Category: Innovation

How to measure innovation: a quick guide for managers and leaders

Over the past couple of months, I received multiple requests to explain how innovation can be measured. The Covid19 pandemic has caused managers at many organisations to consider innovating for the first time, as established business models were threatened and they began exploring new markets, products or services.

Here is a short note I thought I’d share for those interested. If you have thoughts, comments or resources to share, please post them in the comments section.

Measure dilligently, but be careful what you measure.

Continue reading “How to measure innovation: a quick guide for managers and leaders”

How to tax the platform economy?

In the engine room of nation states, ie the tax departments, the coming battle with platform providers is taking shape. Uber, airbnb, facebook, linkedin, ebay, jobseek, and a myriad of specialised platform providers facilitate micro-trades that are largely untaxed by the authorities. In stead, the platform providers themselves take a cut, partially via advertising and partially via a direct fee for their services. They have taken over an activity that has mainly been provided by governments in the past: places to trade. The town square, the stock exchange, public infrastructure, and the unemployment office are relics of a past where governments were market providers that facilitated trades. Now, it is largely private companies with tax-avoidance structures that have taken on this role on the internet. That role is set to expand hugely.

This is a crucial battle that, so far, the tax authorities are losing because they have not yet grasped the magnitude of the shift. They lack the key new power that they must attain: the power to deny the operation of a platform provider in their country.

At the moment, tax authorities around the world, lead by the Scandinavians whose tax needs are high, are going the usual ‘reporting route’. They are trying to get Uber, Airbnb, and all the other ones to report the trades and the value of the trades that they have facilitated. Understandably, these companies are refusing to play ball because they of course are taxing the same trades themselves in a different way. They are competing with national tax authorities and hence their business model depends on tax evasion, so of course they refuse to help their competitors. Their lawyers make millions from refusing to play ball. The horror example for these companies is the 2015 data on Uber that had to be released to the Dutch tax authorities and that was subsequently shared with Denmark which promptly went after the drivers for added tax payments. This reflected the circumstance that the administration of Uber was in the Netherlands at that time, which allowed the Dutch to force Uber to hand over some of their data, a mistake Uber wont make again. The others too will have learned a salutary lesson from that episode.

Frustrated, the tax authorities are turning to pretty hopeless measures, such as new international treaties on the reporting of micro-trades by private entities. In a race to the bottom between countries trying to attract large companies, that is just a hopeless avenue where the authorities will always be many steps behind the tax-advisers of the big trading platforms.

What are the next moves we might then see when the tax authorities get up to speed? I think two developments are likely: full internet observation by national agencies and government-lead internet firms.

Full internet observation follows the model of China, which now has the capacity to track most of the internet activity of most of the population. That allows it to observe the trades facilitated on internet platforms, which in turn can be used for tax purposes. Those observations can be used to directly go after individual traders or can be used to go after the platform providers, simply by making their activities illegal if the platforms do not assist in tax observations. Adopting the China route would spell the end of internet privacy, but it probably works. And tax is such a key part of the nation state that it in the end trumps privacy concerns.

The second possibility is for the government to re-enter the market for platforms and set up its own internet firms for micro-trades and social media. It can simply copy the best examples on the internet for how to set these things up. The transition will come with losses, but authorities can appeal to national pride to get support from their populations and companies cannot compete with that. For micro-trades within a country or tax region (the US and, in the future, the EU) that should work. For international trades, one should expect more difficulties because government-backed firms from different countries might then directly compete with each other, which in turn might lead to competency battles and new dispute resolution mechanisms.

Review: Tomer’s Advanced Introduction to Behavioral Economics

In the next couple of months I shall, in preparation for an invited longer review essay on recent books on BE, post reviews of individual books such as Tomer’s, Angner’s A Course in Behavioral Economics, Cartwright’s An Introduction to Behavioral Economics, and Dhami’s The Foundations of Behavioral Economic Analysis. Comments are welcome.

Here is the first review, for your entertainment:

Tomer, John F. Advanced Introduction to Behavioral Economics. Elgar (2017). ISBN: 978 1 78471 991 3 (cased), ISBN: 978 1 78471 993 7 (paperback)

Tomer, an Emeritus Professor of Economics at Manhattan College, covers much ground in a fairly superficial manner. We are lectured about the scientific practices of “mainstream economics” (narrow, rigid, intolerant, mechanical, separate, individualistic; see p. 10) and the emergence of behavioral economics (BE). In passing, we hear about different “strands” of BE (chapter 3: “The bounded rationality strand”, chapters 4 and 5: “the psychological economics strand”, chapter 6: “behavioral finance”), “BE, public policy, and nudging” (chapter 7), “law and BE” (chapter 8), “behavioral macroeconomics” (chapter 9), “the empirical methods of BE” (chapter 10), and neuroeconomics (chapter 12). We are also treated to an answer (I am sure you can guess it) to the question: “Are mainstream economists open-minded toward behavioral economics or do they resist it?” (chapter 11) In chapter 13 the author enlightens us about paths “Toward a more humanistic BE” and in chapter 14 we can read about “Behavioral economic trends”.

Each of these chapters are about 10 – 12 pages long. Along the way we hear about ENE’s (Early Neoclassical Economics) and NE’s (Neoclassical Economics) “lack of behavioral realism. NE’s lack of connection to other social sciences in particularly regrettable for those who place a high value on a unified social science or at least on having many viable linkages among the different social sciences.” (p. 9) Referring to a decade-old study of his that was published in an inconsequential journal, we learn that “The results for NE (also referred to as mainstream economics) are quite clear. NE is rated high on all six dimensions (narrowness, rigidity, intolerance, mechanicalness, separateness, and individualism,” (p. 12). After this paper tiger has been successfully constructed, we are told how it is being torn to smithereens: “ In contrast, the eight strands of BE … are in general far less narrow, rigid, intolerant, mechanical, separate, and individualistic than NE. … Overall, there is clear evidence that BE is 1) less positivistic than NE … , 2) distinctively different from NE, and 3) much more integrated with other social science disciplines than NE. In other words, BE is arguably better than NE in the way it conducts its scientific practices.” (p. 12)

This tired rhetorical figure has been used by those marketing BE for a long time. It also shows up regularly in the press (e.g., Elliott 2017 but see Attanasio et al. 2017 or for that matter Ortmann 2012), the related blogosphere, and even literature (Schumacher 2014): while BE is much more realistic and useful, NE is the old staid economics (that has done little for us). In the words of the protagonist of Dear Committee Members, “ … sociology has gone the way of poli-sci and econ, now firmly in the clutches of rabid number crunchers who have abandoned or forgotten the link between their abstruse theoretical musings and the presence of human beings on the planet’s surface; .. ” (p. 152)

That lack of behavioral realism is, so we learn, addressed by behavioural economists’ wholesale adoption of psychological insights which inevitably “enrich” the dismal models of mainstream economists. Ignoring the interesting question what the trade-off is that these richer models come with – in this book this trade-off is never discussed -, there are at least two issues here.

First, and to repeat a theme that I have belabored elsewhere (see also this comment here), there is no such thing as a monolithic body of evidence in psychology that economists could mine to inject more behavioral realism in their allegedly dismal models. The fact is, much of the evidence on heuristics and biases that is being appealed to has been questioned left and right. Every halfway knowledgeable (behavioral) economist will agree that the only interesting question about cognitive biases (such as reference dependence, endowment effects, availability, anchoring & adjustment, and representativeness) is when, and under what circumstances, they exist (if they exist at all).

Second, and more importantly, psychology as a field has, at least since Bem (2011), gone through what many people have called a replicability crisis (e.g., OSC 2015, Spellman 2015, Schimmack 2018) that played out at first in blogs and discussion groups such as the Facebook Psychological Methods Discussion Group, but increasingly also in journals and their practices. You would not know that some such upheaval is happening from reading Tomer’s book.

Take, for example, Tomer’s telling discussion of Zak’s oxytocin research in chapter 13. We learn that he is “a well-known economist who appreciates the softer, more intangible side of human behavior” (p. 145) and has shown through his research that “there is a direct link between the amount of oxytocin in humans’ blood and brains and humans’ concerns for each other. … Most importantly, oxytocin fosters trust. Oxytocin surges in a person’s bloodstream when an individual is shown a sign of trust and/or when something engages in a person’s sympathies and they experience empathy. ” (lit cit) Unfortunately, these claims have been thoroughly debunked and even effectively ridiculed in one of John Oliver’s excellent shows. All the literature I know suggests strongly that Intranasal oxytocin has no discernible effect and claims to the contrary are about as much bogus science as claims of ego depletion and the empowering effects of power poses: what these alleged phenomena reflect is little but shoddy science that people got away with for too long, demonstrating a cavalier attitude to questionable research practices from p-hacking over lack of proper powering up to hiding unsuccessful trials in drawers. You would not know about this crisis if you trusted Tomer who seems completely unaware of these developments that are slowly also starting to be recognized in economics.

Yes, I am not impressed by Tomer’s book. The knowledge laid out in Tomer’s slim volume is severely out of date and unabashedly partisan. According to the December 2017 IDEAS/RePeC data, there are at least 50,000 research economists out there world-wide and they innovate every day in what is most likely one of the most brutally competitive industries the world has seen. The idea that somewhere someone (“mainstream economics”) has a monopoly on doctrinal truth and can enforce it, shows a stunning cluelessness about the current state of the art (and science) of economics and its sociology. In his recent presidential address, Alvin E. Roth – an outsider of sorts himself — has argued that economics has been very open to various outsiders and their ideas and practices and you have surely seen that in the emergence of experimental economics and also in some quarters of BE (although BE remains afflicted with many charlatans, often of the non-academic kind that sell BE as panacea to everyone who thinks they can get something for nothing).

I doubt that Tomer’s slim volume is “particularly useful for advanced undergraduate students, graduate students, policymakers, and other professionals who participate economic-related matters.” (statement on the back of the book) In fact, I fear it will promote more sloppy science of the kind that is on display in this book. That kind of sloppy science is also too often on display when you speak with policy makers and Behavioral Insights architects and the like these days.

When all is said and done, it is this kind of sloppiness that undermines trust in the joint enterprise called science.

Lemonade and the question of (laboratory) evidence

Lemonade Inc., the New York based fintech startup that sells home and renters insurance has been in the news recently. It has raised tens of millions in venture capital and also considerable interest in the top echelons of corporate Australia. I know because I was asked to reflect on it as part of a workshop on behavioral economics/behavioral science that I conducted a couple of months ago. I have to admit that I did not know about Lemonade before that request.

Turns out that Lemonade uses “Behavioral Science (and Technology) To Onboard Customers and Keep Them Honest”, so the title of a piece in Fast Company earlier this year. Lemonade bets that insights from Behavioral Economics (BE) will give it the edge over incumbent competitors. It bets specifically that the BE insights of Dan Ariely (he of Predictably Irrational and TED talk fame, and now Lemonade’s CBO = Chief Behavioral Officer) will provide that edge, important components being “trusting our customers” and “giving back” to charity all unused excess funds. On top of these components, or maybe undergirding it, is the promise that Lemonade commits to spending at most 20 percent of its income on administration and marketing, which presumably prevents it from profit maximizing at the expense of its customers. Lemonade also promises that it will process claims fast and relatively un-bureaucratically, at least by the standard of an industry that has a reputation for delaying tactics and for its persistent attempts to evade having to pay up. Examples of speedy processing are featured prominently on Lemonade’s website.

And not only that: A couple of months ago, Lemonade launched its Zero Everything policy which gets rid of deductibles and rate hikes after claims and is supposed to pay for itself through elimination of the paperwork that comes with relatively small claims.

BE principles are also appealed to when customers that make claims are asked to submit a brief video outlining their claim and to provide at the same time a honesty pledge which supposedly induces more honesty.

In sum then, Lemonade builds its business allegedly on the trust(worthiness) of its customers, and of itself, and also honesty on the part of both parties.

Let’s start with the (laboratory) evidence for trust(worthiness). On its web page, Lemonade illustrates the advantages of trust(worthiness) with one of the workhorses of experimental economics, the trust, or investment, game. According to the web page, a person that invests (the trustor) will see her investment to a trustee of $100 quadruple and then see the trustee return half of that $400 to herself (the trustor), for an impressive ROI of one hundred percent. Trust pays off, we learn: “We are more trusting and reciprocating than what standard economic theory predicts.”

Ignoring the stab at economic theory (which shows little more than a lack of elementary knowledge of modern economic theory), there are at least three problems with the Lemonade narrative. First, it is not clear at all why this particular game, in this particular parameterization, captures the customer – insurance company situation. Second, I am not aware of anyone ever having experimentally tested this game with that specific parametrization (specifically, a multiplication factor of 4), and I am not aware — the multiplication factors typically used being 3 or 2 — of responders returning more than what was invested. In fact, the results of my own work (which are very much in line with the literature in this area) suggest that trustors invest about half of what they were given and trustees return slightly less than what was invested. It is noteworthy that there is much heterogeneous behavior to be found in these experiments, with many of those that trust (“invest”) being brutally exploited.

“Everyone has a price, the important thing is to find out what it is.” (P. Escobar)

Which brings us to the question of honesty. There is indeed some evidence that the way in which people are being prompted makes a difference and, more generally, that context matters (see Various, JEBO 2016). Friesen & Gangadharan (Economics Letters 2012) use an individual performance task (“matrix task”) after which they ask their subjects to self-report the number of successes that participants had. While very few of their participants – only one out of 12 — are dishonest to the maximal extent, about one out of 3 are to different degrees, with men (in particular those of Aussie and NZ provenance) being more dishonest, and more frequently so, than female participants. Rosenbaum, Billinger, & Stieglitz (Journal of Economic Psychology 2014) review experimental evidence of (dis)honesty 63 experiments from economics and psychology (including Friesen and Gangadharan EL 2012) and find the robust presence of unconditional cheaters and non-cheaters with the honesty of the remaining individuals being particularly susceptible to monitoring and intrinsic lying costs. Most of these experiments involve fairly low stakes, so those intrinsic lying costs are unlikely to be much of a constraint when stakes increase. The fraction of unconditional non-cheaters is almost certain to shrink towards the Escobar limit when stakes increase.

Interestingly, notwithstanding its public declarations in the good of people, Lemonade tells itself that, while trust is good, control is better. It runs its claimants, on top of the honesty pledges, through 18 different fraud detection algorithms before it pays up. On top of this, Lemonade engages in blatant cream-skimming. For example, it did not quote half of their customers that wanted to insure their homes. And it reports that the customers that are joining, or allowed to join, are younger, educated, tech-savvy, above-average earners, and female. So much for trust, trustworthiness, and all that BE marketing horsemanure. Pretty cold-blooded standard economic theory if you ask me. Note that this screening takes care of a key problem with their advertised approach: the likely adverse selection of bad types that mere trusting would invite, a very likely whammy on top of the moral hazard problem that every insurer faces.

So is Lemonade a viable business model?

Time will tell.

In the State of New York, Lemonade claims to have overtaken Allstate, GEICO, Liberty Mutual, State Farm, etc. in what is probably the single most critical market (renters and home insurance) share metric of all: NY renters buying new insurance policies since 1 Jan 2017.

Lemonade, we are told, is growing “exponentially” = “new bookings have doubled every ten weeks since launch, and show no sign of letting up.” According to its most recent Thanksgiving Transparency ‘17 report, Lemonade has now branched out into, and is selling in, Illinois, California and Nevada, Texas, New Jersey and Rhode Island, and has been licensed in 15 other states.

Of course, collecting insurance premia is one thing. Paying insurance claims and balancing the books is another thing altogether and the verdict on that one will be out for a while.

If Lemonade succeeds – and we all should hope it does –, it will do so because it engages in cream-skimming, targeting of low-risk market segments, and massive control and surveillance of its clientele. It will not do so because of its invocation of the feel-good alleged BE findings so prominently displayed on its web page.

 

 

 

 

 

 

 

 

Why Blockchain has no economic future

When Bitcoin went public in 2009 it introduced to the world of finance and economics the technology of blockchain. Even the many who thought Bitcoin would never make it as a major currency were intrigued by the BlockChain technology and a large set of new companies have tried to figure out how to offer new services based on blockchain technology. It is still fair to say that very few economists and social scientists understand blockchain, and governments are even further behind.

I will argue that blockchain has no economic future in the regular economy. I will give you the bottom-line, then describe blockchain, discuss its key supposed advantages, and then take it apart as a viable technology by giving you a much more efficient alternative to the same market demand opportunities.

The bottom line for those not interested in the intricacies of blockchains and public trust

The essence of my argument is that a large country can organise a much more trustworthy information system than a distributed network using blockchain can, and at lower costs, meaning that any large economic role for blockchain is easily displaced by a cheaper and even larger national institution.

So in the 19th century, large private companies circulated their own money, in competition with towns and princedoms. In that competition, national governments won, as they will again now.

The reason that the tech community is investing in blockchain companies is partially because some are in love with the technicalities of blockchain, some hope to attract the same criminal and gullible element that Bitcoin has, some lack awareness of the evolution and reality of political systems, and some see a second-best opportunity not yet taken by others. But even in this brief period of missing-in-action governments, large companies will easily outperform blockchain communities on any mayor market. Except the criminal markets, which is hence the only real future of blockchain communities. Continue reading “Why Blockchain has no economic future”

Opportunities for innovation in Australia

The Australian startup ecosystem is growing too slowly, but existing firms are becoming more interested in innovation as a source of competitive advantage.

MBS students brainstorming during the Innovation Bootcamp

” data-medium-file=”https://coreeconomicsblog.files.wordpress.com/2015/09/dsc2144-mbsbootcamp.jpg?w=300″ data-large-file=”https://coreeconomicsblog.files.wordpress.com/2015/09/dsc2144-mbsbootcamp.jpg?w=840″ class=”wp-image-10133 size-medium” src=”https://i0.wp.com/economics.com.au/wp-content/uploads/2015/09/DSC2144-mbsbootcamp-300×199.jpg” alt=”MBS students brainstorming during the Innovation Bootcamp” width=”300″ height=”199″/>
Students brainstorming during the MBS Innovation Bootcamp

Australia performed poorly in the global startup ecosystem ranking 2015 which was published recently (http://goo.gl/UXcGcO). Sydney fell 4 spots and now ranks 16th in the world, while Melbourne fell entirely out of the top 20 despite being on that chart in the previous version of the report published three years ago. The study expresses concerns about the Australian ecosystem that echo those in other studies performed by academics as well as in the Australian Government’s Innovation System Report (http://goo.gl/kvQZhK). The 2014 AIS report sums it up nicely: “Australia performs relatively poorly on ‘new to market’ innovation”.

Yet on the ground, interest in innovation and startups has never been stronger than before in Australia. Compared to five years ago, we now have many more ‘meetup’ groups in Melbourne and Sydney for founders and entrepreneurs, a variety of incubators and accelerators, and a number of innovation-oriented programs at leading universities including Melbourne, UTS, Swinburne and QUT. There is strong interest in courses on “design thinking” and “lean startups”. MBS has our innovation bootcamp for MBA students, while the University of Melbourne now has an accelerator and is about to launch a new Masters in Entrepreneurship program. A growing number of entrepreneurs are contacting me to discuss new business models, market entry and how to protect their innovations. These will take time to bear fruit.

How do we reconcile the weak findings at the ecosystem level with growing interest at the ground level? Part of what’s happening is that other startups ecosystems are maturing faster than the one in Australia. Many ecosystems abroad have continued to enjoy stronger government support, better access to venture capital and closer industry-university linkages. The most successful ecosystems (including Silicon Valley, New York, Los Angeles, Boston, Tel Aviv) have continued to develop and reinforce a coherent system for connecting resources, talent, funding and market access. Here in Australia, we have bits and pieces that are good in each major city, and we also have specific firms and sectors that are incredibly innovative. But that distribution is uneven and the parties involved are not as seamlessly interconnected as they could be.

A second part of the explanation is due to the business environment in Australia. Given our small domestic market, many of our startup entrepreneurs will continue to sink at least one foot (if not both feet) into other ecosystems. This makes sense from the point of view of being close to market and expertise.

A big change however is the growing interest in innovation by existing firms. In recent years, incumbent firms in industries ranging from retail to energy, news and financial services have been jolted out of a comfortable (often monopolistic or duopolistic) existence due to the threat of entrants, both online and offline.

The embrace of innovation by Australian firms has taken a long time, partly due to the difficulty of changing the mindsets of senior executives who run these organizations. However, it is clear that in a variety of industries across the globe, the terms of competition have changed and Australia is no exception. In conversations with senior managers at Australian organizations, I am discovering a growing interest in innovative strategy, business transformation, ‘design thinking’ and ‘business model innovation’. These conversations often begin with a reactive or defensive tone reflecting a need to respond to market or technological threats. However at some organizations the discussions have begun to advance beyond that stage: managers at some firms start to view innovation as an opportunity to reconsider their existing ways of doing things, engage new stakeholders and to develop new capabilities.

In the short run, I see a good opportunity in helping existing Australian firms learn to innovate and become more agile and competitive. In the longer run, it would be nice to see the startup ecosystem flourish in Australia, but that is something that will take time and sustained effort.

Note: I was invited to write this article for the Melbourne Business School student newsletter. It is reprinted above, sightly edited.

Unlocking DRM Lets You Open Multiple eBooks Simultaneously

The Amazon Kindle, Apple iPad and other e-readers are fast becoming mainstream and their usability has improved tremendously over the past years. However there is one area in which printed books are still much better: the ability to open multiple books at once. This might not matter if you are reading the latest “50 shades” novel and want to be uninterrupted. However, if you are working on a research project and constantly need to switch across multiple books, you will find that current eBook readers are a nightmare. Switching eBooks involves creating bookmarks, returning to a main menu (library page), going to another book and navigating it. This quickly becomes tedious. I cannot understand why tabbed browsing is absent from eBook software since it is rudimentary and exists in practically every web browser.

One solution is to buy multiple eBook readers and open one book per device. This turns out to work quite well. One might argue that the savings from not having to ship printed books will more than cover the cost of additional eBook readers. However it occurred to me recently that another solution exists: simply remove the DRM from your existing books. This is really easy to do. You can then manage your books using software like calibre, which allows multiple eBooks to be opened at the same time. On a fast computer with a large screen, this is a liberating experience! A 27″ or 30″ screen is sufficient to give me as good an experience as with 3-4 printed books. You can even do things that you cannot with regular books (without mutilating them) such as opening multiple instances of the same book for quick cross-referencing across different sections. If you take the extra step and export your library into pdf format, you then have the ability to manage, annotate and search your eBooks using software like Papers 2, treating them just like any other pdf file and merging them with your collection of journal articles.

There are other benefits of unlocking DRM, including the ability to prevent vendor lock-in (e.g., read your Amazon ebooks using Apple iBooks), avoid arbitrary and unfair removal of your books, and to overcome silly device download limits. For some of us, opening multiple books at the same time is another big plus. I suspect that over time, eBook DRM will go away. We are at the stage of the eBook industry that we were at with music 10 years ago, when we had to rip music from our personal CD collections or the proprietary formats on iTunes and convert them into unlocked files that were more flexible. Today music is sold unlocked and I don’t see why it should end up otherwise with eBooks.

(ps: yes I know eBooks are licensed, not sold, but lets save that for another discussion).

Reading multiple books at once

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Your 30″ monitor can show all these books at the same time

“Blue Ocean” strategy? Actually it does not matter what colour your ocean is

Blue Ocean strategies promise to break the tradeoff between costs and willingness to pay. But they don’t really. The tools offered by the blue ocean approach are useful such as the strategy canvas and ERRC framework, but irrespective of whether your ocean is blue, red or some other colour.

The blue yonder, Mt Eliza

Yesterday my MBA students and I discussed “Blue Ocean Strategy”, a popular book on strategic management by Kim and Mauborgne. A good thing about the book is that it encourages managers to be innovative and to pursue new markets rather than competing in highly competitive existing arenas, i.e., playing in “blue oceans” instead of “red oceans”. According to the authors, this way of thinking has served well for companies like Cirque du Soleil, Nintendo and Casella, an Australian firm that has succeeded in selling easy-to-drink wine in the US. Managers are encouraged to use the Strategy Canvas as an organizing framework (see here for an example). This encourages managers to ask themselves whether their products and services are really distinct after all, and along what dimensions they actually differ from the competition.

So far so good. But the problem is that in their enthusiasm, Kim and Mauborgne go on to make a tantalizing claim that the blue ocean approach allows you to break the tradeoff between pursuing differentiation and low costs. This puts them at odds with many leading strategy textbooks, which argue that it is often difficult for firms to increase consumer “willingness to pay” (WTP) while simultaneously reducing cost, all else being equal. You usually have to spend money on R&D, marketing and better execution in order to increase WTP. The “blue ocean” claim leads to all sorts of confusion among MBA students.

Does the blue ocean approach actually offer a silver bullet? Unfortunately not. The truth lies in the details. For a blue ocean strategy to work, you aren’t just supposed to add new activities that increase willingness to pay. You are also supposed to look for opportunities to eliminate or reduce others in order to cut costs. This is presented as the “ERRC” framework (pg 35 of the book) which asks managers to raise and create new dimensions for their product/service, while eliminating or reducing others. For example, Cirque du Soleil increased willingness to pay by introducing broadway-style themes, artistic music and dance, and better stage lighting to their productions. Meanwhile they reduced costs by eliminating animal shows and star performers, both of which are expensive cost components for a circus.

From the above it should be apparent that you still face a tradeoff between costs and willingness to pay. But you are just avoiding it by removing some of the costly activities. In other words, it isn’t the case that all else is equal. If Cirque du Soleil were able to offer all the new features in addition to having animals and circus stars (but at no marginal cost), then it would be legitimate to make a claim that the cost-WTP tradeoff had been broken. But fundamentally this tradeoff remains, and while the exciting new features enabled Cirque du Soleil to differentiate themselves from ordinary circuses and to increase ticket prices, the removal of animal shows and star performers inevitably meant that some customers who valued those things were now less willing to pay for a show.

Overall, the strategy map and blue ocean approach are useful because they encourage managers to think outside the box when looking for new competitive opportunities. But personally I find the distinction between blue and red oceans somewhat forced, especially when you realize that a firm produces multiple products, and these are likely to fall along a spectrum ranging from red to blue and beyond. So while the Nintendo Wii was blue ocean in approach, other Nintendo products at that time such as the DS were clearly not. In a fundamental sense, increasing WTP and reducing costs are complementary (Athey & Schmutzler, 1995). Hence, finding new and innovative opportunities to increase WTP and reduce costs should be something a manager ought to do anyways, regardless of whether their ocean is blue, red, purple or some other colour.

Cloud computing and the “me versus you” problem

A Personal Workspace

I’m finally getting back to blogging after spending a couple of months traveling then catching up with work. This week I was invited to speak at a “guru forum” of managers and academics who work in information technology. Among the many issues that were discussed, two conflicting trends were identified. On the one hand many corporate organizations are moving towards cloud services and all-in-one outsourced solutions (Oracle, SAP, IBM, …). On the other hand individuals are moving towards a “bring your own” model, bringing their own computers, e-books, cellphones, iPads and other devices to their workplaces. With the advent of smartphones and social media platforms such as Facebook, computing is becoming more consumer-centric and primarily a means for social interaction, rather than just a tool for specific tasks like word precessing and accounting.

These opposing trends create a disconnect at the workplace between the ability of firms to manage and control information (especially proprietary information) versus the desire to give employees flexibility and freedom in choosing the tools they really want to use. My view is that the trend towards consumer-centric computing will dominate the other paradigm. There is no turning back the preferences of modern information workers who grew up with their iPads, Android phones and Kindles. Companies should embrace rather than fight the trend.

How do we solve this “me versus you” problem? i.e., organizing information on multiple devices in a way that separates private from work and other shared information in an easy but manageable way? Existing solutions are unsatisfactory because they do not adapt to the different and changing contexts that individuals find themselves in. Companies like Apple, SAP and Oracle take a fully integrated approach, allowing you to run everything on their software and leveraging their own cloud solutions, treating each device as a client. Bringing this to the extreme, you can run entire virtual machines from your own device with everything hosted on the service provider, such as via Amazon S3 or OnLive. Unfortunately this is often an all-or-nothing proposition, so while it creates separate contexts, the operation across contexts is not seamless. You’re basically running separate computers (or syncing to separate clouds) from within your own device, and it is slow and clunky to inter-operate between them.

In contrast, other firms like Dropbox provide services that integrate into your existing applications and folders, but end up being highly fragmented especially when it comes to setting permissions and giving access. Each application and each collaborator needs to be authenticated, so coordination can be a hassle. This week my colleague tried to set up a shared Dropbox folder for the faculty members at our school, and it seemed a lot more of a hassle than it needed to be, especially the bit about inviting each user and trying to get them to actually sign up to the Dropbox cloud.

The good news is that the solution of the “me versus you” problem is closer at hand than many might think. The architecture for such a solution already exists in products like Google Circles and VMware but is not yet pervasive. Here’s an example of what one such solution might look like. At present most operating systems support multiple workspaces, but for now they are all tied to the same set of permissions and applications. Well, imagine a future in which each workspace on your device is authenticated to different sets of applications and clouds. For example, your device could include a personal workspace that authenticates to Apple and Dropbox and which contains your personal files, apps and Facebook page. A second workspace could authenticate to your office, with the IT system at your office determining what apps and cloud services are made available and which of these you can transfer across workspaces. A third workspace could be one created by your friend so that when you visit her house, her workspace would appear along with some of the data and services from her home network that your friend is willing to share with you.

A small number of us already have something close to this setup running on our computers by using multiple virtual machines that are active simultaneously. But it isn’t the same thing. I’m thinking of something with much more integration than is available in existing virtual machines and with much less of the “heavy machinery” that is needed to support multiple operating systems on the same machine (the action is in the data and apps, not in the operating system itself anymore). I also have in mind something more dynamic, for example with the ability to seamlessly add or remove workspaces when the context around a person changes. In the example above, if your friend defines a workspace that is shared with you when you visit her, that workspace should actually exist in a virtual sense, and it should slide on and off your various devices in a consistent manner including your smartphone, iPad and notebook computer.

Granted, the ideal solution in my head might be a bit far-fetched. However I suspect it will become prevalent in the next several years. I don’t know what it would cost in terms of implementation and adoption. However, the fundamental issues are of great concern among industry practitioners such at those attending the IT Guru forum, so I suspect that over the next few years entrepreneurial firms will end up exploring solutions and frameworks along these lines.

Videos now online: New Models for Book Publishing

Several months ago I wrote about a public forum we organized on the future of book publishing. Our panelists included Piers Pickard (Editorial Director at Lonely Planet), Graeme Connelly (CEO of Melbourne University Bookstore), Nathan Hollier (Manager at Monash University Press), Max Barry (independent author) and Emmett Stinson (Melbourne University lecturer in publishing and communications). Since then, dramatic changes have occurred. Lonely Planet has reorganised while moving aggressively into apps and digital publishing. Amazon has entered the publishing business, bypassing traditional publishers. Books have gotten shorter with efforts like Amazon’s Kindle Singles and TEDBooks being particularly interesting. Closer to home, Melbourne University Bookstore will be privatised soon. So, I decided to spend some time during the weekend editing the video from our public discussion. The podcast is now online. Please follow the link and watch it if you are interested in book publishing.