Monthly Archives: November 2011

Competing online syllabus

Name of course: Competing online
Time: February 7-8, 2011
Place: Lorange Institute of Business, Zürich, Switzerland
Instructor: Espen Andersen, Assoc. Prof. Norwegian Business School

The course, a two-day seminar aimed at senior business decision-makers, will give insight into the strategic and tactical choices facing companies going into electronic commerce, whether from a pure online strategy or using an online presence as a support for their regular service and sales channels. The syllabus is not meant to be conclusive – the right to make changes is most explicitly reserved.

If you are interested, you can sign up here.


Tuesday, February 7

Session 1, 0830-1000: Introduction, the promise and peril of online competition
This session will introduce the course and use a short case as a starting point for discussing the impact of online competition on traditional companies. Please read and be prepared to discuss the following:

Study questions for the case:

  • Is eHerramientas a threat to Catatech?
  • What should Marisa do to design a strategy to counter eHerramientas’ competition?
  • What should Marisa to to communicate her strategy within Catatech?

Session 2, 1030-1200: The mechanisms of electronic commerce: Searchability and findability
Google provides the context in which you will need to be found on the web. Amazon shows a company that helps you find the right product when the customer lands on the site. In this session we will study the offerings by both companies, and see how they have evolved over time.

  • Article: Rangaswamy, A., C. L. Giles, et al. (2009). “A Strategic Perspective on Search Engines: Thought Candies for Practitioners and Researchers.” Journal of Interactive Marketing23: 49-60.
  • Article: Andersen, E. (2006). “The Waning Importance of Categorization.” ACM Ubiquity7(19).
  • Google technology overview, “What is AdWords” video,
  • Article: (for the more advanced student): Brin, S. and L. Page (1998). The Anatomy of a Large-Scale Hypertextual Web Search Engine. Seventh International WWW Conference, Brisbane, Australia. (this is the paper that started Google).
  • Amazon: “Inside Amazon” video, as well as this article: Linden, G., B. Smith, et al. (2003). “ recommendations: item-to-item collaborative filtering.” Internet Computing, IEEE 7(1): 76-80.

Session 3 and 4, 1330-1700, with break: Evolving the pure online company
In this session we will study the evolution of, a company that helps graduate schools selectively recruit international students for their MBA and M.Sc. programs. We will be joined in this discussion by Mr. Linus Murphy, CEO of Masterstudies.

Session 5, 1700-1730: An introduction to disruptive innovations
In preparation for the group work for the night, there will be a short introduction to and discussion of the theory of disruptive innovations.

  • Articles: Christensen, C. M., M. Raynor, et al. (2001). “Skate to Where the Money Will Be.” Harvard Business Review (November): 73-81.

Session 6, after 1730: Group work

  • Case: Schibsted (HBS case 707474, Bharat Anand)
  • Article: “More media, less news”, The Economist, August 24, 2006
  • Assignment: On a group basis, prepare a short presentation for tomorrow’s morning session. More precise instructions will be distributed in class.

Wednesday, February 8:

Session 7, 0830-1000: Responding to online competition:

  • Case: Schibsted (HBS case 707474, Bharat Anand)
  • Group presentations, prepared the night before

Session 8, 1030-1200: Responding to the social web: Blogs, Facebook, Twitter

Social media represents many challenges to business organizations – but also opportunities for increasing brand awareness, learning from customers and .

  • Article: Mangold, W. G. and D. J. Faulds “Social media: The new hybrid element of the promotion mix.” Business Horizons 52(4): 357-365.
  • Case: A blogger in their midst (HBS case R0309X, Halley Suitt)
  • Case: Coca-Cola on Facebook (HBS case 511110, John Deighton, Leora Kornfeld)

Session 9, 1330-1500: Responding to the technical threat

Security and disaster management is often ignored by senior management – partly because the issues are, well, technical and difficult. The iPremier case, in cartoon form for your reading pleasure, allows for a discussion of how to think about and prioritize security in an online business environment.

Case study questions:

  • How well did the iPremier Company perform during the seventy-five minute attack? If you were Bob Turley, what might you have done differently during the attack?
  • The iPremier CEO, Jack Samuelson, had already expressed to Bob Turley his concern that the company might eventually suffer from a “deficit in operating procedures.” Were the company’s operating procedures deficient in responding to this attack? What additional procedures might have been in place to better handle the attack?
  • Now that the attack has ended, what can the iPremier company do to prepare for another such attack?
  • In the aftermath of the attack, what would you be worried about? What actions would you recommend?

Session 10, 1530-1700: Short written examination

  • TBA.

Session 11: 1700-1730: Concluding remarks

Fulfilling the status role of books

Espen Andersen (Photo: Nard Schreurs)In my office at BI Norwegian Business School I have many books, accumulated over the years. In my living room I have even more, having spent time building bookshelves and defending the wall space against family members who think it could be put to better use. And in my basement I have stacks of cartons with even more books, which I do not have the heart to throw out – hey, I might get around to reading the complete works of Hermann Hesse, in German, some day – but not the space to display.

The book collection is nice – I like books, I can remember almost viscerally where most of them are, and often all that is necessary to remember what is in them is just to take them out of the shelf. And they do tell everyone around me that I am a bona fide intellectual, should anyone wonder.

But I (almost) don’t read books on paper any more – I buy them and read them on my Kindle or PC or iPad. Electronic books are searchable, weightless, cheap, accessible and cost nothing to store. But nobody can see how many books I have on my PC or Kindle. Having many books signals status, to the point where there are companies that will fill you bookshelves for you, in any color and style you want, for a fee. The usefulness of books as status signals will diminish over time, however, just as what has happened with CD racks, which you don’t display anymore, unless you have thousands of vinyl records and cross the threshold from music lover to music fanatic. So, what to do?

The Norwegian publishing and bookselling industry, an astonishingly backward group of companies when it comes to anything digital, yesterday introduced a new concept for e-books that, even for them, is rather harebrained. They want to sell e-book tablets where you can buy books not as downloads (well, you can do that, too) but as files loaded on small plastic memory cards, to be inserted into the reader [article in Norwegian]. This preserves their business model (though they can probably stop using trucks and start using bicycles for distribution). According to their not very convincing market analysis, this is aimed at the segment of the book buying market who do not want to download books from the net (but, for some reason, seem to want to read books electronically.)

imageI initially thought I would make a joke about having to replace my bookshelves with neat little minishelves for the plastic cards, when it dawned on me that perhaps we have the solution here – i.e., a model where we could get the accessibility of digital books with the status display of the paper version. Why couldn’t the publishing industry sell you a digital book (for downloading, if you please) bundled with a cardboard book model, with binding and all, to put in your bookshelf? This would look great, allow you to effortlessly project your intellectualism and elevated taste, while avoiding the weight, dust, and (since these books would only need to be a in inch or two deep) space nuisances of traditional books. You could even avoid physical distribution by letting the customer self-print and cut and fold the “shelf-book” in the right format.

You could even electronically link the two, so that you cold pick your cardboard book from the shelf, wave it in the direction of the e-book tablet (using transponder, 2D barcoding or other identifying techniques) and the book would show up in your reader. If you really wanted to show off, you could add a little color coded bar indicated how far you were in each book, much like a download bar for your computer, to be displayed on each book. Moreover, such as book could be lent from one reader to another.

I recently bought Don DeLillo’s Underworld for my Kindle. Imagine if it came with with nice little book spine, leather as an expensive option, with a barcode and a “read” bar as illustrated here…status, spatial memory, interior decoration, and a way to gradually replace the paper library with an electronic one without disruption.

Remember, you saw it here first!

(In case you wondered: Yes, I am being facetious.)

Two books on search and social network analysis

Social Network Analysis for Startups: Finding connections on the social webSocial Network Analysis for Startups: Finding connections on the social web by Maksim Tsvetovat
My rating: 3 of 5 stars

Concise and well-written (like most O’Reilly stuff) book on basic social network analysis, complete with (Python, Unix-based) code and examples. You can ignore the code samples if you want to just read the book (I was able to replicate some of them using UCINet, a network analysis tool).

Liked it. Recommended.

Search Analytics for Your Site: Conversations with Your CustomersSearch Analytics for Your Site: Conversations with Your Customers by Louis Rosenfeld
My rating: 4 of 5 stars

Very straightforward and practically oriented – with lots of good examples. Search log analysis – seeing what customers are looking for and whether or not they find it – is as close to having a real, recorded and analyzable conversation with your customers as you can come, yet very few companies do it. Rosenfeld shows how to do it, and also how to find the low-hanging fruit and how to justify spending resources on it.

This is not rocket science – I was, quite frankly, astonished at how few companies do this. With more and more traffic coming from search engines, more and more users using search rather than hierarchical navigation, and the invisibility of dissatisfied customers (and the lost opportunities they represent) this should be high on any CIOs agenda.

Highly recommended.

View all my reviews

Human-computer interaction, indeed

This event was great fun – fun as a show, but also impressive in what both the student teams (well, MIT didn’t do that well…) and the computer could do. Jeopardy is a very complicated game, relies on wordplay (In the category “presidential rhymes”, the answer is “George W.’s bottoms”, the question “What is Bush’es tushes), obscure knowledge and word combinations (such as combining two movie titles into a new one, as in “Millon Dollar Baby Boom”).

If only the HBS team hadn’t played it safe towards the end – they bet just enough money so that they would not lose to MIT if they missed the last question – we would have had the first instance where the computer had lost to a human team. Oh well…

Addendum: A perspective from Stacey Higginbotham: Why Watson can’t talk to Siri. (I wonder if they used the same questions at that event, since Chile was an answer in the HBS one, too. Doesn’t mean they are cheating, though – it is quite easy to make a computer forget…

Big data and the study of connections

I read this very interesting article at Om Malik on Broadband, where Dr. Alex Szalay of Johns Hopkins argues that Big Data – the enormously increased availability and analyzability of data as the world increasingly becomes digitized – will mean as much to science as the microscope once did.

It made me think of Douglas Adams’ wonderful lecture on “Parrots, the Universe and Everything.” One of his central points there is that science is changing – from a focus on taking things apart to understand to one where we put them together so that we can watch them interact.

On a smaller scale, I think this is extremely important for businesses, especially those that can be characterized as value networks, i.e. companies whose main value provisioning consists of connecting people and helping them exchange information, goods or money (well, OK then, money is information, I agree, but still.) At present, these companies segment their customers mainly by demographics (age, gender, location, education, etc.) or, for business customers, by size, industry and location. Massive data analysis will allow them to stop segmentation (which is only a representation reducing your market transaction cost, but also providing a less tailored product for the customer) and instead offer services and connections based on which other users each member is connected to and what they exchange.

Imagine instead if your telephone company, bank or insurance company could analyze you in terms of your interactions with others. That would allow the telephone company to group and tailor their services for the customers that create the most traffic, have the biggest impact, prevent the most accidents or in other ways cause desirable changes in behaviors of those around them. This is now done in a very primitive way and after the fact – imagine if you could do it in real time.

Notes from Eric Schmidt at MIT

After the jump, my notes from Eric Schmidt’s talk at MIT today. I am sure this will be available as a video at some point. I found the the whole exercise a bit pat – he didn’t really say anything new, but there were a few nuggets of interest here and there (and my notes are not complete.)

Update 17. nov: MIT writeup.

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Hard technology talk in very civilized package

Cory Doctorow likes this talk by John Naughton – which, given how often he quotes Cory without mentioning him, is a bit surprising, but then Cory has always been a very open fellow. I did not find much new here, but the last couple of minutes, and the answers at question time are generally good (including the discussion of copyright and the future of teachers). Decent intro for folks who need an explanation of the Internet in clipped British tones, without PowerPoint and ideology.

And academic speakers in the UK get a bottle of whisky, which I cannot help but see as an improvement…

To quote Cory: Technology giveth, technology taketh away… And incidentally, the idea that the bumblebee shouldn’t be able to fly is a myth.

Truth, time, context, and computation

A reference to Jeanne Ross’ exhortation to companies to find one agreed – or declared – one declared source of truth got me thinking this morning. Jeanne’s point is that in order to get organizations to start discussing solutions rather than bickering over descriptions, it is better to declare a version of the truth to be the real one. If there are inaccuracies in the source of the data, then people can do something about making them more precise, an exercise that in most cases is much more fruitful than trying to suggest alternative numbers.

I very much agree with Jeanne in the main of this statement (probably a smart move, given that I am her guest at MIT CISR this year), as well as the need for it in many organizations. But it got me thinking – what is the truth, and how has what we consider to be the truth been influenced by advances in computation? With Big Data increasingly available, we can now analyze our way to most things. How does this change our concept of what is truth? Moreover, at what level should a CIO declare the one source of truth?

Truth as a function of time and context

I remember a conversation sometime in the nineties with colleagues Richard Pawson and Paul Turton at CSC – the discussion was on how object orientation changed the nature of systems, from being a computationally limited representation (a function, if you will) to being a simulation of the organization. We saw three stages in this evolution:

VERNER Swivel chair, white Width: 24 3/8 " Depth: 27 1/2 " Min. height: 42 1/8 " Max. height: 47 1/4 " Seat width: 20 1/2 " Seat depth: 18 1/2 " Min. seat height: 16 7/8 " Max. seat height: 23 5/8 "  Width: 62 cm Depth: 70 cm Min. height: 107 cm Max. height: 120 cm Seat width: 52 cm Seat depth: 47 cm Min. seat height: 43 cm Max. seat height: 60 cm  First, truth as a stored value. The example we thought of was inventory level – what is inventory level for a certain product? In a world with limited computer resources, the simplest way to have this number would be to periodically calculate it, and then store it so people can have access to it. When you go to IKEA’s web site to search for a nice and cheap office chair (such as the pictured Verner), for instance, they will give you an estimated number in the store closest to you. I don’t know how IKEA calculates that number, but I doubt if they dip into the local POS system of each store to precisely check it each time you query. (If they do, more power to them.) If this number is calculated on an intermittent basis, it will of course be rather imprecise – but it is computationally easy to get to. Similarly, if you ask Google about the distance to the moon, they will come back with documents which have that number in them, generally agreeing on an average of 384,403 km (238,857 miles). However, that is an approximation, since the moon is can be as near as 363,104 km (225,622 miles) and as far as 405,696 km (252,088 miles) depending on where it is in its elliptical trajectory.

I suspect much of the discussion over which are right in most corporations are about these kinds of numbers – calculated after the fact, subject to interpretation because we just don’t know what the precise situation is, and very often we do not know how we got to that number.

However, computation comes to the rescue – with more powerful computers, sensors and faster networks, we can actually move to the second stage: Truth as a calculated number.

For the distance to the moon example, the simple answer is Wolfram Alpha, the mathematical search engine, which will give you the calculated distance to the moon at the time of the query. For the IKEA example, this would mean calculating the number of Verner chairs in the store each time a customer asks on the web. This can be done varying levels of precision. The simplest way would be to get it from the POS system, which records when a chair is purchased and can subtract it from the inventory. A more precise method, given the length of IKEA’s checkout lines, would be to have a sensor on the chair and track when it is taken out of the shelf and placed on the customer’s cart. Precision is largely a question of how much you are willing to spend. For a physical store, tracking cart volumes is expensive, for an online store, it is, in theory, cheap, since a customer moving an item from inventory to cart is done digitally.

This kind of number is much closer to the truth, and much more operationally useful – and the job of the CIO is to declare how this number should be found, tracked and displayed. It may seem somewhat simple to say this, but this is where there should be no question of the source of the truth – every company should have one and only one, and much of the work of CIOs and their organizations in the last 10-15 years has been in moving companies along until they are capable of calculating the one true number.

Then, we move to the next (and so far last) stage: Truth as a calculated number in context. Context very gets more difficult as the need for precision goes up (which, I suppose, blatantly ignoring the quantum mechanical context, is a sort of business version of the Heisenberg uncertainty principle.)

For the distance to the moon example there is little room for context. You could argue that it be different based on where on earth you are, or for what you are going to do with the information (launching a satellite or calibrating your telescope, for instance) but for most uses, there is little need for contextual customization.

For the IKEA example, the situation is rather different for different parts of the organization, and for different types of customer. If I am a customer looking up the number from my smartphone while close to the store, the POS number might be OK, since I would get to the product in short time and the consequences of imprecision would be small. If the nearest IKEA store is several hours’ driving away, then I might want a different number, one that incorporates not just the current situation but also the likelihood that the number would be zero before I get there. Or, I might want a reservation function, either setting the product aside or at least allowing me to report that I aim to buy one within the next x hours and thus would like the number shown as available to be reduced until I can make it to the store. In an online store, the problem is the diametrical opposite – there, customers can have carts sitting for days and it becomes an operational necessity to have some policy declaring at what point the products in the cart will have to be made available to other customers.

Similarly, the very concept of inventory level itself means different things to different parts of the organization. For a store manager, it is a cost concept, something to be optimized in a balancing act between capital costs and stock-outs. For a supply chain manager, it is also a flow concept, something to be optimized between stores. For someone managing the physical space of the warehouse, it is a physical concept – goods that have been sold to a customer but not yet picked up are very much something you need to manage. And for a sales person, inventory levels is an availability concept, often subject to negotiations and transfers within the organization.

So, what is a CIO to do?

I think the declaration of a source of truth is a question of hitting the right level, navigating between the simplicity of simple numbers and the complexity of inferred context. In most cases, I suspect, the optimum lies in providing the ability to find the truth, giving customers (i.e., of the IT organization) their numbers at the source – which should be the one, declared one – but also giving them the tools to interpret them in light of their own context.

The key here is not to try to move from the first phase to the third without missing the second. Unfortunately, in my view, many IT organizations have done just that, by responding to requests for customized reports, systems and views from archival rather than current, operational data. As each number becomes institutionalized through use within its context, transitioning to a declared truth can become an exercise in power rather than rationalism. Better to promise context after speed and precision has been provided – and even better, provide the context in a format the end consumer can relate to within their own context.

For IKEA, that might be giving me the number of chairs available plus a prediction (based on history and, say, number of cars in IKEA’s parking lot) as to how many chairs are likely to be sold, with variance, within the next x hours. For the rest of organization, well – it depends. But ones you provide real-time access to well defined operational data, you can safely leave the question of what it depends on to the person wanting to use it.

Steven Pinker on the decline of violence

Steven Pinker, just out with a new book (The Better Angels of Our Nature: Why Violence Has Declined), gives a talk outlining how rates of violence are falling in the world, and the causes of this. Excellent, highly recommended, and available for free in high resolution:

Progress is actually progress. Hans Rosling would agree.

Update March 30, 2012: I really should clean up my notes and add to this post, but this review by Peter Singer sums it all up nicely, so I won’t bother. But it is worth a read, 800 pages and all.

Epicurean financial readability

The Epicurean DealmakerThe Epicurean Dealmaker is one of my favorite blogs – witty, learned, topical, writing anonymously and eruditely on topics financial and others. That someone can profess to be an epicurean and at the same time an investment banker may seem like a contradiction in terms, but from his/her writings, the worthy blogger seems to pull it off. May he never be found out – or worse, may he not be found to be an out-of-work high school dropout with a Unix box, a Greek library and CTS.

Anyway, his latest missive on the continuing counterparty risk caused by investment banking consolidation and market monopolization is definitely worth your time and not inconsiderable effort. The causes of the last financial crisis are a alive and well, thank you very much. Lest you think the worthy Epicurean is an insider with an ax to grind, let me offer his elegant, is snarky, caveat emptor defense of the industry as well.

Investment banking and the whole “structured products” industry is so complicated that anyone can get lost – and most politicians and economists seem to avoid discussing it, much like most executives avoid discussing technological and network externalities. It simply is too hard, too complicated, and lacking in easy, sellable solutions. Better to not talk about it, at least not in detail.

By the way, he blames the lawyers for much of the complication of financial regulation. Hard to disagree.

Hoisted from comments: Entering the networked society

I liked this video, mentioned by @karthix in the comment for the previous post on examples of how computers are encroaching on domains formerly thought to be exclusively human:

Aside from the elegant examples, I found it relatively concrete and hubris-free – compared to this rather anemic vision of the future Microsoft has bestowed on us. It actually works better as a parody.

(And yes, I know that “hoisted from comments” is a Brad DeLong expression. Why not learn from the best?)

Computers taking over: Examples

I am currently thinking about how computers are taking over more and more of what we humans can do, in ways we did not think about just a few years ago. The impetus for this, of course, is Brynjolfsson og McAfee’s recent e-book Race Against The Machine, where the main examples given are Google’s driverless cars, instant translation software, and automated paralegal research. I’ll use this blog post as a repository for examples of this, so here goes:

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Trapping the wily professor

I wrote this piece in 2004, and it was published in European Business Forum, a journal sponsored by Boston Consulting Group, which since has disappeared (the journal, not the company!) Hence, I am making it available here in my blog, for your reading pleasure:

Trapping the wily professor
A hunting guide for CLOs
February 2004

Recently, I attended a meeting of senior HR executives from large European companies. The attendants were all engaged in designing and/or running various forms of management training and education in their companies, and a discussion about how to deal with outside suppliers – particularly business schools – came up.  A key problem, it transpired, was getting the good professors to engage in company programs.  While the schools were more than willing to sell their branded programs, most corporations wanted something tailor-made, designed to achieve a specific corporate learning goal.  Furthermore, they wanted it tailor-made by the big names – that is, the professors the students were likely to know.  This had proved very difficult.  These were big, prestigious companies – why couldn’t they get the big, prestigious professors?

Coming from the supply side of this relationship, I have little problem understanding the difficulties these managers have – so I herewith offer a little guide to hunting down and keeping that rarest of animals, the business-savvy and interesting professor.  A warning, though: This is not a task to be approached lightly.  Hunting requires knowledge of the prey itself, its living environment, and its reward structures.  It requires patience and a keen sense of observation, as well as an ability to communicate with the natives – or at least not to offend them too much.

First: Hunt professors on your turf, not theirs.  The best place to hunt for professors is not through the business school sales channels.  Instead, invite the professor to come into your company to give a short talk on some very specific point of interest – half an hour is fine – at some small executive meeting, with lunch and informal discussions thereafter.  Pay the professor for the presentation.  If there is no chemistry, you have listened to a (hopefully) interesting presentation and the professor has made a little money and is likely to think of your company with benevolence.  Incidentally, the best referrers of professors are other professors – so use the occasion to extend your network.  Carefully cultivated, most professors will come when you call and leave you alone when you want them to.

Secondly: Avoid the obvious blunders.  This should go without saying, so the experienced professor-hunter may want to disregard this paragraph.  However, any high-powered and dynamic business executive can unknowingly scare away the wily professor without meaning to – the equivalent of putting on aftershave before the hunt and then ondering why you never see any prey.  Professors are academics, and you hunt them because they are.  Consequently, never use the word “academic” to mean “irrelevant”, “hypothetical” or “impractical”.  Never refer to them as “educators” – in academic cynical parlance, an “educator” is someone forced to live by teaching because he can’t do good research.  And never – never ever – ask them to include that interesting best-seller (“Who drank my café latte?”) you saw in the airport bookshop in their program curricula.  Professors are extremely jealous of outside intellectual competition, and anyone preferring the Heathrow School of Management to them is treated with extreme suspicion, if not outright hostility.

Third: Don’t deal with intermediaries.  Typically, the CLO seeking a management education program interacts with a relationship manager from the business school.  This person is pleasant, nicely attired and means well, will sell you the standard programs and tell you what you want to hear, but is incapable of trapping the wily professor on your behalf.  If you want a program out of the ordinary, talk to the person most critical for its success – and that better be the professor, because if program responsibility lies with the salesperson, you are in trouble. That being said, the school’s relationship manager is very useful as a support person – so let your own support person deal with him or her, and make sure that the minute any content issues spring up, the problem is escalated to you – and the professor. (And, by corollary, don’t fall into the trap of becoming an intermediary yourself, in the case when a business colleague needs a program and asks you to set it up.)

Fourth: Ask not what the professor can do for you, but what you can do for the professor.  Professors are not motivated by money. Actually, that is a whopping big lie – they certainly are, but it needs to come in a form palatable to the world they inhabit. Doing executive education does not help a professor in his or her career – at best, it earns him or her non-tradable brownie points for helping the school. What counts in the academic hierarchy – at least officially – is publishing what to the layman appears as unreadable articles in obscure journals read by few and remembered by even fewer.  These articles are created through back-breaking work and qualified through an evaluation process that makes Purgatory feel like a day at the beach. To do the work, the professor needs money, in the form of research grants.  To get through the evaluation, he or she needs data, obtained by getting access to corporations.  If you can give the professors research money and access to data (i.e., your company,) they will happily create executive education programs as part of the research process. They will even teach them.  (It is possible to bag a few professors through money alone, primarily the younger ones, but on a repeated basis this will yield a lower quality of prey).

Fifth: It is not what you say, it is what you do.  The above will attract and retain professors, but will not earn their undying love. To achieve that, you need to follow through and do what they say. Professors seeing their theories listened to and applied will do anything you ask of them – sit on your Board, talk to your executives, co-write career-enhancing articles with you in trade magazines and even listen to your suggestions for making their theories better.  The danger herein lies in that you may go native yourself – and what a tragedy that would be.

So there you are – to bag a professor, start by wining and dining them, paying them for a small presentation, then lure them with money and access to provide you with tailor-made and interesting executive programs.  It is easy.  You can start now.  My email is at the top of the page.