Excapite

Startup Incubator Economics, Revisited

noreply@blogger.com (MobCon) — Sun, 29 Jun 2014 07:37:00 +0000

Reading Nikki Durkin's post "My startup failed, and this is what it feels like…" prompted me to scrape some data on the economics of incubators.

If only to expose one of the great myths surrounding this disruptive new innovation model. i.e. Once you have been invited to join an incubators like Y-Combinator or Techstars you significantly reduce your chances of failure (e.g. Why hardly any Techstars companies fail).

To demonstrate the how the narrative is shaped in the media I have scrapped the Seed-DB data from the top 12 start-up incubator programs.

As you can see, based on the raw number of start-ups being churned out by the incubators, the survival narrative is self evident. The failure rate pales into insignificance compared to the survivors and exits.

How ever things look very different once you pivot the data into a new visualisation.

As you can see the historical record suggests, even when the amount of incubator product available to the market is scarce, the failure rate dramatically increases once you factor in the time it takes to achieve an exit on the investment.

More over the probability of achieving an exit dramatically reduces after the first 2 years of operations.

The reason for the distortion is simply a function of the explosion in incubators since 2011.

Suddenly, thanks to the wave social media IPO's, everybody is investing the incubator innovation model.

Product is being released into the market faster than the historical failure rate for this type of investment.

What the historical data suggests is, rather than the incubator ecosystem being a robust, lower risk, higher margin start-up accelerator model for would be investors and entrepreneurs, the current incubator ecosystem is significantly overweight with unrealised product (i.e. start-ups) that it will struggle to exit (i.e. achieve a return on investment) over the next 3-5 years.

If, as was the case with the 2005/06 sample, a market of 26 hand picked, closely mentored start-ups delivered a failure rate of nearly 50% after 7 years, what are the chances of a market in excess of 500, maybe even 1000 start-ups pumped out of a global array of incubator clones, loosely modelled on the Y-Combinator model, delivering a better success rate in the next 3-5 years?

Probability suggests the failure rate should sky rocket. Who knows it may get as high as 80%, 90% or even 99.99%.

But that is the whole point. Incubators are not about reducing the rate of failure as a pathway to achieving success. They are about amplifying it. This is why the incubator narrative represents such a delicious paradox. 12 weeks in the casino re-imagined as an education.

For what is the incubator ecosystem if not a Monte Carlo Simulation, a dice game, played out by the placing of bets on the hopes, aspirations and talents of a generation of young entrepreneurs who struggle to comprehend the mathematics, never mind the patterns in the big data.

For the incubator and its investors is all about playing the odds. And in the Monte Carlo Simulation he, or she, who roles the dice more often than the competition, inevitably wins. For it is the sum of the roles that counts in your favour. Not the one chance you have to role the dice.

Put simply, if you enter into this game thinking you have a winning ticket just because you have secured a spot in an incubator, you can be sure you have been well and truly played.

At least until next time ;-)

What are we writing about today? Find out at Tymbals

Are Government Cloud Marketplaces the next vapourware?

noreply@blogger.com (MobCon) — Fri, 13 Jun 2014 06:58:00 +0000

The Government Cloud Marketplace. The holy grail of the Government Treasury and Finance Office. The promise of saving your digital dollars by paying just networked pennies. App Store economics re-imagined for the public sector

But just how do you take this...

And turn it into this?

The success of these cloud market experiments has been mixed.

In Sept 2009 the Obama Administration announced a new way for Government Agencies to consume ICT products and services. It was the Apps.Gov store front.

By Dec 2013, after only US$5 Million in sales, it was closed down. The bold experiment had failed.

Described vicariously as “lipstick on a pig”, “a fashion makeover for the 10 year old GSA Advantage” and “innovation without purpose”, it failed to motivate both vendors and buyers into a new way of doing business. For the agencies there was no mandate to migrate to the “baby cloud”. The program failed to address initial agency concerns over cloud security, data portability, and the lack of cloud expertise, and ultimately, the nature of the way ICT procurement is negotiated between agency and vendors.

Smaller COTS and commercial cloud based solutions could be handled by credit card via pre-existing commercial offerings and nobody was about to add $500,000 worth of SaaS to the online cart without detailed negotiations with the vendor.

The few products that did sell through the cloud store were new to the market Storage as a Service and Messaging, Communication & Collaboration solutions.

Ultimately, even though it provided a showcase for over 3,000 products and services, it failed to attract the agencies necessary to achieve ignition of the cloud marketplace.

Compare and contrast the US adventure in the cloud with the UK experience.

Inspired by the US initiative and launched in February 2012 today the UK’s G-Cloud boasts US$294 Million in sales – 60% of which have been secured by SME.

So what did the UK Cloud Store project do differently and what are the lessons to be learnt from the UK experience?

Mine the big data published by the G-Cloud team, rearrange the service catalogue along the lines of infrastructure, platforms, apps and people and you'll discover very quickly something of a surprise.

The core business of the G-Cloud is Specialist Cloud Services or what is better understood as Body Shopping as a Service - BSaaS.

What remains - IaaS, PaaS and SaaS - constitutes about 0.25% of the annual UK Government ICT Spend.

And yes, one could observe that Government is nothing of not a game of choosing the right metrics to validate your agenda, but that would be too easy.

Likewise one could make the observation that perhaps what we should be talking about is the future of "Service as Software" rather than "Software as a Service". But again that would be too easy.

The deeper observation is, the metrics reveal, we use the network - this cloud - to connect with people, rather than information or functionality. The most popular SaaS licences are messaging and collaboration tools. We primarily use this technology to connect with others. Known and unknown.

The big data reveals the cloud is a marketplace for relationships.

And that, once you sweep away all the hype about software eating the world, mining the big data and our future in the cloud, is something worth thinking about when it comes time to plan your Cloud strategy.

The Facebook lesson is simply this. The killer app of the network economy is Relationships as a Service. Not IaaS, PaaS, DaaS or SaaS.

Which is perhaps why apps.gov failed and the G-Cloud appears to be thriving. It is in the business of connecting people with people. It is, by any definition, a "real world" marketplace.

What are we writing about today? Find out at Tymbals

Revisiting the convergence of Metcalfe's Law, Shannon's Law and McLuhan's "The Medium is the Message"

noreply@blogger.com (MobCon) — Mon, 24 Feb 2014 00:05:00 +0000

Yesterday's post on WhatsApp, Facebook, Google and the acceleration of the Network Effect in a Mobile World was RT'd by Bob Metcalfe.

Ironic in the sense that it was a RT from Bob a few years back that inspired the journey to mash together Shannon's Law with Metcalfe's Law and McLuhan's "The medium is the message" into a new media model.

What happens when "The medium is the message" converges with "Information is meaningless" (or more accurately "Meaning is irrelevant") and the Network Effect?

It was, as they say a good question. A deep question. A complex question. But alas we don't have time to go back over that journey in detail. And much of the journey has been consigned to the 80/20 rule. Which means if Google didn't like it has been consigned to the realm of digital dementia.

But let's revisit one aspect of the journey.

What happens to software when it collides with the network effect?

The answer being it fragments into a collection of function points. The network being the database and the future of software, if not the now, being combinatorial on demand. An endless mash-up, nay a remix, of functionality.

The price? Free of course. At least for anyone who can pay the price of entry... to the telcos. The new media monopoly.

So let's map it out. Using yesterday's data.

First the growth in the networks. Extended to include the PC. You'll note Smartphones and Facebook traverse the same timeline.

Now add revenues into the mix.

Do you see the trend?

Here. I'll make it easier to see.

The same idea applies to the growth in the Smartphone App Stores

And, yes you can put an estimate in the ratio of decline.

Each new Billion+ network is apparently worth less when it crosses the magic threshold. The question being will it be worth more in the future.

Google, at least for the moment, suggests yes. Yahoo! suggests no.

Remembering of course the App Stores are aggregate values of the eco-system. The value to Apple or Google is 70% less than the figure stated. Map that into the equation and we discover is back down in Facebook Territory.

Over the 3 generations the network effect translates into 100:60:30. i.e. 2nd Generation generates 60% of the first Generation Revenues. The 3rd Generation generates 30% of the Second Generation Revenues. This suggests the 4th Generation will be generating 15% of the 3rd Generation Revenues when it achieves 1 Billion Users.

Do you see the progression?

And it harks back to this idea explored in the Angry Birds Post.

The new market reality for software developers is there has never been more customers but prices have never been this low.

And it is something of a paradox when the accepted theory of the network economy is more = more.

i.e. The more you are connected the more value is generated.

In the end the answer to this paradox is very simple.

Media has been unbundled by the network. And by that I mean what once was sold as a wholesale product (Think Newspaper, Magazine or Music Album) is now sold as fragments (Think pages and songs). So too with software. Software is under going the same unbundling. What was sold as a wholesale bundle of function points (Think: COTS software) is now being unbundled and sold off as function points and limited functionality (Think: API's and Apps). The reason being of course, when it comes to the long wave of the product cycle the spreadsheet and the word processor, 30 to 40 years on, is looking very much like end of cycle, and is under the types of market pressures one would expect of a mature market.

You see this is what happens to software when it collides with the network effect. It fragments into a collection of function points. The network being the database and the future of software, if not the now, being combinatorial on demand. An endless mash-up, nay a remix, of functionality.

The price? Free of course. At least for anyone who can pay the price of entry... to the telcos. The new media monopoly.

The same thing applies to relationships. But we won't go there this time around.

But needless to say this points to the fundamental flaw in the Facebook business model. It is designed to profit from our old ideas about networks. Ideas which have now been disrupted by the network effect.

Or more accurately what happens when Metcalfe's network effect converges with Shannon's Law: "Information is meaningless" (or more accurately "Meaning is irrelevant") and McLuhan's "The medium is the message".

For the lesson here is Google's Search Engine is a function point endlessly combinatorial. Facebook is a collection of function points. To disrupt Google you need to build a better function point. To disrupt Facebook, as with Microsoft, you need merely to fragment the Platform.

So have a think about that... at least until next time :-)

What are we writing about today? Find out at Tymbals

SnapChat, Instagram, Pinterest, Angry Birds and the myth of the Viral App

noreply@blogger.com (MobCon) — Sat, 14 Dec 2013 23:39:00 +0000

What follows is a series of tear-downs design to explore a single idea. That idea being the network effect is a function of PR and not, as so often reported, word of mouth (i.e. sharing across the social network).

I had hoped there would be some industry data readily at hand but in its absence here are some mash-ups that help us to explore the idea.

We'll begin with SnapChat. Or what is more popularly understood as the "Sexting" App.

Did it go viral or was it good old fashioned PR? Here you decide...

This chart maps the growth in the number of daily snaps on Snapchat vs. the media coverage as tracked via Google Trends. Note the investment by Lightspeed and within a month the "ignition" coverage in the New York Times. The key to the PR campaign was of course building the Snapchat story around the growth (imagined or otherwise) in teen sexting.

Now let's take a look at Instagram. Again note the New York Times "ignition" coverage and the Justin Bieber "Ignition" moment. Or what is popularly known in the trade as the celebrity endorsement.

Finally, at least when it comes to mobile apps, let's take a quick look at Angry Birds. Again we see the correlation between media coverage and growth.

So much for the "viral" Mobile Apps. Now let's take a look at the correlation between growth and media coverage across the popular social media web platforms.

We'll begin with Pinterest. Again we see a correlation between injection of VC investment funds, followed by media coverage by the New York Times, as the pivot point for igniting "viral" growth in the user base.

And now Tumblr

And of course Twitter.

Now growth across these three old school social networks appears to be less vigorous than the explosive growth of the mobile apps. The question being why?

Now the interesting thing with Twitter is the myth tells us it popped at SXSW in March 2007. And indeed The New York Times and the mainstream press extensively covered Twitter after the SXSW moment. However it didn't really pop for another 2 years. Arguably the explosive growth didn't really begin to happen until the press amped up the volume following the Series C funds injection.

Again the indicator appears to suggest virility is a function of the size of the audience rather than the size of the network.

The key advantage the Mobile Apps have of course is the App Store charts. Mobile apps operate under the same dynamic as the old Top 40 Hit Parade. Success becomes a feedback loop. Not because of the network effect but because of the power of Rank on the List. It is easier to belong when you know what to belong to. The List as social indicator.

Now I have left Facebook until last. Not because press coverage wasn't a factor in its growth. It was even in the earliest days at Harvard. But because it is an indicator of another key aspect of achieving "viral" ignition.

History tells us that Facebook had its origins in Harvard. Snapchat mirrors this, only this time the viral playground was Stanford.

The key point being virality is a function of proximity and not scale. It is about the aggregated audience, each one busy looking at you, looking at me, looking at you, and not the scale of the network.

And now for the quantum leap.

There is a famous experiment conducted by Loren Carpenter [Think: Pixar] at the 1991 Siggraph.

It involved a lecture theatre full of people playing Pong. An old video game projected on a big screen at the front of the auditorium. The takeaway is the crowd played pong using remote controllers. It was the golden moment that inspired a whole generation of revolutionary thinkfluencers.

Gamification, the network effect, the wisdom of the crowd, groupthink, the economics of free. All these ideas and more emerged and evolved into Byzantine constructs out of this moment.

What was missing of course is the fact it worked, not because of the technology, not because the technology brought us together, augmented our collective behaviour, but because everybody was in the same room. It was as much an experimental proof of the power of the technology to bind us as a collective as the rock concert singalong, where the girls sing a chorus and then the boys sing a chorus. It wasn't the power of the network effect. It was simply the power of persuasion in action. Managing the audience to maximum effect. the art of selling the sizzle. The experiential moment. The art of the ringmaster to delight the audience with simple pleasures.

And here in lies the key to understand viral ignition. It is infinitely easier to ignite an audience than it is to ignite each and every individual, one by one, to engage in the conversation.

All of which is to say ignition is a function of shared time and space, not shared technology.

If there is a secret recipe for viral growth or what we now call social networking it is that you launch your Beta in an institution, or more accurately with your fans, and launch your product bootstrapped to a high quality PR campaign.

It is the business of Music circa 1950's and 60's. Make your product in the pubs and clubs. Promote your product on the radio and focus all your marketing and promotional energies on making it to the top of the hit parade.

As to the question do you really need a Venture Capitalist's money to achieve this? Only you can answer that one. But either way you will need a manager or investor who knows a good press agent.

Have a think about that, at least until next time...

Postscript:
@Frabcus requested a profile on WhatsApp. The general consensus being this is a low profile messaging app that has gone viral by osmosis.

As with all start-ups early adoption numbers are difficult to come by. So what I have done is mapped publicised numbers in dark red and an estimated trend in light red. So think of the light red as merely indicative based on a typical Zipf curve adoption rate common to most *viral* apps.

He also pointed out that your graphs are cute, but don't separate which is cause and which is effect. What's a good way of doing that?

The point being of course the focus on cause and effect is to miss the point. The objective is create a feedback loop. An endless narrative that delivers endless growth.

This is the lesson of the iPhone and the iPad. Stoke the fires of anticipation so brightly that when the product does arrive it has already ignited the imagination.

This is advertising and marketing at its best.

Here is the Google news trend for the Apple iPhone product line.

Here is cumulative effect on Brand awareness.

The growth sales? Why bother mapping them. The iPhone is the most universally recognised successful product launch of the past decade.

The point being the language of the network economy may have changed the way we describe events, marketeers may choose to think of themselves as more social or more thinkfluential, but the rules remain the same. Buzz creates sales. Sales creates buzz, but only if you let the world know about it. The challenge is to amp up the volume until you ignite the imagination.

What interests me is the price of ignition. Is it by osmosis or is it by manufacture? Truth is, like any type of innovation, ignition is is the result of a thousand failed experiments or years of experience. One comes at a cost. The other comes at a price.

Either way, as with any investment, timing comes down to a matter of time in the market.

The other key question is of course are we talking about the chicken or the egg? The answer of course is, if the data is readily available, providing a logical proof to the question of correlation or causation is relatively easy. One just has to iterate through the big data.

A = All Apps in the store or market
V = Those apps which go viral (i.e. Reach the Top the Charts)
PR = Those Apps which receive press coverage prior to going viral
NPR = Those Apps which receive no press coverage prior to going viral
FPR = Those Apps which received press coverage but failed to go viral

The relative weighting of the last three metrics (i.e. is PR > or =< NPR + FPR?) will provide a reasonable proof of the impact of press coverage on viral growth.

The challenge isn't the writing the algorithm, it's scrapping the data.

In defence of the PR model, it would appear this trend isn't limited to viral Apps and Web Sites. Laura Edwards undertook an analysis of the rise of the Gangnam Style meme back in November 2012. Her interpretation was that mainstream media coverage initially brought it to many people's, including celebrities attention. The key to ignition being the stories published between 30th of July and the 3rd of August

Likewise a quick glance at the press coverage of Google during the period 1998-2000 would suggest the world's press played no small part in amplifying the rate of adoption of the new search engine.

So if one was to postulate a working model from all this data it would look something like this.

The lessons to be learned from the model, assuming you had the inclination and the time? I would suggest

focusing on the what these viral apps and social media sites were doing right and/or wrong prior to ignition.
focusing on which stories worked and which ones didn't (e.g. Color probably failed at least in part because its ignition story was we have raised a lot of money, now all we have to do is decide what we are going to do with it).
focusing on how the marketing team fuelled the feedback loop with additional newsworthy material to keep the moment of ignition fresh. And by that I mean each new story, or should that be press release?, is the ignition point for multiplying the user base.

What are we writing about today? Find out at Tymbals

Just how important has click fraud been in shaping the growth of the web economy?

noreply@blogger.com (MobCon) — Thu, 25 Oct 2012 06:13:00 +0000

No discussion on the growth of online advertising over the past 15 years and the disruption of the print industry would be complete without taking a brief look at the problem of click fraud.

Click fraud is the widespread practice of using botnets or a low paid workforce to manufacture large-scale increases in impressions and/or click throughs to improve advertising response rates.

Talk to regular buyers of online advertising and they will tell you that today click fraud is reluctantly factored in as a cost of doing business online. They don't like it but they grudgingly accept that it is all part of online advertising equation.

Click fraud has been with us since the birth of internet advertising and industry estimates on just how big the problem is vary widely. General consensus puts the range of estimates somewhere in between 10%-40%. With the US market being at the higher end of the scale.

Calculating a dollar value for the industry estimates would put its global revenues at somewhere between 3 to 12 times larger than Facebook.

To help you visualize what that means I have prepared 4 charts.

In this first chart I have mapped the problem against the IAB's breakdown of the online advertising market.

As you can see as a worse case scenario click fraud is bigger than Banner/Display, Video and Rich Media advertising combined. The best case makes it as big as online classifieds and bigger than video.
Moving on this next chart illustrates the potential size of click fraud vs the advertising revenue model.

Again looking at a worse case scenario the click fraud industry is bigger than impression based advertising.

In this third chart what I have done is mapped the range of potential revenues generated by the global online click fraud industry against the other players in the US advertising market.

Again the estimates for the worse case scenario makes click fraud a bigger industry than US Radio, Magazines and the TV Broadcast Networks.

The interesting thing about click fraud is of course the question: If it did not exist would the online advertising market be as big as it is today or would it be significantly smaller? It is an important question because online advertising today has grown to become a $54 Billion industry and if you extract 30%-40% out of that market it significantly changes the story.

The answer to that question of course is another question: If click fraud didn't exist would the advertisers expect to be paying less (i.e. the same rate but fewer hits/clicks) or about the same (i.e. higher rate and fewer hits/clicks) to compete in a more efficient market?

In the end it is the cost to purchase equation that matters and as we have seen above on that basis online advertising is no more efficient than traditional mass media advertising.

So even if the effective CTR rate for search fell from 0.91% to around 0.6% would it make any difference to the market?

Advertising and Direct Marketing Response rates

The answer to that, at least for the experienced direct marketing practitioner, is probably not. At the end of the day you measure direct marketing program by conversions to purchase. However if you are just an SME advertiser then you are probably happy just counting impressions and ad responses. So you may be thinking the ad campaigns working because at least you are getting noticed.

This suggests that perhaps some of the growth in online advertising has come from the myth that online advertising is a more responsive platform than traditional mass media channels and if that is the case then one can't help but feel that the traffic generated by the click fraud industry has played some part, however insignificant, in helping to create that illusion.

So one final chart to try to explain the potential impact of click fraud on the web economy.

The chart below maps the trends across the major advertising channels in the USA over the past 15 years. Today the web advertising industry is celebrating because it is bigger than the newspapers, radio, magazine, cable TV and the directories industries. But if we factor in the industry estimates of a 35% click fraud rate then we discover the "legitimate" internet advertising may be only about the same size as radio.

What's more if we take Google's 7 years spectacular growth out of the equation we now discover that the rest of the "legitimate" web advertising industry is potentially the smallest player on the block.

What is equally apparent is, even before we factor in any click fraud and as we have seen before, the web advertising market just isn't growing fast enough to accommodate the wholesale decline across the print sector. The question then needs to be asked is just how much is click fraud a contributing factor in this growing gap in lost advertising revenue as the print media struggles to migrate its business model online?

Sources:

Here's why Gamefication = Garbage

noreply@blogger.com (MobCon) — Thu, 22 Mar 2012 23:59:00 +0000

If you had walked into a room full of business executives 20 years ago and said the future of brand advertising will be about family photo albums and a scrap booking then you would have been laughed out of the room.

Today people get paid good money to do this kind of thing for a living. They walk into rooms. Big rooms full of highly paid business executives and tell them that, if they hadn't noticed yet. The future of business is here... and it's all about getting yourself into the family photo album and the online scrapbook.

Of course we call them social media and they have global brand names like Facebook and PinInterest. But they are what they are. Online photo albums and scrapbooks. Public places where people play and interact with digital media.

The bottom line? The takeaway? The Competitive Edge you are missing out on?

If you are in business today you can't afford not to be in the game.

But is this true?

You see the whole Social Network story is based on the simplistic idea that the future of marketing is about target marketing. Or what we have now come to describe as contextual marketing.

The more I know about you. The more accurately I can target you with goods and services that will meet your needs and expectations.

So the theory drives a business model that focuses on harvesting audiences by creating free, user friendly activities that allow the vendor to measure relationships.

Not only relationships with other people but also relationships with activities and things.

To build these vast self interest networks. The vendors of these online scrapbooks and photo albums have been smart enough to leverage the dynamics of gameification to accelerate the process.

The problem of course is gameification improves your growth prospects. But it also significantly undermines the value of data generated by the game platform.

Take for example influence. Influence as measured by the number of friends or followers or likes or even links. Once influence becomes an accelerant in the gameification process for building a platform then the value of the influence data being generated by the platform falls rapidly to Junk or Garbage status. Why? simply because, prior to the rules of the game being publicised, these relationships did not matter. Now they do. Everyone becomes actively involved in building connections with people and things they had no prior interest in simply to conform to the rules of the game.

Take for example LinkedIn, Twitter or Facebook. 10, 50 and even 100 contacts or friends = a loser when the average player has 135 connections. 500 = an above average player. 1000 = a real player. 1 Million = a winner. And so the game goes. No matter what the game. The players learn the rules. Understand the objective and game the system to their advantage. that is the nature of game play.

The problem is each new game connection. Each new virtual connection = a Garbage relationship being recorded and tracked by the database. Inevitably as the process of gameification accelerates across the platform the database trends towards garbage and ultimately if the continuum stretches out long enough chaos. Of course it doesn't get to that stage simply because the players become bored and move on to the next game.

We know this to be true simply because of the experiments we have run here on Excapite. We have discovered that Twitter players with significant influence (i.e. 10,000+ followers) translates into 10, 20 maybe 50 page hits tops. Why? because the 10,000+ relationships they have accumulated on the platform are just a game token. Database garbage. Junk Analytics. Noise on the radar.

And this ultimately is the root problem with the mining of the Social Graph business model. The methods by which you choose to build your social graph ultimately impact on the quality of the data you collect. When you gameify you ultimately trade off quality for quantity. But the paradox is if you don't gamify then your growth is so week your platform dies from lack of connections. The absence of the network effect.

This then is ultimately what I see to be the fundamental weakness of the network effect. Growth through gamification = growth in garbage data.

So Gamification fuels the Network Effect which fuels the collection of Big Data which = the Complex Analysis of Garbage Data

Or more simply

Gamification = Network Effect = Big Data = Garbage

or what one could best describe as problems one normally associates with an Enterprise Data Warehouse writ large on a global scale. i.e. Garbage In = Garbage Out.

Again this points back to my simple message our ideas about applying network theory to this challenge are fundamentally wrong. This is a complex adaptive system. You change the shape of it simply by changing the rules not counting the connections.

What are we writing about today? Find out at Tymbals

Revisting the Law of Plentitude 15 years on

noreply@blogger.com (MobCon) — Mon, 27 Feb 2012 07:16:00 +0000

So can we use the New Rules for the New Economy as the basis of a proforma template to organise our thoughts into something more concise and readable? Something fresh and original like the 12 much newer new rules of the network economy?

Perhaps not but I think it is worth revisiting rule number 2 - The Law of Plenitude or the idea that on the network more gives more - before we move on.

Curious things happen when you connect all to all. Mathematicians have proven that the sum of a network increases as the square of the number of members. In other words, as the number of nodes in a network increases arithmetically, the value of the network increases exponentially. Adding a few more members can dramatically increase the value for all members.

The benefits of the Law of Plentitude are self evident if we map the world wide growth in the number Internet Subscribers against the growth in global online advertising revenues between 1995 and 2009.

Even if you factor in the growth in click fraud (See the Red Line for the estimate of Ad Revenue Growth Minus Click Fraud) the economics of the network effect are there for all to see. The growth in revenues has been far greater than the growth in subscriber numbers.

Put very simply the revenue creating capacity of the network is significantly more than the sum of its parts. More subscribers = More Advertising Revenues Per Subscriber.

Of course the growth isn't quite so impressive when you convert it into percentage terms. You see the growth in online advertising is only growing 3 times faster than the number of subscribers.

... and the problems really set in once you factor in the growth in the number of web sites. You see the benefits of the network effect may be self evident, if somewhat marginal, on the customer side of the equation. But not on the supply side of the equation. i.e. Where the money is made - at least in content circles.

You see the growth in web sites over the same period is 10x that of the advertising revenues supporting the network. 32x the number of subscribers. Plus the growth is exponential. 235 Million websites in 2009 became 500 Million in 2011. Supply is outstripping demand. The network is flooded with unlimited inventory.

This of course is the story that we uncovered back in November 2010 when we undertook an indepth analysis of Mary Meeker's Web 2.0 online advertising data. (e.g. Web Economics 101 or why the Long Tail of the web is free and Why the online vs offline ad spend is still out of whack) Here we discovered that, based on 2009 advertising revenues, the web economy could only support about 20,000 media web sites (Think So just how many web sites can the advertising industry support?).

So the real story of the economics of the Network Effect isn't about a network of plentitude where increasing the number of nodes in a network increases the value of the network increases exponentially. A network where adding a few more members can dramatically increase the value for all members.

The real story of the economics of the Network Effect is about fragmentation of wealth.

A network economy where more means less. A lot less. For the majority of members on the network. Particularly once the economics of the Zipf curve are factored in.

You see the great tragedy of the network effect is the value of the network economy is worth significantly less than the sum of fits parts. Not more as the theory predicts.

In the end though what interests me most about the Law of Plentitude isn't the immediate economic impact of a network awash with unlimited inventory. It is the long term impact the Law of Plentitude is having on innovation.

You see on the network of plenty, the network of infinite abundance, the only talent that thrives is the talent for discovery or replication. The cost of origination is simply just too high.

This then is the Law of Plentitude 15 years on...

Curious things happen when you connect all to all... and it is not what the mathematical models predicted.

What are we writing about today? Find out at Tymbals

Russia's Winter of Discontent, the Arab Spring and Facebook

noreply@blogger.com (MobCon) — Sat, 10 Dec 2011 03:12:00 +0000

I was just reading Forbes's article on how Twitter and Facebook are fuelling Anti-Putin protests in Russia and I couldn't help but wonder how accurate was this assessment? Particularly when we take into account the relatively low levels of adoption of both the Internet and Facebook in Russia today.

Just how influential could Facebook and Twitter be in this discussion when a. the majority of Russians don't have access to the Internet and b. the majority of those that do are connected to other social networks (e.g. VKontakte)?

The story also makes reference to how earler this year the Arab Spring relied heavily on Twitter, Facebook and other social media sites to spread revolutions across Africa and the Middle East.

This of course reinforces the underlying subtext that Social Media - Twitter and Facebook especially - is empowering the "wisdom of the crowds" the world over to embrace democracy and (hopefully) make the world a significantly better place to live in.

Within this context the idea (i.e. meme) that Facebook and Twitter are global change agents becomes both self evident and self reinforcing. It has already happen there and now it is happen here... So it is probably worth while exploring the question: How much of this is urban myth and how much is this a reality?

For example, some reports suggest that Facebook and Twitter were responsible or at least key to Arab Spring uprisings. While others suggest that Facebook and Twitter were just tools.

Anyway I thought I would just take a quick look at the scale of reach of the Internet and Facebook in some of these countries to see what the data may reveal about the probability of this universal story of a "Revolution by Social Media" being true.

Here is a data sample of countries from the African and Middle Eastern Region. Again China and the USA are in the mix to fix the scale of the chart so that you can appreciate the relative size of these Internet economies.

Once again a cursory glance at the chart suggests that the below levels of adoption of both the Internet and Facebook suggest that wide scale disruption organised via social media is unlikely - at least on a Many:Many basis.

If social media was used then it would have been as a communications tool to connect the social influencers who in turn communicated directly with their social network via word of mouth or perhaps, given the much high adoption rates for mobile vs. Internet across all these markets, Mobile Phone.

This suggests the role of Facebook and the other social media platforms was more of an ad-hoc "Just in Time" communications channel for the network of organisers than an underlying strategy for achieving social "ignition".

Again the commentators appear to be confusing Facebook, Twitter and the other social media platforms as a new form of broadcasting when all the evidence to date suggests they are not.

They are personalised communications (i.e. Nanocasting) channels whose DNA resides with SMS, Email and Database Marketing rather than mass communication channels like TV, Radio and Print.

[Updated 22/12/2011]
The New York Times has uncovered some some research into the Egyptian and Tunisian uprisings that suggests the bulk of the Social Media activity during the uprisings was undertaken by peripheral actors (e.g. Bloggers and Journalists). In these samples Activists on Tweeter represented just 12.4% of those actively engaged with the social network in relationto the Egyptian uprising. In Tunisa's case it was just 11.9%. These actors seeded 19% and 10% of the conversations conducted on Twitter but interestingly only 6.6% and 8% of these conversations were conducted between activists.

This suggests that Twitter acted more as an amplifier of ideas within the "Global SocioSphere" than as a "Just in time" communications tool for the activists.

Looking back even further the research stats released by Sysomos in January of this year suggest that the ratio of Tunisians to Tunisans with active Twitter Accounts was around 10000:1. Or, about the equivilent of a single grain in a handful of desert sand. This suggests that Twitter's role in the Arab Spring in Tunisia would be something akin to the Butterfly Effect.

What are we writing about today? Find out at Tymbals

Here's why Analog Dollars equals Digital Pennies

noreply@blogger.com (MobCon) — Tue, 11 Oct 2011 01:59:00 +0000

Of course my original take on why Analog Dollars = Digital Pennies for the online media industry is a very different take on the view outline in Matt Shanhan's post on The Faulty Comparison of “Analog Dollars” to “Digital Dimes”.

As you can see in this next October Archival Revival. The key to unlocking who makes the Digital Dollars in a hyper connected world is who owns the network and the devices connected to the network. Not the content.

The idea of exchanging analog dollars for digital pennies online is not a new concept. The phase was originally coined in 2008 by NBC Universal’s CEO Jeff Zucker. If you follow the link to Brad Dick’s Broadcast Engineering Blog you can watch a video clip one of the interviews in which he provides insight into the problems TV broadcasters face when trying to prepare a digital strategy. (See Spending analog dollars to get digital pennies).

The paradox for TV broadcasters is no different to that facing the newspaper industry.

The growth rate of Internet advertising is now three times that of television and twice that of cable. However for traditional media it has now become apparent that it isn’t going to be the opportunity they thought it was originally going to be.

How and why the traditional media managed to get the Internet so wrong has filled many a page – both online and in print.

Probably the most informed analysis on the Analog Dollars = Digital Pennies discussion can be found in Fred Wilson’s post Trading Analog Dollars For Digital Pennies and Andrew Chen’s From analog dollars to digital pennies: The crisis in traditional media.

Both writers provide deep insight into the problems facing the mass media in their efforts to monetize their “analogue” products online.

Fred deals with the fundamental change in the perception of time. While Andrew examines how the established media model of consolidation and vertical integration has failed on the Internet.

Both writers explore how the cost of entry into the media industry has been dramatically reduced by the introduction of digital technologies; and how this has democratised the medium. Something we first saw with the emergence of Desktop Publishing (i.e The Apple Mac, Photoshop and Quark Express changed the face of commercial and private publishing and printing in the late 1980’s and early 1990′s)

Fred’s position can be summarised as…

Analog and digital, it turns out, are polar opposites. Analog has physical costs which lead to scarcity driven business models. Digital has zero marginal cost (or near zero) which leads to ubiquity driven business models.

Meanwhile Andrew’s take is

… and any entrepreneur with a couple hundred grand might end up with a website bigger than anything the old-school media companies can put together

So is the “zero” cost of entry the really the biggest problem facing traditional media companies online? How about the collapse of cyclical time or the fragmentation of the value chain?

The answer is no. The real problem, as Andrew acknowledges in his post, is who owns (or should I say dominates) the value chain.

The point is, Disney and the many companies that would be considered its peers (Viacom, Fox, Sony, Vivendi, and the like) own the entire value chain from start to end in traditional media.

The problem for traditional media, online at least, is they don’t own the whole value chain. In fact they don’t even own a significant portion of it. Online their role in the value chain is simply that of the low value primary producer.

The reason why traditional media is exchanging analogue dollars for digital pennies online is not because of any structural revolution or technology break through. It is simply because they have ceded the pivotal role of distributor in the value chain to the Telcos.

Today it is the Telcos who own and operate the desktop and mobile internet’s equivalent of the expensive printing presses and broadcasting systems. If you can’t plug into the web you simply don’t exist (on the web at least).

That’s why today it is the Telco’s (e.g. AT&T, Vodafone, Telstra) and the mobile handset manufacturers (e.g Apple, RIM and Nokia) who are making the Digital Dollars while the News Corp, the New York Times and the other Newspaper Publishers, TV Broadcasters, Magazine Publishers, Radio Stations, Music Publishers, Book Publishers, Facebook, MySpace, YouTube, Twitter, the bloggers and yes even Google are left “scavenging” for Digital Pennies online.

The unresolved question of course is how did the media industry allow this happen? and what can they do to make sure it doesn't happen again as the world adopts mobile media?
Well, if we go back to the birth of the information superhighway, we discover that in the beginning three key industries entered into the MobCon convergence landscape seeking to dominate it.

Each industry held a unique key and a gateway to profitability.

Media had content (i.e. The Data)
IT had the applications, databases and the gadgets (i.e. The Nodes)
Telecoms had the pipes (i.e. The Network)

Without each contributing their magic key the promise of the world wide web (i.e. MobCon 1.0) evaporated.

Without content (media) or a web browser(I.T) the need for a monthly dialup or broadband subscription quickly disappeared.

The media could leverage its existing content and acquire more eyeballs. I.T. could sell media based software and gadgets. Telecoms could leverage media content to sell more bandwidth. The convergence landscape offered a high growth opportunity for all three players.

It appeared to be a win:win:win scenario for all players and if the convergence landscape had been kept as a Walled Garden (i.e. AOL’s original model) it probably would have been.

The problem was each industry mis-read where the real value was in their segment of the convergence landscape.

Telcos invested in bandwidth

Telcos, for example, chased bandwidth and invested heavily in new infrastructure. This massive over investment in infrastructure eventually led to a glut of bandwidth, the scramble to invest in high risk online start ups take leverage this excess bandwidth and the inevitable Dot com bust in 2000.

The real value in the convergence market for Telcos was not the network but owning the gateway to the network.

The gateway to the network is the toll gate to the network. As owner of the toll gate the Telcos could have become the transaction engine of the convergence value chain. Collecting all the revenues from the customers on the network and distributing it downstream to the media and IT vendors.

Why did this not happen? It’s very simple really. The telcos do not think like bankers. They think and act as telcos. They build and manage networks and their world outlook back then, as it still is today, is fatter pipes equals more revenues and more revenues equals more profit.

Media is bandwidth heavy so pumping media down the pipes was a great way to make more profits.

So charging customers for content makes little sense when the promise of unlimited free content will increase bandwidth usage a 1000 times.

The problem with this scenario is of course for Telcos to win Media must inevitably lose.

Fast forward from the birth of the information superhighway to the launch of the iPhone and the game was being apparently reset. The illusion was still in play that the telcos and the handset makers needed media content to help them sell mobile bandwidth and devices.

But did they? When I crunched the raw data and the financials back in mid-2007 with 6 months of the launch of the game changing iPhone the trend was already apparent that wireless broadband was going to be more important to the Telco's bottom line than mobile content.

Even with the arrival of the iPhone and then the App Store the game wasn't about to change. It was still going to be a case of Analog Dollars = Digital Pennies for the media industry.

This then raise the obvious question. Why didn't the media companies try to become telcos or at least invest in virtual mobile telcos (e.g Mobile Virtual Network Operators or MVNO)?

The reality is some tried to do this. But they soon discovered that the key to becoming a successful telco had little if anything to do with media content.

Indeed the quickest and biggest losers so far in the MVNO market (e.g Disney and ESPN) made this fundamental error of judgement. They thought that content was the hook to build a successful MNVO business. As Virgin proved they were wrong. What you need to succeed is great Customer Relationship Management (CRM). Get that right and the rest is relatively easy.

The primacy of CRM in the MVNO Business Model is the reason why the MVNO model is not the answer to the future of Newspaper or Web Portals.

Yahoo!, MSN, The New York Times and News Corp may have enormous online traffic but they do not have a relationship intimacy with their customers in the same way that a retailer, bank, hotel chain, rental car or airline may have.

I guess you could say they have followers rather than customers. Sadly,the Disney and ESPN experience proves that these online followers do not easily translate into profitable mobile phone customers.

So in the end, if securing the distribution network was the key to media profiting from the internet and mobile, why did the market leaders lose so much money implementing this strategy?

There was nothing wrong with the strategic objective. Owning the distribution network is essential if you want to make Digital Dollars from the web and mobile. If newspapers and magazines are to move up from being the bottom feeders of the online and mobile value chains they must acquire ownership of both the distribution platform and the distribution network.

Hindsight has taught all of us that the real challenge the media industry faces isn’t technological. It isn’t even strategic. The real challenge is cultural.

The real problem for media is traffic doesn’t equal customers.

Media companies don’t have customers they have traffic and they will not be able to profit from operating the distribution network until they learn how to turn traffic into customers.

This is the same strategic challenge any online media company faces today. They all need to make the transition from a product driven business model to a service driven business model. This then isn’t about strategy it’s about culture.

Today Media companies don’t need Internet, iPad, iPhone, Google or Mobile strategies. They need something far more fundamental. They need relationship strategies. More accurately, they need business strategies that revolve around customer relationships.

The Traffic =! Customers equation cuts both ways. The strategic objective in a digital world is Traffic = Customers.

Old media was about traffic. New Media is about relationships. That’s why old media values and strategies just don’t cut it online or on the mobile.

If newspapers and magazines do die it will be because their collective culture did not allow it to evolve from products to services. From traffic to customers.

The strategy is simple. The barrier for the incumbents is cultural. Too bad culture eats strategy for lunch.

Why do the smartest people operate the dumbest businesses?

noreply@blogger.com (MobCon) — Fri, 07 Oct 2011 21:51:00 +0000

This time last week Tomi Ahonen was busy posting his memoirs as the world's leading "Mr Mobile Consultant Dude" (See Ten Years of TomiAhonen Consulting. Wow what a ride! Thank you to my customers and readers).

During the week a number of readers have asked me why I don't do what Tomi does. Write a book and hit the road. Do the radio, TV and lecture tours.

The simple answer is I feel far more comfortable these days playing the role of the "Fool on the Hill" than the "Goat on the Road" ;-)

These days I find I am more in the business of listening than talking. When my customers are talking I know I can find opportunities. If I do all the talking I may as well be looking in the mirror.

But I can understand the appeal of being the world's most celebrated mobile road warrior and so for all of you out there who aspire to join Tomi or envy him his "James Bond" lifestyle here is something I have dug up out of the archives (Circa 2000)...

I think everyone at sometime has probably dreamed about running their own business. The freedom to do it better by doing it your way.

But beware your dream doesn’t become a nightmare. The price of freedom is high.

99% of all start-ups fail within 10 years.

So ask yourself this question: How can I survive the odds?

The self-employed professional tends to value freedom and independence. For these people industry respect and quality are equal, if not more important, drivers than money.

That’s why the successfully self-employed are always very busy people.

They think in terms: My expertise, My time, My money

They are constantly threatened by others: The weak let them down. The strong are unwelcome competition.

The value driver is to always be “Be Better”.

The problem is they do not have the resources to deliver on the promise in a truly commercial context. They always want to be “Be Better” and yet they simultaneously suffer from the flexibility and the limitation of the “power of one”.

The daily challenge they face is finding work, then delivering it on time and in fill and then find the time to make sure the clients pay. Depending on their cycle their business capability is either higher than their sales or they are swamped with work. This why business continuity is a real challenge for the self-employed. They sit at the bottom of the industry food chain.

These are highly intelligent people operating a very dumb business model. The power of one.

In contrast successful business people are busy building networks.

They think in terms of where is my next job coming from and who is available to do the work?
They also recognise that all business is brokerage.

“It’s not what I can buy it for that counts, it’s what I can sell it for!”

They think in terms of Other people’s expertise, Other people’s time, Other people’s money.

They may not have all the skills to deliver on the promise but they know that what they don’t have they can find. All they are really interested in is getting paid and getting a referral out of the client.
They are constantly strengthened by others:

The weak present an opportunity to make a profit.
The strong are invited to strengthen the business.

As you can see successful business people think differently to the professional and the self-employed. That’s why, in the end, one owns the business and the other just works for it.

Don’t worry there is nothing to be ashamed about if you think and act like a professional. After all that is how you have been conditioned to think. Not only at School and University but also in the workplace.

However, if you are thinking about going into business and you think like a professional then take my advice: Don’t. Stay where you are. The time to leave and set up shop is when you are thinking like a business person. Until then enjoy the fruits of your career ;-)

A new Facebook experience needs a new Facebook metric

noreply@blogger.com (MobCon) — Mon, 26 Sep 2011 01:29:00 +0000

We all know the Facebook success story is based on a massive growth in membership and engagement over the past 5 years.

That's why the most popular chart in any So.Me presentation is this one. The growth in Facebook members since 2007.

The other chart is this one. The increase in the level of engagement with Facebook in the US. Expressed here as the average minutes per month per unique.

Finally we have the growth in Facebook Revenues.

It's a win, win, win scenario.

The bigger the network, the more rewarding the user experience which all ads up to bigger revenues.

But as we have seen before at the granular level the metrics don't always tell the same story. For example. Facebook's ARPUs were actually falling prior to the introduction of Facebook Credits.

Indeed much of Facebook's recent growth can attributed to the growth in Social Gaming as opposed to the growth in Social Advertising and Marketing.

Anyway the introduction of the new Facebook inspired me to seek out a new Facebook metric to assist in the understanding of how increasing the level engagement can impact the bottom line of the social network. (Plus the fact everybody now appears to be using ARPU as a metric).

Here then is a new metric: The Average Revenue per Minute of User Engagement. Specifically designed to measure just how successful the changes that you make to your UX really are to your bottom line.

Now I haven't mapped the changes Facebook has made to its UX over the past 5 years but as you can see Facebook still has a little bit of work to do to match the experience it was delivering back in 2007. So it will be interesting to see if the Timeline and the Entertainment hub deliver the "bankable" experience Facebook is no doubt hoping to deliver to its members.

So having established a new metric for measuring the relative performance of the world's largest social network what insights does it reveal about the economics of Facebook in relation to other media properties?

Sadly not really anything we didn't already know.

Previously, when we first explored just how hard it was to monetize a Social Networks, we established that Social Networks were among the lowest ARPU's of all the web business models.

Now we discover when we apply the metric for the Average Revenue per Minute of Engagement Served to each Unique across other popular media types that Social Media is once again the poorest performing business model.

Should we be surprised? Probably not. But it does once again highlight the enormous challenges facing anyone trying to monetize a Social Network.

Just take Twitter for example. We all know the Twitter story in 2011. Traffic is up, Time is up, Revenues are up, ARPUs are up and so is the market valuation. So I won't trouble you with any charts or infographics. You can find them elsewhere.

Now Twitter hasn't been making money for very long and so it is early days to go looking for trend lines but as you can see by the chart below there is a correlation between the ARPMOE of the two Social Networks that proves my original hypothesis that the So.Me deals in fractions while the rest of the media world deals in Dollars and Cents.

Needless to say it is worth finishing off this series on the value of measuring the Average Revenue Per Minute of User Engagement by comparing the So.Me economy to the old Dot.Com Portal and the Google Search model.

Depending on your outlook for the So.Me economy you will either see this as an opportunity (i.e. Just think what Facebook could be worth if it can achieve Yahoo!'s ARPMOE) or a validation of the Google model.

Finally I couldn't help but wonder what the long term trend lines in the Average Revenue Per Minute Of Engagement may reveal about Facebook's chances of improving it's ARPMOE over the next 5 to 10 years.

So what I have done is calculated Yahoo!'s ARPMOE circa 2000 and Google's ARPMOE circa 2005 prior to the purchase of YouTube and the strategic focus on Google the social media portal rather than Google the search engine.

Two things clearly emerge from the chart. Firstly Yahoo! has improved its ARPMOE by about 30% over the past decade but if we apply the same growth potential to Facebook or Twitter it does little to substantiate the current market valuations.

Secondly the trend line for Google's ARPMOE suggests the stickier that Google tries to be (i.e. by bundling more and more social media properties into its offering) the lower is its ARPMOE. By trying to become more like the rest of the web Google is somewhat paradoxically becoming more inefficient in its ability to generate revenue against the amount of time people spend using its services.

This again suggests that, contrary to popular belief in Silicon Valley, the recipe for success on the network isn't about trying to be sticky but focusing all your energies on being unsticky.

[Update 5-5-2012] Facebook vs. The Superbowl ARPMOE

After reading those 2011 ARPU figures on Techcrunch for Facebook I couldn't help but run a quick comparative model between the ARPMOE performance of Facebook vs. Superbowl.

The top line figures are Facebook has the bigger US audience with and estimated 160 Million users vs the 113 who watched the Superbowl this year. The average amount of time spent on Facebook is estimated at 16 minutes per day. While the time it takes to watch a game of American Football on TV is about three and half hours. Or a little under the average amount of time the average American spends watching TV each day.

The ARPU for Facebook was $9.51. The Superbowl broadcast $2.21.

All of which means the average revenue per minute of user engagement [ARPMOE] on Facebook is around 1/5th that of the Superbowl (i.e. $0.0016 vs. $0.009) and half that of the ARPMOE for all US TV (i.e. $0.003).

This suggests there is room for growth in Facebook's advertising revenues based on existing user engagement patterns but should also be noted that the CTRs for Facebook ads continue to under perform against the online industry average.

So what is the difference between Activity Based Costing and Management?

noreply@blogger.com (MobCon) — Thu, 04 Aug 2011 01:31:00 +0000

[Originally published Nov 2003]

Activity Based Costing is a management tool that records the historical consumption of resources to produce products. It is an accrual consumption system rather than an accrual compliant system. It provides a more intuitive understanding of the underlying costs and true profitability of the individual products and services offered by the business.

The assumption being as the cost of products and services (or outputs) are made visible, "what if" analysis or scenario modeling to be conducted to determine what resources are required if operations are scaled back or expanded.

Predictive modeling, process re-engineering and transfer pricing decisions can also be initiated. This means the potential of Activity Based Costing to assist management at all decision-making levels is therefore very powerful.

In Activity Based Costing the resources that are used to do an activity are mapped to the activity to create cost objects. It is these cost objects that are evaluated by the business to determine what is the true cost of delivering each individual product and service.

Properly implemented an Activity Based Costing System will be able to deliver answers to management on operational questions like:

a) what takes up the time of production line staff?
b) are the right amount of resources are in place?
c) what factors drive particular types of work or work volume?
d) how are the different products, customers and suppliers influence these factors?
e) is it costing more or less than it should to manufacture the product or deliver the service?
f) How can we go about doing things more efficiently? and
g) Should we do more or less or even stop doing what we have been doing?

When planning an Activity Based Costing Sytem you should be aware that the system will require regular access to high quality operational data from the corporation's HRM, Accounting, ERP, Sales, Transactional and Asset systems. This means although it can be difficult to design the ABC system to meet the business's requirements it is still far easier to implement the initial Activity Based Costing system than it is to sustain it. Any changes to the source systems will naturally impact on the downstream data model of the system. The system will also evolve as the business re-engineers itself to take advantage of the strategic planning information provided by the system.

Experience will tell you to keep the initial system very simple and allow it evolve as the business embraces both the model and the benefits of the information generated by the system.

So what is the difference between ABM and ABC?

Activity Based Management (ABM) and Activity Based Costing(ABC) are inter-related methodologies. ABC provides the strategic information you need to make informed management decisions. ABM is the real time monitoring of the tactical activities you undertake to deliver those strategic decisions.

This is why ABM is displayed as an extension of the ABC model in the diagram below. The horizontal axis of the Turney Cross# represents the business process view. The vertical dimension (Resources, Activities and Cost Objects) represents Activity Based Costing (ABC). When the second dimension is added (made up of Cost Drivers and Performance Measurement), the result is Activity Based Management.

Activities are what organisations do. Activities generate an organisation’s products and services. To make changes, one must change what people or equipment does. Therefore, changes must ultimately be made to activities. Activities are the fundamental building blocks of all organisations and generally remain stable over time. However, the ‘owners’ of the activities may change from time to time (for example, as a result of restructuring.

In ABM an activity has the following characteristics:

it is based on an activity type;
it consumes resources to produce outputs;
it describes the way an enterprise employs time and resources to achieve business objectives;
it forms part of a chain, or business process;
it is a collection of tasks;
it will have a function and sub function associated with it; and
it is performed by an organisational unit.

As with all Executive Information and Management Information strategies ABC/M is fundamentally about changing the way you do business so you can take full advantage of the knowledge currently stored within the business. This means ABC/M projects follow the 80/20 technology project rule. Where by the development of the information technology system represents only 20% of the total effort required to successfully implement the strategy.

Hands on project experience will teach you that an ABC/M strategy is based undertaken as an evolutionary process that begins with a rapidly developed pilot system and grows with the business wide acceptance of the methodology and the results it delivers back to the business. This approach is a common theme when reviewing successful Business Intelligence project case studies from around the globe.

# Turney, P. (1992) Common Cents – The ABC Performance Breakthrough