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Jim Highsmith on the Financial Implications of Technical Debt

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Jim Highsmith launched his new blog/website last week. I have no doubt whatsoever it will be a thought leadership blog. Moreover, knowing Jim I would expect the blog will address and integrate concepts and ideas from numerous disciplines, not “just” from software methods.

Jim’s first publicly available post  – The Financial Implications of Technical Debt – explores the impact of technical debt on capitalization. To quote Jim:

So the bottom line for technical debt. It’s expensive to fix, but much more expensive to ignore. Technical debt reduces future earnings, but even more critically, it destroys predictability which in turn impacts market capitalization in the near term, not in the future.

Figure 1: Loss of Predictability

Jim’s post nicely closes the {financial –> technical –> financial} loop. Ward Cunningham’s original debt metaphor borrowed the financial term to apply it to software development. Jim is now bridging from the technical arena back to the financial world.

If you are into any form of agility – technical, managerial or business – you owe it to yourself to follow Jim’s blog.

Written by israelgat

November 1, 2010 at 6:44 am

Fresh Perspectives on Technical Debt

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Update, October 15: The issue has been posted on the Cutter website (Cutter IT Journal subscription privileges required).

Cutter is just about ready to post the October issue of the IT Journal for which I am the guest editor. Print subscribers should receive it by the last week of the month. Jim Highsmith and I will be reflecting on it in our forthcoming seminar on technical debt in the Cutter Summit.

This issue sheds light on three noteworthy aspects of technical debt techniques:

  1. Their pragmatic use as an integral part of Governance, Risk and Compliance (GRC).
  2. Extending the techniques to shed light on various nuances of technical debt that have alluded us so far.
  3. Applying the techniques in new domains such as devops.

Here is the Table of Contents for this exciting issue:

Opening Statement

by Israel Gat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  3

Modernizing the DeLorean System: Comparing Actual and Predicted Results of a Technical Debt Reduction Project

by John Heintz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

The Economics of Technical Debt

by Stephen Chin, Erik Huddleston, Walter Bodwell, and Israel Gat . . . . . . . . . . . . . . . . . 11

Technical Debt: Challenging the Metaphor

by David Rooney . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Manage Project Portfolios More Effectively by Including Software Debt in the Decision Process

by Brent Barton and Chris Sterling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

The Risks of Acceptance Test Debt

by Ken Pugh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Transformation Patterns for Curing the Human Causes of Technical Debt

by Jonathon Michael Golden . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  30

Infrastructure Debt: Revisiting the Foundation

by Andrew Shafer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36


Action Item: Apply the techniques recommended in this issue to govern your software assets in an effective manner.


Overwhelmed by a “mountain” of technical debt? Let me know if you would like assistance in devising and carrying out plans to reduce the debt in a biggest-bang-for-the-buck manner. Click Services for details.


The Real Cost of One Trillion Dollars in IT Debt: Part II – The Performance Paradox

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Some of the business ramifications of the $1 trillion in IT debt have been explored in the first post of this two-part analysis. This second post focuses on “an ounce of prevention is worth a pound of cure” aspects of IT debt. In particular, it proposes an explanation why prevention was often neglected in the US over the past decade and very possibly longer. This explanation is not meant to dwell on the past. Rather, it studies the patterns of the past in order to provide guidance for what you could do and should do in the future to rein in technical debt.

The prevention vis-a-vis cure trade-off  in software was illustrated by colleague and friend Jim Highsmith in the following figure:

Figure 1: The Technical Debt Curve

As Jim astutely points out, “once on far right of curve all choices are hard.” My experience as well as those of various Cutter colleagues have shown it is actually very hard. The reason is simple: on the far right the software controls you more than you control it. The manifestations of technical debt [1] in the form of pressing customer problems in the production environment force you into a largely reactive mode of operation. This reactive mode of operation is prone to a high error injection rate – you introduce new bugs while you fix old ones. Consequently, progress is agonizingly slow and painful. It is often characterized by “never-ending” testing periods.

In Measure and Manage Your IT Debt, Gartner’s Andrew Kyte put his finger on the mechanics that lead to the accumulation of technical debt – “when budget are tight, maintenance gets cut.” While I do not doubt Andrew’s observation, it does not answer a deeper question: why would maintenance get cut in the face of the consequences depicted in Figure 1? Most CFOs and CEOs I know would get quite alarmed by Figure 1. They do not need to be experts in object-oriented programming in order to take steps to mitigate the risks associated with slipping to the far right of the curve.

I believe the deeper answer to the question “why would maintenance get cut in the face of the consequences depicted in Figure 1?” was given by John Seely Brown in his 2009 presentation The Big Shift: The Mutual Decoupling of Two Sets of Disruptions – One in Business and One in IT. Brown points out five alarming facts in his presentation:

  1. The return on assets (ROA) for U.S. firms has steadily fallen to almost one-quarter of 1965 levels.
  2. Similarly, the ROA performance gap between corporate winners and losers has increased over time, with the “winners” barely maintaining previous performance levels while the losers experience rapid performance deterioration.
  3. U.S. competitive intensity has more than doubled during that same time [i.e. the US has become twice as competitive – IG].
  4. Average Lifetime of S&P 500 companies [declined steadily over this period].
  5. However, in those same 40 years, labor productivity has doubled – largely due to advances in technology and business innovation.

Discussion of the full-fledged analysis that Brown derives based on these five facts is beyond the scope of this blog post [2]. However, one of the phenomena he highlights –  “The performance paradox: ROA has dropped in the face of increasing labor productivity” – is IMHO at the roots of the staggering IT debt we are staring at.

Put yourself in the shoes of your CFO or your CEO, weighing the five facts highlighted by Brown in the context of Highsmith’s technical debt curve. Unless you are one of the precious few winner companies, the only viable financial strategy you can follow is a margin strategy. You are very competitive (#3 above). You have already ridden the productivity curve (#5 above). However, growth is not demonstrable or not economically feasible given the investment it takes (#1 & #2 above). Needless to say, just thinking about being dropped out of the S&P 500 index sends cold sweat down your spine. The only way left to you to satisfy the quarterly expectations of Wall Street is to cut, cut and cut again anything that does not immediately contribute to your cashflow. You cut on-going refactoring of code even if your CTO and CIO have explained the technical debt curve to you in no uncertain terms. You are not happy to do so but you are willing to pay the price down the road. You are basically following a “survive to fight another day” strategy.

If you accept this explanation for the level of debt we are staring at, the core issue with respect to IT debt at the individual company level [3] is how “patient” (or “impatient”) investment capital is. Studies by Carlota Perez seem to indicate we are entering a phase of the techno-economic cycle in which investment capital will shift from financial speculation toward (the more “patient”) production capital. While this shift is starting to happens, you have the opportunity to apply “an ounce of prevention is worth a pound of cure” strategy with respect to the new code you will be developing.

My recommendation would be to combine technical debt measurements with software process change. The ability to measure technical debt through code analysis is a necessary but not sufficient condition for changing deep-rooted patterns. Once you institute a process policy like “stop the line whenever the level of technical debt rose,” you combine the “necessary” with the “sufficient” by tying the measurement to human behavior. A possible way to do so through a modified Agile/Scrum process is illustrated in Figure 2:

Figure 2: Process Control Model for Controlling Technical Debt

As you can see in Figure 2, you stop the line and convene an event-driven Agile meeting whenever the technical debt of a certain build exceeds that of the previous build. If ‘stopping the line’ with every such build is “too much of a good thing” for your environment, you can adopt statistical process control methods to gauge when the line should be stopped. (See Using 3σ  Control Limits in Software Engineering for a discussion of the settings appropriate for your environment.)

An absolutely critical question this analysis does not cover is “But how do we pay back our $1 trillion debt?!I will address this most important question in a forthcoming post which draws upon the threads of this post plus those in the preceding Part I.


[1] Kyte/Gartner define IT Debt as “the costs for bringing all the elements [i.e. business applications] in the [IT] portfolio up to a reasonable standard of engineering integrity, or replace them.” In essence, IT Debt differs from the definition of Technical Debt used in The Agile Executive in that it accounts for the possible costs associated with replacing an application. For example, the technical debt calculated through doing code analysis on a certain application might amount to $500K. In contrast, the cost of replacement might be $250K, $1M or some other figure that is not necessarily related to intrinsic quality defects in the current code base.

[2] See Hagel, Brown and Davison: The Power of Pull: How Small Moves, Smartly Made, Can Set Big Things in Motion.

[3] As distinct from the core issue at the national level.

The Gat/Highsmith Joint Seminar on Technical Debt and Software Governance

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Jim and I have finalized the content and the format for our forthcoming Cutter Summit seminar. The seminar is structured around a case study which includes four exercise. We expect the case study/exercises will take close to two-thirds of the allotted time (the morning of October 27). In the other third we will provide the theory and practices to be used in the seminar exercises and (hopefully) in many future technical debt engagements participants in the workshop will oversee.

The seminar does not require deep technical knowledge. It targets participants who possess conceptual grasp of software development, software governance and IT operations/ITIL. If you feel like reading a little about technical debt prior to the Summit, the various posts on technical debt in this blog will be more than sufficient.

We plan to go with the following agenda (still subject to some minor tweaking):

Agenda for the October 27, 9:30AM to 1:00PM Technical Debt Seminar

  • Setting the Stage: Why Technical Debt is a Strategic Issue
  • Part I: What is Technical Debt?
  • Part II : Case Study – NotMyCompany, Inc.
    • Exercise #1 – Modernizing NotMyCompany’s Legacy Code
  • Part III: The Nature of Technical Debt
  • Part IV: Unified Governance
    • Exercise #2 – The acquisition of SocialAreUs by NotMyCompany
  • Part V: Process Control Models
    • Exercise #3 – How Often Should NotMyCompany Stop the Line?
  • (Time Permitting – Part VI: Using Technical Debt in Devops
    • Exercise #4 – The Agile Versus ITIL Debate at NotMyCompany)

By the end of the seminar you will know how to effectively apply technical debt techniques as an integral part of software governance that is anchored in business realities and imperatives.

Written by israelgat

September 30, 2010 at 3:20 pm

Why Spend the Afternoon as well on Technical Debt?

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Yesterday’s post Why Spend a Whole Morning on Technical Debt? listed eight characteristics of the technical debt metric that will be discussed during the morning of October 27 when Jim Highsmith and I deliver our joint Cutter Summit seminar. This posts adds to the previous post by suggesting a related topic for the afternoon.

No, I am not trying to “hijack” the Summit agenda messing with the afternoon sessions by colleagues Claude Baudoin and Mitchell Ummel. I am simply pointing out a corollary to the morning seminar that might be on your mind in the afternoon. Needless to say, thinking about it in the afternoon of the 28th instead of the afternoon of the 27th is quite appropriate…

Yesterday’s post concluded with a “what it all means” statement, as follows:

Technical debt is a meaningful metric at any level of your organization and for any department in it. Moreover, it is applicable to any business process that is not yet taking software quality into account.

If you accept this premise, you can use the technical debt metric to construct boundary objects between various departments in your company/organization. The metric could serve as the heart of boundary objects between dev and IT ops, between dev and customer support, between dev and a company to which some development tasks are outsourced, etc. The point is the enablement of working agreements between multiple stakeholders through the technical debt metric. For example, dev and IT ops might mutually agree that the technical debt in the code to be deployed to the production environment will be less than $3 per line of code. Or, dev and customer support might agree that enhanced refactoring will commence if the code decays over time to more than $4 per line of code.

You can align various departments by by using the technical debt metric. This alignment is particularly important when the operational balance between departments has been disrupted. For example, your developers might be coding faster than your ITIL change managers can process the change requests.

A lot more on the use of the technical debt metric to mitigate cross-organizational dysfunctions, including some Outmodel aspects, will be covered in our seminar in Cambridge, MA on the morning of the 27th. We look forward to discussing this intriguing subject with you there!


Why Spend a Whole Morning on Technical Debt?

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In a little over a month Jim Highsmith and I will deliver our joint seminar on technical debt in the Cutter Summit. Here are eight characteristics of the technical debt metric that make it clear why you should spend 3.5 precious hours on the topic:

  1. The technical debt metric shifts the emphasis in software development from proficiency in the software process to the output of the process.
  2. It changes the playing fields from qualitative assessment to quantitative measurement of the quality of the software.
  3. It is an effective antidote to the relentless function/feature pressure.
  4. It can be used with any software method, not “just” Agile.
  5. It is applicable to any amount of code.
  6. It can be applied at any point in time in the software life-cycle.
  7. These six characteristics of the technical debt metric enable effective governance of the software process.
  8. The above  characteristics of the technical debt metric enable effective governance of the software product portfolio.

The eight characteristics in the aggregate amount to technical debt metric as a ‘universal source of truth.’ It is a meaningful metric at any level of your organization and for any department in it. Moreover, it is applicable to any business process that is not yet taking software quality into account.

Jim and I look forward to meeting you at the summit and interacting with you in the technical debt seminar!

Written by israelgat

September 22, 2010 at 7:32 am

Outline of the Technical Debt Seminar at the Cutter Summit

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Pictured above are speakers of the forthcoming Cutter Summit. Between the seventeen of us we will cover a broad spectrum of IT topics such as Agile, Enterprise Architecture, Business Strategy, Cloud Computing, Collaboration, Governance and Security. Inter-disciplinary seminars, panels and case studies will weave all those threads together to give participants a clear view of the unfolding transformation in IT and of the new way(s) companies are starting to utilize IT. Click here for a details.

As Jim Highsmith and I continue to develop our joint seminar on technical debt for the summit, I would like to give readers of this blog a sense of where we are and ask for feedback. Right now we are considering the following building blocks for the seminar:

  • The Nature of Technical Debt
  • Technical Debt Metrics
  • Monetizing Technical Debt
  • Constructing Roadmaps for Paying Back Technical Debt
  • Risk Assessment and Mitigation
  • A Simple Software Governance Framework
  • Schedule in the Simple Governance Framework
  • Enlightened Governance
  • Baking in Quality One Build at a Time
  • How Often Should the Project Team Regroup?
  • Multi-Level Governance
  • Extending  Technical Debt Techniques to Devops
  • Use of Technical Debt Techniques in Agile Portfolio Management
  • The Start Afresh Option
  • Technical Debt as an Integral Part of a Value Delivery Culture

In the course of going through a subset of these building blocks, we will cover the latest and greatest from the October issue of the Cutter IT Journal on technical debt, present two case studies, and conduct a few group exercises.