Archive for the ‘økonomi’ Category

Den fjerde mobile bølgen – og fremveksten av de neste trillioner dollar

Jeg fikk anbefalt en spennende rapport og konferanse av Tim Bajarin, en av skribentene jeg følger i min nyhetsleser. Siden det var om mobil har jeg brukt litt tid på den. Der er på førti sider og er ment som forberedelse til konferansen Mobile Future Forward. Jeg kan desverre ikke delta, men rapporten er svært interessant og er vel verdt å nevne.

Utdrag og grafikk er gjengitt med velvillig skriftlig tillatelse av Chertal Sharma. Han har fullstendig copyright til sine materialer og kopiering er ikke tillatt av hans innhold.

Her er velkomstordene av Chertal Sharma til mulige deltagere:

It is very clear to us that we are entering the ‘Connected Intelligence’ era. These two operative words are going to define the next phase of human evolution and are going to dramatically change every industry vertical from the ground up. Welcome to the Golden Age of Mobile.

Mobil IT leder opp til fremtidens nye syklus og vi en nå i begynnelsen på den fjerde bølgen, som er mobilt digitalt innhold og tjenester.

Her er punktene jeg merket meg i rapporten:

Mobil påvirker alt

Mobil synes som den eneste industrien (på mer en billion dollar), som kan endre alle de andre store industriene som reise, helse, energi og finans.

Trillion dollar businesses

If we look at the major industries that contribute to the global GDP (figure 1), mobile is the only one that impacts every other trillion dollar industries in ways that can fundamentally change how that vertical operates. There are new “mobile only” companies that are disrupting each of these verticals by redefining consumer engagement, productivity, and life on the go.

Størrelsen på den fjerde bølgen

Mobilt digitalt innhold og tjenester vil bli større enn både tale, SMS og data tilsammen, i løpet av de neste ti år.

Shared revenue

Databehandling-landskapet – Fra PC til post-PC

PC har på ti år gåttt fra å ha 90% av det globale markedet til 25% idag. Figuren viser overskudd hos hhv Microsoft, Google og Apple og illustrerer dette tydelig:

ecosystem revenue 2013

If we look at how the quarterly revenue base has changed for these players, the shift from PC to Post-PC is clear. Figure 2 illustrates the performance of these three leaders across the PC and Post-PC dimension. In 2008, Microsoft dominated the two with roughly 58% of the revenue. By 2013, the situation completely flipped and now Apple is ahead with 56% of the revenue base while Google’s share remarkably stayed constant (Figure 3).

Elementer i den fjerde bølgen

Rapporten snakker mye om kontekst, og mener med det sammenhengen brukeren er i, som lokasjon, temperatur, bevegelse, bilde, hva du har gjort før og hva du tenkes å skulle ville akkurat nå.

Sikkerhet og privatlivets fred, hevdes også å kunne bli viktig igjen. Noe som i dag synes som en selvfølgelighet etter alle etterretningsskandalene i USA i sommer.

The most critical layer that will drive user behavior and competitive battles will be that of context – the most valuable currency on the 4th wave…

…Thus the context layer forms the critical intelligence layer that enables the applications and services. Given the importance of context and data, capabilities to process enormous amounts of data in real-time and eke out valuable insights becomes an important aspect of what 4th wave is all about – designing services at an individual level. Security becomes very important when systems can put together a complete profile of the consumer in a matter of seconds using disparate data sources. Also, given that we will have multiple connected devices per individual, technologies that are able to tie the user-experiences across all the devices while preserving the context will be invaluable and players who play on all the connected dimensions will stand out.

Akseptere feil og kunsten om å lære

As we mentioned before, the managing growth on the 4th curve requires a different temperament that embraces failures, learns from it and moves on. One is not going to succeed in all initiatives or make an impact on all verticals. So, one has to experiment, formulate, execute, and move on, repeatedly. Companies who are able to create the culture that embraces failure will remain viable. Players who continue to work in traditional ways are unlikely to make a big impact over the course of the next decade.

Den fjerde bølgens påvirkning av økosystemet

Verdien i den fjerde bølgen vil skapes oppå IP-laget, dvs på toppen av mobile nettverk og lagring i nettskyen.

It is very clear from the discussion above, that the 4th wave will democratize the mobile revenue streams. The IP layer is a great leveler, once an application provider has access to it, it can create a direct relationship with the consumer and can create a platform and an ecosystem that has scale and longevity. The competitive landscape will be completely altered by the 4th wave.

…the number of players they can sell to will expand dramatically which means they will also have to adjust how they design products, establish relationships, and conform to revenue goals. Also, for the first time, software more than hardware will drive the revenue growth curve for the vendors.

Rapportens konklusjon

Rapporten hevder at det ikke vil være den industri som ikke vil endres totalt pga. mobil.

There will be hardly any vertical that is not transformed by the confluence of mobile broadband, cloud services, and applications. In fact, the very notion of computing has changed drastically. The use of tablets and smartphones instead of PCs has altered the computing ecosystem. Players and enterprises who aren’t gearing up for this enormous opportunity will get assimilated by the tides of consolidation.

“Det er det som blir bygget plattformene (Apple, Google) som er fremtiden, og ikke plattformene selv”, er min frie oversettelse av konkulsjonen:

Indeed the future of mobile is not just about the platform but rather what’s built on the platform. It is very clear that the winners will be defined by how they react to the 4th wave that will shape mobile industry’s next trillion dollars.

www.mobilefutureforward.com sitt inhold er bekyttet slik:
© Copyright 2013, All Rights Reserved. Use without permission is strictly prohibited.

Ærlig og grådig – eller snill og feig? Adferdsøkonom tester eiendomsmeglere mot sykepleiere.

Spill-teori er en metode for å skape målbare resultater i forskning. Vi er stolte over at en av bloggens skribenter har levert masteroppgaven som er basis for artikkelen. Vi gratulerer Karin Johanne Jacobsen med oppgaven og med oppslaget i Aftenposten!

En post fra aftenposten.no har hele historien. Her er siste del:

Sykepleier Inga Storli Holm (t.v.) tar ikke sjansen på å kjøpe den lukrative Rådhusplassen, en beslutning motspiller og eiendomsmegler Kristian Falk ikke kan forstå. Representantene for de to yrkesgruppene gjør langt på vei sine valg i Monopolspillet i tråd med resultatene i en studie masterstudent Karin Jacobsen har gjort. FOTO: DAN PETTER NEEGAARD

Slik gir viSykepleiere er mer gavmilde enn eiendomsmeglere, og kvinner gir mer enn menn. Men pleierne er feigere enn meglerne, viser en fersk studie. Mannlige meglere er minst gavmilde
Når de kan velge hvor mye av en 100-lapp de vil gi til et godt formål, så gir sykepleiere i gjennomsnitt 75 kroner, mens eiendomsmeglere gir 61 kroner. Begge grupper gir mer enn gjennomsnittet i andre, tilsvarende studier.
Mer enn halvparten av sykepleierne ga bort alt, ingen ga bort 0 kroner, men det gjorde 12 prosent av eiendomsmeglerne.
Kvinnelige eiendomsmeglere gir langt mer enn mannlige kolleger, mens det er liten kjønnsforskjell blant sykepleiere.
Mannlige eiendomsmeglere er de klart minst gavmilde, mens deres kvinnelige kolleger er mer på nivå med sykepleierne.
En større andel sykepleiere enn meglere foretrekker en utvei der de slipper å velge mellom et godt formål eller å putte pengene i egen lomme, en såkalt exit-løsning.
Resultatene kommer frem i en studie basert på flere kontrollerte eksperimenter, bygget på det såkalte Diktatorspillet, som tester deltagernes givervilje.
Eksperimentene danner grunnlag for en masteroppgave utført av Karin Jacobsen ved Økonomisk institutt, Universitetet i Oslo, med tittelen «Den situasjonsbetingede pliktfølelsen». 

Kilde: Artikkelen «Are nurses more altruistic than real estate brokers?»

Forfattere: Karin Jacobsen, Kari Eika, Leif Helland, Jo Thori Lind, Karine Nyborg 

Ærlig og grådig – eller snill og feig? Adferdsøkonom tester eiendomsmeglere mot sykepleiere.

Spill-teori er en metode for å skape målbare resultater i forskning. Vi er stolte over at en av bloggens skribenter har levert masteroppgaven som er basis for artikkelen. Vi gratulerer Karin Johanne Jacobsen med oppgaven og med oppslaget i Aftenposten!

En post fra aftenposten.no har hele historien. Her er siste del:

Sykepleier Inga Storli Holm (t.v.) tar ikke sjansen på å kjøpe den lukrative Rådhusplassen, en beslutning motspiller og eiendomsmegler Kristian Falk ikke kan forstå. Representantene for de to yrkesgruppene gjør langt på vei sine valg i Monopolspillet i tråd med resultatene i en studie masterstudent Karin Jacobsen har gjort. FOTO: DAN PETTER NEEGAARD

Slik gir viSykepleiere er mer gavmilde enn eiendomsmeglere, og kvinner gir mer enn menn. Men pleierne er feigere enn meglerne, viser en fersk studie. Mannlige meglere er minst gavmilde
Når de kan velge hvor mye av en 100-lapp de vil gi til et godt formål, så gir sykepleiere i gjennomsnitt 75 kroner, mens eiendomsmeglere gir 61 kroner. Begge grupper gir mer enn gjennomsnittet i andre, tilsvarende studier.
Mer enn halvparten av sykepleierne ga bort alt, ingen ga bort 0 kroner, men det gjorde 12 prosent av eiendomsmeglerne.
Kvinnelige eiendomsmeglere gir langt mer enn mannlige kolleger, mens det er liten kjønnsforskjell blant sykepleiere.
Mannlige eiendomsmeglere er de klart minst gavmilde, mens deres kvinnelige kolleger er mer på nivå med sykepleierne.
En større andel sykepleiere enn meglere foretrekker en utvei der de slipper å velge mellom et godt formål eller å putte pengene i egen lomme, en såkalt exit-løsning.
Resultatene kommer frem i en studie basert på flere kontrollerte eksperimenter, bygget på det såkalte Diktatorspillet, som tester deltagernes givervilje.
Eksperimentene danner grunnlag for en masteroppgave utført av Karin Jacobsen ved Økonomisk institutt, Universitetet i Oslo, med tittelen «Den situasjonsbetingede pliktfølelsen». 

Kilde: Artikkelen «Are nurses more altruistic than real estate brokers?»

Forfattere: Karin Jacobsen, Kari Eika, Leif Helland, Jo Thori Lind, Karine Nyborg 

 

What Caused the Financial Crisis?

Seeing red numbers. Credit: thedaylimind.com

While goverment reports names two reasons, here is a short article that names ten.

A post from .com by has the whole story. Here is a part:


Bill Thomas, Keith Hennessey, and Douglas Holtz-Eakin have a dissenting statement in response to the final report of the Financial Crisis Inquiry Commission:

What Caused the Financial Crisis, by Bill Thomas, Keith Hennessey, and Douglas Holtz-Eakin, Commentary, WSJ: Today, six members of the Financial Crisis Inquiry Commission … are releasing their final report. Although the three of us served on the commission, we were unable to support the majority’s conclusions and have issued a dissenting statement. …

We recognize that … other … narratives have popular appeal:… Had the government not supported housing subsidies (the first narrative) or had policy makers implemented more restrictive financial regulations (the second) there would have been no calamity.

Both of these views are incomplete and misleading. … We believe the crisis was the product of 10 factors. Only when taken together can they offer a sufficient explanation of what happened:

Starting in the late 1990s, there was a broad credit bubble in the U.S. and Europe and a sustained housing bubble in the U.S. (factors 1 and 2). Excess liquidity, combined with rising house prices and an ineffectively regulated primary mortgage market, led to an increase in nontraditional mortgages (factor 3) that were in some cases deceptive, in many cases confusing, and often beyond borrowers’ ability to pay.

However, the credit bubble, housing bubble, and the explosion of nontraditional mortgage products are not by themselves responsible for the crisis. Our country has experienced larger bubbles—the dot-com bubble of the 1990s, for example—that were not nearly as devastating… Losses from the housing downturn were concentrated in highly leveraged financial institutions. Which raises the essential question: Why were these firms so exposed? Failures in credit-rating and securitization transformed bad mortgages into toxic financial assets (factor 4). Securitizers lowered the credit quality of the mortgages they securitized, credit-rating agencies erroneously rated these securities as safe investments, and buyers failed to look behind the ratings and do their own due diligence. Managers of many large and midsize financial institutions amassed enormous concentrations of highly correlated housing risk (factor 5), and they amplified this risk by holding too little capital relative to the risks and funded these exposures with short-term debt (factor 6). They assumed such funds would always be available. Both turned out to be bad bets.

These risks within highly leveraged, short-funded financial firms with concentrated exposure to a collapsing asset class led to a cascade of firm failures. … We call this the risk of contagion (factor 7). In other cases, the problem was a common shock (factor 8). A number of firms had made similar bad bets on housing…

A rapid succession of 10 firm failures, mergers and restructurings in September 2008 caused a financial shock and panic (factor 9). Confidence and trust in the financial system evaporated, as the health of almost every large and midsize financial institution in the U.S. and Europe was questioned. The financial shock and panic caused a severe contraction in the real economy (factor 10). …

[I]t is dangerous to conclude that the crisis would have been avoided if only we had regulated everything a lot more, had fewer housing subsidies, and had more responsible bankers. Simple narratives like these ignore the global nature of this crisis, and promote a simplistic explanation of a complex problem. Though tempting politically, they will ultimately lead to mistaken policies.

I don’t think the conclusion that better regulation would not have stopped the crisis follows from the factors they list.

$76 billion a year from a tableful of products $aapl

A post from .com by has the original story. Here it is with kind permission:


During the calendar year 2010 Apple spent nearly $2 billion in R&D. That is a significant increase from $714 million in 2006. However, as a percent of sales, R&D spending has decreased. Sales have grown more rapidly than resources hired to develop the products (or to sell them).
In Q4 2005 Operational Expenses (costs which are not tied directly to units of production–sometimes called fixed costs) were 14.2% of sales. In the last quarter of 2010, the ratio was 9.2%. Sales and administrative expenses (which include advertising, promotion and overhead) were 7.1% and R&D (which includes all engineering, testing) were 2.2%. As percent of sales both reached new lows.

The efficiency with which Apple creates sales is legendary. There can be many explanations for this but the most telling evidence of causality I can find is the small number of products in the portfolio. Tim Cook stated that given the sales value, there is more concentration of product at Apple than at any other company except perhaps an oil company. All the products Apple sells can fit on one average sized kitchen table and they generated $76 billion in sales last year.

How is this possible? First, a few words about the often misunderstood process of product development.
Most observers of technology are not aware of the pace of its development. It’s natural to assume that most R&D costs are in the product creation, or early phases of development. Coming up with something new must be hard. But that’s not actually true. Most R&D work is routine polishing of products and coordination late in the development cycle. “Productization” is far more resource intensive than “concepting”.
It stands to reason that making go/no-go decisions early in the pipeline is a lot less expensive than making stop-ship decisions prior to launch.

I have no specific evidence that this is the case, but I guess Apple conceives of plenty of concepts, but chooses to move forward to develop and market very few. Most companies don’t have the ability to decide early and proceed with costly R&D and marketing in order to find out whether products will “work” in the marketplace. The proliferation of flawed products is a big cause of the inefficiency of product development.

But launching flawed products is also detrimental to brand value, something which rarely hits the books and is thus invisible to operational managers.

This uncanny ability to pick winners early in a long gestation period is my guess for why Apple is so efficient with OpEx. The question of how to develop this ability is left for another day.