Posts Tagged ‘Software Decay’
The Runway of Software Products
“… the “runway” available for software products to mature and take off is both limited and precarious. Software products are subject to two over-arching phenomena that affect the runway big time: open source software and software decay…
Click here for a discussion how the two phenomena – open source and software decay – affect both the runway and the hardware v. software discussion.
Agile Enterprise Forum 2011
Charles Handy, Chris Potts, Don Reinertsen, John Seddon and I are the featured speakers in the Agile Enterprise Forum 2011. The Forum will be held on March 10, 2011 in the Chandos House at the Royal Society of Medicine, London. Attendance is limited to 30 CIOs.
The theme for the forum is Agility for Complex Organizations. The overarching message is nicely captured in the following summary by James Yoxall:
There are two strands of interest for a CIO: strategy and delivery. The Agile/Lean message can be summarised as “merging” the two, so that delivery can start before strategy is complete, and delivery informs strategy through feedback loops. This leads to a faster/earlier delivery and a better end result.
My own workshop – Agile Governance: Tying Delivery to Value – builds on this message by describing a specific strategic initiative which is not achievable without the use of advanced delivery techniques. Here is the abstract for my workshop:
This workshop will explore mechanisms for unlocking the full potential of existing software through the combination of Agile/Lean methods with technical debt techniques. These mechanisms apply to complex organisations that rely on in-house development teams as well as to third party delivery partners. Israel’s approach emphasizes the need to continuously monitor and mitigate the decay of software that more often than not had been developed over many years. Most importantly, it shows how well-governed software can become the enabler for unleashing the synergistic power of cloud, mobile and social.
You can think of the workshop as linking past, present and future. The “sins” of the past require technical debt reduction initiatives today. These initiatives utilize the classical Agile/Lean techniques of continuous measurement and tight feedback loops. Without such initiative, the value of existing software cannot be unlocked in the future. In particular, competing in the hyper-segmented markets that cloud, mobile and social generate will be next to impossible for legacy software that has not been modernized.
How Technical Debt Ties to Cloud, Mobile and Social
http://en.wikipedia.org/wiki/File:West_Side_Highway_collapsed_at_14th.jpg
Many years ago, when I came to the US, I was shocked to the core seeing the collapsed West Side Highway in New York City. I simply could not believe that a highway would be neglected to that extent amidst all the affluence of the city. The contrast was too much for me.
Nowadays I often have a deja vu sensation in various technical debt engagements in which I find the code crumbling. This sensation is not so much about what happened (see The Real Cost of a One Trillion Dollars in IT Debt: Part II – The Performance Paradox for an explanation of the economics of the neglect of software maintenance during the past decade), but about the company for which I do the assessment giving up on immense forthcoming opportunities.
Whether you do or do not fully subscribe to the vision of the Internet-of-Things depicted in the figure below, it is fairly safe to assume that your business in the years to come will be much more connected to the outside world than it is now. The enhanced connectivity might come through mobile applications, through social networks or through the cloud. As a matter of fact, it is quite likely to come through a confluence of the three: Cloud, Mobile and Social.
http://en.wikipedia.org/wiki/File:Internet_of_Things.png
In the context of current trends in cloud, mobile and social, your legacy software is like the West Side Highway in New York City. If you maintain it to an acceptable level, it can become the core of two major benefits of much higher connectivity and connectedness in the not-too-far future:
- Through mobile and social your legacy software will enable you to flexibly produce, market and distribute small quantities of whatever your products might need to be in niche markets.
- Through cloud it will enable you to offer these very same products and many others as services.
Conversely, if you consistently neglect to pay back your technical debt, your legacy code is likely to collapse due to the effects of software decay. You certainly will not be able to get it to interoperate with mobile and social networking applications, let alone offer it in the form of cloud services. Nor would you be able to wrap additional services around decaying legacy code. Take a look at the warehousing and distribution services offered by Amazon to get a sense of what this kind of additional services could do for your core business: they will enable you to transform your current business design by adding an Online-to-Offline (O2O) component to it.
What is the fine line differentiating “acceptably maintained” code from toxic code? I don’t think I have conducted a large enough sample of technical debt assessments to provide a statistically significant answer. My hunch is that the magic ceiling for software development in the US is somewhere around $10 per line of code in technical debt. As long as you are under this ceiling you could still pay back your technical debt (or a significant portion of it) in an economically viable manner. Beyond $10 per line of code the decay might prove too high to fix.
Why $10 and not $1 or $100 per line of code? It is a matter of balancing investment versus debt. An average programmer (in the US) with a $100,000 salary would probably be able to produce about 10K lines of Java code per year. The cost of a line of code under these simplistic assumptions is $10. Something is terribly wrong if the technical debt exceeds the cost per line. They call it living on margin.
Action item: CIOs should conduct a technical debt assessment on a representative sample of their legacy code. A board level discussion on the strategic implications for the company is called for if technical debt per line of code exceeds $10. The board discussion should focus on the ability of the company (or lack thereof) to participate in the business tsunami that cloud, mobile and social are likely to unleash.
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Considering modernization of your legacy code? Let me know if you would like assistance in monetizing your technical debt, devising plans to reduce it and governing the debt reduction process. Click Services for details.
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What 108M Lines of Code do not Tell Us
Source: Nemo
Coming on the heels of Gartner’s research note projecting $1 trillion in IT Debt by 2015, CAST’s study provided a more granular view of the debt, estimating an average of over $1 million in technical debt per application in a sample of 288 applications. Between these two studies, the situation examined at the micro-level seems to be quite consistent with the state of affairs estimated and projected at the macro-level.
My hunch is that the gravity of the situation from a software quality and maintenance perspective is actually masked by efforts of IT staffs to compensate for programming problems through operational excellence. For example, carefully staged deployment and quick rollback often enable coping with defects that could/should have been handled through higher test coverage, lesser complexity or a more acceptable level of code duplication.
Part of the reason that the masking effects of IT staffs are not always fully appreciated is that they are embedded in the business design of IT Outsourcing companies. The company to which you outsourced your IT is ‘making a bet’ it can run your IT better than you can. It often succeeds in so doing. The unresolved defects in your old code plus those that evolved over time through software decay have not necessarily been fixed. Rather, the manifestations of these defects are handled operationally in a more efficient manner.
Think again if your visceral reaction to the technical debt situation described in the Gartner research note and the CAST study is of the “This can’t possibly be true” variety. It is what it is – just take a quick look at Nemo to see representative technical debt data with your own eyes. And, as indicated in this post, it might even be worse than what it looks. As Gartner puts it:
The results of such [IT Debt] an assessment will be, at best, unsettling and, at worst, truly shocking.
Measuring Agile Success Rate the Right Way
Much has been said recently about the success/failure rate of Agile projects. In particular, a debate arose around the success rate of Scrum vis-a-vis Kanban. For example, in a post entitled Some Day Kanban will fail 75% of the Time, colleague Jurgen Appelo states as follows:
Unfortunately, some people arguing against Scrum include these ScrumBut teams in their evaluations of the “high failure rate” of Scrum. They love quoting that “at least 75 percent of Scrum implementations fail.” And I think “Yes of course, 75% fails when that includes the teams that don’t understand what they’re doing.”
I would like to add one other “dimension” to the discussion: boundary conditions.
Any Agile initiative – Crystal, Scrum, Kanban, etc. – typically starts from a certain state of affairs of the code that has already been developed using a Waterfall method or no method at all. Even brand new projects produce code that invariably interacts with other software components that are already deployed, warts and everything. Pristine environments with no technical debt for the Agile initiative to deal with are rare.
Like it or not, the Agile initiative is saddled from the outset with a certain amount of technical debt. Code has been duplicated, rules violated, complexity ran amuck, etc. A typical enterprise software team starts with hundreds of thousands $$ in technical debt, if not millions. This debt needs to be “paid back.” Probably not over night, but certainly over a period of time. As illustrated by the following figure from Jim Highsmith, things get ugly if the debt is not paid back over an extended period of time.
The evaluation of success or failure of the Agile initiative needs to take technical debt into account. A team of 50 with an accrued technical debt of $100,000 has a much easier job on its hands transitioning to Agile than a similar size team starting with $1M in technical debt on its hands.
Whatever criteria you use to determine whether an Agile initiative has been successful, I would suggest the following boundary condition needs to be satisfied:
Technical debt at the end of the project/initiative must be significantly lower than technical debt at the start of the project.
Use the techniques outlined in Using Credit Limits to Constrain Development on Margin to calculate technical debt before and after. In addition to qualifying your Agile success, quantifying technical debt will do a lot towards improving the quality of your software.
Make the Hairs on the Back of Your Neck Stand Up
Cote sent me the recent CIO Magazine article entitled ERP’s Paralysis Problem and the Repercussions for Business Everywhere. The article discusses the findings from a December 2009 study conducted by IDC and sponsored by ERP vendor Agresso, as follows:
A couple of verbatim responses from respondents should make the hairs on the back of your neck stand up: “Capital expenditure priorities are shifted into IT from other high-payback projects” just to perform necessary ERP changes, noted one respondent. Said another: “Change to ERP paralyzes the entire organization in moving forward in other areas that can bring more value.”
To make doubly certain the message gets across, the article finishes with the following “nocturnal” paragraph:
As the sun finally sets on the first decade in the new millennium, it’s high time we say good night to ERP. A new day will be starting soon, and the blemished legacy and failings of ERP’s nearly four-decade-long reign will be a distant memory.
Maybe. While ERP systems no doubt have their own particular twists, the sorry state of affairs described above is true of various industries that have developed complex software systems over prolonged periods of time. Just in the past few months I have witnessed such situations in banking and health care. In previous life I had been exposed to more of the same in other industries. The software decayed and decayed but technical debt had never been reduced. Consequently, the cost of change, any change, today is horrendous. As Jim Highsmith‘s chart below indicates, “once on the right of the curve, all choices are hard.”
In Estimating Software Costs, author Capers Jones quantifies five-year cost of software application ownership (for the vendor). He examines three similar applications, each of nominal size of 1000 function points, as a function of the sophistication of the corresponding projects. The respective life cycle costs are as follows:
- Lagging projects: $2,316,000
- Average projects: $1,860,000
- Leading projects: $1,312,000
Jones goes on to issue the following stern warning:
All known compound objects decay and become more complex with the passage of time unless effort is exerted to keep them repaired and updated. Software is no exception… Indeed, the economic value of lagging applications is questionable after about three to five years. The degradation of initial structure and the increasing difficulty of making updates without “bad fixes” tends towards negative returns on investment (ROI) within a few years.
Enough, indeed, to make the hairs on the back of your neck stand up…
Rusty Automobiles
No, this post is not about today’s GM bankruptcy filing. Rather, it is about coming to terms with a phenomenon similar to rust – software decay.
An IT application development team I met with recently indicated they reached the point of allocating 80% of their resources to software maintenance. Various colleagues of mine report similarly worrisome figures experienced in their practices. As a matter of fact, some of my colleagues consider such figures endemic.
It might indeed be hard to visualize a rusted line of code. Decay, however, applies. To quote Capers Jones:
All known compound objects decay and become more complex with the passage of time unless effort is exerted to keep them repaired and updated. Software is no exception… Indeed, the economic value of lagging applications is questionable after about three to five years. The degradation of initial structure and the increasing difficulty of making updates without “bad fixes” tends towards negative returns on investment (ROI) within a few years.
Hazardous that software decay is operationally and economically, it is lethal once it becomes embedded as a revenue generator in the business design for enterprise software. In particular, high maintenance costs as part of planned obsolescence invariably lead to the sorry state of affairs characterized as “Consumer Underworld” in The Myth of Excellence.
If you find this post a bit dramatic, please read Christensen’s recent post on the titanic efforts to turn things around launched by GM when it was already too late. Christensen concludes his post with a very pointed warning:
If you’re curious to know what lies in store for Seattle and Silicon Valley, spend a day walking around Detroit with the Ghost of Christmas Future.
The Agile Executive 
