Strategy

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.

Standard Oil dominated the oil products market initially through horizontal integration in the refining sector, then, in later years vertical integration; the company was an innovator in the development of the business trust. The Standard Oil trust streamlined production and logistics, lowered costs, and undercut competitors. "Trust-busting" critics accused Standard Oil of using aggressive pricing to destroy competitors and form a monopoly that threatened consumers.

John D. Rockefeller was a founder, chairman and major shareholder.

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.

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.

Coca Cola

- 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.....).
- Huge use of consumer research plus experts in new ways of packaging/dispensing.
- Shift in what they are looking for in R&D from deep science, to people who can influence and get things done. Technical capability is taken for granted. Global talent pool is good, but competition for scientists from ICT businesses

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:

- Customer experience
- Business model change
- Internal operation

Their test for a true Cloud infrastructure rang true to me too

- Self Provision
- PAYG
- Flexible capacity automatically

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

Startups Session

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
- not an IT thing, it's a business thing.
Volume, Variety, Velocity
Who do you hire?
- 2 actuaries, modellers. Curiosity is key - means you are enthusiastic and not wedded to status quo
- need people who are tech skilled, but must have EQ skills, also must be able to ask the right question.

Notes from Day 2 of the FT Innovate Conference

Hal Gregersen

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.
- Questions without actions are useless - 3 types of solvers: Observers, Networkers, Doers. Need all to see and solve problems.
- Look for the Surprises. Find an inside/outside stimulus - networking, find people outside of the people surrounding the problem
- Just experiment, test, try.....key is to reduce the cost of experiments so many experiments can be done

Other points

- Innovation is a Combinatorial Play (Einstein allusion) - putting new combinations/permutation
- Try and work out where you get new ideas, and do it more often.
- Biggest driver of innovation is curiosity, back to asking hard questions.
- Innovators spend 2x more time finding ideas, c 4 months a year vs 2 months. Numbers game, they discover/generate more combinations to play with.

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

- educational
- social
- vitality/emotional

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.

Other notes

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. Grundfos

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.

Questions

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

3 Pillars:
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

Latin America

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.

(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



 

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?
- How can we deal with risk and help realise the visions we imagine for London, and the UK?
- How can we overcome industry, economic, and financial barriers?

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
- Reduce setup costs – combine modern CNC machine tools and methods to minimise setup costs

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
- High Design Input to create diferentiation
- Fast change/Fashion - make things that are hard for long lead time supply chains to replicate quickly
- Design unique capability into a product

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
- Business investment, especially longer term, is much harder in the UK than in competing countries
- London costs are fairly extreme, every time an old factory site is converted to execuive housing it reduces available industrial space. There needs to be designated industrial space running at lower rent/rates than commercial or residential property or else it will be increasingly uneconomic to manufacture in London.

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
- Pick the parts of the supply chain to “re-shore” where you are competitive, get the rest of it done in lower wage countries

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.

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.

1. The relationship between cost of choice and value - in general, the more personal choice or configuration one requires, the higher the cost of production, and the higher the price needs to be to cover it. Not all choice is valuable to customers however

2. The trade-off between batch size and unit costs. If the input costs of making something is very low (materials, labour etc) , but the setup costs (design, machine setting,s tooling etc) to make it are very high, a short batch run will make it very expensive vs someone else making a much larger batch size.

3. The trade off between production costs and logistics costs - in the 1980's it was cheaper to mass produce things in China, ship them over to the West, and store in large warehouses. As Chinese wages rise, and transport costs rise, the economics of making something in London, despite its higher labour costs, becomes more viable as transport costs are lower

4. If the product is fashionable, or has a short lifecycle, then the lead tme from making it in China can be too high, and it can be better to be able to make it close to the market, at short lead times. It is more expensive, but it is also there when people want to buy it.

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

2. What will be hardest to compete with is product that is both highly configurable, and fashionable - is I want it my way, and i want it now. That is very difficult for an offshore mass production system can match.

3. Highly configurabe products are likely to be made in small numbers however, so they need to be products that achieve high value for their configuration. What do people really care about, when paying for choice

4. This means a focus on the ratio between setup cost and product direct cost, and batch size.

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.

Fascinating article by Rory Sutherland in the Spectator:

It’s hard to tell the difference between a university and a business school nowadays. Where are all the hippies, the potheads and the commies? And why is everyone so intently serious and sober all the time? ‘Oh, it’s simple,’ a friend explained. ‘If you don’t get a 2:1 or a first nowadays, employers won’t look at your CV.’

So, as a keen game-theorist, I struck on an idea. Recruiting next year’s graduate intake for Ogilvy would be easy. We could simply place ads in student newpapers: ‘Headed for a 2:2 or a third? Finish your joint and come and work for us.’

Let me explain. I have asked around, and nobody has any evidence to suggest that, for any given university, recruits with first-class degrees turn into better employees than those with thirds (if anything the correlation operates in reverse). There are some specialised fields which may demand spectacular mathematical ability, say, but these are relatively few.

So my game theoretic instincts suggest that if we confine our recruitment efforts to people in the lower half of the degree ladder we shall have an exclusive appeal to a large body of people no less valuable than anyone else. And such people will be far more loyal hires, since we won’t be competing for their attention with deep-pocketed pimps in investment banking.

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:

I am planning to offer an exclusive service to Spectator readers from 2015. Send me a litre of Tanqueray and I’ll happily confirm that your son or daughter performed a magnificent four-week internship with me. Meanwhile your kids can all go off to Goa and spend the summer smoking drugs on the beach as God intended. Nobody will be any the wiser — and nobody will be any worse off.

And you know he's right.....and also I hope he really, really likes Tanqueray

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....

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

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]

1. Joining the social matrix

Social technologies are much more than a consumer phenomenon: they connect many organizations internally and increasingly reach outside their borders. The social matrix also extends beyond the cocreation of products and the organizational networks we examined in our 2010 article. Now it has become the environment in which more and more business is conducted. Many organizations rely on distributed problem solving, tapping the brain power of customers and experts from within and outside the company for breakthrough thinking.

[Its a transaction cost game - see our thoughts on this over here - and in very early days. It is also largely Just Another Channel, not a New Paradigm - that was so 2012]


2. Competing with ‘big data’ and advanced analytics

Three years ago, we described new opportunities to experiment with and segment consumer markets using big data. As with the social matrix, we now see data and analytics as part of a new foundation for competitiveness. Global data volumes—surging from social Web sites, sensors, smartphones, and more—are doubling faster than every two years. The power of analytics is rising while costs are falling. Data visualization, wireless communications, and cloud infrastructure are extending the power and reach of information.

[The problem with Big Data (or data analysis, as it used to be known in the Olde Days, c 2010) is that the low hanging fruit is soon plucked (if it hasn't been already - people used quaint old ideas like Statistics and Operations Research to estimate these larger datasets and optimise things in them thar Old Days). The other issue is Beautiful Mind Syndrome* where people see patterns in the data where none exist (or worse, you anchor on non patterns you want to see) and chase after will o' the wisps. Big Data is a lot like SEO - typically once you've done the fairly obvious things (that you may well have already done - see Statistics, use of, above) you can shave small incremental benefits off things by analysing them to the nines, but a crap business will still be a crap business and you're better off changing that than crunching yet more data]

3. Deploying the Internet of All Things

Tiny sensors and actuators, proliferating at astounding rates, are expected to explode in number over the next decade, potentially linking over 50 billion physical entities as costs plummet and networks become more pervasive. What we described as nascent three years ago is fast becoming ubiquitous, which gives managers unimagined possibilities to fine-tune processes and manage operations.

[We have been active in this area for 20 odd years, and the hype still outpaces the reality unfortunately. Unit costs per sensor and the cost of integration, lack of standards and reliability of these systems at any scale are still huge barriers to widespread deployment. But it is coming, one day...see our take on it over here]


4. Offering anything as a service

The buying and selling of services derived from physical products is a business-model shift that’s gaining steam. An attraction for buyers is the opportunity to replace big blocks of capital investment with more flexible and granular operating expenditures. A prominent example of this shift is the embrace of cloud-based IT services. Cosmetics maker Revlon, for example, now operates more than 500 of its IT applications in a private cloud managed by an external provider. It saved $70 million over two years, and when one data center in Venezuela was hit by a fire, the company was able to shift operations to New Jersey in two hours. Moves like this, which suggest that cloud-delivered IT can be reliable and resilient, create new possibilities for the provision of mission-critical IT through external assets and suppliers.

[The best X As A Service operators are making thin margins at best, and increasingly having to grow by acquisition (Salesforce.com), and most are still heavily subsidised by their parent companies or running on investors money. The hassle factor of running key services remotely, with the same level of reliability and flexibility as in house, is still not a slam dunk for anything but the very basic commodity services. Exits (and valuations) are a function of hype over reality still]


5. Automating knowledge work

Physical labor and transactional tasks have been widely automated over the last three decades. Now advances in data analytics, low-cost computer power, machine learning, and interfaces that “understand” humans are moving the automation frontier rapidly toward the world’s more than 200 million knowledge workers.

[This we will watch with interest, as those 200 million are the bulk of the educated elite in developed countries, they are connected and (still) wealthy, and are not going to take this development lying down. Business leaders were able to push Globalisation when it was boomtime and only low end blue collar jobs were being hit, lets see if it still works with high end white collar ones, in Great Recession hit democratic countries. Also, the automation of knowledge work has been a holy grail through at least the last 3 main tech cycles - remember Knowledge Engineering, Artificial intelligence etc - and so far has still not got very far in practice]


6. Engaging the next three billion digital citizens

As incomes rise in developing nations, their citizens are becoming wired, connected by mobile computing devices, particularly smartphones that will only increase in power and versatility. Although several emerging markets have experienced double-digit growth in Internet adoption, enormous growth potential remains: India’s digital penetration is only 10 percent and China’s is around 40 percent. Rising levels of connectivity will stimulate financial inclusion, local entrepreneurship, and enormous opportunities for business.

[The next 3 billion citizens are very uninteresting by Western advertising economics standards, but Western price Ads (or selling data to advertisers) is required to fund the Western Dotcom industry at its current cost levels. It will thus be interesting to see the business models used for the next 3 billion, because most of the current Ad based ones won't work with Western based infrastructures]


7. Charting experiences where digital meets physical

The borders of the digital and physical world have been blurring for many years as consumers learned to shop in virtual stores and to meet in virtual spaces. In those cases, the online world mirrors experiences of the physical world. Increasingly, we’re seeing an inversion as real-life activities, from shopping to factory work, become rich with digital information and as the mobile Internet and advances in natural user interfaces give the physical world digital characteristics.

[Remember 2nd Life? All this was promised, back then. It tanked, and nothing has changed that reduces the ikelihood of another failure just yet]


8. ‘Freeing’ your business model through Internet-inspired personalization and simplification

After nearly two decades of shopping, reading, watching, seeking information, and interacting on the Internet, customers expect services to be free, personalized, and easy to use without instructions. This ethos presents a challenge for business, since customers expect instant results, as well as superb and transparent customer service, for all interactions—from Web sites to brick-and-mortar stores. Fail to deliver, and competitors’ offerings are only an app download away.

[Today, most of your competitors are still no better than you, finding the right App is a nightmare, it's not a given it'll work on your device, and there is a lot of stuff we still won't buy online - see below. But this is probably one of the areas that is tightening up faster than some of the others]


9. Buying and selling as digital commerce leaps ahead

The rise of the mobile Internet and the evolution of core technologies that cut costs and vastly simplify the process of completing transactions online are reducing barriers to entry across a wide swath of economic activity. Amped-up technology platforms are enabling peer-to-peer commerce to replace activities traditionally carried out by companies and giving birth to new kinds of payment systems and monetization models.

[Except that there is a large swathe of things we don't want to buy without physically examining them first, and a larger swathe we won't buy if we don't trust the seller, service, payment process etc. We are happy in the main with buying low cost, low risk commodities online. For everything else, we still like face to face communication. Its changing, but slowly, and in fact we are starting to see online retailers look at bricks and mortar stores to increase their penetration. Very few payment systems are "new", most have been thought about for 20-odd years (just look at all the dotcom initiatives), typically the blockers have been technology costs, vested interests or lack of user takeup]


10. Transforming government, health care, and education

The private sector has a big stake in the successful transformation of government, health care, and education, which together account for a third of global GDP. They have lagged behind in productivity growth at least in part because they have been slow to adopt Web-based platforms, big-data analytics, and other IT innovations. Technology-enabled productivity growth could help reduce the cost burden while improving the quality of services and outcomes, as well as boosting long-term global-growth prospects.

[I've been doing Internet strategy for nigh on 20 years, this area is always just about to take off in a big way. However data privacy, the problem of getting the last 20% to use new services to realise the financial benefits and related worries about democratic representation, the huge discrepancy between who pays and who benefits from public money, and expensive past failures are all big barriers to major adoption. We see no compelling short term drivers for major changes. In the medium term the cost of providing for the elderly, and public services, will force changes.].

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