From a stereotypical “dot com” baby in 1998, to the rapidly maturing teenager of 2010. Ian charted the way in which the business’s strategy, structure and ownership had evolved as it matured from something with the turnover of a small local pub, to a multi-billion enterprise. Covering the problems of merging acquired companies, the need to scale costs, and the change from a public (stock market) ownership to private equity.

This article is based on Ian’s talk. It concludes with some personal analysis of the future, with particular reference to my favorite topic, public transportation information… On this page:

• A Tale of 2 Founders
• Acquisitionial Chaos
• The Squeeze
• Going Private
• Beyond Cost Reduction
• Is it Over Already?

A Tale of 2 Founders

Lastminute.com was founded by 2 people:

• Brent Hoberman – characterised as a visionary, highly intelligent, able to process multiple threads of thought at once.
• Martha Lane-Fox – characterised as charismatic, able to convince other people to do things, able to understand consumer needs.

The original idea was to fill empty hotel rooms and restaurant tables, by reselling them cheap at the, erm, last minute. It evolved to resell “everything a young professional wants to do” (including travel, theatre tickets, etc). But an innovative idea was only part of the reason for success:

• They didn’t “burn money” like other internet startups of the period, such as the infamous boo.com.
• They used their media profile (“the poster children” of the internet age) as a negotiating position with much larger businesses, such as advertising agencies. In the first year lastminute.com had the sales turnover of “a poor pub”, yet was routinely featured in national newspapers and other media.
• They completed an IPO (selling the business to the public via the stock market) the day before the “dot-com crash“. At the, erm, last minute…

Is timing everything?

The dot-com crash inverted the way the world saw Brent and Martha: Suddenly everyone seemed to hate lastminute.com. Especially that part of the world that had invested money in a technology-related business, and had just lost most of it. Brent and Martha’s reaction to their “first storm” was to seek help, by establishing a highly experienced board of non-executive directors. This board was hugely more experienced than would be normal for such a (then) small company. Ian attributes Martha’s charisma as key to convincing these people to join lastminute.com.

Acquisitionial Chaos

The IPO had gifted lastminute.com with a lot of cash, but also meant they were responsible for spending it: They had to use the money to expand, and justify their actions to their shareholders. Shareholders who often didn’t understand the business they owned. Rather than trying to create new sales by spending on marketing (which “the stock market” often regards as inappropriate), lastminute.com grew through acquisition. 15 acquisitions, to be precise. Over just 3 years.

The acquired companies were typically similar businesses to lastminute.com, primarily in Europe and Oceania. Lastminute.com did not initially expand into the United States, even though there would have been advantages: Little (at that time) competition, single legal/currency system, and lower “cultural complexity”. Ian pragmatically suggested that lastminute.com simply did not have “the people” (expertise) to successfully enter the US market at that time.

By 2003, the combination of 15 acquisitions and strong “organic” growth (40-80% increase in customers each year) had raised the value of total sales to around £300 million. Big number? It is easy to be blinded. The actual earnings from sales will be far lower, because lastminute.com is a primarily reseller. And very often reselling cheap. Margins on some products, such as airline tickets, may be very low indeed (Ian used the US grocery phrase “the milk in the store” – one has to package them with a sale of something else to profit). However, lastminute.com was starting to live up to the pre-2000 hype, and demonstrate that the underlying business model worked.

Unfortunately, all those acquisitions came with a new set of problems:

• Organisational complexity and chaos: 20 different financial ledgers and brands. 27 different “mid-office” (administrative) systems. 2,500 employees, most of whom were completely disconnected from the rest of the organization.
• High fixed costs: Each acquired business continued to use its original systems. While lastminute.com was bigger, it had none of the economies of scale associated with a larger business.
• Original leadership team unable to cope: Lastminute.com was still being run by the original core staff. While Ian clearly had a lot of respect to Brent, Martha and the non-executive directors, he characterised many of the others as “personalities” or worse. Meanwhile the founders of acquired businesses were often frustrated by having become a (largely ignored) regional office of a larger organisation, and their frustration was influencing the morale of their employees.

“Awful, but Interesting Awful”
One might wonder why Ian took the job in 2003? At Nokia he had previously been responsible for one of the first 3G networks (which initially wasn’t entirely successful), and he wasn’t keen on roles that may follow with Nokia. It is clear that the main attraction of lastminute.com was the combination of its founders and non-executive directors. But I suspect he wouldn’t want another job that involved merging so many different companies together…

The Squeeze

As business sectors/markets mature they tend to become “scale plays”: Competition means it becomes ever harder to make a profit, and reducing the cost of underlying systems (fixed costs) becomes more critical to success. Alternatively, they could differentiate (for example, focus on a niche), but differentiation can be hard to maintain at scale. I suspect that shareholders (who often purchased with the expectation of “instant riches”) would not accept a niche role for lastminute.com.

Ian McCaig set about constructing a scale-based business:

• Reducing fixed costs, and focusing on variable costs.
• Explaining the strategy to acquired companies.
• Simplifying organisational complexity, including “firing people that were hurting the business”.

Beyond that, “it’s not so much about strategy, more about how you manage trade-offs”. The end result of is clear: Between 2003 and 2010 lastminute.com grew the value of sales about 5-fold (Ian was reluctant to disclose current sale turnover, stating a vague “1-2 billion”), yet now only has 1,000 employees – less than half of 2003’s headcount.

The Founder Problem
“There are only 2 things to do with a founder-entrepreneur in an acquired business: Given them a bigger job, or fire them.” Founders have a parental relationship to their businesses. Criticism of their business is like criticism of “their child”. And without control of their child, founders tend not to enjoy their work. The brutal reality is that often founders are not suited to operating a maturing business.

Martha Lane-Fox moved on, but Brent remained to make key decisions, and continue to innovate the product. Even after 2003, a lot of ideas continued to come from Brent. Indeed, the company’s culture included the term “to be Brented” – to have one’s head filled with Brent Hoberman’s ideas. Ian’s role was to filter out the good ideas that could (realistically) be implemented.

But meanwhile the company’s structure and culture was changing. It had to. And not just because of the focus on cost reduction, rather than wild early-years innovation. Founder-driven decision-making doesn’t scale, and it doesn’t always understand some of the more mundane problems, as this exchange reveals: Brent doesn’t think he needs to explain his strategy to everyone else because “it’s obvious.” “Well, not to others…” “Well can’t we just hire brighter people?” “But then we’d never get anything done!”

Ian gradually removed the “decisions Brent wasn’t interested in” from Brent, while reversing “single person innovation” in the wider company. The resulting structure is focused on people, rather than process. A “low hierarchy” structure, with individual accountability for the execution of projects. As the market has become more competitive, and there is “less water to swim in”, the creative/implementation process has become constrained: An initial timed debate, Ian’s synopsis agreed upon, followed by a decision to execute. And after that decision, execution occurs without further debate.

Going Private

By 2005 the market had “grown up”. Large, well-funded competitors were appearing, while the free marketing of the early years had gone. As a lone (if fairly large) company, lastminute.com was becoming vulnerable. Ian considered the best chance of success was to sell lastminute.com to a larger parent holding company (Travelocity/Sabre), who both understood the market/business model, and had experience of removing complexity from the business. Growing regulation in the United States (such as the Sarbanes-Oxley Act) was a particular issue. For example, between 1998 and 2005 lastminute.com had had 13 different Chief Technology Officers – it can’t have been the easiest company to document.

In 2006 Brent Hoberman left lastminute.com.

Sabre Holdings was de-listed in 2007, ownership transferring to private equity (Silver Lake Partners/Texas Pacific Group).

As a PLC, lastminute.com had to make (sometimes “hellish”) quarterly reports to shareholders, who often didn’t understand the business model, but needed to know the details anyway.

In contrast, the only thing Ian’s private equity masters care about is the money. This stark reality has benefits, because the relationship between operator and owner is far more transactional: Make a proposal supported by “robust numbers”, and you’ll probably get the cash to implement it. Deliver what you say you will, and you’ll get more money. Just make sure you deliver…

In-Sourcing or Out-Sourcing?
Lastminute.com has an intriguing business model because it can both act as a merchant (for example, when selling its own package deal) and as an agent (for example, when selling a 3rd-party package or service). In this environment it would be relatively easy to out-source almost everything, and leaving lastminute.com itself as little more than a brand and underlying technology. Simple, transactional processes, such as finance, are out-sourced. However the more complex the process, the more likely it is to be kept in-house. Likewise, the “moment of truth” (the actual sale) is in-sourced (presumably to stop a 3rd party contractor simply walking away with their customers).

Beyond Cost Reduction

These final sections are primary based on my own analysis.

Currently lastminute.com is doing well, in spite of the fact that 2009 saw some of the toughest trading conditions in recent times. Especially for travel and leisure businesses, who tend to rely on disposable income – the types of purchases people stop making during economic recessions:

• Party this is because lastminute.com now have very strong control over costs.
• Partly because of increased demand for selling cheap, unsold inventory.
• Possibly (in my view) also because their (private equity) funding didn’t dry up as fast as some other businesses, so they were still able to exploit opportunities.

Ian was asked where he saw future growth coming from, since there is no further scope for cost reduction. The answer was mooted: He highlighted that their theatre-ticket business was London-centric, hinting of expansion to other cities. That their range of hotels in smaller cities is not always as good as competitors. That their market share for lifestyle products isn’t universally high across every European market. The only hint of strategic difference was a desire to make money out of web traffic (earn money by referring potential customers on to other websites). While their website visitors tend to be looking for something – so there is some money to be made here beyond simple advertising – this is also a well-established practice, from which untold riches are unlikely to emerge.

In short; more of the same please. And that’s probably inevitable given their more structured product development: It tends to kill the best innovation, because the best innovation happens hours/days/weeks into actually working on a problem, or from relentlessly iterating on designs in response to customers behavior. Of course such practices also tend to double the cost, a luxury lastminute.com no longer has.

I’m strangely reminded of the post-deregulation (1986 onwards) history of UK bus operating companies: A sudden rush of minibuses into a brave new (commercial) world (minibuses are “innovation” relative to that industry), followed by a land-grab of acquisitions, IPOs, and brutal cost-cutting. Then after 10 years, when there’s nothing left to buy/sell/cut, some bright spark utters the words – “I know what we need: more passengers!” – and their colleagues look confused, because anyone with innovative tendencies got culled in about 1988.

Lastminute.com isn’t quite so extreme. Random acts of innovation are far from dead. And they’re clearly capable of significant organic growth. Yet this part of the internet has grown up very fast indeed: Cost-centric, with the early stages of risk-aversion creeping in. Ian likened the 2010 lastminute.com to a teenager that’s currently deciding which university to attend. It will probably have an unimpressive academic career (only uprooting the odd tree in a drunken haze), before settling down with a wife and kids to a reliable, but largely uneventful career in accountancy. Or something.

Reliable until we realize that the economy has become so intangible that conventional accounting practices are worthless. Obviously.

Is it Over Already?

Everything matures. No large business lives at the bleeding edge of creativity forever. Right?

After the talk I had a familiar conversation. It takes different forms, but it generally involves someone with a technical or creative background who has a really great idea for using local public transport data. Mostly I send people away with a depressing dose of reality, roughly summarised as: If this data was freely available, I would have done that 10 years ago. If you are still curious, I’ve written about this topic in the past. The sheer weight of innovative people trying to do something with a dataset that appears to be public, but isn’t, might eventually force the situation. But right now, there is no easy option.

During the dot-com era, things were even worse: Local (non-rail) data was not always held in an electronic format, and if it was, not in a standard interchangeable format. Not that anyone was keen on distributing that data: There was minimal acceptance of the need to do anything more that publish copies of timetables on an operator’s website. And the nascent commercial attempts to work with this information (specifically the Great Britain Bus Timetable/Xephos) were inadvertently all but killed off by the Blairite edict that “government should provide” (that eventually gave us TransportDirect).

Unsurprisingly, the successful British travel websites from the dot-com era (lastminute.com, Cheapflights.co.uk) use a lot of transport data, none of it local.

There’s mostly no commission model for selling local transport journeys, so any commercial consumer internet use of this data would need to sell something else. Fortunately most people travel for a reason, and often they’ll spend a lot more money on “the reason” than they will travelling. I used to use the example of selling someone a theatre ticket or restaurant table on the back of an inquiry about how to get to, say, (London’s) Leicester Square. Curiously, that’s almost what lastminute.com already do, it merely requires the consumer interface to be inverted: Selling by location, rather than selling by desire. The underlying systems are very similar. I think you can see where this is heading.

Except nothing is so simple. If this information were to suddenly become available, it might be too risky for an established business to embrace. Equally, a new startup might struggle to gain sufficient economies of scale (technical, contracts, experience) to prosper. Perhaps local transport information will never be profitable, and will be the preserve of hobbyists and naive startups. Or maybe it will all morph into one huge contract and never become truly public data. The outcome is uncertain.

What’s made me stop and think is that the first wave of dot-com era startups seem to be just as mature (and potentially unresponsive) as the old-world businesses they originally poached customers from. What’s less clear is whether later waves of startups can thrive, since they don’t have a clear technological (internet vs non-internet) advantage over the first wave. What was possible in 1998, might never be as easy again.

Perhaps the timing with which data becomes available influences what information “wired consumers” ultimately build their lives around? And if so, perhaps we’ll eventually look back at a decade of closed public transport information provision, and judge it to be as damaging to wider local transport policy (and related businesses) as other, seemingly irrelevant “decisions” that actually had far-reaching consequences?

(An example is the late 1980s/early 1990s UK’s parental choice policy for schools. A decision that had nothing to do with transport, but yet resulted in longer, more diverse journeys, causing significantly more congested urban road networks at peak times.)

But then e-commerce is full of unexpected outcomes and paradoxes. Like the ability to order online and collect goods from your local store tripling online conversion rates. Or the most successful internet-based merchant becoming profitable by selling the 2 items the internet was most likely to make obsolete: Books and CDs.

• Cloud Computing
• Benefits
• Hyper-Virality
• Funding and Revenue Models
• Exploding Intangibles
• People
• The Caveat

Cloud Computing

Cloud computing is poorly defined. Offering computer resources as a service. Across a network. Probably the internet. I prefer Frank Gens’ description – a “grid-utility model”, that anyone can use. Grid computing is the use of lots of individual computers as one. Utility computing is paying for computing resources as you use them. So instead of investing in lots of private computing capacity, one simply buys computing resources from an internet-based cloud of (effectively infinite) computing resources, as they are needed.

Benefits

What’s the advantage?

Most private computing resources are woefully under-utilised. A typical buisness’s computers lie idle while employees are sleeping, and are probably only partly used when they are working. Most websites/services are hopelessly over-resourced to accomodate occasional peaks in traffic. And then promptly collapse when the peaks transpire to be bigger than anyone expected. Sharing huge clouds of computing resources between many users – each with their own peaks and troughs – logically allows the total current demand for computing resources to be met with far fewer computers. Utility charging provides the mechanism that translates “fewer computers” into “lower cost”.

But there’s far more to cloud computing than “making existing things more efficient”.

Hyper-Virality

I define hyper-virality as the near-instantaneous adoption of a service or product by consumers, distributed through a pyramid of social connections.

It is the theoretical end-point of many current social internet trends: That ideas, optimisations, and methods that enhance the efficiency or well-being of humanity, move around the world ever faster than before. The actions of a handful of dominant, successful, or somehow innovative “thought leaders” are copied by those they lead, who are in turn copied those they lead. Since all the people on the planet are connected to each other by a surprisingly small number of links (you know someone, who knows someone, who knows someone, who… not many more times to link to everyone), distributing something down to absolutely everyone is potentially easy.

In an extreme case, a service that really is, the greatest thing since sliced bread, could almost instantly be benefiting billions of people. Clearly this level of hyper-virality is theoretical. The whole notion of absolute hyper-virality may itself be nonsense: That any one idea can be so clearly the best thing to do, that almost everyone is immediately prepared to adopt it. But in a limited way, it is already happening:

The best current examples of the concept are probably Facebook applications. These are still far from hyper-viral, but do demonstrate basic behaviour: When a user starts using a service, that user automatically informs their “friends”. If the service is desirable, those friends start using it, and in turn, inform all their friends. It is already possible to grow from no users to millions of users in a matter of weeks.

With traditional computing services, it is very difficult to scale computing resources up fast enough to keep pace with that growth in demand. Even if you can find enough machines, you probably cannot organise and configure them. You would need to anticipate millions of users and plan sufficient computing resources beforehand. And probably anticipate the wrong number – either be left with a lot of unused, but costly resources, or be unable to meet demand.

Cloud computing solves this problem, because precisely the right amount of computer resources are available, with costs always in proportion to the amount of resources used.

(Well, actually it is not yet a complete panacea – some caveats are discussed later.)

In concept, this “agile deployment” of internet-based services to the cloud, enables true hyper-virality to occur, since it creates the ability to deliver the ultimate product or service to everyone, almost instantly. This becomes far more important if we assume that our economies are becoming highly intangible entities, which primarily function over communications/internet-type services (see a Socio-Economic Environment based on Nothing) – most economic activity will occur in this communications/internet-type environment. But even if we don’t accept that assumption, the cloud potentially changes how we finance internet-based services.

Funding and Revenue Models

In a hyper-viral environment conventional business plans need to be rethought. A wild guess at future usage won’t do: “Somewhere between 3 and 3 billion users, with growth occurring sometime between today and the next decade”. That’s already a real dilemma for anyone developing a mass-market internet-type application.

Instead one needs to answer the question: How do I rapidly scale to meet demand? At the very least covering marginal costs (operating costs).

Broadly, there are 2 solutions:

1. A revenue model that earns money in proportion to usage, with ultra-efficient cash-flow, that allows increasing revenue to immediately pay for increasing operating costs.
2. An ultra-efficient capital market, that will invest in proportion to growth in usage, pending the later establishment of revenue streams.

Both approaches differ from what we tend to do now: Convince someone to invest some money, and hope we’ve established enough growth/revenue/”something good” by the time we’ve burnt through the cash.

Some fairly basic revenue models fit the first method well, such as display advertising or subscription-only services. In others models revenue may lag behind growth slightly: Premium versions of services that don’t earn money until users have enjoyed a free trial, or methods that rely on first building user engagement or trust, such as micro-transactions.

There is a risk of bankruptcy due to slow cash-flow: If your advertising revenue is still written on a cheque, lost for weeks in the postal or banking systems, what do you pay the cloud computing bill with? Fortunately, both incoming revenue and outgoing costs tend to lag behind by about the same amount. Cloud computing tends to be billed after use, not before, so everything is delayed by the same arcane business payment practices. But there’s still an element of Russian Roulette to whether the credit or debit clears the system first.

Parts of the financial system have the potential to be ultra-efficient. For example, in minutes, stock markets can adjust to changes in relative demands for capital. Except that such markets are dealing in established businesses that investors have some understanding of. Even high-risk investors, such as venture capital or private equity, may be unable to respond fast enough to new hyper-viral investment opportunities.

Note that established organisations will face slightly different problems to new entrants. For example, a historic focus on capital expenditure and fixed budgets may require structural change to occur within the organisation.

Astute readers will note that I have only addressed funding after a product or service’s launch. Cloud computing and virality won’t make it any cheaper to actually develop that product/service to the point where it is ready to be used. I hope to return to the topic of iterative product development on the internet in a later article – I contend that less time should be spent trying to develop a “finished” product before launch, and instead design should gradually iterate improvements on a live, “permanent beta” product or service. A logical extension of agile development into the iterative specification of the product itself.

Exploding Intangibles

Corporate finance still seems to be biased towards physical assets. This is great for factories: You can add up the value of all the machinery, materials and stock – all the physical stuff – and discount it all year-to-year. But if the most expensive physical asset is the coffee machine, classic accountancy tends to struggle. Highly intangible companies are not new – plenty of businesses are built up around intangible assets, like brands or franchises. And methods have evolved to account for the value of these companies, even if the process is inherently less precise.

What’s not clear is whether a rapidly expanding, but totally intangible, business can gain access to any conventional forms of finance. Our hyper-viral, cloud-based internet business didn’t even exist last month, and (because of the hyper-virality of unknown potential competitors) might not exist next month. So what is additional investment secured against? The coffee machine? While it is easy to point towards the rise (and fall) of major technology startups that have grown to be stock market-listed within a few years, the ultimate hyper-viral business would want to make that leap almost instantly.

Can finance move as fast as hyper-viral businesses? Current practices suggest not. But that misunderstands the potential advantage in fast-paced hyper-virality: Everything can move faster, including the return on capital. Invest for a few months, instead of a few years. So perhaps the challenge shifts to creating “stuff” that better informs capital markets, which can then react appropriately to other sectors?

People

Does this work organisationally?

Is it naive to assume that one individual can ever develop a solution that can gain mass-appeal, without significant help? Just as at the start of the first internet bubble, many believed that “2 kids in a garage” were going to destroy established businesses. While small developers do sometimes come to dominate emerging markets, most historic business empires remain in tact. And if that help takes time to organise, won’t that human organisational factor limit the speed of virality, giving existing organisations significant advantages over lone individuals?

Perhaps there are just to many unanswered questions? Technology and capital is easy – people are far more complicated!

Curiously, if people both define the structure through which hyper-virality occurs, and are the reason why hyper-virality isn’t quite as fast as it might be, it will be people that naturally establish a happy equilibrium. It would be limited by people, not technology or capital.

The Caveat

A small caveat: Cloud computing cannot yet deliver all its promised potential.

For example, by consensus the cloud does not handle database-driven applications well, particularly where a lot of data is being written (presumably we need to radically re-think the way databases work). Techniques for scaling resources within the cloud, to meet rapidly changing computing demands, are still evolving. It is not yet as automated as it sounds. There are a plethora of concerns related to issues such as security (by consensus, more perception than actual problem), and standards (some commentators suggest inter-operability will be resolved through clever use of APIs, much as different database software were made to “talk” to each other).

Ownership and privacy is a potentially important, but poorly explored issue: Logically a handful of huge cloud computing providers could gain considerable control and influence over the creativity of individual developers (much as early-modern “publishers” historically came to dominate people that worked as printers).