The big IPO investment news in the innovation economy this week was LinkedIn and its valuation.
Here’s the story in Fast Company and also in Washington Post, Forbes blogs, with interesting take in The Australian and Technorati about LinkedIn.
Fast company set our some P/E maths:
At the $45 per share opening price, LinkedIn stock traded at 46 times its projected 2011 earnings. Anything above 25 and a company is expected to have unusually high growth projections. Either that, or they’re in bubble territory.
The positives on LinkedIn can be seen in the following paragraph from FC:
LinkedIn’s entire business model rests on amassing as many users as possible–particularly top-shelf professionals–and getting them to invest the time in keeping their profiles up-to-date. That’s because LinkedIn makes its nut from selling services to recruiters and advertisers who want to reach the company’s white collar members.
The Australian creates the negative case (many Australians do on U.S. stocks), in short — cheap money, high tide stocks:
The Fed’s super-easy policy, including the about-to-conclude purchase of $US600 billion ($562m) of Treasury securities, was designed in part to perk up riskier investments, such as stocks, with the view to create beneficial effects in the real US economy.
The final price at $104 seems high, after a launch at $45.
I’m not sure about LinkedIn price, but for 2thinknow I can see the investment in the innovation economy — especially exciting SMEs and start-ups — as good news in net trend terms.
It may not be the end of the world today (!) but nascent trends are now starting.
Network Goods & Geo-think
Actually, from my view, LinkedIn is a ‘network good’. I don’t have a view on the stockmarket price itself, but would observe LinkedIn is a key piece of identity architecture on the internet, that can be leveraged. And the internet can be leveraged to change the value of geography.
The virtual landscape will reshape the value of the real landscape, in a networked economy.
Innovation Economy tool.
So, there’s a lot of life in LinkedIn yet, irrespective of the stock price. Which puts me in the positive believer camp, as there are many new innovative applications for LinkedIn that have not yet been implemented. Those new applications broaden the value of innovation…
Whilst LinkedIn has been around since 2003, the innovation economy is new and in play.
Keep innovating,
Christopher Hire
MIT on LinkedIn is running a poll on whether:
“Designers can be better business strategists than MBAs?”
So far 69% or around 2/3rds say yes on 126 votes. Here’s the Poll.
Whether this is a self-selection answer (i.e. designers self-select, and have more incentive to vote as they have more to gain) — it is interesting.
Below is my comment from the poll.
I attended AGSM MBA program, and found it valuable. But I also graduated from Visual Arts and worked in Design. Our firm, 2thinknow is based on the tension between design and economics. Our Innovation Cities Program integrates Cultural Assets, Human Infrastructure and Networked Markets. i.e. Arts, business, economics MBA / Design are complementary – but only in people who view the textbook on topics such as Human Resources with some scepticism, and question Friedman or Chicago School economics (alongside Keynes). Designers have the maverick spirit business management has the centrism needed to orient. I would tend to say it depends on the sector, which is better. Keep innovating, Christopher Hire Exec Dir 2thinknow ICP
I would add that design without a financial focus is problem not useful. And that having worked as a designer when younger (21-23 mainly), and as an analyst later I have found it is rare to wear both hats well.
Author Daniel Pink wrote MFAs are the new MBAs some time back.
As an innovation analyst for 2thinknow, I integrate design in my processes every day. So if I had to commit to answer, and had no room for explanation, the answer would be:
YES.
What would your answer be?
The Cloud has been the next big thing for some time.
Globally the Cloud has entered the ‘adolescent’ phase as an innovation. In San Francisco Bay Area and other tech hubs in India, the Cloud is now entering the mainstream as a concept.
Microsoft adverts ‘To the Cloud’ are telling consumer the Cloud is ready. Google and Gmail has made the cloud easy. And I would guess from previous form an alarming amount of business data worldwide is stored in Hotmail and Gmail related cloud portals by executives with passwords like [petname6]. Mostly spreadsheet dumps from large enterprise data, from my prior experience…
Yesterday I attended the Microsoft Partner Connect Roadshow on the Cloud for developers as an analyst. Analysts and developers are the canary in the coalmine for business adoption of the Cloud. When analysts / developers feel this is ‘business ready’, that’s when users get their first ‘formal’ cloud apps.
So today, the enterprise data store which is ’SQL Server’ in the Microsoft world is now available and ready in the Cloud in a secure data centre. It’s called Azure SQL. And is exciting as you can choose to get rid of the internal SQL server and all those maintenance tasks. In theory you can recycle all your SQL and code as well. I say in theory because developers know that is rarely so simple.
Like web hosting, it is a pay per month contract model, so the Cloud on Azure for business has limited barriers to entry.
I was impressed, as I’d rather my data in a Microsoft data center than a decentralised data center. It’s a rare case where centralism can work, but data centers may be that case. There are 22 data centers, none in Australia, but a cache in Sydney.
I was impressed by the Azure cloud innovation potential.
Connect on twitter @christopherhire
Disclosure: The author was a guest of Microsoft and has worked for companies in the MS Partner Program since 2003. The innovation analysis / terms used in this article derive from his innovation analysis work for 2thinknow.
As is often said in politics, the only poll that counts is the one on election day.
Certainly, the data from long time polling shows a massive variability to poll day results. Poll data is obtained via survey of voting intentions. This uses a sub-set of voters
a) available
b) willing and
c) selected.
(New technologies are impacting polling accuracy too.) This sub-set forms a microcosm of the macrocosm of national voting intention when processed using statistical methods by each pollster.
So how do you read today’s Newspoll of ALP 30% support if you’re interested in the electoral data in Australia?
In general the further a poll gets into ‘bedrock’ support territory the more worried politicians get. So 30% is deep in bedrock. But that said, perhaps an analysis of the behavioural reasons might challenge that view.
Here’s 7 psychological insights in behavioural responses to change that may explain the poll result.
1) Carbon tax will raise cost of living (current issue)
2) Electricity companies ripping off consumers
3) Banks ripping off consumers
4) Supermarket/everything duopoly raising prices to support lower milk/bread prices (i.e ripping off consumers)
5) Lack of belief politicians will act on consumers being ripped off
6) Belief that politicians can act on consumer prices
7) Belief that politicians are acting to make prices more expensive.
The point: There is a deep suspicion that Left politicians want to raise the cost of living.
And, many intellectual hard-Left voters (university Marxists et al) have moved to the Greens (the Protest party).
It is not (just) the leadership of the ALP, it is about ‘policies that raise the cost of living’.
So the ALP is getting a 10-12% points protest vote about ignoring cost of living.
Actual support I believe would put the actual ALP support would put the support at 10-12% higher giving the ALP 40-42%, and Coalition around the same, with greens losing support as people examine their pay-packets. 2PP probably is closer towards 48% ALP, 52% coalition, but this may be misleading. (*)
Of course an alternate simplistic way to examine the Newspoll data is:
LEFT 30+15% = 45% (Labor + Greens)
RIGHT = 45% (Coalition)
In short where we were at the election. The data on the 2 party horse race is in other words tighter than one would think. Perhaps, it’s a 3 way horse race.
For the record, politicians can act to lower the cost of the living for the majority, can act to prevent asset bubbles, can act to regulate quality of goods and services (and prevent rip-offs). So the Greens may have a point…
Links:
Newspoll: http://resources.news.com.au/files/2011/03/07/1226017/334899-110308-federal-newspoll.pdf
Columnist: http://blogs.theaustralian.news.com.au/mumble/index.php/theaustralian/comments/newspoll_history_repeats/
[*Note this paragraph has been corrected at 8.44pm 8/03/11]
Which is more accurate? (The answer may surprise you.)
9.2 Million or 9.27 Million or 9.271 Million or 9,271,675?
The answer is… it depends.
The perception is that the more numerals data has, the more accurate. This perception is in GDP, unemployment rates, economic and other data. Yet it’s not strictly true.
Any of the figures could be less or more accurate, but additional digits imply certainty. When collating economic or aggregate data, such as GDP, the chances are in any case the underlying data is an estimate, or a sum of sources based on estimates.
So if a country has a GDP per capita of $33,000 or $31,987 it may in fact be absolutely no different in real terms. Yet it looks and sounds different. This is the problem with a presumption of perfection or accuracy in statistics.
Do a mental experiment, next time you hear a figure, round it up or down.
Chances are 5.1% or 5.7% unemployment may not be accurate, in any case. Australia has 2 million people not ‘employed’ yet has unemployment of around 5% on a population of 22 Million. The quoted figure may be technically accurate, but is it the ‘actual’ real world figure?
To know the accuracy of a data figure, you have to read all the assumptions and notes accompanying the calculation.
It’s worth ignoring all media reports on television or radio on economic data without reading the actual data. Newspaper reports tend to have more time to give background. Although data can be tainted by the source, so you really need to evaluate that.
(I always look for independent non-political data for benchmarking, or at least, a multitude of views.)
Without reading the basis and source… you may as well round the figure mentally before taking it at face value. This trick can get you out of the habit of making differences between small movements in any number.
Connect with me via twitter: @christopherhire
One aspect of buying food these days is reading labels. At least for me. I find I am often checking any processed food before purchasing. Both the ingredient list, and the side nutrition panel.
Doing this for awhile, brings up 2 interesting data points you may not know.
1. The Ingredient list is from largest quantity to smallest quantity. This can be useful for measuring how much fish is in fish, say. Sometimes fish is less than 50% fish. aka not fish.
2. The second is that a decrease in’ real ingredients’ can lead to an increase in calories. An example is ice cream.
Streets (really Unilever) Blue Ribbon Vanilla Icecream is my new purchase. Blue Ribbon Vanilla Icecream has as ingredients 1 and 2: 51% Buttermilk, followed by cream. Which is what ice-cream is really.
This means a lower energy reading of 858 kJ or 205 Calories per 100mL. Or around 500kJ for 2 small scoops.
This compares with readings of 1000kJ or more for other ice creams which have less dairy product (as they substitute sugar). A single Eskimo Pie or Drumstick is equivalent to 3,4 or 5 scoops.
So read your food labels. Check the 100mL/or gram values. And, examine the first few ingredients.
If they don’t read in the ‘correct’ logical order for ‘natural’ food, then perhaps the data is telling you something!
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