Balancing Capex and Opex

Government has a cash problem. It simply doesn’t have enough cash allocated to running costs for IT. Projects that were traditionally funded out of capital are, in the cloud world, funded out of operating budgets. This is going to hurt.

For many years, IT projects have been funded by capex (capital expenditure). Whatever came out of the project – servers, software licences, code, automation tools etc – sat on the balance sheet and was depreciated over an agreed period. Usually, for software, it was thought to be too long a period, but given that many of our systems are still working 20, 30 or even 40 years after launch, and so long since depreciated to zero, we clearly under-estimated the longevity of code. Similarly, we probably over-estimated the life of laptops and mobile phones where 5-7 years depreciation is common, but they have quickly become replaceable after 2 or maybe 3 years.

With the move to cloud, the entire infrastructure base switch from capex to opex – that is, it’s funded out of day to day expenses and nothing is held on the balance sheet. Millions of pounds of servers (and all the switches, routers and other kit associated with them, as well as some software, where SaaS products are used) left the balance sheet.

Governments tend to be capital rich – there are few departments who complain about not having enough capex. Capex buys actual things – in IT terms, servers with flashing lights and spinning disks that can be looked at, making the spend tangible (hence the use of tangible and intangible assets for different kinds of IT assets).

This has created a challenge for some departments who want to spend their capital, but also want to move to the cloud. There was a similar challenge early in the cloud era when VAT was not recoverable, putting further pressure on strained opex budgets.

I’m seeing a change though, now, where even software development is run as an opex project – on the basis that the code is expected to turn over rapidly and be replaced through an iterative agile approach. If a project goes wrong – at a micro or macro level – there’s no write-off (which can be important to some). At the same time, treating everything as opex means that, in some cases, there’s a building soon to be legacy code base (becuase it’s a fallacy to think that this code is iterated and replaced regularly) that is going unmaintained, meaning that there’s ever more spaghetti code that isn’t being looked at or tweaked. Knowledge of that code base is held by a smaller and smaller set of people … and changes to it become more difficult as a result.

It’s a strange move – one that perhaps implies that there is less scrutiny over opex spend, or that the systems being built will not be in use for the long term and so don’t quite count as assets. But IT systems have a habit of surprising us and sticking around for far longer than expected – ask the developers, if you can find them, of the big systems that pay benefits, collect tax, monitor imports, check passports at border etc what the expected life of their system was when they built it and the answer will never (ever) be “oh, decades.”

That’s not to say that there isn’t a case for classifying some IT spend as opex. If you are a fast moving startup building products for a new market and striving to reach product/market fit, you might be crazy to think that it was worth having IT on the balance sheet. If you know that you are building a prototype and will throw it away in a few weeks or months, it would, again, be crazy to capitalise it. If you’re doing R&D work and you’re not sure what will come out of it, you might well classify it as opex initially and revisit later to see if assets were created and then re-classify it.

I suspect that the tensions between capex and opex in government still have more room to play out

The Trouble With … The Green Book

The Green Book is, for some, akin to a Bible.  It’s 118 pages of guidance on how to work through the costs of a project (not to mention 130 pages of guidance available on how to move from SBC to OBC to FBC – you get the ideas).

Across government, departmental approval bodies revere the Green Book with its detail on NPV, risk assessment, Monte Carlo models and benefits realisation.  The Green Book is for all projects covering whatever kind of policy outcomes are relevant – providing benefits to the right people, improving water quality, connecting communities and, of course, IT.

Despite all of the comprehensive guidance contained within it, the outcome of many projects suggests that risks aren’t properly evaluated, that costs are not fully calculated and that the outcomes expected don’t always occur.  Recent experience with ever inflating HS2 numbers demonstrate that only too clearly.  That said, trying to forecast costs many years out has never been easy (and the error bars increase with every year) – and in case you think government doesn’t think long term, the Green Book contains a table that shows how you would discount cost of cash out 500 years.

Some paragraphs in the Green Book show how far we have to change to make the move from traditional project delivery to an approach that is faster, lighter and more agile:

5.61 There is a demonstrated, systematic, tendency for project appraisers to be overly optimistic. This is a worldwide phenomenon that affects both the private and public sectors.Many project parameters are affected by optimism – appraisers tend to overstate benefits, and understate timings and costs, both capital and operational.

Optimistic? Really?

Or how about this:

6.23 Implementation plans should be sufficiently complete to enable decisions to be taken on whether or not to proceed. So that evaluations can be completed satisfactorily later on, it is important that during implementation, performance is tracked and measured, and data captured for later analysis

Perhaps the get out here is “sufficiently complete” – one man’s sufficient is another person’s hopelessly inadequate.  But entire business cases are routinely laid before approval bodies right across government that claim to have looked ahead 10 years and figured out what will happen year to year at a sufficiently detailed level to forecast costs and benefits, albeit with inevitable optimism. Only recently – perhaps the Olympics and, now, HS2 – has contingency been a visible and public part of budgets.  It will be interesting how the spending of it is reported and tracked

And then this:

6.33 Benefits realisation management is the identification of potential benefits, their planning, modelling and tracking, the assignment of responsibilities and authorities and their actual realisation. In many cases, benefits realisation management should be carried out as a duty separate from day to day project management.

Generally the people delivering the programme are not the ones who have to make it work on the ground and so achieve the cost savings that the approval body has been promised.  As it says above, “realising the benefits” is a separate duty from day to day project management.  That is, then, part of the problem – delivery being isolated from the business means decisions can be taken for the good of the programme that are not for the good of the business.

None of the above is intended to be critical of the Green Book – it was very much a product of its time and perhaps where contruction of vast architectural feats such as dams and, indeed, railways that go from South to North (and back again) are being planned, it still makes enormous sense.

With a desire that IT projects be agile, flexible, iterative and
responsive to the ever-evolving user need, the guidance looks
increasingly anachronistic.   If you’re not sure what functionality
you’re going to deliver when because you might replace A for B or drop C
altogether, how do you calculate either costs or benefit with any
reasonable confidence only a few months out?  The best you might be able
to do is calculate the likely cost of the team – but what if it needs
to grow suddenly to deliver an identified need?

The Green Book is doubtless being refreshed now by a combination of GDS, Cabinet Office and HMT but, and it’s a big but, convincing finance directors across government that 200 page business cases with all of the options mapped out and separately costed are a thing of the past will be challenging.  And interesting to watch.

“Minister, there are three options … the first two pretty much lead to nuclear war, the third will be explosive and there will be terrible consequences, but I think we will survive … I recommend the third option … do you concur?”

How Do Freelancers Really Spend Their Time?

There have been endless stories over the last few weeks about freelancers “dodging tax” through using limited companies.  Seth Godin published a lovely graph (via SwissMiss via APhotoEditor) and I thought, why not publish the same for a freelancer?  So here it is … how the Daily Mail thinks their time is spent and how I imagine it is probably spent:

Seth’s text goes like this:

“Part of the magic (and the risk) of the internet is that if you want to, you can use your access to tools, markets and media to go even further in the direction of the chart on the right. You can become your own booker, accountant, publicist and more. Hey, it’s free! You get to keep all the money!  Of course, it also means you don’t get to spend very much time at all doing what you set out to do in the first place, which is shoot pictures, or write music or coach or whatever it was.The other thing you can do is find the guts and resources to move even more to the left. Hire other people (at huge expense) to do all those things you certainly could do on your own, so you can actually do the work you were born to do. One thing to consider: finding and retaining a great salesperson is more difficult than you might think, since a great salesperson might very well contribute even more value than you do.”

I think the same could be written for any freelancer in business.

The Spending Challenge


HMT are going to be working hard over the next few weeks … they say they’re up to 18,000 suggestions for the Spending Challenge.

Whilst reluctant to suggest a Downing Street Petitions type site (much as I loved it), fearing too many votes for “Abolish tax”, “Pay Ministers Nothing” or “Scrap the Department of X” … But …

This kind of idea volume could be dealt with through the over-used crowd sourcing with the best couple of hundred ideas being worked up by whoever wants to work on them, aided by government insiders (who would know the data that would be needed), leading to ideas that were implementation-ready far sooner than they might otherwise be. And, perhaps, a ready and able gang of volunteers who could help manage and monitor them through the delivery process.

Anyway, I submitted that idea under the label of “not really a cost save …”

Have You Been Goldman’d – Part 2

The US Government’s pursuit of Goldman Sachs for allegedly mis-selling Collateralised Debt Obligations (or perhaps for taking both sides of a trade to the advantage of itself and just one of its clients). I wrote a little about the background to this a month ago. Goldman Sachs were certainly not first in to the Global Financial Crisis (shouldn’t that be written all in caps?) but they were almost certainly first out – via a little Federal money and a rejigging of their banking status, some money from Warren Buffet and the benefit of money on loan at a rate of virtually zero that could be invested at leverage ratios that, whilst not as high as in the go go years, were certainly greater than one.

Goldman were but one player in a long list as I said in the first post on this topic:

The chain of people involved in this crisis is long and distinguished – involving everyone from individual home owners, to local banks, to big syndicating banks, to international buyers, global insurance sellers, regulators in each and every country, rating agencies, the media and others, including you and me

I thought i’d explore what was going on in the market in the years leading up to the crisis. I combed several sources and found many US federal sources and some private sector ones that had copious amounts of data. Here is some of what I found.

Here are two graphs showing, first, how vast the mortgage market has become over the last 50 years and, second, how dramatic growth in the volume of refinancing appears to be a leading indicator in increasing foreclosure rates some 3 years later, just as interest rate adjustments kicked in and increased borrowing costs:

US Mortgage debt outstanding, 1952-2008, Home Mortgages only


Data sourced from the Board of Governors of the Federal Reserve System. Figures in actual US$, not discounted for inflation.

Mortgage Originations (Purchase and Refinance) versus Foreclosure (Entering and Already In Foreclosure)


Source: Mortgage Bankers Association of America, Washington, DC

Those home loans were turned into asset backed securities – and the growth in this graph inevitably maps closely with the growth in origination and refinancing in the previous graph. The fall off maps, in the same way, with the huge growth in loans either in or entering foreclosure.


Source: Thomson Financial, Bloomberg, SIFMA

If the previous graph showed issuance, this graphs shows outstanding securities (the big section in the middle is credit card debt)


Source: Thomson Financial, Bloomberg, SIFMA

The graphs above paint a picture of an economy growing at a huge speed fuelled by debt pulled down from the equity within a house (with that equity often put into another house, so reducing the available supply and pushing up prices) and also by credit card debt (which spiked highest in the period when home loans were reducing – that is, when house prices were already falling and taking equity from the house wasn’t an option, but credit cards were).

Looking at the instruments that Goldman is alleged to have used inappropriately, here are two graphs showing the same dataset for CDOs, split by currency and by purpose. There are two obvious conclusions:

1) The vast bulk of CDOs were issued in US dollars (covering US originated loans) with Europe lagging US growth by at least a year

2) If the second graph is right, then the purpose of CDOs is to arbitrage. Or perhaps speculate?

CDOs by Currency (2000-2010)


Source: SIFMA

CDOs by Purpose


Source: SIFMA

The cliff all of the issuance graphs fall off in 2006/7 coincides with the sudden leap in foreclosure rates.

The big question for those chasing down Goldman is:

If you were sitting inside a bank, a financial institution, a pension provider or a hedge fund in February 2007, would you have known that that was the time to get out? The TIME TO SELL?

Here’s another graph showing asset backed security issuance in 2007, quarter by quarter


Source: SIFMA

Would that have been enough? In February 2007? To my eye, it looks like it would have been tough to see until sometime after the Q2 figures were in. Some smart people saw it earlier than that of course – they saw those foreclosure rates start to climb in 2006 and made their bets.

Did Goldman mislead? I have no idea. Doubtless they – and other Financial Institutions – will be negotiating settlements now where no fault or liability is admitted.

But every market ever traded is asymmetric. Someone always has more information than someone else – or they think they do. For every seller there has to be a buyer. For every buyer, a seller. Often there is both a buyer and a seller, sitting in the middle making the trade.

Part 3 of this blog will be on this very asymmetry.

This is the second part (of three). The first part was published here a month ago.

Have You Been Goldman’d?

201004251100.jpgSmart money, dumb money: Buy housing, sell housing. Buy bonds, Sell bonds. Buy banks, Sell banks.

Smart money, dumb money: Sell housing, buy housing. Sell bonds, buy bonds. Sell banks, buy banks.

What was smart is dumb. What was dumb is smart. The trouble is, at the time, everyone thinks they’re smart. People forget there’s always a fool at a poker table, and if you can’t see who it is, it’s you.

With the most recent market gyrations, initially caused by subprime mortgages, I’m reminded of M.C. Escher’s famous picture, from 1961, titled, simply, “Waterfall” – what goes down, must go up. Until it goes down again.

Now the famously smart money, Goldman Sachs, is being pursued what many had previously labelled the dumb money (Madoff, Stanford, Moody’s), the Securities and Exchange Commission. Did the smarts just get dumb, or are the dumbs smart again?

Doing God’s work indeed.

Subprime bonds were packaged in tranches (a more positive way of saying layers which would imply some kind of hierarchy where if you’re at the bottom, you don’t want to be). Tranches were weighted in letters essentially from A to Z, but rather than say it that bluntly, special codes were created where AAA was exactly what you’d imagine it was (originally the lowest risk, where risk was relative rather than absolute) and BBB or BBB- was a much higher risk (how much higher is again a relative term – in this case it was much like sticking your feet in concrete as it was setting and just as the steamroller was firing up the engine. You could tell bad things were going to happen, but it wasn’t going to be quick).   

The real art in the subprime market was packaging tranches that were originally BBB or worse into new tranches that magically – David Blaine kind of magic – were suddenly AAA. Classic three card monte. Find the lady, watch her fly, where’d she go? Oh I see, she ran off with your money.

The dumb money, thinking they were making a bet in a one way market, thought they were buying AAA yet they were buying BBB. In many cases, they weren’t even buying the bonds themselves, but selling insurance that those same bonds wouldn’t default. For a few million for every hundred million you wanted insured, they’d sell you a policy – a binary bet: if the bonds defaulted, they’d pay you face value, if they didn’t, you’d keep paying your insurance premium.

The insurance premiums payable were calculated on two simple things

1) The risk weighting of the bonds. Given the diversity of the US property market, and keeping it simple, the risk models assumed that if you owned the mortgage on a house in Florida and one in San Diego, the odds of them each defaulting were independent, that is, there was no correlation. Multiplying that across all states of the USA (where nearly all of these mortgages originated), the correlation was assumed to be even lower. You soon learn that whenever someone brings algebra and applied mathematics into investing, you need to keep your wallet closed.

2) The one way moves in house prices over the prior years meant that market volatility was low (that is to say that prices hadn’t bounced up and down but had only moved up in the previous 10 years) and so the risk premium was further lowered.

The oddest thing about the insurance market for such bonds was that you didn’t actually have to own anything to buy insurance.

– You didn’t have to be the house owner taking a bit of insurance in case your freshly bought house suffered a loss in value.

– You didn’t have to be the banker who had sold the mortgage taking additional insurance in case your client couldn’t pay.

– And you didn’t have to be the eventual buyer of the securitised loan tranches that had been painstakingly assembled

This is much the same as me being able to buy a fire insurance policy on an allotment shed and then being able to throw a can of petrol and a match into it – without anyone knowing that you were going to be the beneficiary of the insurance policy.

Actually, the people buying these insurance policies didn’t need any petrol. They had studied the market and decided that the unvarying ascent of house prices couldn’t go on and so they’d decided to bet against it – that is, to go short.

In stock markets, if you want to go short you have to find someone to lend you the stock (you then sell it for them, promising to buy it back and deliver it back to whoever you borrowed it from). This has the neat effect of meaning that you can only go short what is out there – you can’t find twice as much stock as exists to go short. It is also self-regulating – the more stock that is borrowed, the more risk there is that a sudden spike in the price driven by a news event can financially cripple those going short.

Those shorting the subprime market didn’t need to own any of the bonds, didn’t need to borrow them from anyone, they didn’t even need to know how many were out there. Entirely synthetic (i.e. made up) transactions could be created that mimicked the behaviour of the real bonds. And they could be made up in huge volumes – far higher volumes than existed of those bonds. $1 of bonds could be insured once, ten times or a hundred times. Worse still, the lack of a central clearing house and a liquid market meant that everything was priced individually – there was no easy way to get a price for what you were buying (or selling) other than from whoever had their hands on it at the time. This was Michael Milken and Drexel’s junk bonds all over again.

With the housing market moving up, those buying insurance were widely thought of as the dumb money. Insurers were happy to collect a couple of million on a $100 million portfolio every year. After all, housing was strong, the economy was strong, house prices hadn’t gone down in 10 years and it was easy money. All money in such instances is easy. Until it isn’t. We’ve been here before – the South Sea bubble, the LTCM crash, the dotcom bubble and so on.

And as everyone surveys the global wreckage and now that the money has been spent to prop up the banks, the regulators are going after the perpetrators. They have, though, started in an interesting place. Goldman Sachs, the poster child for banking profitability (and one of the few banks left standing largely on its own two feet after the crisis). Others will follow – it looks like Morgan Stanley is already next in line. This feels a bit like the Martha Stewart prosecution – go for the highest profile victim, hope to get a quick settlement and sizeable fine and then use that to scare everyone else into paying up without a fight. Martha resisted for a long time and went to jail for her trouble. It seems likely that Goldman will resist too.

The chain of people involved in this crisis is long and distinguished – involving everyone from individual home owners, to local banks, to big syndicating banks, to international buyers, global insurance sellers, regulators in each and every country, rating agencies, the media and others, including you and me. It’s important, I think, to look at the role each of those played in creating this monster of a market, but concluding on the guilt and innocence of the chosen target, Goldman Sachs/

As Escher himself said:

“So let us then try to climb the mountain, not by stepping on what is below us, but to pull us up at what is above us, for my part at the stars; amen”

This is Part 1 of 3.