For over two years, HBX CORe has taught thousands of students from over 100 countries the language of business. Using Harvard Business School's case-based methodology, CORe provides an immersive and powerful learning experience.

But don't take our word for it - as one of our past participants said,

"CORe really broke down all of the business concepts I had vaguely heard of and introduced new material in the clearest way with unique examples."

See what CORe graduates have to say about us and how the program has impacted them educationally and professionally:

• View HBX CORe student profiles
• See how HBX CORe helped our students in the job hunt

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Interested in learning more?

Considering enrolling in an HBX program but still have questions? The HBX team has done a little roundup of existing resources to help you find the answers you've been looking for! 

1. Start With our FAQ Pages

Whether you have questions about course structure, the admissions process, grading, fees, or financial aid, check these pages for answers to dozens of the most common questions we get about our programs:

• CORe FAQs
• Courses FAQs
• Disruptive Strategy FAQs
• Leading with Finance FAQs

2. Read Through Facebook Reviews and Past Q&As

We are lucky to have such a rich and supportive community of learners from around the world. Some of them have been kind enough to write up thoughtful reviews of their HBX experiences or join us for Facebook Q&A sessions, answering questions for prospective students. You can read through the entire conversations here: 

• CORe Q&As (Part One and Part Two)
• Disruptive Strategy Q&A

3. Learn About Other Past Participants Through Their Student Profiles

“Is this program right for me?” This is a question we hear all the time, but it's a difficult one for us to answer objectively. Often times, what people are really asking is if their educational background, professional goals, interests, or existing skill set will position them for success in an HBX course or if they will find the investment of time, energy, and money to be worthwhile. 

Our Student Profiles are a great resource for anyone who wants to hear firsthand from a variety of past participants about why they chose to participate in our programs, what they hoped to gain from the experience, and how they are using what they learned. 

• CORe Student Profiles
• Disruptive Strategy Student Profiles

4. Browse the HBX Blog

The HBX Blog is a place where you can dive a little deeper into the subject areas covered in the HBX programs (i.e. What does Cash Conversion Cycle mean, or why should I study accounting), or for those who want to hear more from students who have participated in an HBX program. Here are a few types of posts you may be interested in:

• Student Blog posts 
• CORe
• Disruptive Strategy
• Finance

5. Still have questions? Ask them using #AskHBX on Twitter!

If you've read through these resources and still can't find the answers to some of your burning questions, feel free to ask them on Twitter using #AskHBX. We will keep an eye out for questions and answer as many as we can!

If you read the results of any type of study, you've likely been told that results are "significant" in at least some cases. Clickbait headlines may use the word "significance" to make readers think the finding is important. But significance and importance are two very different things.

What is statistical significance, again?

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Statistical Significance: A statistic is considered significant if the likelihood of it occurring by chance is less than a preselected significance level (often 0.05 or less).

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If you're in need of a more in-depth refresher, check out this helpful article from Harvard Business Review HERE.

How can you tell if a finding that is statistically significant is actually important? Here are three things to keep an eye out for.

1. Just because something is statistically significant does not mean that it isn't due to chance.

For example, if you tossed a coin 5 times, it is unlikely to come up heads all 5 times. There are 32 possible outcomes for tossing a coin 5 times and only one way to get 5 heads. So you'd only expect to get 5 heads one time out of 32 on average, or about 3% of the time. Generally, anything that would happen by chance less than 5% of the time is considered to be statistically significant. Thus, an unscrupulous researcher could get "significant" effects simply by conducting a lot of analyses and picking the ones that reach the threshold.

2. Just because something is not statistically significant doesn't mean that it isn't due to a real effect.

If one hundred people each tossed a fair coin 5 times, we'd expect 3 of them to get 5 heads in a row. Similarly, just because something is not statistically significant doesn't mean that it is due to chance. If a weighted coin that comes up heads 80% of the time is tossed 5 times, it may well come up 4 heads and 1 tail, a distribution that would happen 16% of the time by chance with a fair coin, so it would not reach statistical significance. Thus, an unscrupulous researcher could report "no effect" of something simply by conducting a study with a very small sample and little power to detect differences.

3. Just because something is statistically significant does not mean that it is practically significant.

When I was in graduate school, I fractured my navicular bone, a small bone in the wrist. My doctor told me that I could get a cast that stopped either right below my elbow, or one that continued past my elbow & would keep my arm bent until the cast came off. He informed me that medical research indicated that people spend (statistically) significantly longer in a cast if it stops below the elbow.

That certainly seemed like a good argument for getting a longer cast! But I asked for the average time spent in a cast under each condition. He told me that people who got the shorter cast spent, on average, a full six weeks in a cast while those who had their elbow immobile were out of the cast in only five weeks and six days! This may have been statistically significant, but the practical significance was not great enough for me to give up bending my elbow for a month and a half.

When you hear about a "significant" finding, you should take it with a grain of salt, especially if it's only seen in one study. A report about, say, chocolate significantly reducing the chance of hair loss (something I'm completely making up – I've never seen that particular claim), could be the result of either lots of analyses producing one statistically significant result by chance. Or it could be the result of a study that found a very small connection (for example, eating 5 pounds of chocolate a day would delay the onset of hair loss by 45 minutes), that happened to be unlikely due to chance.

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Interested in learning Financial Accounting, Business Analytics, and Economics for Managers?

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Sheneka Balogun is a Program Manager at Western Governors University who enrolled in the April 2015 cohort of HBX CORe in order to advance her career. She will be beginning an Ed.D. in Entrepreneurial Leadership at Johns Hopkins University School of Education this fall.

What do you do for work?

I am Program Manager in the College of Business at Western Governors University, one of the largest non-profit universities in the country that has been featured in Money Magazine, MSNBC, U.S. News, TIME, and even CNN for low-cost education that measures learning rather than seat time.

I performed consistently in the top 20% in the Mentoring Department and was promoted within a month of receiving my passing scores at HBX CORe.

Why did you decide to sign up for CORe?

I took CORe for several reasons. I wanted to advance in my career in higher education, and in order to do that I needed to better understand the core principles of business that would match my work ethic and high performance. I was eager to enroll in an MBA program and later pursue a terminal degree. Completing CORe, I thought, would position me to be a more competitive applicant during the admissions process.

What was your favorite part of the program?

Because there were so many facets of HBX CORe that I enjoyed and that were beneficial in me grasping an intricate understanding of the content, it's hard to single out just one part.

If I had to choose, I would say the interactive text throughout each module was my favorite part. Learning came to life! The videos from the professors, the interactive cold quizzes where you were randomly selected to participate (those gave me chills by the way!), the case studies that enhanced and often captured the essence of objectives and learning goals were all embedded in each module. This made learning fun, engaging, and student-friendly.

I think it's important to mention that the amount of support I felt during the CORe program was incredible! HBX CORe was much more than a tripod of rigorous courses. The sense of community that developed from all the various social platforms that were unique to HBX that provided me the platform to interact with other students from all over the world in various industries were instrumental in my application and understanding of the concepts.

See! I told ya it was hard to name just one favorite part!

How are you applying what you've learned in CORe?

At Western Governors University, measuring learning as opposed to seat time is at the core of what we do to improve student outcomes. As a Program Manager, I am constantly evaluating the current practices the College of Business, and even my individual team of graduate faculty have in place and seeking out innovative strategies that will reduce attrition, increase the number of graduates, and improve learning outcomes for our students.

"HBX CORe has provided me a dynamic understanding of how to measure and understand those outcomes. I can now confidently translate statistical data into a graphical presentation or employ different statistical techniques to help me better understand the pulse of student progress."

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The CORe community consists of a rich and diverse group of learners. Want to learn more about other students who've participated in the program?

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Have you ever walked into a store and wondered how they paid to fill it with products to sell? The easy answer might be, "with the money they made from the things they sold last month," and that's partially true, but what about for brand new stores? There's probably millions of dollars of inventory on the floor of many large retailers and hundreds of thousands of dollars of inventory on the floor of many small businesses. This working capital must be paid for - but how?

Many companies will take on debt to finance their inventories. Suppliers, eager to get business, will often offer credit terms, and each company decides how and when to take advantage of these through maintaining an Accounts Payable balance. This gap between paying for the products and receiving the money for selling them is called the cash conversion cycle.

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Cash Conversion Cycle: the amount of time that passes between when a company spends money to buy an item and when they receive the money for selling it.

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To calculate the cash conversion cycle, take the average number of days it takes to sell inventory, plus the average number of days it takes to receive payment for that sold inventory, minus the average number of days before paying for received inventory. In terms of accounting ratios, this is: 

Cash Conversion Cycle = Days Inventory + Days Receivables – Days Payables

A typical company receives inventory, pays later for that inventory, sells the inventory, then receives payment for it.

The implications of the cash conversion cycle are powerful. To illustrate with an example, imagine a company that buys t-shirts for $10 and sells them for $15 – a very simple business. If they have a cash conversion cycle of seven days, this implies that for one week they have lost the $10 needed to purchase each t-shirt but have not yet received the $15 for selling them. Where do they get money to buy more t-shirts and maintain their inventory? 

Financing this time through debt can impose a considerable cost on the company, especially for companies with very long cash conversion cycles. The longer the cash conversion cycle, the higher the interest paid on the debt.

Imagine a company that has a negative cash conversion cycle, like Amazon. By selling inventory quickly (low Days Inventory), receiving payment immediately for most sales (low Days Receivables) and putting off payment to suppliers for as long as possible (high Days Payables), their Cash Conversion Cycle is negative.

That means that Amazon actually gets paid for items they sell before they pay for them themselves. So, instead of paying interest to buy items for sale, they are receiving interest by holding cash in their bank account (or investing it in growing their company). This produces a powerful engine for cash generation and growth.

To learn more about the cash conversion cycles of Amazon and other organizations, take a look at this article from Forbes.

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Interested in learning more about accounting as well as analytics and economics?

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This post is from The Bitter Student, an online multimedia forum started by past HBX CORe participant Sam Campbell. Click here to see the original article.

In early May, I traveled to Boston, MA to attend the HBX ConneXt conference at Harvard Business School. The institution invited students who completed the online educational platform, HBX. I was a participant in HBX CORe and was part of the June 2015 cohort (shout out to my fellow classmates!).

CORe provides the fundamentals -- the ‘core’ concepts -- of business (accounting, analytics, and economics) from leading Harvard Business School faculty, who use the renowned case-study method.

In this post, I hope I can not only discuss my experience and journey with HBX CORe last summer and my trip to HBS, but hopefully, I can also provide some valuable insight and also inspire others to take these or similar courses.

As with any story, there was a beginning. That beginning was in June of 2015. At that time, I thought there would be no end. I could not see the light at the end of the tunnel, as you might say. Note: this is not where my inspiration or jollification starts.

I was still an underclassman in college, and had just concluded my first year. I was completing a full-time internship on top of the twelve hours of course work a week. The courses started right when school ended, and the program spilled over into the start of my sophomore year.

I remember groggily working on these courses after being brain dead from work or while at the beach with friends. The silver lining in all of this though was that I was not alone. There were multiple students who were completing this program during an internship, a 40+ hour work week, or other time-consuming commitments.

A takeaway here is: do not go into these courses thinking you can wing anything, or that the time commitment will be easy to juggle with other responsibilities. It’s possible to pass, but nearly impossible. We learned at the HBXConneXt conference that procrastinators were more likely to fail CORe, while those who focused their efforts more efficiently were more likely to reach high honors. Those who do not put work off and get ahead of their tasks are more likely to be successful in the long run (see chart below).

During the conference in May, there was a session titled: “What’s Next for Online Learning: A Conversation” featuring Anne Dwane (Partner & Co-Founder, GSV Acceleration), Larry Culp (former CEO of Danaher Corp. and senior lecturer at HBS), and Chip Paucek (CEO & Co-Founder at 2U, Inc.). The guest speakers mentioned a couple of thoughts (of which I, of course, took note) about what they think when they see HBX CORe on someone’s resume. I am paraphrasing here; nonetheless, the speakers noted:

1. Desire. Hunger. Self-motivation. Bias to invest in oneself.
2. Lead & win potential.
3. Talent in plain sight.
4. Risk takers because they had confidence in an organization's newly founded program and confidence in themselves to complete the program.
5. Real results. Hard work. Not superficial.
6. Aspiration.

Why persist, you might ask?

I can’t speak on behalf of my cohort, but I persisted for three reasons:

1. I believe knowledge is more than the timeless idiom, “knowledge is power.” Knowledge isn’t just power. Knowledge can be used to empower. It equips us with the tools to help us make a difference in the world.
2. As Michael Priest tells us this in his book 101 Things I Learned in Business School, "Those most likely to be successful in business in the long run have the broadest and most open understanding of it.” 
3. We are at a time in history and live in a world where we need leaders now more than ever.

Community and connection

The platform also requires you to connect and interact with peers. One aspect of the grading is participation. My advice: answer others’ questions as much as possible! Not only are you increasing your grade, but also, as you explain these perplexing concepts to peers – you are learning the material better. Your knee-jerk reaction is to speed through the course, but go ahead and spend the extra hour. This is another great way to make lasting connections because you are investing in others’ education, not just your own.

Once you’re signed up for the program, you have the opportunity to join your classmates in one large Facebook group, as well as cohort-specific Facebook groups. As you start to browse their profile, yep, Facebook stalk, your section mates, you’ll quickly realize how unaccomplished you are. No, really. These accomplished adventurers you will meet are CEO’s of Silicon Valley startups, aids in Washington, DC, and interns at Facebook. They are world changers, to say the least. So, don’t just grow your LinkedIn profile – communicate with these people. Network. Establish relationships.

Putting it all together

The question I have been asked the most, “So what else did you get from this program?” The course taught us the language of business, and it also taught us how to take a case and apply the principles we learned. It challenged us mentally and intellectually, to think critically and analytically. And it taught us how to visualize problems and solutions through a different lens.

After 11 weeks of a rigorous work load – there were three finals to prepare for, that we took at one time at a testing center, that is timed, where there is a whole thirty second break, so you have just enough time to breath (maybe).

Reflecting back to the beginning, I never thought I’d finish. It was a dark tunnel for the longest time, and I still cannot believe I passed. I told myself the entire way, even if I failed the entire thing – I was going to make it to the very end. I could forgive myself if I failed; I could get back up from failure, but I could not forgive myself if I gave up.

These courses were an uphill battle. It was an incredibly difficult journey to get from point A to point B. But does anything actually worth having come easy? Experience CORe, or similar courses – it’s worth the challenge; challenge yourself (in ways you never thought possible) make connections, and use this knowledge to change your world and the world around you.

Thank you, Harvard Business School and Professors Bharat Anand, Jan Hammond, and V.G. Narayanan for this incredible and enlightening journey.

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Out of laundry detergent? Just press an Amazon Dash Button. Out of trash bags? There’s an Amazon Dash Button for that too. What might appear like a seamless way to allow users to order common household products is a new source of data for Amazon to better understand consumer behavior.

How? By using predictive modeling. Predictive modeling is a statistical modeling technique that forecasts an outcome or behavior. This type of modeling often uses historic or current data to predict a future outcome, which can be validated as more data becomes available.

The data collected by the Dash Button is valuable to both Amazon and the manufacturers of products. Dash Buttons give insight into individual patterns of frequency of purchase into a sample of Amazon’s users. Pair this consumption data with Amazon’s rich demographic data, and Dash Buttons are giving new insights to fuel future growth for Amazon.

With this type of data available, perhaps a predictive model could anticipate future consumption and ordering behavior of customers. The future of shopping for household items could mean enrolling and letting predictive modeling take over from there. What if Amazon could accurately predict the amount of laundry detergent and trash bags to ship to you based on your past behavior? This is the future of retail with predictive modeling. 

While the verdict is still unclear if Dash Buttons are a viable, profit-producing technology for Amazon, the data they produce may be more valuable than the products they sell. Every product sold through a Dash Button is a valuable data point that will contribute to Amazon’s next generation of services and products.

To learn more about Amazon’s Dash Button’s data here, check out this article from Fast Company.

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Want to learn more about predictive modeling and other business concepts? HBX CORe will teach you the basics of Business Analytics, Economics, and Financial Accounting using Harvard Business School's renowned case-based methodology!

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During Thursday’s Brexit vote, the value of the British pound fluctuated wildly – starting at $1.47/￡, it climbed as high as $1.50/￡ before dropping to $1.35/￡. What causes these currency fluctuations? 

While the easy answer is “uncertainty” – and there is certainly a lot of uncertainty in Britain right now – the harder question might be “if I were running a business and needed to know what the value of the pound should be, what should I do?” Financial investors do this every day, and thousands were doing so Thursday night – and their actions caused the shifts in value.

The stunning collapse of the British pound, in one chart https://t.co/XaGPqevTMp

— Washington Post (@washingtonpost) June 24, 2016

Before the vote, it was speculated that the appropriate value of the pound if the "Remain" campaign were to win would be $1.55/￡, and the appropriate value of the pound if the "Leave" campaign were to win would be $1.30/￡. By the end of the vote – one of these would be true, but until then, how should they value the pound?

The best way to do this is to consider each scenario in a weighted average of their probabilities. This will yield what in finance is known as an “expected value.” In this case, if we believe the probability of "Leave" to be p%, then the expected value of the pound will be $1.30 * p% + $1.55 * (1-p%). 

Across the world Thursday night, analysts who wanted to know the value of the pound furiously tried to determine what p% would be, and from that, determine what they should do. Let’s say you were such an analyst, and you believed the possibility of a "Leave" victory was 25%. What should you do? 

Well, first, you would figure out what you believed the value of the pound should be, so: $1.30(.25) + $1.55(1-.25) = $1.48.

If the current value of the pound is $1.47/￡, then you believe that it is undervalued. You should buy pounds, because they are currently cheap. If everyone believes that the probability of a "Leave" victory were 25%, then everyone will do the same, and eventually, the increased demand for the pound will increase the price – to exactly $1.48/￡.

You can also take the current price and back out the assumed probability. As the exit polls came out, and a "Remain" victory looked likely, the value of the pound spiked to $1.50/￡. What did that mean about p%?

Consider: $1.30(p%) + $1.55(1-p%) = $1.50. The value of p% is 20%. That means, at that point, investors believed there was a 20% chance of a Leave victory (meaning an 80% chance of a "Remain" victory). Overnight, as voting was counted, the value of the pound dropped to $1.35. $1.30(p%) + $1.55(1-p%) = $1.35. That means p% is 80%. The expected probability had flipped, with "Leave" now having an 80% chance of victory.

Thursday night, financial analysts were constantly revising their figures in an attempt to get ahead of their peers. The questions they were asking – what is the value of the pound if "Leave" wins? What is the value of the pound if "Remain" wins? And what is the probability of a "Leave" victory? – were translated into decisions to buy or sell the pound, which corresponded immediately into changes in its value.

These simple equations, along with your own intuition, can be the edge in preparing for uncertainty and knowing the expected future.

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Want to know more about finance? HBX CORe will teach you the basics of Business Analytics, Economics, and Financial Accounting using Harvard Business School's renowned case-based methodology!

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Every year since 1999, the Madden NFL video game cover has featured an NFL star player from the previous year, similar to an athlete being featured on the Wheaties box. Fans have noticed a trend where these star players end up playing worse or even getting injured the following year. Hence the idea of a “Madden Curse,” and a subset of fans who are adamantly opposed to their favorite players being featured on the cover.

What does this have to do with statistics? Well, there is a concept in statistics called “reversion to the mean.” Reversion to the mean is the idea that if we observe an extreme event (e.g. a surprisingly strong NFL season), we can expect the following event to be closer to the average (e.g. the season following a particularly strong NFL season will be less impressive). This might explain why players featured on the Madden cover generally do worse the following year.

GRONK. SPIKE.

Introducing the cover of #Madden17! pic.twitter.com/iCZUwIAuYO

— EA SPORTS Madden NFL (@EAMaddenNFL) May 12, 2016

The player's reversion to the mean does not indicate that they are actually playing worse than they normally do, it’s just that we raised our expectations of them! We can look at a similar phenomenon at the team level. Historically, football teams that do very well (e.g. records of 14-2, 15-1, or 16-0) typically do worse the following season.

This concept relies on there being some randomness to the events. If an NFL season were purely the result of skill, then we would always expect the following season to be as good as the previous one (barring injury or other external factors). But as we all know, there is some luck (or randomness) involved in most human endeavors, and as a result we are all susceptible to reversion to the mean.

The good news is that reversion to the mean applies to extremely bad events as well. So, if you did particularly poorly on a recent exam (compared to similar exams you have taken), keep your spirits up because most likely you will do better on the next one!

Food for thought: Why do you think that when teams fire their coach, they usually improve? Does reversion to the mean play a role here? Can you think of any other situations where reversion to the mean plays a meaningful role? Let us know in the comments!

To learn more about the Madden Curse, check out this piece from Forbes.

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Want to know more about statistics and other business concepts? HBX CORe will teach you the basics of Business Analytics, Economics, and Financial Accounting using Harvard Business School's renowned case-based methodology!

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As you've likely heard by now, Microsoft purchased LinkedIn. So why did LinkedIn's leadership decide to sell the company? Many have started to speculate that Linkedin's reliance on stock-based compensation could be a contributing factor. 

So what exactly is stock-based compensation and why has it become so pervasive in corporate settings? 

One unspoken reason behind the LinkedIn sale https://t.co/tl5APXXdFb

— The New York Times (@nytimes) June 14, 2016

One reason that companies started offering stock-based compensation was to correct what is called the “principle/agent problem.” Simply stated, the employees of a company (the “agents”) may not have the same incentives that the owners of a company (the “principles”) may have. If someone is both the owner and the manager of a business, they tend to be very careful with expenses – they economize by flying coach instead of 1^st class, for example, or they maintain a simple office instead of an expensively furnished one. 

When the manager of a company is not also the owner, they have an incentive to make decisions that benefit themselves at the expense of the owners – they fly first class or maintain expensive offices. Giving employees stock-based compensation is an attempt to make them also part-owners of the company, and align their interests with the other owners.

Another reason, especially for small tech-based startups, is to avoid paying out cash. For many small companies, cash may be exceptionally tight, and paying employees in the form of stock offers payment tomorrow for work today. This can cut expenses for the company in the short-term and can be exceptionally profitable for the employee in the long-term – think about stories of the Google janitor now being worth millions, for example. Obviously, if the company does poorly, this isn’t the case.

So why all the concern? Well, when stock-based compensation is offered, it dilutes the existing shares of stock and reduces their value. If we imagine that the equity of a company is worth a set amount and doesn’t change depending on how many shares are outstanding, then issuing new shares must reduce the value of the existing shares – by exactly the amount given out in new shares. 

In this way, stock-based compensation should hurt Net Income by exactly the same amount as its listed value, just like an expense. But since it’s non-cash, many companies “adjust” their EBITDA to not include it. However, as this dilution effect can be very large, pressure has come from investors for companies to include this as an expense when reporting earnings.

As you can see in this New York Times article, many companies, including Facebook and Microsoft, have started doing exactly that.

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Interested in learning more about Accounting, Economics, and Business Analytics?

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