Bailing out the automakers: are finished goods assets?

So the big autos are going to get bailouts. But there is a condition attached - they must have a plan to be "viable" by the end of 2009.

My suggestion? Use this crisis to make fundamental changes to they way they manage and report the bottom line. My (limited) understanding is that currently most of the big autos treat finished goods as assets, which looks great on the balance sheet and makes investors happy. But are they really assets?

TheAge newspaper just published an interesting article on the mounting costs of new cars that are sitting idle in storage yards as a result of the downturn. It includes an estimate that the australian auto industry losing approximately $2M a week just in storage costs, let alone in the depreciating value as those vehicles age and become less attractive to customers.

These cars are not assets. They are liabilities. They are non-liquid, have high "operational costs" (storage) and are losing value. A very bad investment indeed.

I think the balance sheets of the big autos need to be changed to reflect this. I would suggest instead focusing on ROI, as calculated in a throughput accounting model as:

ROI = (throughput - operational expense) / inventory
where throughput = net sales - totally variable costs

In this model, the bigger the inventory, the proportionally smaller the ROI (the same goes for the operational costs, although this often has less impact). Looking at things this way immediately shows the ridiculousness of treating these cars as valuable assets.

My understanding is that the Japanese auto makers report in exactly this way. Revenue is not recognised until the car is sold to a customer - not when it rolls of the production line to sit in a big finished goods yard. In the past, however, this sort of change would probably have been suicide; any firm making this change would take a massive hit to the balance sheet that would have decimated the share price. But given they now are already in a huge mess, perhaps this is exactly the time to be making big changes like this.

The future of proof

One of my favourite authors and bloggers, Bruce Schneier, recently posted an interesting blog on "The Future of Ephemeral Conversation". Essentially, the premise is that conversation, as it increasingly occurs over electronic mediums, is becoming less ephemeral, meaning that it is now lasting for much longer periods of time than we have previously experienced. This has complex ramifications on privacy as, due to the nature of storage and retrieval that electronic mediums provide, "private" conversations can potentially come back to haunt one years later.

There is another part to this. Electronic mediums provide not only a longer lifetime for communications, but also a wider spread. We no longer just experience direct conversation with our friends or colleagues, but we also experience the conversation they are having with their other friends or colleagues. It is now much more common to 'carbon-copy' communications, to post notes or details on (semi-)public and aggregated mediums like blogs, facebook, myspace or twitter, such that our conversations reach a much wider audience than in the past.

The effect of this is facinating and concerning. Firstly, it leads to the "information overload" that I believe our society is currently grappling with. There is much more information available, especially of a more personal nature involving our friends and colleagues, and we need to be more rapid in our consumption of it. There are many ramifications of this, which are all worthy of their own discussions, but I believe one direct result is that we have, or will, become increasingly less critical and more trusting. We will no longer critique each item of communication for it's accuracy or it's authenticity. This is result of necessity, as we will need to be more efficient at processing information and reduce wasted time. With so much more information available, and the barrier to dissemination of it so much lower, the vast majority of the communications we are privy to will be both accurate and authentic, so the assertion of this naturally become a task to compromise on.

The ramifications of this on our systems of law will be profound.

One ramification will be on the nature of "proof". Currently, a person cannot be held responsible for a written letter unless it is proven in some way that they wrote it. In an electronic world, this proof is almost impossible and yet we can already see that we no longer look for it or think of it as required. There are many legal cases already that are premised on emails sent and yet email is both trivial to forge and has no identifying traits like a writing style or signature to authenticate on. It is incredibly hard to prove who was sitting at the keyboard, or even which keyboard. But our increasing implicit trust will (if it hasn't already) sway people away from this sort of critical thinking. If the overwhelmingly majority of communications they have been privy to are authentic, then they will likely a have greatly reduced level of scepticism when it comes to proof.

The second ramification will be on due process and the burden of proof. Under our existing process, it is required that reasonable proof be supplied before a person is considered responsible for their words or actions. In addition to lowering the expectation for proof, the rapid and wide dissemination of information will result in a great potential for consequence to be enacted before proof has been offered. We are already starting to see this in media, when reporting influences the opinion of the public on an issue before it has been determined in a court. Whilst our existing system has mechanisms to prevent this perversion by the official media, there is no such mechanisms in place for the myriad of alternative information channels that are now becoming available. Combining rapid, wide and personalised dissemination of information with an increased trust in the accuracy of it creates a risky new landscape in which we all tread.

I do believe that electronic communications, with all their ramifications, are overwhelmingly a good thing for our society. The value they provide is massive. But we must consider the consequences in terms of (reduced) privacy, increased visibility into the past opinions of an individual that may no longer be correct or even relevant, the nature and burden of proof and legal due process. We just have to consider the effect these consequences will have on our systems and adjust them accordingly. Ignoring the changing environment and assuming our systems are, and remain, perfect would be a failing for all of us.

XDR-TB: A preventable pandemic

[This blog post will be off-topic, but I feel inspired to write it.]

It saddens me to see that there is so much more we could achieve in this world, if we weren't confounded regularly by politics and greed. And it makes me angry when I see real problems, the sort that could destroy our world as we know it, that could easily be stopped if we put politics and greed aside and co-operated as a race of human beings.

I recently learnt, courtesy of a TED talk, about Extremely Drug Resistant Tuberculosis. TB is a horrific and dangerous disease, but one that we barely give a real thought to in the modern western world - because it's totally treatable and preventable. However in the rest of the world it still kills 4400 people every day.

This, unfortunately, is not the real problem with the current state of TB. Due to lack of funding and co-operation, especially with poorer countries, TB has been mistreated on a large scale - usually by supplying insufficient courses in the antibiotics that treat the disease. Because of this under-treatment, TB has evolved into a new form that is resistant to the antibiotics. This new form of human-made TB, known as Extremely Drug Resistant Tuberculosis (or XDR-TB) is not preventable or treatable with most current drugs.

It's heart breaking to see how easily the west can ignore poverty and other problems in poorer nations. In this case, however, the "problem" isn't going to stay out of sight forever. There is absolutely no reason for this disease to have been created, other than through politics, greed and ignorance. And it needs to be stopped now, or a global pandemic will threaten the population of the world.

Product development is not a good analogy for software delivery

In a quick break from my current obsession with Throughput I thought I'd talk about something I often hear from folk theorising about software development, especially those running Agile software development teams - that the process of delivering software bears more similarity to industrial product design and development than it does to industrial manufacturing.

I believe this to be true for shrink-wrap software product delivery. However the majority of software development is not shrink-wrap software products. The majority are software systems that support or enable a business function - things like websites, transaction management systems, scheduling systems, etc. In these cases I believe that the analogy to industrial product design is misleading.

The ultimate goal of all business software delivery is to make money for the business. In the shrink-wrap product case it's to create revenue through sale of the product. For the rest it is to create revenue by enabling or improving a business function. The software delivery process is a business process improvement mechanism; and the software is simply a side effect.

The last point is important - software is a side-effect. If the business could achieve the same improvement/enablement goal, by some cheaper or more effective mechanism than producing software, then that's exactly what they should do. Luckily for us in the software industry there are many cases where software is the best solution!

So given that we're usually not producing software to sell as a product and instead producing it as side-effect of improving a business function, it makes sense to try and provide any improvements as rapidly and efficiently as possible. In this sense, software delivery is less like the design of a product and more like a continuous manufacturing process for discrete business benefits.

Of course, there are differences between delivery of business process improvements through software and traditional manufacturing. The most obvious one is the substantially larger degree of uncertainty in the effort that will be required to deliver a given improvement (benefit). Manufacturing can often predict how long it takes to build a product down to minutes or seconds. We don't have that luxury. As a result software delivery suffers from much larger statistical variation in each stage of the process, which has large ramifications on the way we must manage the process (hopefully I'll discuss this in further detail in future posts on throughput). On the positive side, software delivery often has a simpler process than many manufacturing processes - in many cases it's quite linear with a single chain of clear and well understood dependent stages.

The presence of uncertainty and variation is what leads people to think of software delivery as a product development process. I can really see the attraction of this thinking because it captures the creative nature of much of the work that occurs and thus makes the larger degree of uncertainty and variation implicit. However I think applying this thinking too widely has detrimental ramifications to how we understand and improve our value to businesses. It leads us to think about the end software system exclusively and to create software 'projects' that attempt to build the whole system, rather than thinking about how we can deliver each individual business process improvement separately (and rapidly). This form of batch thinking can severely limit the flexibility and the value software delivery offers businesses. In turn, I believe this to be a clear reason why many CxOs are afraid of IT and look for ways to avoid involving IT in new business initiatives. If everytime the CxO wants to make an improvement or change to their business and asks IT for help, then gets told "we'll need a new XYZ system", they'll quickly learn to stop talking to IT.

In summary, whilst I believe that the design and development of discrete changes or additions to software systems to be a "product design" activity, I consider the software delivery process, which provides for continuous and on-going addition of value (through business process improvement), to be more analogous to manufacturing. It's about moving peices of work (a software system change/addition) through a continuously improving pipeline.

Defining Throughput

In this second part to my series on Throughput Accounting, I'm going to explore the concept of Throughput, starting with a definition.

Every system has a goal it is trying to achieve. For most business processes this goal is revenue - money given to the organisation by customers due to sales of product or services. Given this, 'Throughput' is simply defined as a measure of the rate at which a system is achieving its goal. It is not a measure of profit or any indicator of efficiency, it is just a measure of flow.

Throughput is often expressed in terms of 'goal units'. In for-profit organisations, these units may be dollars of revenue. For non-profit organisations it may be expressed by another measure, such as patients successfully treated in a hospital emergency ward.

When dealing with monetary goal units, Throughput (T) is often measured as gross revenue from sale of a product (S) minus totally variable costs (TVC), which are only the costs that vary directly with the system output. In a manufacturing setting, TVC is often just the cost of raw materials. Thus T = S - TVC.

In the example from my last post, a company was producing 800 widgets per month. Their TVC, for materials, was $40 per widget. If those widgets were being sold at $50, the throughput per widget would be $10 and the system throughput is $8000 per month, or around $0.18 per minute.

In calculation, this is identical to the cost accounting metric 'contribution margin'. The contribution margin is used to determine the fraction of sales that contributes to offsetting fixed costs and can be used to disambiguate some decisions, such as the purchase price example from my previous post. As Throughput Accounting manages fixed costs separately, it is not required for this purpose - but has a much broader role.

It is important to note that Throughput is measured only as the ultimate achievement of a system, for example it may be the final sale of a product or service. It is not measured in terms of production of assets that will then be processed further to achieve the ultimate goal (eg. assets sold to achieve revenue). This is inventory - which I will discuss in a later post.

A good question is how to define Throughput in the context of a software delivery engagement. Ultimately the software system supports a business process which is in turn producing revenue - so it could be defined in terms of dollars made by the business. Pragmatically, however, it is more useful to define Throughput as the rate at which software additions and/or modifications are delivered into an environment where they can be utilised by the business process.

It is tempting to measure this rate in terms of 'business benefit' (possibly also in dollars), which is the ultimate goal unit of the entire business process. This is an important thing to focus on as often the best improvements can involve organisational changes as well as software changes. However, when the software production process is the organisation's constraint (as it often is) then we are focussed on just this process alone. In which case we need to use a 'goal unit' that is reflective of the amount of the work done to produce some change in software.

In Agile software delivery methodologies there is the concept of 'story point', which is simply a relative measure of the effort required to deliver a particular requirement. Given its relative nature, we can measure it over an arbitrary time period to determine the rate of delivery of story points, which we can use as Throughput. This is effectively the same as the Agile term 'velocity' and this comparison is useful for applying some TA concepts to software delivery. I'll return to this point in future posts...

Throughput Accounting

Let me declare today that I have a new enemy - Cost Accounting.

In 1981, at a conference of Management Accountants, Eliyahu Goldratt declared Cost Accounting to be "Enemy #1 of Productivity". In my work as a consultant for ThoughtWorks, I value productivity highly. Hence the enemy of my friend is also my enemy.

Goldratt, author of the popular business novel "The Goal", showed how traditional cost accounting easily and trivially leads intelligent managers and other decision makers to make bad decisions - decisions that have massive negative effects on performance and profitability. This was actually not surprising news, as the problems with cost accounting had been recognised. But Goldratt also proposed an alternative.

His alternative was titled "Throughput Accounting", and was described in the 1998 book by Thomas Corbett. It is an accounting model which does not focus primarily on local cost optimisation and instead focuses primarily on overall system throughput. Importantly, it does not attempt to allocate overhead costs across products and services.

Why is this important? Cost accounting attempts to allocate a companies fixed costs over a given time period to the products or services produced in that period. It enables managers to ignore the fixed costs and focus instead on the results of each period in relation to the products produced. This made sense in the 1890s, when cost accounting was developed, as most companies had extremely low fixed costs. The majority of costs were labour, which at the time was fully variable, as workers were only paid for the hours they laboured at the demand of the employer. Although there was distortion due to the overhead allocation, it was extremely small.

Modern businesses, however, have a much lower proportion of fully variable costs. Most costs are fixed, especially labour as now most employees work fixed hours regardless of demand. Due to this environmental change, the distortion caused by cost allocation is much larger and can cause management decisions, based on cost accounting, that directly result in large loses of productivity and profit.

As an example, imagine a company has fixed overheads of $10,000 (plant and labour) per month and currently produces 800 widgets with a materials cost of $40. The unit cost per widget would be $52.50 ($40 + $10,000/800). If an order now came for an additional 500 widgets at a price of $50, then management based on cost accounting should reject the order as it would result in a loss of $2.50 per widget. However, as the majority of costs are fixed, the increase in production would actually result in a new unit cost of $47.69 ($40 + $10,000/1300), so profits would actually increase by $1,153.85. This might seem clear, but imagine this example with many different products and prices in the mix and quickly it becomes hard to see the mistake. This is only one example of a poor decision made due to a cost accounting metric.

So why am I so concerned? In the software industry, especially, there is very little variable costs. The overwhelming expense is for developers, which are typically in short supply, so they are not a variable cost. Basing our decisions around software projects and the ROI from software delivery on cost accounting can lead to incredibly poor outcomes.

In future blog posts, I'll also explore what I believe is another critically important aspect of Throughput Accounting - the focus on throughput and inventory reduction over costs. I believe this has the potential for a massive effect on the software delivery process, especially when combined with the Lean practices that ThoughtWorks is pursuing in the industry.

Believe me when I say this - Throughput Accounting will become of major importance in our industry. It will make a dramatic change to the way we finance software projects and it has the power to put real numbers around why we use Agile and Lean principles and practices (as shown in David Andersons book "Agile Management for Software Engineering").

If your interested in another good introductory text, in addition to Corbetts book, try the book by Steven Bratt, also titled "Throughput Accounting".

The 3 Ps of Estimation

There's been a few posts recently regarding estimation on agile projects, all expressing issue with the way it is most commonly approached. A common theme to these posts seems to be a slight under-appreciation for the multiple purposes of story estimation.

I consider there to be 3 roles for estimation, which can be categorized with 3 Ps as follows:

Prediction (or Planning)

The most commonly observed purpose of estimation is for prediction - trying to determine at what time a certain amount of work will be completed, or what amount of work will be completed at a given time. With an estimate on each story in the backlog and an understanding of the rate of completion of those stories (velocity), either of these can be predicted with an accuracy equal to the accuracy of the estimates. Note that the accuracy tends to rapidly decrease as the amount of work or the timeframe gets larger.

Prioritisation

Prioritisation can be considered as the task of scheduling work by decreasing value. So when prioritising stories, the one with the highest value is scheduled first, followed by the next, and so on. This of course begs the question of how we determine the value.

I've blogged this topic previously, but I consider that value is essentially determined by a comparing benefit and cost. The story describes the benefit and an estimate on it can be used as a measure of the 'cost'. Thus estimation is essential for prioritisation.

Note that for prioritisation it doesn't matter what sort of estimation metric is used. It will still be treated as relative, as the prioritisation is about the relative value of each story.

Performance

Estimation is also required to measure changes in the performance of a team. The throughput (velocity) of a team is determined by the amount of 'work' being done over a given time-period and is measured in terms of the estimate. When changes are made to the team or the environment, the previous and new throughput can be compared to see if an increase (or decrease) in performance has been observed.