  3. Carnal: Somewhere Over 40 Winks
    by Rom LcO’Feer
  4. The Bluest Eye
    by Toni Morrison
  5. Bury My Heart at Wounded Knee: An Indian History of the American West
    by Dee Brown

Random Phrases of the day

  1. Poke Fun AtMeaning: Making fun of something or someone; ridicule.
  2. Foaming At The MouthMeaning: To be enraged and show it.
  3. Ugly DucklingMeaning: One who may seem plain at first in appearance or capability, but later turns out to be beautiful or great.
  4. No Ifs, Ands, or ButsMeaning: Finishing a task without making any excuses.
  5. Goody Two-ShoesMeaning: A smugly virtuous person.

Two States. Eight Textbooks. Two American Stories. – The New York Times

via Two States. Eight Textbooks. Two American Stories. – The New York Times

With . so many . Fake historians on the Dynasty roll – It happens in India too .  Only the Indian MHRD does overlook at these .


Darius FoRoux Newsletter – I subscribe and recommend

On The Cyclical Nature Of Life

On The Cyclical Nature Of Life

4 min read

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Up and down. That’s how you can describe real life in three words. But instead of accepting that life is cyclical, and that bad times are normal, we expect that we should always be on an upward cycle.

Almost everything we do involves other people. And because we’re emotional and inconsistent beings, outcomes are not consistent. Value investor and author of The Most Important Thing, Howard Marks explains this concept as follows:

“Mechanical things can go in a straight line. Time moves ahead continuously. So can a machine when it’s adequately powered. But processes in fields like history and economics involve people, and when people are involved, the results are variable and cyclical.”

We can extend that conclusion to life in general. I can’t think of a human process that’s not cyclical. Take personal energy. It would be great if our energy would be consistently high, wouldn’t it? But most of us have days we feel great, and we have days we feel like a bag of potatoes.

My aim with personal energy is to be as consistent as possible. I would rather be at 80% of my full energy potential every day instead of being 95% one day and 30% the next.

There is only so much within our control. And even if we work with things that are inside of our control, we still can’t control everything. Again, personal energy is a perfect example.

You can have a balanced lifestyle with enough sleep, nutritious food, and regular exercise, but still, you will have days you lack energy. Why is that? No one knows. The human body and mind are not like math. But this is something we don’t appreciate enough in life.

Measure the temperature

When Howard Marks talks about market cycles, he clearly states we can’t predict the future. Just because the market is going up for X years, it doesn’t mean that next year it will go down. You can’t extrapolate trends.

Understanding cycles will only help you to understand where you are now. When it comes to investing, Marks recommends to “figure out where we stand in terms of each cycle and what that implies for our actions.” Here’s what a market cycle looks like:

Image by: Gavinsblog

Let’s say that the market is currently in a Euphoria state. Does that mean it’s close to an Anxiety state? No one knows how long the current state will last. So we can’t make predictions.

But we must know where we are in the first place. When we’re aware of what’s going on around us, we won’t be battered around by our surroundings. That’s one of the key strategies value investors use. And I think we can apply it to life in general. Here are a few examples:

  • Businesses—How long have you been in business? How many people in your industry are aware of your business? What’s the state of your industry? Is your product/service widely accepted? Or is it still considered as an innovation that’s not for everyone? How mature is your market?
  • Careers—How many years of experience do you have? How big is your network? How much knowledge do you have? Is your skill still relevant in the economy?
  • Energy—How do you feel? Do you have any big injuries? What does your lifestyle look like? Do you use drugs? Do you drink alcohol? What season is it? Do you feel tired in the winter?

Everything is cyclical. Some businesses grow fast and bust quickly. Other businesses grow slow and never experience any exponential growth. Most jobs become irrelevant at some point. Some days, weeks, or months, you might feel weak. Or you might feel strong for years in a row and never get injured or ill.

But nothing will remain the same forever. None of the above questions and implications means you can predict the future. If you’ve been feeling low on energy for the past four weeks, it doesn’t mean you will automatically feel better next week. It also doesn’t mean you’ll feel worse.

Use cycles to make your decisions

Understanding where we are in a cycle helps us to make better decisions. When you’re low on energy, you want to preserve it and avoid actions that drain you. When you’re spread too thin, you want to take a step back, you don’t want to start a new project. Because what happens if you do that? You might burn out.

I’ve been using cycles to make career decisions as well. When I started my blog, I tried a lot of different things. I created different types of content, changed the design of my site, covered all kinds of topics, used different media channels, and so forth.

In the beginning of the cycle, I said yes to everything. But 4,5 years later, I’m more focused on specific actions. I say no to more things. For now, that helps me to build something very specific. Later in the cycle, that might change again.

The main lesson I learned is that nothing in life is static. We must respect the cyclical nature of life. And when we’re aware of where we stand in the cycle, we can make better decisions.

While there are a lot of ups and downs, understanding cycles will make you less susceptible to those changes. In fact, when you make good decisions, cycles will work in your favor.

That’s how value investors like Warren Buffett and Howard Marks weren’t affected in the financial crisis of 2008-2009. They realized where they were in the cycle and adjusted their actions.

If we do the same for every aspect of our lives, we can thrive when cycles go up and down.

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“Good leadership requires you to surround yourself with people of diverse perspectives who can disagree with you without fear of retaliation.”

“In order to “win a man to your cause,” Lincoln explained, you must first reach his heart, “the great high road to his reason.”

― Doris Kearns Goodwin

Data-driven decisions start with these 4 questions | UPS – United States

via Data-driven decisions start with these 4 questions | UPS – United StatesData-driven decisions start with these 4 questions

Data has become central to how we run our businesses today. In fact, the global market intelligence firm International Data Corporation (IDC) projects spending on data and analytics to reach $274.3 billion by 2022.

However, unwise spending accounts for much of that money. Gartner analyst Nick Heudecker‏ estimates that up to 85 percent of big data projects fail.

A big part of the problem is numbers that show up on a computer screen take on a special air of authority. Once pulled in through massive databases and analyzed through complex analytics software, we rarely ask where data came from, how it’s been modified or whether it’s fit for the intended purpose.

The truth is to get useful answers from data, we can’t just take it at face value. We need to learn how to ask thoughtful questions.

In particular, we need to know sourcing, which models were used to analyze it and what was left out. Most of all, we need to go beyond using data simply to improve operations and leverage it to imagine new possibilities.

We can start by asking:

  1. How do we source the data?

Data is the plural of anecdote. We record and store real-world events such as transactions, diagnostics and other relevant information in massive server farms. Yet few bother to ask where the data came from, and unfortunately, the quality and care with which data is gathered can vary widely.

In fact, a Gartner study recently found that firms lose an average of $15 million per year due to poor data quality. Often data is subject to human error such as when poorly paid and unmotivated retail clerks perform inventory checks.

However, even with an automated data collection process, there are significant sources of error such as intermittent power outages in cellphone towers or mistakes in the clearing process for financial transactions.

Data of poor quality or used in the wrong context can be worse than no data at all. In fact, one study found that 65 percent of a retailer’s inventory data was inaccurate.

Another concern, which has become increasingly important since the EU passed stringent GDPR data standards, is whether proper consent accompanies data collection.

So don’t just assume the data you have is accurate and of good quality. You have to ask about sourcing and maintenance. Increasingly, we need to audit our data dealings with as much care as we do our financial transactions.

“To get useful answers from data, we can’t just take it at face value. We need to learn how to ask thoughtful questions.”

  1. How do we analyze the data?

Even if data is accurate and well maintained, the quality of analytic models can vary widely.

Often open-source platforms such as GitHub pull together and repurpose models for a particular task. Before long, everybody forgets where it came from or how it is evaluating a particular dataset.

Lapses like these are more common than you’d think and can cause serious damage. As models become more sophisticated and incorporate more sources, we’re also increasingly seeing bigger problems with model training.

One of the most common errors is overfitting, which basically means the more variables you use to create a model, the harder it gets to make it generally valid. In some cases, excess data can result in data leakage in which training data mixes with testing data.

These types of errors can plague even the most sophisticated firms. As we do with data, we need to constantly ask difficult questions of our models.

Are they suited to the purpose we’re using them for? Are they taking the right factors into account? Does the output truly reflect what’s going on in the real world?

“Increasingly, we need to audit our data dealings with as much care as we do our financial transactions.”

  1. What does the data not tell us?

Data models, just like humans, tend to base judgments on the information most available.

Sometimes, the data you don’t have can affect your decision making as much as the data you do have. We commonly associate this type of availability bias with human decisions, but often human designers pass it on to automated systems.

For instance, in the financial industry, those who have extensive credit histories can access credit much easier than those who don’t. The latter, often referred to as “thin-file” clients, can find it difficult to buy a car, rent an apartment or get a credit card.

Yet a thin file doesn’t necessarily indicate a poor credit risk. Firms often end up turning away potentially profitable customers simply because they lack data on them.

Experian recently began to address this problem with its Boost program, which allows consumers to raise their scores by giving them credit for things like regular telecom and utility payments. To date, millions have signed up.

So it’s important to ask hard questions about what your data model might be missing. If you are managing what you measure, you need to ensure what you are measuring reflects the real world, not just the data that’s easiest to collect.

“We often call data the new oil, but it’s far more valuable. We need to start treating data as more than a passive asset class.”

  1. How can we use data to redesign products and business models?

During the past decade, we’ve learned how data can help us run our businesses more efficiently. Using data intelligently allows us to automate processes, predict when our machines need maintenance and serve our customers better.

Data can also become an important part of the product itself. To take one famous example, Netflix has long used smart data analytics to create better programming for less money. Yet where it gets really exciting is when you can use data to completely re-imagine your business.

At Experian, they’ve been able to leverage the cloud to shift from only delivering processed data in the form of credit reports to a service that offers its customers real-time access to more granular data that the reports are based on. That may seem like a subtle shift, but it’s become one of the fastest-growing parts of Experian’s business.

We often call data the new oil, but it’s far more valuable. We need to start treating data as more than a passive asset class.

If used wisely, it can offer a true competitive edge and take a business in completely new directions. To achieve that, however, you can’t start merely looking for answers. You have to learn how to ask new questions.