Wednesday, December 4. 2013
We are told fairly frequently these days that data is the new Oil (or not?). If it is, then is Google the new Standard Oil?
To refresh everyone's memories (Wikipedia):
Standard Oil Co. Inc. was an American oil producing, transporting, refining, and marketing company. Established in 1870 as a corporation in Ohio, it was the largest oil refiner in the world. By 1890, Standard Oil controlled 88 percent of the refined oil flows in the United States.Its controversial history as one of the world's first and largest multinational corporations ended in 1911, when the United States Supreme Court ruled that Standard was an illegal monopoly.
In other words, Standard Oil built up a near monopoly position in oil, not unlike Google's near monopoly position in digital data. Like Standard, Google also uses profits in one area (advertising) to offer free services in many other areas, making it very difficult for competition to emerge in those spaces.
Opinions are still divided about the breakup of Standard by the way:
Some economic historians have observed that Standard Oil was in the process of losing its monopoly at the time of its breakup in 1911. Although Standard had 90 percent of American refining capacity in 1880, by 1911 that had shrunk to between 60 and 65 percent, due to the expansion in capacity by competitors. Numerous regional competitors had organized themselves into competitive vertically integrated oil companies, the industry structure pioneered years earlier by Standard itself. In addition, demand for petroleum products was increasing more rapidly than the ability of Standard to expand. The result was that although in 1911 Standard still controlled most production in the older US regions of the Appalachian Basin (78 percent share, down from 92 percent in 1880), Lima-Indiana (90 percent, down from 95 percent in 1906), and the Illinois Basin (83 percent, down from 100 percent in 1906), its share was much lower in the rapidly expanding new regions that would dominate US oil production in the 20th century.
We are certainly seeing China emerge as an independent digital data region, and othes are splitting off various segments of the digital data mining and refining business. It remains to be seen whether the expected rapid growth in digital data moves at such a pace that Google can no longer supply it all. That will probably be the acid test in the Digital Oil business.
Interestingly, after the breakup, bits of Standard slowly got together again - Two of the resulting companies were Jersey Standard ("Standard Oil Co. of New Jersey"), which eventually became Exxon, and Socony ("Standard Oil Co. of New York"), which eventually became Mobil. They are now Exxon-Mobil. Other Standard spin offs re-combined to form Amoco and Chevron.
Microsoft, came under antitrust investigation for being inherently too large for market competition. The only company since the breakup of Standard Oil that was broken up like Standard Oil was AT&T, and as with the breakup of Standard Oil, many of the "Baby Bells" ended up merging together after changes in regulations and technology, with one of them eventually buying AT&T and adopting the AT&T name.
But, little surprise that Google is ramping up its lobbyist engine in Washington, as reported today:
Google Inc. is moving its Washington office closer to Capitol Hill after spending $18.2 million on lobbying, more than Northrop Grumman Corp. and enough to rank the technology company as the eighth-biggest advocacy spender.
Google is one company that understands that those that forget the past are doomed to repeat it.
Sunday, November 10. 2013
Its been a very busy last few weeks what with conference season. work and whatnot so stories ave been piling up in the Broadfstuff inbox. First to go out then is the notes from the FT Innovate Conference. I found this year the best one of all those I have been to over the years as I think its really beginning to sink in that Innovation does NOT mean doing what you did last year, just a bit better, if you want to survive in the modern world order - especially if you a re a high wage, low growth OECD country.
Anyways, notes from Day One here. As per usual, I select what really struck me as new/novel.
- Innovation is increasingly about getting products to the remoter areas, and finding new products to push through the channels ( aka fuller understanding of the consumer.....).
Werner Vogels, Amazon
The talks was on the Amazon Cloud - Pay as you Go, stick to core competencies, hire flexibly when you need something, great for small companies etc etc but really its basically an argument for the asset rental model. As Nick Carr predicted, someone had to do it, I'm more interested that it remains Amazon in the forefront rather than Telco or a Hoster after several years. I guess they already have the asset base doing something else, so can cost optimise retail hosting at offset prices. Vogels says Amazon Cloud operation has No CIO, No R&D, no innovation teams etc - but the business units are under pressure to improve performance. Sounds like its still small, or it runs on top of an Amazons infrastructure platform that is managed elsewhere. Having been part of large scale Web Hosting in my time, no way do I believe that you can run something like this without a CIO, a large Ops staff and a control room that looks like Cape Canaveral somewhere in the architecture
CapGemini report on Cloud based disruption
Report over here
3 main Cloud drivers:
Alec Ross, on various trends
- Data is the raw material of the information age, as land was for the agricultural economy
- No shift of power to east, shift of power to data owners - from heirarchy to heterarchy (question from me.....how does one prevent robber barons capturing all the data)
- Wide difference in attitudes to entrepreneurial activity, Europe lowest. Too much "grey twilight" in Europe - nothing ventured, nothing lost. Quotes Disraeli - success is the child of audacity
- The best strategy for any society is one that reduces barriers to participation of women in the economy - 50% of brainpower (is this true - see more money chasing same things)
- But girls fall away from STEM very rapidly post 16 y/o
- Need to manage pregnancy and childrearing as part of corporation operation, ditto mentoring
- Next generation will be a very tough time for middle class - need to learn how to change with the winds, learn new skills etc. Don't havevto be an entrepreneur, but need to know how to work for them.
- The Cloud is just another means of driving labour costs down. If Europe puts up privacy requirements they will go elsewhere.
- Government procurement via lowest cost provider is like buying cheap clothes for a big date
- Government is poor at surgical intervention, good at big picture intervention eg allow SEs to grow to MEs.
- Baby boomers are slowing innovation, high youth countries are increasing innovation. Robotics is being driven by needs of old people care
Gerd Leonard, on various trends 3 - 5 years out
Privacy/Security - Faustian bargain, we are increasingly reneging now - market in tools emerging
- biometrics future? GL thinks there will be limited adoption until it is settled who owns the data and the exchange - digital bill of rights. Technologies not backed up by social contract won't take off
Increasing automation will take rote knowledge jobs away eg Gerds bookkeeper with Xero. Machines will start to do our thinking
Increasing issue around trusting the facts
Shell - looks at 30 years horizon, big infrastructure plays tend to do this
How to force thinking in scenarios - wildcard game (similar to our high sensitivity analysis)
Existing players try to use current tools (eg legislation, regulation) to put off short term changes (online music example)
China - safer? GL thinks they will have to play by global village rules
Opportunities - efficiencies, solutions to major issues
UK is the most tracked country - why? We are a more dysfunctional model, UK bases itself on what US used to do.
Use of data in organisations - the quantified employee - but does it measure the qualified employee. Qualified employee is "economical with the truth"
Can you use this to create a super-intelligent business, but need permission and payback
XL - hard to get data out of old systems, not always accurate in company need to think out the box, size matters but so does innovation and speed
Burberry - some bits very innovative, some bits startup
HSBC - no shortage of ideas, how do you make innovation happen
Shell - good at innovation in own business, harder to work with emergent non traditional models
Ericsson - ex startup guy, how to get mentality in large companies
Independent guy - Reputation management
Decoded (Facilitators) - teach people to code in a day, give people ability to code, changes mindsets of people. Argues that anyone can be one...seems to me they are selling a dream of a startup stereotype though (Developer Rockstar, big spiel around salary jump) Genesis was people who can't code/do computing in companies desperately feeling they need to know. Is this due to structural problem in UK culture/education. Demand is global.
How should innovation happen - everybody, or in a department. Can you manage it in, or can you just cultivate it.
Challenge for large Cos is affording the huge number of wasted work and deaths in an innovative startup ecosystem - what are legal risks of deploying failures
Do you need to have a VC mentality in management, bet on probabilities
Burberry - councils with younger members (more involved in detail, digital natives) to think about solutions
Kimberly Holmes XL - Big Data
Big Data is like teenage sex - lots of talk, not a lot of action. But no currency in talking about small data anymore
Companies who use data driven models are more likely to be correct - models show 6% increase in profit, 5% in productivity. Big data has real ROIs
You can't see patterns in small chunks, eg lots of datapoint arrayed correctly is a movie
Plan for the Big Data, it will come - too many wins for people not to use it - Billy Bean, Moneyball example. Knew he couldnt win otherwise. Biggest risk is doing nothing
XL is first company in space to have centralised analytical team, big benefits quickly.
Aim is not to outrun the bear, but to outrun the others.
Execution is an issue, eg
- Correlation is not causality - need subject matter experts to interpret
Notes from Day 2 of the FT Innovate Conference
Survey - 7000 respondents, mapped behaviour of innovators. Some points on characteristics:
- Ask disruptive questions ie questions they dont know answers to. Drucker - need to know what questions to ask.
- Innovation is a Combinatorial Play (Einstein allusion) - putting new combinations/permutation
Lynda Grattan, LBS
London Business School - Future of Work trends - 32 trends on future of work (book The Shift - website Hotspots), 10 big ones now:
1. People going on line - growth of online 2x faster than growth of PC usage ie hugely mobile
2. Connectivity drives brain cycles available, 14yo poor Pakistani girl wrote exams for Stanford online, not possible 5 yrs ago. India does have a way to get this talent identified at 13 (does Britain?). Baby boomers did not have to compete with the global talent pool. Lecturer - one of her kids did Medicine, "he is fine". Business school books increasingly not US/EU focus.
3. Innovation is created in 2 structures
- people who are experts getting together
- diverse people getting together
- Globalization/online collaboration will drive huge innovation.
4. Data being available online means brains anywhere can see data these day and work/ learn/make impact.
5. Hollowing out of work in the medium skill area (used to have 1/3 splitbof skilled, medium skill and unskilled. Outsourcing is moving to more skilled work now. Rise of the Specialist, and it's becoming an Art based world. Low Skill jobs will also always be salary limited by new immigrants
6. urbanization is increasing, the dream of electronic cottages is not true (is this due to - but not all cities are the same, seeing creative clusters (patents filed very spiky by city). Specialists need to be near each other. great cities need to attract great people, need great schools, lifestyle etc
7. Demographics/Generation Groups - Boomers, Gen X, Gen Y etc are different. Also look at demographic pyramid. Huge numbers of unemployed educated men equals massive instability. There is no demographic dividend if you don't educate people. Kids today will live to 100, will have to work to 83 to pay for pension at 50% - impossible. What are demographics of companies, and how does that impact things?
8. Huge rise of developing world middle class while hollowed out middle class in West is disappearing.
9. Need to build intangible assets/resilience
No signals in western countries on what kids should study - art history will no longer get you a job. Have to be educated to be able to transition.
10. Climate change is a fact (even if it isn't, but perception = reality) driving lots of silliness.
Social Media is a huge enabler.
Patents are a poor measure of Innovation,also look at R&D budgets
Panel on New Era Workforce
1. Strategos - founded 20 years ago, Gary Hamell.
Innovation - not enough to get talented people, but need to follow through when they want to do stuff or they will bugger off/lose motivation.
2 options globally to deal with global differences:
- Franchisers recruit locally
- Corporations try and mandate global cultures
Pumps are not cutting edge.....but are 10% of energy consumption in world. Message to potential recruits is they want to contribute to sustainable world via innovations - very attractive message to talented people. Be crystal clear on how Grundfos changes the world, motivates and inspires. Key to getting output is leadership - giving people freedom, setting up communities that share knowledge.
3. Funding Circle
Allows investors to lend directly to small busineses, c £180m throng it so far, recently started in US.
4. Index Ventures
Real shortage is execution ability. Looking for Doers, ideas is not enough. Isn't this just for small startups? Bias is energy over wisdom, youth over experience - main tell though is making stuff happen with severe capital constraints.
Grundfos - measure young on output, older on targets - can't use one model for all. Thing you do for all is create common understanding of the why.
2 types of innovation - exploration and exploitation. Exploitation only goes to local optima, very exciting as feedback loops are faster, but need to keep eye on exploration.
Q. Conference focusses on Technology innovation,what about Management innovation (are despots like Jobs better than democrats - tent pole companies tend to be led by despots)?
A. Too much focus here on former.
Q. Source of the Skilled Workforce?
A. Grundfos - Universities are not preparing people for future, are still in the industrial paradigm. Not seeing speed of change in Education market. This is not being debated in public forum, esp how to have high skills in West?
A. LSE - universities can never produce the workers that companies need Now! Can only play on longer trends. Companies need to do some of the training themselves,again,as theyonce did.
A. Strategos - kids need broader exposure than narrow pipe courses
A. Index - many small startups in Europe are people who have worked with each other awhile, impossible to do in Valley - Cohesiveness as competitive advantage.
Some points from Samsung Experience of Innovation and reserach done
Crisis Awareness (6 months)
Creativity & Innovation bridges gap between 6 month and 10 years
Future Thinking (10 years)
Crisis today is in delivery, usually because ambition is too high, funding is too low. Lockheed Skunkworks was very well resourced and funded.
Another Crisis is in consumer research, it's too facile. Ethographic research is very expensive, consumer research can be lied to.
Big Data is like Big Oil, to be useful it needs to be separated into constituent parts. Using Black Swan Co to help with data mining.
Biggest issue is Experience.
Different people see different pictures eg human researcher, consumer researcher, technologist, commercial analyst all see world differently, need all to experience everything.
Anybody can buy the process of innovation, what is hard is the management knowing when to persevere vs drop something - entrepreneurs good at that, companies less so. What are your peoples experience? Users?
Process alone gives you gadgets, need experience to get innovative. Experience is a flow chain from product via company, partners and consumers, very few see across this value chain.
Kickstarter is a great pre-test of innovation of "virtual products", great way to test viabiliity of products before you've made them. Also being used as "moral patents". Web being used to float virtual product.
"Experience Farm" - pooling innovation between non competing companies. What is impact on IP though? IP should only be to protect investment in innovation.
Innovation in Developing Markets
Singapore - is small, has to be high value innovation, has to be nimble, multi racial/culture. 3.5% of GDP in public innovation. See integration of design to manufacturing/technology. Nation is doubling support for small companies. Set up institute of consumer insight.
Asia is a Different market, different people - even to skin and hair type. A lot of US/EU data mining/biz model assumptions just don't work
In last 10 years 20% of LA consumers became middle class, while there is 15% population growth = 160% market growth. Huge upgrade in quality of life.
What is signal of cost/benefit - in EU it's the product, in LA it's the brand.
Older technologies in US/EU still very attractive, also adoption of stuff by demographic is very different owing to culture. Favela people have very high hygiene/beauty standards, poor people buying US Middle Class stuff (signal of status as they can't afford more expensive signals)
Big lesson is that OECD HQ stuff won't work in these markets, needs local change ie innovation. Eg hygiene habits differ, need different products.
There are infrastructure gaps in Asia and LA, but it differs by country so different products have different problems.
Quite easy in large companies like P&G to see same habits in different country, need to join the dots between products that work and similar countries - key is analysing data.
Saturday, September 21. 2013
(Social Business patchwork elephant - Image courtesy of Elmer and www.echidnaontheloose.com)
Three years ago, in Social Media Week London, we took an in depth look at the emerging Social Business world. We called it a "patchwork elephant" as it is very large, in the room, but it's hard to see the whole thing!
This year we are doing a review (see here to book) - next Friday, September 27th from 1 to 5.30 pm, at the Hub, Westminster. We will look at what lessons we can learn from the last 3 years since our first event, what is happening today, and where it is all going.
This event is for people interested in discussing the evolution, current state, and future of Social Business, We will discuss issues such as the implementation challenges it will face, how it integrates with existing systems today, which industries and parts of companies are likely to be early adopters, what is the impact on how work is organised and done, and what is still required for it to succeed.
The session will feature talks, Q&A sessions and case studies from companies, consultants and academics working in various parts of the Social Business value chain.
The aim is to leave attendees with a good appreciation of where social business came from and where it is today, and the main opportunities - and threats - going forward. For those already working in the area it will give visibility of more of the whole area from a variety of other viewpoints. Also the event is an opportunity to meet like minded interesting people from the London/UK scene, we will repair to a pub nearby afterwards!.
Our star-studded speaker line up is, in strict alphabetical order:
- Will McInness, Nixon McInnes
- Mat Morrison, Star Media
- Anne-Marie McEwan, The Smart Work Company
- Luis Suarez, IBM
- Neil Usher, WorkEssence
Plus some thoughts from us, the organisers - the Patchwork Elephant motley crew are:
- Janet Parkinson, Technotropolis
- Alan Patrick, Broadsight
- David Terrar, D2C
Twitter Hashtag is #smwsocbiz
The event is sponsored by ComparetheCloud.net
Thursday, September 19. 2013
The "Big Potato" session I participated in was to answer the following questions:
- How can policy makers, government, educators and other organisations help – or avoid hindering – progress in manufacturing?
My answers, in short (we only had a few minutes each), is based on 25-odd years of working with manufacturing companies in the UK and elsewhere, can be boiled down to the the following:
London is high cost, high regulation, low space - you can’t make low value, high volume commodities and win: A company can only win by creating added value and/or by learning to manufacture in small runs, ecomically - ie reduce batch size costs
Reducing setup costs issues was discussed in Part 1 (see here) but in a nutshell you must either:
- Ensure a low low ratio of setup cost to direct product cost – so make valuable stuff, or
Creating added value means creating something people will pay over and above imported mass produced, low cost items in some way. Proven approaches have been adding value by:
- Short Lead Times/Available now
So, what does London need to do to help a manufacturing resurgence? My view is the best thing is forUK and London Government authorities to stop fooling themselves that everything is OK:
Firstly, the UK likes to pretend there is level playing field – there isn’t.
- Hidden Subsidies and Barriers are everywhere else in the world
Secondly, UK regulation forces producers to be responsible, but not consumers. Producers have to adhere to all forms of regulatory and legal constraints. But UK customers are free to buy imports made in countries of dubious human rights records, by near slave labour, in criminally unsafe buildings, under working conditiions that would be criminally prosecutable in the UK. While the intentions of the regulators are laudable, the resulting cost asymmetry means competing with these low cost producers is very difficult
Thirdly, STEM status. Manufacturing STEM careers in the UK have the lowest status in the OECD (and many other countries), despite needing some of the smartest people to compete in the higher added value areas. In the UK someone without an Engineering qualification at degree can level call themself an engineer, for example. In other OECD countries, Engineer is a title on a par with Doctior, Lawyer, or qualified Accountant. STEM salaries are poor compared to salaries in media, finance or even Public service. The UK mass media is by and large anti-technology and anti-manufacturing, in competing countries the prevalent culture is mainly positive. Among the UK Chatterati it's a badge of honour to say you don't understand maths, not a badge of shame. No change, no hope.
Fourthy, for Educators and related worthies, stop all the political posturing. Depending on how you calculate it/which reports you read, between 25% and 40% of the UK school output is practically unemployable in the emerging skilled knowledge service worker world. This will only get worse unless things change, radically. Other countries have good lessons for the UK, there needs to be a radical re-appraisal of the education system, wthout it being hijacked by political and politically correct ideologies.
Fifthly, consider the social makeup of teh City. A high cost city like London, or country like the UK, increasingly won't have the low skill jobs people can do and still afford to live without significant social support, without significant resurgence in high value manufacturing (its dropped from c 20% to 10% of the Uk economy in about 4 decades). Much as I love cutting edge digital high technology, the jobs created even by the giants like Google, Facebook et al are very small per $ of revenue compared to manufacturing.
And Fifthly, for the Entrepreneur – passion is not enough, do the maths
- Don’t make stuff here that hasn’t a hope of competing economically
Incidentally, another participant on the session made a point I broadly agree with - ie stop trying to promote new initiatives by giving money to quangos (Quasi Governmental Organisations) to distribute in penny packets. Just make getting long term funding easier.
Monday, September 16. 2013
Production Costs - trade off of batch size, direct cost and setup cost
I'll be contributing to the Big Potato Group's "Making it in London" conference, on Local Manufacturing on Wednesday, and here is a bit of background to what I'm going to talk about. "Local manufacture" is about using modern technology to make things here, in London, and essentially "re-shore" much of what was offshored so long ago. The end-game that proponents of 3D printing etc expound is the ability to "print off" - ie manufacture - the product, configured to your needs, where you want it, when you want it.
There are 4 key things about Manufacturing Economics that you need to consider to understand the "Art Of The Possible" of Making It in London, revolving around the economics of manufacturing.
So Making it in London has to consider these 4 factors, and it pints towarsd what sorts of goods are most likely to actually make it if they were Made In London:
1. There is no point in making high volume commodities, they can be made cheaper elsewhere, shipped over and stored in warehouses and sold off the shelf
The Unit Cost is the direct costs of the inputs, plus the allocation of the setup costs over the batch, so assuming I'm making some crappy plastic widget ( a plastic Big Potato) with the direct input costs in total are £1 (materials, power, labour etc) and the setup costs are relatively high in comparison - say £100, then a batch size of 1000 has a Unit Cost of £1 + (£100/1000 units) = £1.10. Making a one off is £1 + (£100/1) = £101. You are not going to pay £101 for something that you can make in China for £1.10 unless it costs over £100 to ship it to the UK.
But if I am making say jewellery, say a gemstone studded Big Potato, maybe the direct input costs costs are £200, so the same setup cost of £100 yield different relative benefits. Making 1000 of these is now £200+( £100/1000) = £200.10. Making it in a batch of one is £200+(£100/1) = £300. The difference is not so large, and a 50% premium may well be something that people are willing to pay for a personalised Big Potato.
But now, imagine if I can set up my production equipment to work more like a printer, so it can print out copies of different things - one-offs - without re-setting the system, then the costs change.
The tacky plastic potato still has Unit Costs at 1000/batch at £1 + (£10/1000) = £1.01, a one off is £1+(£10/1) = £11. You can see that it may be cheaper to make it in the UK for £10 than make it in China for £1 and ship it over. Or it may be that you will pay £10 for a very fashionable persianlly coloured purple potato, get it today item in London rather than pay £1 for a "get it now/same as everyone else's" plastic potato
The jewellery now has costs of £200+(10/1000) = £200.01 if made in the thousands, but as a one off the price is now £200+(£10/1) = £210. Now that is a very competitive offering
The chart at teh top of the post shows the relationship between these. As you can see, "Making It in London" will focus on goods with a high input cost relative to their setup costs so there is a low differential, will need to focus on reducing setup costs where there is a high differential, or bring the relative cost difference to a point where it i more expensive to ship and store, and on goods where people will pay a premium for that one off/fast turnaround experience that is greater than the cost differential.
Friday, July 19. 2013
Fascinating article by Rory Sutherland in the Spectator:
As a corollary, its also not true that the "best" Universities will necessarily have all the smartest people. They all want slews of A* marks at A level, and usually only in certain subject combinations - and thus penalise the kids with more eclectic interests (who I'd argue are more likely to be the ones with more creativity etc etc). Also, having looked at the A level papers on subjects I know well (maths, physics, chemistry etc) I can pretty confidently say the difference between a good A and an A* is so marginal that it is no ways a measure of raw ability, but is more measuring a cocktail of multiple extraneous factors during a few minutes of the exam. Yet it sets a line between which universities and courses one can go to, and to which the above recruiters then all troop off, en masse.
As Sutherland points out, the obvious game theory solution is to recruit the kids who are not the First clutching ones at the best Unis, but the ones who are probably as good, somewhere else, who no one else is looking at. I think most people do know this deep down, and yet, and yet....why do people persist with it? Because its the easy way out:
Well, you need to whittle down applications somehow. And to create a spurious veneer of objectivity, recruiters all fall back on the same, lone quantifiable measure (degree class) even without evidence to support it. Tolerable if you are the only person adopting this policy: idiocy when everyone else does. In the words of F.A. von Hayek (praise be upon him) ‘Often that is treated as important which happens to be accessible to measurement.’
Also, it is a safe, not-getting-fired way of recuiting in "The War For Talent".
But I agree with Sutherland. The smartest people when I was at Uni were not the ones with the highest marks, the ones who did best afterwards ditto, the ones who made a real difference in companies I have worked with and for ditto again, and you can count on one hand the giants of the last few decades of the new technology revolution who graduated Oxbridge or Ivy League Summa Cum Laude.
Sutherland quotes Moneyball to make his point:
....[Moneyball] records the story of the baseball manager Billy Beane. Given evidence showing that the metrics historically used to determine the value of a player did not best correspond to his value on the field, Beane made a series of hires which turned the cash-strapped Oakland Athletics into a surprise success.
And its not just graduate hire, or baseball players - the arbitrage bewteen "what everyone else is doing" and reality exists all over, and (in my view) is the really, really interesting application for Big Data analysis. Finding the difference between accepted wisdom, and the actual reality, and making the arbitrage work for you is probably teh really big bang for Big Data bucks.
Last word from Sutherland:
And you know he's right.....and also I hope he really, really likes Tanqueray
Wednesday, July 17. 2013
Singer/Songwriter Amanda Palmer, who mixes acidic satire with an angelic voice and a hellish repertoire of curses (Disclosure - I am of course a fan) had an (ahem) wardrobe malfunction during a recent concert t Glastonbury, and the British "Daily Mail" tabloid decided, in true Olde Meedja style, to write a review on her focusing more on her nipple and its unscheduled emergence, rather than her music.
So what does Amanda do - write a letter of protest to the Mail? "Fuck That" (as Amanda would put it), she writes a song slagging off the Daily Mail in return - and performs it in the nude - for arts sake, of course (see the video above). Then she sticks it up on YouTube, launches a campaign via her followers to make it go viral,and the story - and video - gets covered in many more newspapers globally than the orginal, and all those articles fisk the Daily Mail report as well as show off her (musical, of course) assets
Now that's a riposte.....and boosts her own street kred and viral online rep to boot - win-win!
Lesson for Olde Media and its old mores - fisking wired targets is no longer quite like shooting fish in a barrel, they can come and bite back....
Wednesday, May 29. 2013
McKinsey Disruptive Dozen Technologies
Hot on the heels of our look at McKinsey's Top 10 Technologies, we look at their "Disruptive Dozen" (They really have taken the "Number Of X" blogpost trope to heart ).
The first thing that hits me, looking at the chart above, is that some of these are relatively tiny in impact, so its unclear how they will be "disruptive" in any significant way. The other thing that hits me is that three of these tiny ones are new energy sources. This implies a huge discrepancy between the new energy source hype/expectations, and the likely reality. I am impressed that they have not been carried away with the hype around 3D printing, we believe it won't be that high impact either (see here)
Looking at the high impact technologies, the Cloud and Mobile internet are both already large, and their change vectors are well known. Existing systems have existed for quite some time, so why will these be disruptive? If you look at previous true disruptions, it usually comes from the "first off" delta with high penetration which has arguably already happened, not the later "build ons", in this case to the existing, globally available Server Farm/Web Hosting and Mobile Internet systems.
And as for "Knowledge Automation", this is supposed to remove the jobs of the 200 million Western knowledge workers. These, however are the people who are most connected and have political power. Besides, we suspect - again if the past predicts the future - that offshoring to lower wage economies is far more likely. Whichever, selling Automation and Globalisation was one thing when it was for blue collar workers in the boomtime, it'll be another thing when it hits lawyers, doctors and bankers in the Great Recession. History implies this will be a bunfight....
The areas that they do flag that we agree are both large and disruptive are the Internet of Things, and Advanced Robotics (of which autonomous vehicles are really just a subset). More on our thinking about these here and here.
They seem not to have featured one thing they did have in their Top 10, ie the next 3 biliion people in poor countries joining the internet via mobile systems - now history suggests that will be extremely disruptive across all vectors.
It's a bit Curate's Eggy in my view, no doubt to spur debate. Anyway, the report is well worth a read, and there is a livechat later today on the topic on #McKDisrupt on Twitter
Sunday, May 26. 2013
Modified Gartner Hype Curve applied to McKinsey Forecasts
McKinsey's latest set of ICT trends. This is a follow on from their 2010 forecast (we reviewed that here). Here is the Broadstuff expurgated version, and probably one of the few where you are likely to get a bit of a qualified reality check [In Brackets]
We are not saying these things won't come to pass, but we are saying it is going to happen far more slowly than this paper implies. This will mainly be a slow evolution, not revolution. To help you work out what is real, what is coming, and what is hot air we present the Broadsuff Modifiied Gartner Hype Curve, complete with the Perpetual Hype Re-Cycle for those topics that go up and down the curve time after time but never seem to create a new service.
*I've just invented it, but I'll bet it exists by 2015 as anyone who has worked with big datasets or simulaton models has seen this phenomenon. The behaviour of anchoring - seeing things you want to see that aren't there, or stopping when you see something you like and not testing for anti-patterns - is also already well documented
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