1 month, 25 days ago

Regulating Platforms

On Friday, Transport for London (TfL) declared that Uber was not fit and proper to hold a private hire operator licence. Uber’s current licence expires next week. However, Uber can continue to operate in London until any appeal processes have been exhausted. (TFL Press Release, 22 September 2017)

By Saturday afternoon, a petition in Uber’s favour had raised half a million signatures. Uber seems to put more energy into campaigning against evil regulators than into operating within the regulations, and was evidently already prepared for this fight. (You don’t send out messages to millions of customers at the drop of a hat without a bit of forward planning.) As Emine Saner writes,

“Calling for better legislation certainly is not as exciting as a glossy app, or whipped-up social media reaction, but it may make your trip home safer – and would be a better use of online petitions.”

The protests follow a number of well-worn arguments

  • Many users of the Uber service (especially young women) have become dependent on a cheap, convenient and supposedly safer alternative to public transport and expensive taxis.
  • Many drivers have borrowed heavily to invest in the Uber business model, and fear being thrown into penury.
  • This is an anti-competitive and technologically backward move, prompted by entrenched interests. And as TfL is itself a transport operator, it is not appropriate that TfL should regulate its competitors.

None of these arguments can be taken completely at face value.

  • It is true that many women believe the Uber model is safer than the alternatives; however, some women have been raped, and other women have had extremely scary experiences. Uber is accused of failing to carry out proper checks, and failing to report serious incidents.
  • Uber service is cheap not only because it cuts costs and exploits its drivers, but also because it is subsidized by Uber investors. This looks suspiciously like predatory pricing rather than fair competition. Analysts such as Izabella Kaminska argue that Uber will only become profitable when it has driven its competitors out of business, at which point it will be able to increase its prices. Like much of Silicon Valley, it appears to operate according to the Peter Thiel anti-competition playbook. Even Steve Bannon has been heard arguing for closer regulation of what are effectively monopoly platforms.
  • Technology companies such as Uber sometimes describe themselves as “disruptive”. While it is true that disruptions sometimes yield socioeconomic benefits, the belief that disruption is always good for competition is based on ideology rather than evidence. Regulation is generally opposed to disruption.
  • And as Stephen Bush points out, it’s not as a digital start-up company that Uber has fallen foul of regulations, but as an old fashioned minicab operator. (As John Bull explains, Uber London is just a minicab company; the app is operated by Uber BV in the Netherlands. This corporate separation helps Uber to finesse both regulation and tax.) Persuading politicians and economists to see Uber as a shining example of technological progress is just “a very, very clever marketing trick”.

I’m quoting Steve Bannon because I’m just amazed to find something I agree with him about.  Regulating platforms is not the same as regulating regular companies, and the general art of regulation needs a kick up the proverbial. However, that is no reason to diss the current regulations or regulators, who are doing the best they can with insufficient regulatory mechanisms and resources. Experience from other cities shows that if Uber can’t get its act together, there are plenty others that can.

John Bull, Understanding Uber: It’s Not About The App (Reconnections 25 September 2017)

Stephen Bush, The right are defending Uber, because they don’t really understand it (New Statesman 22 September 2017)

Martin Farrer, Nadia Khomami et al, More than 500,000 sign petition to save Uber as firm fights London ban (Guardian 23 September 2017)

Ryan Grim, Steve Bannon Wants Facebook and Google Regulated Like Utilities (The Intercept, 27 July 2017)

Hubert Horan, Will the Growth of Uber Increase Economic Welfare? (September 14, 2017)

Izabella Kaminska. For references see earlier post Uber Mathematics 2 (December 2016)

Sam Levine,‘There is life after Uber’: what happens when cities ban the service? (Guardian 23 September 2017)

Jason Murugesu, Night bus or black cab – what will save stranded Londoners post-Uber? (New Statesman 22 September 2017)

Andrew Orlowski, Why Uber isn’t the poster child for capitalism you wanted (The Register, 26 September 2017)

Emine Saner, Will the end of Uber in London make women more or less safe? (Guardian, 25 September 2017)

Related posts (with further references): Platform, Regulation, Uber

3 months, 4 days ago

Digital Disruption, Delivery and Differentiation in Fast Food

What are the differentiating forces in the fast food sector? Stuart Lauchlan hears some contrasting opinions from a couple of industry leaders.

In the short term, those fast food outlets that offer digital experience and delivery may get some degree of competitive advantage by reaching more customers, with greater convenience. Denny Marie Post, CEO at Red Robin Gourmet Burgers, sees the expansion of third-party delivery services as a strategic priority. So from agility to reach.

But Lenny Comma, CEO of Jack in the Box, argues that this advantage will be short-lived. Longer-term competitive advantage will depend on the quality of the brand. So from assurance to richness.

Stuart Lauchlan, Digital and delivery – which ‘D’ matters most to the fast food industry? Two contrasting views (Diginomica, 16 August 2017)

Related post: Reach, Richness, Agility and Assurance (Aug 2017)

3 months, 5 days ago

Reach, Richness, Agility and Assurance

The concept of TotalData™ implements the four dimensions of data and information – reach, richness, assurance and agility. But where did these dimensions come from?

I first encountered these four dimensions in discussions of net-centricity, which spilled out from the US defence world into the commercial world over ten years ago. Trying to dig up the original material recently, I found a military version in a report written in 2005 by the Association for Enterprise Integration (AFEI) for the Net-Centric Operations Industry Forum (NCOIF).

Going further back, the first two dimensions – reach and richness – had been discussed by Evans and Wurster before the turn of the millennium. They argued that old technologies had forced you to choose (either/or) between reach and richness, whereas the new technologies emerging at that time allowed you to have both/and.

Source: Evans and Wurster 1997

The authors also introduced the concept of affiliation, by which they meant transparency of relationships – for example, knowing whether the intermediary agent is working for you or working for the other side. Or both. And knowing who really wrote all those “customer reviews”.

According to the authors, it would be these three factors – reach, richness and affiliation – that would determine the success of e-commerce. Clearly some sectors would be more open to these factors than others – according to The Economist in February 2000, online trade was then dominated by business-to-business (B2B). The three factors identified some of the challenges facing other sectors, including professional services, in going online. As Duncan, Barton and McKellar argued for legal firms, “The Web provides Reach, but offering Richness and the sense of community required for creating and sustaining relationships with visitors could be difficult.”

Meanwhile, new architectural thinking had shown ways of resolving the traditional trade-off between speed (agility) and quality (assurance). (A very early version of this was known as Bimodal IT. Some industry analysts are still pushing this idea.)

When agility and assurance were added to reach and richness to produce the four dimensions of net-centricity, affiliation appears to have been divided between community (reach) and trust (assurance). But the importance of affiliation was never entirely forgotten. As Commander Chakraborty observes, “organisational affiliations and culture … play very significant roles in a networked environment.”

So whatever happened to net-centricity? It has been replaced by data-centricity, which, as Dan Risacher argues, is probably a more accurate term anyway. Or as we call it at Reply, TotalData™.

Notes and References

Much of the original material for the NCOW Reference Model is no longer available. This includes the pages referenced from Wikipedia: NCOW (retrieved 8 August 2017). Net-centric concepts were incorporated into DODAF Version 1.5 (April 2007).

Define and Sell (Economist, 24 Feb 2000)

AFEI, Industry Best Practices in Achieving Service Oriented Architecture (SOA) (NCOIF, April 2005)

Devbrat Chakraborty, Net-Centricity to Ne(x)t-Centricity (SP’s Navel Forces, Issue 4/2011)

Peter Duncan, Karen Barton and Patricia McKellar, Reach and Rich: the new economics of information and the provision of on-line legal services in the U.K. (16th Bileta Annual Conference, 2001)

Philip Evans and Thomas S. Wurster, Strategy and the New Economics of Information (Harvard Business Review, Sept-Oct 1997)

Philip Evans and Thomas Wurster, Blown to Bits – How the New Economics of Information Transforms Strategy (Boston Consulting Group, 2000) – excerpts. See also reviews by McRae and O’Keefe.

Hamish McRae, The business world: Three factors that lead to successful e-commerce (Independent, 17 November 1999) – review of Evans and Wurster (2000)

Jordan Moskowitz, Richness versus Reach (Service Channel, 29 Jan 2013)

Terry O’Keefe, The strategy of information: Richness and reach (Atlanta Business Journal, 1 November 1999) – review of Evans and Wurster (2000)

Dan Risacher, The Fundamentals of Net-Centricity (a little late) (4 February 2013)

Related Posts: Beyond Bimodal (May 2016), New White Paper – TotalData™ (August 2016)

TotalData™ is a registered trademark of Reply Ltd.

4 months, 2 days ago

On the Nature of Platforms

There are several ways of thinking about platforms.

Economists tend to view platforms as essentially containers for transactions. Canonical examples: Amazon, Airbnb, iTunes, Netflix, Uber.

One of the economic advantages of these transaction platforms is that they also act as container for content. When it launched in 1995, the Amazon website boasted a million books – far more than you could find in any bookshop. (This is related to the concept of the Long Tail.) So it becomes a place you can browse books and check reviews, independently of any intention to buy.

Transaction platforms may also enable a significant reduction in transaction costs. This creates an opening for micro-transactions of various kinds – in other words transactions that would previously have been too small to be economically viable. Smaller-grained transactions can allow previously under-utilized assets to be used more economically – for example selling an empty passenger seat on a car journey.

Transaction platforms may also act as a container for data and/or metadata. Dave Chaffey describes “Customers Who Bought X … Also Bought Y” as Amazon’s signature feature. (Amazon.com case study, 30 June 2014)

This notion of platform can be extended to containers of other modes of activity or collaboration or exchange, where there may be no direct financial transaction. Canonical examples: Facebook, PlayStation Network, Linked-In, Skype.

There are various business models underlying these activity platforms, including freemium (Linked-In, Skype), post-sale delivery and engagement (PSN), and advertising. As many people have observed, Facebook inherits a principle that was originally formulated for commercial television – if you are not paying, you are the product. In other words, the underlying transaction is the one between Facebook and its advertisers, whereby Facebook rents out the user to its paying customers.

These platforms are typically described as two-sided or multi-sided. Among other things, multi-sidedness implies some choices about pricing strategy – how to distribute the costs and added-value of the platform between the different sides. For example, credit card provides a transaction platform between consumers and merchants – the credit card company has a choice whether to charge everything to the merchants or to charge the consumers as well. And Facebook and Google provide user services for free, although perhaps one day we shall be so addicted to their services that they can make us pay hard cash to continue.

A different way of thinking about platforms is as a container for capabilities or services. Here, the canonical example would be Amazon Web Services (AWS). At the CBDI Forum, we were writing about AWS over ten years ago, but many people only became aware of AWS when it grew into a massive business in its own right. (Amazon and eBay, August 2004)

The key idea here is that you can build a business on top of a platform. Thus a start-up online retailer doesn’t need to build all the necessary capabilities in-house, because there is a platform of services already available. In the 1990s, telecoms companies were looking for ways to create value-added services on top of the basic communication platforms.

Many companies already have a platform, but they are trying to raise it. For example, the traditional role for telecoms companies is as a platform of telecoms connectivity. But it has been obvious for ages that there is no long-term profitability for telecoms from providing services at this level. So telecoms companies have long understood the need to raise the platform, to offer higher-value services. But they are still struggling to formulate and implement this strategic change. Why is it so difficult? (Business as a Platform, March 2006) 

Similar structures can be found in the physical world. In addition to managing real platforms at railway stations, Network Rail provides a “platform” on which the train operating companies can run their business. In theory these are services with strict service level agreements and contractual or regulatory penalties, although the actual stack geometry is arguably flawed. (Business Service Architecture – Railway Edition, June 2006)

In retail, some large department stores have turned themselves into marketplaces in which franchise retailers can sell their products. Other retailers have experimented with a business model in which the goods are owned by the supplier up to the point at which they are purchased by the supplier. Thus the store becomes a platform for the supplier to merchandise and sell products. See also Nick Vitalari, Walmart and The Power of the Business Platform (Sept 2011).

Platforms are sometimes described as more or less open or closed. For example, the Open Banking Platform. Platform controllers often seek to impose quality or technical constraints on businesses using the platform – for example, Apple iTunes. Thus the notion of openness has a range of meanings, from market openness (e.g. no barriers to entry and exit) to technological openness (e.g. flexibility of mechanism). (Types of Openness, November 2001)

So when business strategy consultants talk about a platform business, this can also refer to the flexible and open-ended exploitation of an asset or capability, to create or co-create value in as many ways as possible. For example, here is John Hagel in 2006, talking about Steve Jobs and Disney.

In a world of scarce attention, creators of media products will need to compete with those who re-conceive media products as platforms. What is the difference? Products are designed to be used on a standalone basis – you buy it and you view it or listen to it in the specific way the content creator intended. Platforms are designed to be built upon – they create opportunities for the original creator, third parties or the customers themselves to extend, enhance and tailor the content in ways that the original creator never anticipated. Offered as a platform, content can create far more value than any equivalent standalone product. (Disney, Pixar and Jobs, Feb 2006)

Finally, we may note that although many of these platforms may be described as “digital”, many of the same basic characteristics can be found in both digital and non-digital modes. And what even counts as “non-digital” these days, when every aspect of our lives can be wired to the Internet? So I prefer not to talk about digital platforms any more – they are just platforms.

Further Reading

Philip Boxer, What Distinguishes a Platform Strategy? (Asymmetric Design, May 2012)

Diane Coyle, The Social Life of Platforms (Enlightenment Economics, May 2016)

For John Hegel’s latest thinking about platforms, see The Big Shift in Business Platform Models (Edge Perspectives, January 2017)

Related posts: Multi-Sided Platform Strategies (April 2013)

4 months, 5 days ago

The Idea of Showrooming

According to Wikipedia, the word “showrooming” was coined in the 2010s. The earliest reference I can find is in a Wall Street Journal article dated April 2012, which opens as follows:

“Shoppers who scope out merchandise in stores but buy on rivals’ websites, usually at a lower price, have become the bête noire of many big-box retailers.”

By September 2012, showrooming is being described as a “commonly held belief”, and being dismissed as a falsehood by the CEO of Best Buy.

But the idea of showrooming was mooted many years previously, in discussions between Jeff Bezos and HP. Nick Earle, then an executive with HP, mentioned this in a keynote speech in June 2000.

During his speech, Earle recalled a conversation he had with Jeff Bezos, the founder and chief executive of Amazon.com Inc., an HP client. When Earle asked Bezos to describe a “killer application” from Amazon.com’s perspective, he described a handheld device with a wireless link and a bar-code reader that would enable customers to scan in a book from another retailer, find out how much cheaper it is sold at Amazon.com, and then order it online for next-day delivery. “We will make one,” Earle promised.

I cited this conversation in 2004, as evidence that Bezos got ecosystem thinking. What I hadn’t realised at the time was that he had basically invented the iPhone. And he had had the idea of showrooming, over a decade before the word was coined.

So I asked Nick (via Twitter) whether HP had ever made such a device.

No they didn’t!

— Nick Earle (@nearle) August 2, 2017

David Jastrow, HP Keynote embraces ecosystem thinking (CRN, 15 June 2000). I have corrected the misspelling of Earle’s surname.

Thomas Lee, Best Buy’s new chief is selling from Day 1 (Star Tribune, 8 September 2012)

Ann Zimmerman, Can Retailers Halt ‘Showrooming’? (Wall Street Journal, 11 April 2012) (paywall)

Wikipedia: IPhone (1st generation), Showrooming (retrieved 15 July 2017)

Related Posts: Jeff Bezos and Ecosystem Thinking (Feb 2004) Showrooming (Label)

Updated 2 August 2017

4 months, 21 days ago

Rhyme or Reason – The Logic of Netflix

@GuyLongworth, who teaches philosophy at Warwick, is puzzled by the Netflix recommendation algorithm.

Having seen both, I can only think that this must have to do with rhyme.

— Guy Longworth (@GuyLongworth) June 29, 2017

Philosopher Guy’s appeal to rhyme rather than reason seems to be based on the view that the two films have nothing else in common. But this is rather contradicted by the fact that he has actually seen both. Netflix has correctly surmised that people like Guy might possibly be interested in both films.

The first thing to understand about recommendation algorithms is that they are not solely (if at all) based on the intrinsic similarity of two products, but on what we might call relational similarity. If I tell you that people who like pizza also like ice-cream, that is primarily a statement about the “people who like”. You might try to explain this statement by observing that pizza and ice-cream both have a high fat content, but then so do lots of other foods.

And when someone has just eaten a pizza, it is perhaps more likely that they will go on to eat ice-cream next, rather than eating another pizza straightaway.

Would it be virtue signalling of me to reveal that I resisted the lure of the second pizza?

— Guy Longworth (@GuyLongworth) June 22, 2017

The second thing to understand is that recommendation algorithms work by trial and error. Netflix wants to know if Guy will accept its suggestion to re-watch Annie Hall, and this feedback will add to its knowledge of Guy as well as its knowledge of relational similarity between films.

Trial and error works better if you have a diverse range of trials. If you watch a couple of films in a particular genre, and then Netflix only ever shows you suggestions within that genre, it will never discover that you might be interested in a completely different genre as well. And you will never discover the full range of Netflix offerings, which could result in your abandoning Netflix altogether.

Diversity of suggestion adds to the richness of the experimental data that are generated. How many members of the “people like Guy” category respond positively to suggestion A, and how many to suggestion B? Todd Yellin, Netflix VP of Product, told journalists in March that “we are addicted to the methodology of A/B testing”.

What is genre anyway? In the past, genres (in book publishing, music, film, video games) were defined by the industry or by experts. In 2013, Netflix employed over 40 people hand-tagging TV shows and movies. But a data-driven approach allows genres to emerge organically from the patterns of consumption. Netflix (and Amazon and the rest) will be much more interested in data-defined genres than in industry-defined genres.

In her rant against the Netflix algorithm, @mehreenkasana makes two apparently contrary complaints. On the one hand, Netflix offers her content that is nothing like anything she has ever watched. She dismisses one suggestion with the words “I’ve never watched a show in a remotely similar vein.” On the other hand, she doesn’t see how Netflix can offer her challenging experiences. “Intensely curated experiences, whether you’re looking to explore movies or to meet people to date, remove one of the most critical aspects of a rich experience: risk, as in going out of your comfort zone.”

But as @larakiara explains, “personalization is key to ensuring users keep coming back. But there’s also the problem of over-personalization, so Netflix has to introduce variants.”

Thus we can see Netflix as an embodiment of at least three of @kevin2kelly’s Nine Laws of God.

  • Control from the bottom up
  • Maximize the fringes
  • Honor your errors

“A trick will only work for a while, until everyone else is doing it.” (Remember Blockbuster.)

Mehreen Kasana, Netflix’s recommendation algorithm sucks (The Outline, 24 March 2017)

Kevin Kelly, Nine Laws of God. Chapter 24 of Out of Control (1994)

Lara O’Reilly, Netflix lifted the lid on how the algorithm that recommends you titles to watch actually works (Business Insider, 26 February 2016)

Janko Roettgers, Netflix Replacing Star Ratings With Thumbs Ups and Thumbs Downs (Variety, 16 March 2017)

Tom Vanderbilt, The Science Behind the Netflix Algorithms That Decide What You’ll Watch Next (Wired, 7 August 2013)

6 months, 15 days ago

The Price of Everything

#PowerSwitch The relationship between the retailer and the customer can be beset by calculation on both sides. The retailer is trying to extract enough data about the customer to calculate the next best action, while the customer is trying to extract the best deal.

There is nothing new about customers comparing products and prices between neighbouring shops, and merchants selling similar goods can often be found in close proximity in order to attract more customers. (This is especially true for specialist and occasional purchases: in large cities, whole streets or districts may be associated with specific types of shop. London has Denmark Street for musical instruments, Hatton Garden for jewellery, Saville Row for made-to-measure suits, and so on.)

But nowadays the villain, apparently, is eCommerce. As a significant share of the retail business migrates from the high street to the Internet, many retailers are concerned about so-called showrooming. It may seem unfair that a customer can spend loads of time in the high street, wasting the time of the shop assistants and shop-soiling the goods, before purchasing the same goods online at a better price. To add insult to injury, some people not only practice showrooming, but then blog about how guilty it makes them feel.

The assumption here is that the Internet can generally undercut the High Street, and there are several reasons why this assumption is plausible.

  • Internet businesses compete on price rather than service, so the prices must be good.
  • An internet store can provide economies of scale – serving the whole country or region from a single warehouse, instead of needing an outlet in each town.
  • An internet store can offer a much larger range of goods without increasing the cost of inventory – the so-called Long Tail phenomenon
  • An internet store typically has lower overheads – cheaper premises and fewer staff
  • An internet business may be run as a start-up, with less “dead wood”. So it is more agile and less bureaucratic. 

However, there are some counterbalancing concerns.

  • The economic and logistical costs of delivery and return can be significant, especially for low-ticket items. With clothing in particular, customers may order the same item in three different sizes, and then return the ones that don’t fit.
  • Investors previously poured money into internet businesses, and the early strategic focus was on growth rather than profit. As internet business become more mature, investors will be looking to see some decent returns on their investment, and margins will be pushed up.
  • And then there is differential pricing …

One of the key differences between traditional stores and online stores is in pricing. Although high street retailers often drop prices to clear stock – for example, supermarkets have elaborate relabelling systems to mark-down groceries before their sell-by date – they do not yet have sophisticated mechanisms for dynamic pricing. Whereas an online retailer can change the prices as often as it wishes, and therefore charge you whatever it thinks you will pay. According to Jerry Useem,

“The price of the headphones Google recommends may depend on how budget-conscious your web history shows you to be.”

I heard Ariel Ezrachi talking about this phenomenon at the PowerSwitch conference in Cambridge a few weeks ago. (I have not yet read his new book.)

“There is an assumption is that the internet is a blessing when it comes to competition. Endless choice. Ability to reduce costs to close to zero. etc … What you see online has very little to do with the ideas we have of market power, market dynamics, etc. everything is artificial. It looks like a regular market, with apples or fish. But because it’s all monitored, it’s not like that at all. What you see online is not a reflection of the market. You see “the Truman Show” — a reality designed just for you, a controlled ecosystem.” (via Laura James’s liveblog)

In his play Lady Windermere’s Fan, Wilde offered the following contrast between the cynic and the sentimentalist.

Lord Darlington: What cynics you fellows are!
Cecil Graham: What is a cynic?
Lord Darlington: A man who knows the price of everything and the value of nothing.
Cecil Graham: And a sentimentalist, my dear Darlington, is a man who sees an absurd value in everything, and doesn’t know the market price of any single thing.

According to one of the participants at the PowerSwitch conference, some eCommerce sites quote higher prices for Apple users, based on the idea that they are less price-sensitive and can afford to pay more. In other words, the cynical Internet regards Apple users as sentimentalists.

If there is an alternative to this calculative thinking, it comes down to reestablishing trust. Perhaps then retailers and consumers alike can avoid an artificial choice between cynicism and sentimentalism.

Emma Brockes, I found something I like in a store. Is it wrong to buy it online for less? (Guardian, 3 May 2017)

Ariel Ezrachi and Maurice Stucke, Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy (Harvard University Press, 2016) – more links via publisher’s page

Laura James, Power Switch – Conference Report (31 March 2017)

Joshua Kopstein, Is Amazon Price-Gouging You? (Vocativ, 4 May 2017) via @charlesarthur

Jerry Useem, How Online Shopping Makes Suckers of Us All (Atlantic, May 2017)

Price-bots can collude against consumers (Economist, 6 May 2017)

The Dilemma of Showrooming, (Daniels Fund Ethics Initiative, University of New Mexico)

Related posts: Online pricing practices to be regulated? (October 2009), Predictive Showrooming (December 2012), Showrooming and Multi-Sided Markets (December 2012), Showrooming in the Knowledge Economy (December 2012).

6 months, 20 days ago

Lawrence Wilkes

My friend and former colleague Lawrence Wilkes died on Friday, after a short illness. Lawrence and I joined James Martin Associates (JMA) on the same day in 1986, so we had known each other for half a lifetime.

JMA was a small consultancy advising organizations on the use of the Information Engineering Methodology and assisting Texas Instruments in developing and supporting the IEF toolset. The Information Engineering part of the company was acquired by Texas Instruments Software in 1991. In 1997, it was sold to Sterling Software and many of us left the company. David Sprott and Lawrence set up the CBD Forum (later CBDI Forum), as a think tank for component-based development, evolving into component-based development and integration, and then evolving into service-oriented architecture (SOA).

As David has written in his fulsome tribute, he and Lawrence spent several years explaining SOA to the large technology companies, including IBM, Intel, Microsoft and Sun. (I can add that they had an article on SOA in the very first issue of the Microsoft Architecture Journal, and I co-wrote something with him for the second issue.)

For my part, I collaborated frequently with them, and became a regular contributor to the monthly CBDI Journal. When the CBDI Forum merged with the US-based consulting firm Everware, I joined Everware-CBDI as a full-time consultant for a few years, working with Lawrence and others to develop a substantial knowledgebase for service architecture and engineering. Although many of us contributed content, it was Lawrence who provided the overall structure and turned our contributions into a coherent whole.

Lawrence was a tireless innovator and perceptive industry analyst, generous with his energy and insight to colleagues and friends. It was a shock when I learned of his illness and forced retirement, and a further shock to learn of his quick demise. I will miss him.


Lawrence Wilkes Blog, Slideshare

David Sprott and Lawrence Wilkes, Understanding Service-Oriented Architecture (Microsoft Architecture Journal 1, January 2004)

Lawrence Wilkes and Richard Veryard, Service-Oriented Architecture: Considerations for Agile Systems (Microsoft Architecture Journal 2, April 2004)

David Sprott, Remembering Lawrence Wilkes – SOA Pioneer (30 April 2017)

6 months, 25 days ago

Uber’s Self-Defeat Device

Uber’s version of “rational self-interest” has led to further accusations of covert activity and unfair competitive behaviour. Rival ride company Lyft is suing Uber in the Californian courts, claiming that Uber used a secret software program known as “Hell” to invade the privacy of the Lyft drivers, in violation of the California Invasion of Privacy Act and Federal Wiretap Act.

This covert activity, if proven, would go way beyond normal competitive intelligence, such as that provided by firms like Slice Intelligence, which harvests and interprets receipts from consumer email. (Slice Intelligence has confirmed to the New York Times that it sells anonymized data from ride receipts from both Uber and Lyft, but declined to say who purchased this data.)

It has also transpired that Apple caught Uber cheating on the iPhone app, including fingerprinting and continuing to identify phones after the app was deleted, in contravention to App Store privacy guidelines. Uber CEO Travis Kalanick got a personal reprimand from Apple CEO Tim Cook, but the iPhone app remains on the App Store, and Uber continues to use fingerprinting worldwide.

Uber continues to be massively loss-making, and the mathematics remain unfavourable. So the critical question for the service economy is whether firms like Uber can ever become viable without turning themselves into defacto monopolies, either by political lobbying or by covert action.

Megan Rose Dickey, Uber gets sued over alleged ‘Hell’ program to track Lyft drivers (TechCrunch, 24 April 2017)

Mike Isaac, Uber’s CEO plays with fire (New York Times, 23 April 2017)

Andrew Liptak, Uber tried to fool Apple and got caught (The Verge, 23 April 2017)

Andrew Orlowski, Uber cloaked its spying and all it got from Apple was a slap on the wrist (The Register, 24 Apr 2017)

Olivia Solon and Julia Carrie Wong, Hell of a ride: even a PR powerhouse couldn’t get Uber on track (Guardian, 14 April 2017)

Related Posts

Uber Mathematics (Nov 2016) Uber Mathematics 2 (Dec 2016) Uber Mathematics 3 (Dec 2016)
Uber’s Defeat Device and Denial of Service (March 2017)

7 months, 11 days ago

Creative Tension in the White House

In his 1967 book on Organizational Intelligence, Harold Wilensky praises President Franklin Roosevelt for his unorthodox but apparently effective management style.

“Roosevelt devised an administrative structure that would baffle any conventional student of public administration.” (p53)

. @tonyjoyce Roosevelt set up “constructive rivalry … structuring work so that clashes would be certain”. Wilensky on #orgintelligence pic.twitter.com/MczcrYlypI

— Richard Veryard (@richardveryard) April 8, 2017

A horrible management technique designed to keep your subordinates so busy fighting with each other they can’t challenge you for leadership https://t.co/WSOiHagBOx

— Jon H Ayre (@EnterprisingA) April 8, 2017

In contrast with FDR’s approach, Wilensky notes some episodes where White House intelligence systems were not fit for purpose, including Korea (Truman) and the Bay of Pigs (Kennedy).

What about President Trump’s approach? @tonyjoyce suggests that Trump is failing FDR’s first construct – checking and balancing official intelligence vs unorthodox sources. However, Reuters (via the Guardian) quotes Republican strategist Charlie Black, who believes Trump’s White House reflects his traditional approach to running his business. “He’s always had a spokes-to-the-wheel management style,” said Black. “He wants people with differing views among the spokes.“


Reuters, Kushner and Bannon agree to ‘bury the hatchet’ after White House peace talks (Guardian, 9 April 2017)

Related posts

Delusion and Diversity (October 2010)
The Art of the New Deal – Trump and Intelligence (February 2017)
Another Update on Deconfliction (April 2017)