Category Archives: Paid Content

Solution to Management Science Series #200: One of the building blocks of data analytics: Probability in the Context of Business (Medium)

One of the building blocks of data analytics: Probability in the Context of Business (Medium)

The probability that a customer buys your streaming service, Halo, is 30%.

The probability that a customer buys your streaming service Halo and signs up for your company’s specific loyalty program is 20%. Every other streaming service offers loyalty program.

Loyalty programs differ among service providers. In order to sign up for the loyalty program, a customer must purchase the streaming service first.

a) Given that a customer buys your streaming service, what is the probability that the customer also signs up for your company’s loyalty program?

b) What is the probability that all customers using all kinds of streaming services also sign up for the loyalty programs of these companies if signing up for the loyalty program is independent of the streaming service they subscribed to?

PS: Current AI tools could not solve this problem.

On why statistics, beefed up as ‘Data Analytics’, is an essential tool to model, predict, and solve business problems

On this planet, understanding the nature of a random experiment solves more than half of the problem at hand.

However, this may be a hard task in some particular circumstances and boundaries are blurred.

How many businesses went bankrupt in the past hour is a discrete variable you can count without trying to predict anything.

How many e-commerce companies will record positive operational cash flows next year may be relatively well predicted through a continuous distribution model.

We live in a world that is more continuous than is discrete. In this article, I expand on this fact, which alone requires everyone involved in the world of business (basically almost everyone living on earth) to know, understand, and use statistics and its tools.

Solution to Management Science Series #199: One of the building blocks of data analytics: Probability in the Context of Business (Easy)

One of the building blocks of data analytics: Probability in the Context of Business (Easy)

The board members of the company, Universe, met to share their forecasts and estimates for the company’s future profit and revenue targets.

60% of the board members think that Universe will beat profit targets while 70% believe that Universe will beat sales.

20% believe that Universe will beat neither profits nor revenue targets.

a)What is the probability that a board member believes that Universe will beat profit, revenue targets or both?

b)What is the probability that a board member believes that Universe will beat both profit and revenue targets?

Historical Returns: Commodity Futures vs Equities. Revisiting the work of Gorton and Rouwenhorst

They did not teach you this in your finance classes 💡

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When using Treasury bills as the margin collateral for the futures position without leverage, fully collateralized commodity futures have essentially the same returns and Sharpe ratio as equities.

Agree or disagree?
In this article, I will investigate how the returns on commodity futures compare with those on Equities.

Solution to Management Science Series #198: Using K-Means Clustering for Customer Segmentation

Using K-Means Clustering for Customer Segmentation
Even Excel, albeit sometimes clumsy, can be a data analytics tool.

Try to solve the following question by using Excel:

Wine retailer, Porto, had 32 different promotion campaigns. You have the information on promotion month, minimum quantity to be purchased to benefit from promotions, discount percentages, varietals, wine’s origin, and whether the wine has passed its peak or not.

All this information is captured by a single Excel spreadsheet.

Then, you also have customer transaction data in a separate spreadsheet. You see that there had been 324 transactions completed.

Segment customers by using k-means clustering method. Use Excel to do so!

Businesses, States, and Governments 🗺️Why a Shinise like Nintendo differs from Boeing

Companies cannot thrive in failed states nor can they become global players.

Those that are relatively successful in a failed state cannot compete in global markets and their insignificant local success is bound by their ability to kowtow to their local governments.

Nonetheless, one should not ignore the fact that many global giants of today, despite them not being founded in failed states, have become such because of their relationships with their respective local governments and their state’s strong economic position in the global markets.

In today’s highly competitive markets, an innate monopoly, a wielder of a patented, well-protected, and inimitable proprietary technology, or a government contractor owning exclusive and never-ending business rights are players whose successes are surest.

Nevertheless, all such sure-to-succeed models, one way or another, are reliant on the very existence of governments and relationships with governments.
In this article, I will explain how companies with close ties to their respective governments thrive through these connections, providing real-world examples of innate monopolies, technology companies, and government contractors. I will elaborate on how these relationships impact the operations of the companies and why such companies succeed regardless of the political and economic system in the original country. I will also expand on why a shinise like Nintendo is an exception and the role of competition.

Solution to Management Science Series #197: Financial accounting as a forensic tool: Selling Receivables, aka pure factoring, Before the Collection Date

Financial accounting as a forensic tool: Selling Receivables, aka pure factoring, Before the Collection Date

Company A sold its receivables to a competitor and was paid in cash. You do not know whether the sale was made on nonrecourse basis or not. How would you label this transaction, financing or operating?

Company B sold its receivables to a bank and agreed to assume the risk of collection while also being granted a loan against the receivables sold. How would you label this transaction, financing or operating?

Company C, a manufacturer of trucks, sold its receivables to a bank on a nonrecourse basis. Nonetheless, if the bank were not able to collect the receivables, Company C should sell trucks in equivalent value to the bank and even repurchase the trucks if the bank were not able to sell them. How would you label this transaction, financing and operating?

As I’ve always been doing, in this article, I will solve this question and demystify the tricky accounts receivable account and what you need to look for lest you not get tricked by financial shenanigans related to receivables.

Making the hard decision of pricing easier: A blueprint comparing different pricing strategies

Pricing is an important decision involving both qualitative and quantitative considerations. 🧭

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From start-ups to strong incumbents, many companies still struggle to find the market clearing price-contrary to what you were taught in your microeconomics class, such a price does not exist in real life 😉

Given current inflationary environment and incessant decline in the purchasing power, this decision is now harder than it has ever been.

Whether your company follows a value-based, cost-based, or a hybrid pricing model, there are still some guidelines working in the pricing universe.

For example, you should know how to set relative prices for the following product pairs: razor and blades, video game hardware and software, printers and cartridges.

In this article, I lay out the fundamentals of different pricing strategies and which strategy makes sense for your company. Comparing different pricing strategies and the rationale behind, I also share examples of different pricing strategies from real-world companies and that particular pricing strategy is suitable for that specific company. The content can be utilized as a blueprint or guide concerning your efforts to determine the price of your services and products.

Solution to Management Science Series #196: Financial accounting as a forensic tool: This time, investigating restructuring projects

Financial accounting as a forensic tool: This time, investigating restructuring projects

Many analysts and investors have a hard time, grasping the reasons behind why companies, especially those that are publicly traded, announce bigger layoff plans than is financially warranted.

Laying off employees is almost always one of the first acts companies undertake in their restructuring efforts. Nonetheless, these restructuring projects may be utilized to smooth earnings. Do you know how? Try to solve the following example:

Assume that the automaker Alliance planned to lay off 200 people and published the developments accordingly. The company offers $60,000 severance package for each person who is going to be laid off.

In fact, laying off only 100 people would have sufficed; however, the company chose to announce a bigger number, i.e. 200 people, and stated the relevant accounts as if it had laid off 200 people.

Why would it do so? How will this restructuring charge affect current period’s operating profit?

How would the operating profit change if the company were to restate the relevant accounts and release the related reserve accounts to reflect the real number associated with these layoffs, i.e. 100 people rather than initially stated 200 people, in the following quarters?

Solution to Management Science Series #195: Valuing Options to Expand

Casca is a video games company based in Midland. It has created many of the most well-known IPs in the video game industry.

Financial analysts of Casca estimate that Casca has a total value of $2.3B according to their DCF models. These IPs and franchises are highly valuable and Casca aims to create new video game franchises for the foreseeable future.

Developing these video game franchises also allows Casca to enter toy and merchandising industry, establishing a new adjacent business activity. Casca could initiate and expand this business activity over the next 4 years.

Current cost of this business activity is estimated to be $1B. Expected cash flows are after-tax $120M per year for 18 years. Cost of capital for toy companies is estimated to be 17%. Casca analysts investigated annualized standard deviations in firm value for publicly-traded toy companies.

With appropriate risk and company-specific adjustments, Casca thinks that the appropriate volatility value for this project is around 27%. Should Casca expand into toy business?