Stanford GSB Sloan Study Notes, Week 4, Autumn quarter
Covered in this issue:
- How Confucius helps the Chinese to consume free MP3s
- How a CEO is stuck between the Board and his team in a complex matrix of conflicting loyalties
- How a side-effect of managing a few trillion dollars in your funds is the need to do a lot of board voting for your shares
- How high-profile VCs can keep your loans in the bank and close your hires
- How startups should tell their story the way seen in Shrek
- How to make the devil’s advocate a resident part of participatory decision making culture
- How citizens should break the government monopoly of environmental and pollution mapping
And here on to the full notes: Read the rest of this entry »
Whenever you are planning to take your startup or a mature company to a new market, planning to export your products there or seeking to open a new office to plug into local talent pool, you always know it will somehow be different than back home. Some of this is quite intuitive, like guessing that the farther you go physically, culturally or linguistically, the larger the change in environment. An enormous amount of differences are more nuanced.
The smart thing to do, of course would be to turn to relevant locals and expats, anthropologists and culture researchers. Maybe even hire a dedicated consultants who have been there and done what you’ve about to. Yet, there is always some of the analysis you need to do yourself, either because you can’t afford the time or resources to get external help, or you just need to prepare before turning to them. As cultural differences are highly contextual, not all of them really matter for your case, but you need to do some thinking on what are the few things that really do, the least.
Years ago I ran a project to figure out where should Skype build our next engineering centre to support the needed hiring pace. We looked at 12 countries in mostly Central-Eastern Europe, drilled deeper on a final shortlist of four and settled on Prague, which has sine been a great part of the Skype product engineering family since and still growing. Despite of the successful outcome, it wouldn’t have hurt to have had a bit more structured understanding beforehand on how to compare all our options.
Hence the very compressed reference list below, of books, frameworks, country data sites and other notes. Meant not to excite any culture theory experts, but rather to provide a very quick’n’dirty toolkit for business people who need to think through an upcoming international move. Read the rest of this entry »
Stanford GSB Sloan Study Notes, Week 3, Summer quarter
Note: as per feedback of longer notes (such as last week) becoming a bit random to read linearly, trying to group them by class this time.
Pages assigned for reading: 255
POLECON239 – Strategy Beyond Markets (prof Jha)
- Trade liberalisation creates new jobs in exporting industries. There still can be very active counter-lobby from concentrated minority interests fearing the potential harm: “jobs that will be lost are identifiable; the jobs that will be created are as yet unidentified” (Baron textbook)
- Few random bits on ethanol business (Kellogg case):
- Brazil stopped the sales of pure gasoline already in 2010 (20-25% ethanol component in all fuel sold).
- There are four ethanol plants in Colorado which use waste beer as feedstock!
- Booming ethanol fuel production has been tracked to raise food prices in the US for 10-15% in a 12 month period.
Stanford GSB Sloan Study Notes, Week 2, Summer quarter
Pages assigned for reading: 310
- Reminder: think of normals not in their absolute value, but as “how many standard deviations from mean” (Statistics)
- After going through the theory and visualisations behind probabilities of standard normal distribution (Z) and t-distributions, I have a growing suspicion, that in 95% (pun intended) of real life business cases needing confidence estimates, we’ll be dealing with a simple constant: 2. (In case of 95% probability on standard normal distribution, Z=1.96 and in cases the sample size n < 30, you should technically use t but, it in reality tends to be so close, that all other uncertainties around sampling and data collection would rarely be less than the benefits of simplicity of multiplication by two) (Statistics reading + class discussions)