Because “technical debt” has the word “debt” in it, many people have decided that it makes sense to think and work with technical debt in monetary terms, and treat technical debt as a real financial cost. This is supposed to make it easier for technical people to explain technical debt to the business, and easier to make a business case for paying debt off.
Putting technical debt into financial terms also allows consultants and vendors to try to scare business executives into buying their tools or their help – like Gartner calculating that world wide “IT debt” costs will exceed $1.5 in a couple of more years, or CAST software’s assessment that the average enterprise is carrying millions of dollars of technical debt.
Businesses understand debt. Businesses make a decision to take on debt on and they track it, account for it and manage it. The business always knows how much debt they have, why they took it on, and when they need to pay it off. Businesses don’t accidentally take on debt – debt doesn’t just show up on the books one day.
We don’t know when we’re taking technical debt on
But developers accidentally take on debt all of the time – what Martin Fowler calls “inadvertent debt”, due to inexperience and misunderstandings, everything from “What’s Layering?” to “Now we know how we should have done it” looking at the design a year or two later.
‘The point is that while you’re programming, you are learning. It’s often the case that it can take a year of programming on a project before you understand what the best design approach should have been.’
Taking on this kind of debt is inevitable – and you’ll never know when you’re taking it on or how much, because you don’t know what you don’t know.
Even when developers take on debt consciously, they don’t understand the costs at the time – the principal or the interest. Most teams don’t record when they make a trade-off in design or a shortcut in coding or test automation, never mind try to put a value on paying off their choice.
We don’t understand (or often even see) technical debt costs until long after we’ve taken the costs on. When you’re dealing with quality and stability problems; or when you’re estimating out a change and you recognize that you made mistakes in the past or that you took shortcuts that you didn’t realize before or shortcuts that you did know about but that turned out to be much more expensive than you expected; or once you understand that you chose the wrong architecture or the wrong technical platform. Or maybe you’ve just run a static analysis tool like CAST or SONAR which tells you that you have thousands of dollars of technical debt in your code base that you didn’t know about until now.
Now try and explain to a business executive that you just realized or just remembered that you have put the company into debt for tens or hundreds of thousands of dollars. Businesses don’t and can’t run this way.
We don’t know how much technical debt is really costing us
By expressing everything in financial terms, we’re also pretending that technical debt costs are all hard costs to the business and that we actually know how much the principal and interest costs are: we’re $100,000 in debt and the interest rate is 3% per year. Assigning a monetary value to technical debt costs give them a false sense of precision and accuracy.
Let’s be honest. There aren’t clear and consistent criteria for costing technical debt and modelling technical debt repayment – we don’t even have a definition of what technical debt is that we can all agree on. Two people can come up with a different technical debt assessment for the same system, because what I think technical debt is and what you think technical debt is aren’t the same. And just because a tool says that technical debt costs are $100,000.00 for a code base, doesn’t make the number true.
Any principal and interest that you calculate (or some tool calculates for you) are made-up numbers and the business will know this when you try to defend them – which you are going to have to do, if you want to talk in financial terms with someone who does finance for a living. You’re going to be on shaky ground at best – at worse, they’ll understand that you’re not talking about real business debt and wonder what you’re trying to pull off.
The other problem that I see is “debt fatigue”. Everyone is overwhelmed by the global government debt crisis and the real estate debt crisis and the consumer debt crisis and the fiscal cliff and whatever comes next. Your business may be already fighting its own problems with managing its financial debt. Technical debt is one more argument about debt that nobody is looking forward to hearing.
We don’t need to talk about debt with the business
We don’t use the term “technical debt” with the business, or try to explain it in financial debt terms. If we need to rewrite code because it is unstable, we treat this like any other problem that needs to be solved – we cost it out, explain the risks, and prioritize this work with everything else. If we need to rewrite or restructure code in order to make upcoming changes easier, cheaper and less risky, we explain this as part of the work that needs to be done, and justify the costs. If we need to replace or upgrade a platform technology because we are getting poor support from the supplier, we consider this a business risk that needs to be understood and managed. And if code should be refactored or tests filled in, we don’t explain it, we just do it as part of day-to-day engineering work.
We’re dealing with technical debt in terms that the business understands without using a phony financial model. We’re not pretending that we’re carrying off-balance sheet debt that the company needs to rely on technologists to understand and manage. We’re leaving debt valuation and payment amortization arguments to the experts in finance and accounting where they belong, and focusing on solving problems in software, which is where we belong.
This guide will introduce you to the world of Software Architecture!
This 162 page guide will cover topics within the field of software architecture including: software architecture as a solution balancing the concerns of different stakeholders, quality assurance, methods to describe and evaluate architectures, the influence of architecture on reuse, and the life cycle of a system and its architecture. This guide concludes with a comparison between the professions of software architect and software engineer.