Showing posts with label Amazon. Show all posts
Showing posts with label Amazon. Show all posts

Tuesday, July 24, 2018

Evidence-Based Planning

Everybody's favourite internet-book-retailer-cum-cloud-computing-giant is planning for a wide range of outcomes after Brexit.
"Like any business, we consider a wide range of scenarios in planning discussions so that we’re prepared to continue serving customers and small businesses who count on Amazon, even if those scenarios are very unlikely," a spokesperson said.

However, a Government spokesperson dismissed speculation about civil unrest, saying
"Where is the evidence to suggest that would happen?"

To which one might counter

"Where is the evidence to suggest that wouldn't happen?"



There is a methodological gulf between these two positions. One is planning for things you can't prove won't happen. The other is NOT planning for things you can't prove WILL happen.

The political problem with planning for things that might not happen, is that people may criticize you for wasting time and money on something that didn't happen. Whereas if you fail to plan for something that is unlikely to happen, and then it does happen, you can appeal to bad luck. Or the wrong kind of snow.

As with other modes of decision-making, planning simply to avoid censure is not necessarily conducive to good outcomes.


Gareth Corfield, I predict a riot: Amazon UK chief foresees 'civil unrest' for no-deal Brexit (The Register, 23 July 2018)

Rob Davies, No-deal Brexit risks 'civil unrest', warns Amazon's UK boss (The Guardian, 23 July 2018)

Related Post: Decision-Making Models (March 2017)

Sunday, February 04, 2018

The Hungry Tapeworm

This week, three American companies announced a joint venture to sort out healthcare for their own employees. Ambitious, huh?

This is not the first time large American companies have tried to challenge tho market power of healthcare providers. According to Warren Buffett, "the ballooning costs of healthcare act as a hungry tapeworm on the American economy". Intel and Walmart are among those that have previously ventured into this area. In 2016, 20 companies including Coca Cola, American Express, IBM and Macy’s joined the Health Transformation Alliance (HTA). So why should anyone take this latest attempt seriously? Only because the three companies are Amazon, Berkshire Hathaway and JPMorgan Chase. And Amazon (need I remind you?) eats everyone's lunch.


John Naughton sees this as a typical play for a data hungry tech giant, based on two hypotheses.
  • Transactional data will lead to transactional efficiencies. The joint venture starts with the three companies experimenting on their own employees, who will "tell Amazon and its algorithms what works and doesn’t work". 
  • "Mastery of big data might yield clinical benefit".
As Pressman and Lashinsky note, the experiment is based on a pretty good sample of Americans: "a diverse workforce spanning low-wage normal folk to the most elite of our society".


Amazon is obviously a major player in the data and analytics world, but so is IBM, which is playing an important role in the HTA. Not only is IBM a corporate member, but IBM Watson Health will do the data and analytics. According to Pharmaceutical Commerce, it will "aggregate participating HTA member companies' data, enabling insights both into outcomes of medical interventions, as well as wellness initiatives to improve employees’ health".

And what about Google? Google Health was discontinued in 2011, following a lack of widespread adoption. Perhaps data isn't the whole story.


But Amazon is not just about data. In an article published before this announcement, Zack Kanter attributes Amazon's strategic dominance to SOA. "Each piece of Amazon is being built with a service-oriented architecture, and Amazon is using that architecture to successively turn every single piece of the company into a separate platform — and thus opening each piece to outside competition."

Moazed and Johnson discuss the platform implications of the healthcare announcement. They argue that "platforms thrive with fragmentation, not consolidation", and that "the new platform needs to offer enough potential scale to outweigh those risks, otherwise manufacturers may be too afraid to join". Sarah Buhr sees this as an opportunity for smaller players, such as Collective Health.

Three employers, even large ones, probably won’t have enough muscle to negotiate fair prices for healthcare and pharma. But if Bezos can create the right expectations, and provide a flexible platform for smaller players ...






Health Transformation Alliance sets its 2017 agenda (Pharmaceutical Commerce, 9 March 2017)

Amazon alliance takes on ‘hungry tapeworm’ of healthcare costs (Pharmaceutical Technology, 1 February 2018)

Sarah Buhr, Collective Health Wants To Replace The Health Insurance Industry With A Software Program (TechCrunch, 11 Aug 2014)

Sarah Buhr, Amazon’s new healthcare company could give smaller healthtech players a boost (TechCrunch, 30 Jan 2018)

Paul Demko, Amazon's new health care business could shake up industry after others have failed (Politico, 30 January 2018)

Zack Kanter, Why Amazon is eating the world (TechCrunch, 14 May 2017)

Paul Martyn, Healthcare Consumerism: Taming The Hungry Tapeworm (Forbes, 30 January 2018)

Alex Moazed and Nicholas L Johnson, Amazon's Long-Awaited Health Care Platform (Inc, 30 January 2018)

John Naughton, Healthcare is a huge industry – no wonder Amazon is muscling in (Observer, 4 February 2018)

Aaron Pressman and Adam Lashinsky, Data Sheet—Why Jeff Bezos Just Might Crack the Health Care Challenge (Fortune, 31 January 2018)

Jordan Weissmann, Can Amazon, Berkshire Hathaway, and JPMorgan Revolutionize Health Care? (Slate, 30 Jan 2018)

Wikipedia: Google Health


Updated 5 February 2018

Wednesday, December 27, 2017

Automated Tetris

Following complaints that Amazon sometimes uses excessively large boxes for packing small items, the following claim appeared on Reddit.

"Amazon uses a complicated software system to determine the box size that should be used based on what else is going in the same truck and the exact size of the cargo bay. It is playing automated Tetris with the packages. Sometimes it will select a larger box because there is nothing else that needs to go out on that specific truck, and by making it bigger, it is using up the remaining space so items don't slide around and break. This actually minimizes waste and is on the whole a greener system. Even if for some individual item it looks weird. It's optimizing for the whole, not the individual." [source: Reddit via @alexsavinme]

Attached to the claim is a link to @willknight's 2015 article about Amazon's robotic warehouses. The article mentions the packing problem but doesn't mention the variation of box sizes.

The claim quickly led to vigorous debate, both on Reddit and on Twitter. Here are a selection of the argument and counter-arguments.


  • Suggesting that the Reddit claim was based on a misreading of the MIT article.
  • Asserting that people working in warehouses (Amazon and other) were unaware of such an algorithm. (As if this were relevant evidence.)
    • Evidence that equally sophisticated algorithms are in use at other retailers and logistics companies. (Together with an assumption that if others have them, Amazon must definitely have them.)
    • Evidence that some operational inefficiencies exist at Amazon and elsewhere. (What, isn't Amazon perfectly optimized yet?)
      • Providing evidence that computer systems would not always recommend the smallest possible box. For example, this comment: "At Target the systems would suggest a size but we could literally use whatever we wanted to. I constantly put stuff in smaller boxes because it just made so much more sense." (Furthermore, the humans being able to frustrate the intentions of the software.)
      • Suggesting that errors in box sizes are sometimes caused by mix-up of units - one item going in a box large enough for a dozen.
      • Pointing out that the solution described above would only work for transport between warehouses (where the vehicle is full for the whole trip) but wouldn't work for "last mile" delivery runs (where the vehicle becomes progressively more empty during the trip).
      • Pointing out that the "last mile" is the most inefficient part of the journey. (But this doesn't stop retailers looking for efficiency savings earlier in the journey.)
      • Pointing out that there were more efficient solutions for preventing packages shifting in transit - for example, inflatable bags.
      • Pointing out that an overlarge box merely displaces the problem - the item can be damaged by sliding around inside the box.
      • Complaining about the ethics, employment policies and environmental awareness of Amazon.
      • Denigrating the intelligence and diligence of the workers in the Amazon warehouse. (Lazy? Really?)

      Some people have complained that as the claim is evidently false, it counts as fake news and should be deleted. But it is certainly true that retailers and logistics companies are constantly thinking about ways of reducing packaging and waste, and there are several interesting contributions to the debate, even if some of the details may not quite work.

      It's also worth noting that the claim is written in a highly plausible style - that's just how people in that world would talk. So maybe someone has come across a proposal or pilot or patent application along these lines, even if this exact solution was never fully implemented.

      Some may doubt that such a solution would be "greener on the whole". But any solution architect should get the principle of "optimizing for the whole, not the individual". (Not always so easy in practice, though.) 



      Will Knight, Inside Amazon’s Warehouse, Human-Robot Symbiosis (MIT Technology Review, 7 July 2015)

      Wikipedia: Packing Problems

      Saturday, July 15, 2017

      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 bĂȘte 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.


      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

      Thursday, March 09, 2017

      Inspector Sands to Platform Nine and Three Quarters

      Last week was not a good one for the platform business. Uber continues to receive bad publicity on multiple fronts, as noted in my post on Uber's Defeat Device and Denial of Service (March 2017). And on Tuesday, a fat-fingered system admin at AWS managed to take out a significant chunk of the largest platform on the planet, seriously degrading online retail in the Northern Virginia (US-EAST-1) Region. According to one estimate, performance at over half of the top internet retailers was hit by 20 percent or more, and some websites were completely down.

      What have we learned from this? Yahoo Finance tells us not to worry.
      "The good news: Amazon has addressed the issue, and is working to ensure nothing similar happens again. ... Let’s just hope ... that Amazon doesn’t experience any further issues in the near future."

      Other commentators are not so optimistic. For Computer Weekly, this incident
      "highlights the risk of running critical systems in the public cloud. Even the most sophisticated cloud IT infrastructure is not infallible."

      So perhaps one lesson is not to trust platforms. Or at least not to practice wilful blindness when your chosen platform or cloud provider represents a single point of failure.

      One of the myths of cloud, according to Aidan Finn,
      "is that you get disaster recovery by default from your cloud vendor (such as Microsoft and Amazon). Everything in the cloud is a utility, and every utility has a price. If you want it, you need to pay for it and deploy it, and this includes a scenario in which a data center burns down and you need to recover. If you didn’t design in and deploy a disaster recovery solution, you’re as cooked as the servers in the smoky data center."

      Interestingly, Amazon itself was relatively unaffected by Tuesday's problem. This may have been because they split their deployment across multiple geographical zones. However, as Brian Guy points out, there are significant costs involved in multi-region deployment, as well as data protection issues. He also notes that this question is not (yet) addressed by Amazon's architectural guidelines for AWS users, known as the Well-Architected Framework.

      Amazon recently added another pillar to the Well-Architected Framework, namely operational excellence. This includes such practices as performing operations with code: in other words, automating operations as much as possible. Did someone say Fat Finger?




      Abel Avram, The AWS Well-Architected Framework Adds Operational Excellence (InfoQ, 25 Nov 2016)

      Julie Bort, The massive AWS outage hurt 54 of the top 100 internet retailers — but not Amazon (Business Insider, 1 March 2017)

      Aidan Finn, How to Avoid an AWS-Style Outage in Azure (Petri, 6 March 2017)

      Brian Guy, Analysis: Rethinking cloud architecture after the outage of Amazon Web Services (GeekWire, 5 March 2017)

      Daniel Howley, Why you should still trust Amazon Web Services even though it took down the internet (Yahoo Finance, 6 March 2017)

      Chris Mellor, Tuesday's AWS S3-izure exposes Amazon-sized internet bottleneck (The Register, 1 March 2017)

      Shaun Nichols, Amazon S3-izure cause: Half the web vanished because an AWS bod fat-fingered a command (The Register, 2 March 2017)

      Cliff Saran, AWS outage shows vulnerability of cloud disaster recovery (Computer Weekly, 6 March 2017)

      Tuesday, December 04, 2012

      Showrooming and Multi-sided Markets

      As a retail phenomenon, #showrooming exposes a conflict of interest between online and traditional retailers. Many shoppers will examine a product in a traditional store, and then buy it from an online retailer or discount warehouse. The first retailer incurs costs - including cashflow, wear and tear on the product, as well as unproductive use of staff time and knowledge - while the second retailer takes the revenue.

      To complete the story, there may be another class of customer, who is happy to buy the ex-demonstration product from the first retailer at a discounted price. Thus there are five distinct roles in this game: the product supplier, the first and second retailer, the first and second customer. (In addition, if the customers are using their mobile phones in the stores, we should add the players in the mobile ecosystem.)

      The earliest manifestation of this I can remember was buying records. You could listen to an LP in the record store, and then get a pristine copy (without the shop assistant's fingerprints) by mail order from a company appropriately called "Virgin".

      Many retailers believe they lose out from this phenomenon, and some have attempted to prevent it. (Ever wondered why you don't get a good cellphone signal inside a large store?) Earlier this year, both Target and Wal-Mart decided to stop stocking Amazon devices, although continuing to stock Apple devices. More recently, Wal-Mart has changed its position, and now claims to embrace showrooming.

      By singling out Amazon, Target and Wal-Mart were making it clear that it is Amazon's role as a retailer that they regard as a competitive threat. Although Apple also sells its devices online, it is presumably not regarded as an equivalent threat. In which case, banning Amazon products looks like a gesture of despair rather than an effective tactic.

      Thinking of this as a multi-sided market prompts us to look at the direct and indirect flows of value between the players. It is as if the first retailer is providing an unpaid "service" to the second retailer, and the first customer is providing an unpaid "service" to the second customer. At present these are not genuine services, but it is possible to conceive of an ecosystem in which the product supplier or second retailer paid some form of commission to the first retailer. For all I know, that may already happen in some sectors.

      Wal-Mart hopes to control showrooming by encouraging its customers to use its own mobile app, which attempts to steer customers towards its own online store. I wonder how many customers will accept this control, and how many will take the trouble to resist it.

      Some large High Street retailers seem to have given up the idea of stocking goods: if you like something on display, you can order it. This has long been true for large furniture items such as beds, but is becoming more common for smaller items, as Simon Heffer complains.

      Meanwhile, showrooming can work both ways. Last week I ordered a book from my local bookshop, having previously looked it up on Amazon. It was 5pm Friday when I placed the order, and they phoned me at 11am on Saturday to tell me it had arrived. (If I'd ordered it from Amazon, paying extra for 48 hour delivery, when would it have arrived? Monday, Tuesday?) So that's showrooming in reverse.

      Finally, instead of selling individual products, the showroom itself can become the experience. @KBlazeCarlson sees IKEA as a prime example, and quotes Alan Penn, professor of Architectural and Urban Computing at UCL, describing the IKEA experience as "psychologically disruptive". "Part of their strategy is to take you past everything," he says. "They get you to buy stuff you really hadn’t intended on. And that, I think, is quite a trick."

      Chris Petersen adds, "Instead of product centric merchandising, IKEA’s showroom is perhaps the ultimate place merchandising, where the consumer solution is focused on the most personalized dimension – the consumer’s own lifestyle and living space." Whether IKEA can replicate this experience online in the virtual world, as suggested in Patrick Nelson's piece, is another matter.



      Kathryn Blaze Carlson, Enter the maze: Ikea, Costco, other retailers know how to get you to buy more (National Post, June 2012)

      Dani Deahl, Amazon granted a patent that prevents in-store shoppers from online price checking (The Verge, 15 June 2017)

      Simon Heffer, My futile hunt for a lamp in John Lewis reveals why the High Street is doomed (Daily Mail 15 January 2013)

      Brett Molina, Is 'showrooming' behind Target move to drop Kindle? (USA Today, May 2012)

      Patrick Nelson, Brick-and-Mortar's Showrooming Scourge (E-Commerce Times, Nov 2012) via First Insight

      Sarah Perez, Amazon, now a physical retailer too, is granted an anti-showrooming patent (TechCrunch, 16 June 2017)

      Chris Petersen, To beat showrooming … change the showroom! (IMS results count, June 2012)

      Marcus Wohlsen, Walmart.com CEO: We Embrace Showrooming (Wired, Nov 2012)

      Amazon's Showrooming Effect And Quick Growth Threaten Wal-Mart (Forbes, Sept 2012)

      Related posts: Showrooming in the Knowledge Economy (December 2012), Predictive Showrooming (December 2012)

      Updated 16 June 2017

      Tuesday, May 01, 2012

      Business as a Platform - Amazon

      #bizarch Excellent article by @haydn1701 on Why Amazon Succeeds (Forbes, 29 April 2012) via @davegray and @ruthmalan.

      Haydn Shaunessy points out the following features of Amazon's strategy.


      Understanding ecosystem

      Shaunessy starts by defining the notion of ecosystem fairly narrowly, and links it to the information market. "Bezos is not as great as Jobs at playing the information market but he is good." This may well be true, but it misses the point. Jeff Bezos's understanding of ecosystem has always been much more profound than that of any of his peers, and Amazon's ecosystem is a lot broader than zen marketing.

      One way of seeing it is that Jobs coerced people to do things that were in his (Apple's) interests, whereas Bezos gives them opportunities to do things in their own interest, from which he benefits in more subtle but perhaps more sustainable ways. But of course there's always another story.

      Radical adjacency

      The ability to go beyond normal business practice and to seize opportunity in widely adjacent markets.

      Business-as-a-platform

      Shaunessy identifies a number of characteristics
      • Tearing business away from "the straight jacket of old management theory" - "the outdated idea of core competency" 
      • Providing a new way to scale business
      • Bringing (shared) value to all parties

      Technical enablers

      Shaunessy identifies two in particular
      • Universal connectors - not merely technical protocols but contractual protocols that radically reduce the transaction costs of using the platform 
      • Cloud computing

      Organizational enablers

      Shaunessy talks about ability to attract and retain very talented, imaginative resources. I would also add the ability to build these into an effective and innovative company - what I call Organizational Intelligence.


      Strategic Outcome

      This combination of strategies has allowed Amazon and Apple to develop what Shaunessy calls complex options portfolios. He notes that "the ecosystem is full of businesses that can jump quickly into new opportunity" and argues that this yields the true meaning of shared value.

      Friday, October 14, 2011

      Google as a Platform (not)

      Google vs Amazon (again). @davidsprott reckons Steve Yegge's rant is spot on. Steve Yegge is a software engineer who used to work for Amazon and now works for Google, despite the supposedly accidental publication of a long and opinionated rant (his words) complaining that

      '[what] Google doesn't do well is Platforms. We don't understand platforms. We don't "get" platforms.'

      (For more context, see Steve Yegge's second thoughts on Google+).

      Waddya mean, Google doesn't get platforms? Surely Google is a major player in platform, especially in the so-called Cloud? Dion Hinchcliffe sounded fairly convinced when he was Comparing Amazon's and Google's Platform-as-a-Service (PaaS) Offerings back in April 2008.

      "Amazon and Google have strategically built up an extensive set of services over the last few years and have made some very interesting assumptions that will determine who their customers are (consumers, startups, enterprises) and what type of business models can sit on top of them (advertising, subscriptions, cheapest source of outsourced computing resources). ... Google and Amazon have emerged to be the leaders in this space while Microsoft, IBM, and especially Oracle and SAP are either well behind or have unclear plans to enter the PaaS space. Both of these companies formed their DNA around the world of the Web and deeply understand how to leverage the enormous strengths of the Web platform."

      So what went wrong? This guy (Yegge) sure knows one thing, says @pardhas, building platforms is not just collecting your products on one plate. For Yegge, platforms is about eating your own dogfood. Not just Amazon, but also Facebook - hey, even Microsoft understands platforms better than Google.

      But there is something missing from Steve Yegge's account. He sees the (lack of) platform from an engineering perspective, but what he doesn't talk about is the enterprise/ecosystem perspective.

      @davidsprott's tweet ends with the formula "SOA + platforms = competitive advantage".  David and I have written a great deal about ecosystem SOA and ecosystem architecture, and we have long credited Jeff Bezos of Amazon as someone who "gets" ecosystem.

      Among other things, "getting ecosystem" means understanding the variety of ways in which the social complexity of collaborations create value for the customer, and therefore how, from the perspective of the supplier, platform architectures can capture indirect value. See Philip Boxer's presentation on supporting social complexity in collaborative enterprises, as well as my presentation on Next Generation Enterprise Architecture, both from the recent Unicom EA Forum in London.

      As I pointed out in my recent VPEC-T analysis of Google, Google is adopting a positional strategy - capturing some territory and defending it against its competitors. Amazon and Apple have shifted towards open source competition on their platforms (relational strategy) while Google is still closed-source.

      In his post on Tomorrow's Networked Economy, @JDeragon praises Google+ for becoming an integrated portal. Er, wasn't that AOL's strategy? And Yahoo's for that matter? Maybe Google has greater ability to execute this strategy than they did, but it still looks more like yesterday's networked economy. Have you read Kevin Kelly's book?



      For Apple's shift from product to platform, see my post on Disney, Pixar, Apple and Jobs from February 2006.

      For the shift from positional stategy to relational strategy, see Philip Boxer and Bernie Cohen, Triply Articulated Modelling of the Anticipatory Enterprise and Philip Boxer, Architectures that integrate  differentiated behaviours.

      For more on Ecosystem SOA and Ecosystem Architecture, please browse the Ecosystem category on this blog. Here are some further links.

      Jeff Bezos Letter to Shareholders (via Geekwire) (April 2011)
      Bob Ellinger, Enterprise SOA vs Ecosystem SOA (April 2011)
      Vaughan Merlyn, From Enterprise Architecture to Ecosystem Architecture (July 2008)
      David Sprott, Introducing Smart Ecosystem Architecture (October 2009)

      Wednesday, June 22, 2011

      Fast data - speed over precision?

      @bmichelson posts a piece on an HP website called Fast Data: Speed over precision for better decision-making (21 June 2011), summarizing a recent interview in MIT Sloan with Ali Riaz and Sid Probstein of software company Attivio https://sloanreview.mit.edu/article/why-companies-have-to-trade-perfect-data-for-fast-info/.


      Riaz and Probstein are not claiming that better decision-making is just about speed: it also requires a continuous refinement loop, including rethinking one's premises. In other words, we need multiple feedback loops at different speeds, to handle different levels of complexity. As I pointed out in my piece on TIBCO's slogan Two Second Advantage, although simple decisions can be taken quickly, complex decisions need what I call "time for understanding".

      One of the architectural challenges of organizational intelligence is to coordinate a complex array of sense-making and decision-making processes operating at different characteristic tempi, and to maintain a proper balance between the very fast (reactive) and the comparatively slow (reflective). Probstein identifies Amazon.com as a successful exemplar.

      It is common for technologists to make a fetish of speed, but business effectiveness and organizational improvement need "time for understanding" as well. Riaz and Probstein appear to understand this, and I look forward to seeing how this understanding is supported by their software.

      Sunday, March 27, 2011

      Complexity and Value - Is Amazon bothered?

      @Cybersal complains about Amazon. "Yet again Amazon ships a tiny book with an unreliable courier that my postman could have shoved through my letterbox." and explains "Post office 10 min walk. Courier depot 30 min drive. Courier not a good option for such a low value item."

      This raises an important question about Amazon's capability and willingness to manage complexity - specifically differentiation. Amazon already uses multiple alternative delivery channels, but introducing an automatic selection according to the value and size of the item might well further complicate its delivery processes. If Amazon wished to differentiate customers according to the convenience / cost of different delivery channels, it would presumably need to have some geographical reasoning capability. And if Amazon wished to differentiate those products that would fit through a customer's letterbox, it would presumably need to know the size of each customer's letterbox.

      We can easily imagine that Amazon could build this kind of capability, perhaps using Google Maps and Google Streetview to check the exact location of Sally's house and estimate the size of her letterbox. But has Sally a right to complain if Amazon doesn't bother?

      To what extent do customers have a reasonable expectation of sophisticated differentiation of service - from organizations in general or from Amazon in particular? We may note that most large commercial organizations are way behind Amazon in their ability to enhance customer value through differentiation, while most small commercial organizations are way behind Amazon in their ability to integrate across a complex ecosystem. Because Amazon has already done some amazing things, we may expect it to go even further. But even Amazon has a practical limit of how much complexity it can manage.

      We are surrounded by organizations that really can't be bothered, and the value deficit in some sectors is quite disgraceful. So it may be unfair to pick on Amazon, an organization that has done more than most to stretch the limits of the possible. But Sally is right - the future belongs to those organizations able and willing to pay attention to this kind of detail, if it helps to produce direct or indirect value.

      Monday, March 17, 2008

      Ray Ozzie

      Ray Ozzie doesn't do many interviews, so lots of people are finding interesting snippets from his interview with Om Malik last week [GigaOM Interview, March 10, 2008]. Jesper Joergensen (BEA) notes that Ray Ozzie plugs Amazon Web Services. Phil Wainewright interprets the entire interview as a signal of Microsoft's surrender to the cloud. Recently Ray has been a strong advocate of Microsoft's Software+Services strategy, which Phil has criticized as bunkum. But Ray has been a strong advocate of collaborative computing, dating back long before he joined Microsoft. In April 2003, when Ray was the Chief Executive of Groove Networks, he wrote this article: Perspective: A mosaic of new opportunities, which I have quoted before on this blog. (In my post Internet Service Disruption (November 2005), I called out a key difference between Ray's thinking and Bill's - a very early signal that Ray might lead Microsoft into new areas.) So I thought it would be interesting to see whether Ray's thinking has changed in five years.

      Loose Coupling

      "The next 10 years will find us moving decidedly from an era of personal productivity to one of joint productivity and social software. That will involve a move from tightly coupled systems to more loosely coupled interconnections." (2003) "If you look at the innards of a Yahoo or a Microsoft, an MSN, or a Google, you will see the people who have designed the systems and have taken a number of the things we’ve learned in the enterprise space. We have to throw them them away, because the way that we did it in the enterprise space was more tightly coupled. We need to be more loosely coupled." (2008)
      A consistent appeal to loose coupling, but a somewhat different emphasis. The 2008 quote was prompted by a question about reliability, and he is invoking loose coupling from the supply side perspective - presumably motivated by his current supply-side responsibilities. In 2003, he was talking about loose coupling in relation to the end-user experience - in other words, the demand side.

      Synchronization

      "These changes will transform the personal computer into an interpersonal computer. This will be a rich, self-synchronized and readily interchangeable device focused specifically on people and what they do with one another online." (2003) "The Internet is this resource in the back end that you can design things to take advantage of. You can use it to synchronize stuff, and communicate stuff amongst these devices at the edge." (2008)
      In his post Ray Ozzie bringing ’syncromesh’ to the Web, Larry Dignam points out that this has always been a consistent theme of Ozzie's work going back to Lotus Notes.

      Power to the Edge

      "What programming models can I give these folks that they can extend that functionality out to the edge? In the cases where they want mobility, where they want a rich dynamic experience as a piece of their solution." (2008)

      Ray didn't actually talk about the Edge in his April 2003 article, but by September 2003 he was writing an enthusiastic review of a book called Power to the Edge. I'd really like to find out what he thinks about this now.

       

       

      Links updated 14 April 2022

      Friday, November 11, 2005

      Mechanical Turk

      For many years, people have been talking about "software services". My objection has always been that this misses the point. If something is a service, hidden behind a service interface, you should no longer know or care about the delivery mechanism - software, firmware, human or white mice.

      Amazon's launch of the Mechanical Turk service reinforces this idea. The idea is that human microtasks can be rendered as services and orchestrated into business processes, just as if they were software-based. Amazon refers to this as "artificial artificial intelligence", which is a nice conceit. It's also called Human Intelligence Tasks (HIT).

      But not necessarily human. Some of the examples of services rendered via Mechanical Turk involve simple picture recognition, and could possibly be done by a trained animal or bird. (After all, homing pigeons are pretty good at direction-finding, and a hawk can spot a tiny animal in the undergrowth.) All they need is something they can peck or paw to record their answer, and they can earn enough to pay for that gilded cage on eBay.

      Some people are sceptical about the economics of human microservices. For example, Patrick Tanguay [update: URL added] says
      Problem is, with the prices they offer so far, you’ll be lucky if you can make 4-8$ an hour. Seems like after years of various people trying to crack the micropayment formula, Amazon is now bringing us micro-outsourcing where any third world person with access to the web can log in and start churning out answers for 3 cents a pop.
      But in my view, the real interest of Human Intelligence Tasks is the potential for aggregating and composing them in complex ways with non-human services. Think of the security applications - get a hundred people around the world to vote whether an airline passenger looks guilty or merely uncomfortable, or to vote whether she looks enough like last year's picture. And we don't have to send every case out for human review - merely a random sample to help calibrate the accuracy of the machine, and to create fear and uncertainty for the bad guys. Think of the marketing and business intelligence applications.

      And what about Internet search? I find I waste huge amounts of time using search engines, wading through pages that have nothing but keywords, cached pages from previous searches, links that no longer exist, pages with no significant content that have been cleverly designed to trick the search engines. I might be willing to pay someone to filter the search results for me - let's say five dollars for twenty minutes of reasonably intelligent work, results delivered within an hour. Or am I asking too much here?

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      Tuesday, September 14, 2004

      Business Geometry

      A business or value chain is composed in a geometric structure. (In the past we have often called this structure an architecture, but this word has lots of different and tangential associations for different people.)

      In SOA, we design a business or value chain as a network of services. This is a powerful geometrical pattern. But there may be many possible network geometries satisfying a given business requirement, all of which count as satisfying the principles of SOA. For example: hub/spoke or peer/peer.

      Business Stack

      Another common geometric pattern for SOA is stratification. A business process is composed of services from a set of lower-level services, presented as a platform. A good example of a business platform is the set of retail services offered by Amazon and eBay. Other service providers have built further retail/logistical services on top of the Amazon/eBay platforms.

      Each platform is in turn built upon even lower services. At the lower levels, there may be collections of IT-based services, known as ESB. There may also be sociotechnical service platforms, such as call centres.

      Thus we have a stratified geometry, in which a person tackling a problem at a given level is presented with a collection of available services, formed into a virtual platform. This can be thought of as a business stack, with one plaform stacked on top of another. Some of the lower layers of the stack may appear to be purely technical services; however a more complete picture should reveal the existence of an IT organization maintaining the platform, in other words a human platform of administrators and programmers supporting the technical platform.

      Variable Geometry, Variable Granularity

      While the SOA principles may provide some geometrical guidance, and mandate certain geometrical patterns, there is still a design job to determine the geometry. This design job may be easy when the requirement is trivial, but gets harder as the complexity increases.

      In many situations, the demand side has more variation than a human designer (or design team) can accommodate. (We characterize this as an asymmetry of demand, which calls for a process of asymmetric design.) We need to start thinking about variable geometry solutions, where the geometry itself can be adapted on-demand.

      For example, in the past we have assumed that granularity has to be fixed at design time. But we can conceive of a web service platform that detects patterns of demand-side composition, defines new composite services automatically, describes and publishes these new services in real time, and notifies likely users of the new service, complete with an incentive to switch. We can conceive of a web service platform that analyses the message content of a certain service, and produces a substitute service with a smaller footprint that would satisfy most of the uses in a more elegant way.

      Value Landscape

      I use the term value landscape to refer to the distribution of cost, benefit and risk across a complex market ecosystem, such as the insurance industry. Technology (including SOA) influences business geometry, not least because it affects transaction costs. The shape of the value landscape changes (has already started to change) as the result of B2B and B2C and BPO. Companies that once occupied safe market positions (the high ground) may find their commercial advantage slipping into the sea, or they may find themselves cut off from their natural markets or supply chains.

      See Microsoft Blog Insurance Value Chain

      Let's suppose an insurance company has the following strategic aims:
      1. Profitability, short-term viability. To deliver the maximum service value as cost-effectively as possible, using available input services and technologies as efficiently as possible, with minimum costs/risks of change.
      2. Adaptability, medium-term viability. To understand and respond to changing demand for insurance services, and to trends in cost and risk, both internally and across the industry. To develop and deploy new services to exploit new business opportunities and avoid emerging business threats.
      3. Survival, long-term viability. Making sure the core business proposition remains valid, and doesn't get eroded by more agile players. Taking strategic action in relation to structural changes in the insurance industry.
      If we are doing business geometry for an insurance company, we need to think about the insurance industry as an ecosystem. We need an AS-IS model of the present ecosystem (largely based on pre-SOA technologies) and a TO-BE model of an idealized ecosystem (based on SOA). We can expect the pre-SOA ecosystem to evolve into some form of SOA ecosystem, although we may not have much idea which of the possible changes is going to happen first. To satisfy all three strategic aims, an insurance company needs to exploit the pre-SOA ecosystem, and prepare for the SOA ecosystem.

      Note that this situation may force the insurance company to implement a variable geometry, both in the organizational platform and in the IT platform. Otherwise, it will either have to operate suboptimally for an extended period, or incur significant organization costs and IT costs every time the industry takes another step towards SOA.

      Sunday, August 01, 2004

      Amazon and Ebay

      Amazon, eBay and PayPal are creating platforms for eCommerce.
      At CBDI Forum, we have been tracking these developments from time to time. See news commentaries: July 2004, February 2004, February 2004, July 2003. See also Jeff Bezos and Ecosystem Thinking.


      Jeffrey McManus of eBay claimed recently that 'we make inefficient markets efficient'. (Source: Aaron Johnson blog.)

      In his blog, Jonathan Schwartz (Sun Microsystems) talks about selling computers on eBay, as a web services experiment. Schwartz expects this experiment to provide "unvarnished" pricing information, as well as providing practical experience with a service-oriented supply chain. This seems to support the McManus claim.

      However, efficiency often conflicts with adaptability. How wise is it for Sun and other firms to link to the eBay platform? What is the likely ecosystem effect of allowing eCommerce services to be defined and controlled by a small number of like-minded firms?

      I've just had a look at the eBay technical documentation. Developers must follow detailed procedures for design, testing and certification, before they are permitted to plug into the live eBay environment. Rightly so no doubt, but this raises questions about service life cycle management and technical change.

      In response to the possible difficulties of raw eBay, a number of service providers are now offering DropOff services that provide a simple eBay front-end. These include AuctionDrop, AuctionWagon, QuikDrop and Picture It Sold! and 1StopAuctions. The last of these makes strong and explicit claims about the difficulty of using eBay. (Success here means not just completing the transaction but getting a good price.)
      "To successfully sell an item on eBay requires marketing and selling strategies unique to eBay – and learning those strategies can take years to master. 1Stopauctions.com has that unique knowledge to successfully sell your items on eBay. We have been buying and selling on eBay since 1998. Over the years we have found the secrets of launching successful listings to obtain the highest possible price ... and so on ..."
      For me, the appearance of these secondary service providers simply confirms that the big issue is business hegemony (power) - the value ladder now belongs to Amazon and eBay, they control the terms on which everyone else is trading.


      Lawrence Wilkes, Amazon and eBay Web Services (CBDI Journal, October 2004)

      Thursday, February 26, 2004

      Jeff Bezos and Ecosystem Thinking

      Lots of commentators and blogs have picked up on a recent Business Week story about Amazon (December 22, 2003).

      But Amazon has been working towards this for a long time indeed. When I searched the web for Bezos and ecosystem, the first page of hits included a story from June 2000, in which a senior manager at HP acknowledged that he had gotten ecosystem thinking from talking to Jeff Bezos.

      Recent developments by Amazon and eBay (as described by David Sprott and Lawrence Wilkes at the CBDi Forum) establish a business service stack for the eCommerce sector.

      But this isn't just a clever tactical move. It follows logically from a strategic direction that Amazon has been pursuing for a considerable time. During the dot-Com boom, there was lots of superficial admiration of Amazon, and lots of companies trying to emulate it. But few of them mastered ecosystem thinking, and few of them survived the downturn.

      Later note. The conversation with HP also indicated that Bezos already had The Idea of Showrooming.(See my post from July 2017.)




      Alan Deutschman, Inside the mind of Jeff Bezos (Fast Company, 1 August 2004)

      Steve Hardy, Guidelines from the Book of Bezos (Creative Generalist, 5 August 2004)

      Robert D Hof, Reprogramming Amazon (Business Week, 22 December 2003)

      David Jastrow, HP Keynote embraces ecosystem thinking (CRN, 15 June 2000)

      Lawrence Wilkes, Amazon and eBay Web Services (CBDI Journal, October 2004)


      Related posts: Binary Advice (July 2004), Amazon and Ebay (August 2004), Business as a Platform - Amazon (May 2012), The Idea of Showrooming (July 2017)

      For more on ecosystem thinking, see my 2001 book on Component-Based Business. Available from Amazon (of course).


      reposted 22 September 2025