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Agile 2.0 in the Cutter Summit

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I will be presenting on the Agile 2.0 subject in the forthcoming Cutter Summit. The premise of my presentation is that markets nowadays are vastly different from those we used to compete in ten years ago. The changes in the markets pose new challenges to software methods. Insofar as Agile methods are concerned, we are starting to see a new generation methods. I perceive these methods as Agile 2.0.

Here is the abstract of my presentation:

Agile, the software method that was conceived as a way to cope with change, is itself dramatically changing. What we are now witnessing is the emergence of Agile 2.0.

Three rapidly converging trends are driving the emergence of Agile 2.0:

  • Markets are becoming hyper-segmented;
  • Markets are also becoming fleetingly transient; and
  • The value chains that serve the markets are dramatically different from yesterday’s value chains.

Traditionally, the Agile movement responded to change by “merging” two strands – development and testing – at the team level. Agile 2.0 extends this single-level approach by simultaneously applying Agile principles at three tiers:

  1. The tier at which development, testing and operations merge
  2. The tier at which strategy and delivery merge
  3. The tier at which problem and solution merge

Agile 2.0 addresses the key challenge posed by “change is changing”: how to solve a problem when it is not understood well enough to produce a viable solution. Rapidly interlinked iterations at all three levels make it possible to substitute learning for planning. It’s through tight feedback loops in and amongst the three levels that the pace of learning accelerates to match the speed of change.

In this presentation, Cutter Fellow and Director of Cutter’s Agile practice, Israel Gat, will divulge the details you need to know about how to implement Agile 2.0 in your organization/company. You’ll get a blueprint for assessing and responding to the new realities of the competitive environment — without compromising the tried and true Agile tenets.

Written by israelgat

December 8, 2011 at 11:12 pm

Super-Fresh Code

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Below is the detailed outline for my August 10, 9:00AM Agile 2011 presentation. I look forward to meeting you and interacting with you in the conference before, during and after this presentation!

Best,

Israel

Super-Fresh Code

Part I: The Changing Nature of Change

  • Traditional View of Agile as a Software Method
  • A New Context for Agile
  • Hyper-Segmented Global Markets
  • A Modern Testing Value Chain
  • Prosumption All the Way to the Brand

Part II: Agile –> Agility

  • Agility as an End-to-End Challenge
  • The Value Delivery Journey
  • Confluence of Agile, Cloud, Mobile and Social
  • Everything as a Service
  • Multiple Forms of Agile

Part III: Your Agile Process has been Obsoleted

  • A Passage in Time with Profound Implications
  • Multi-Level Inspect and Adapt
  • The New Product Backlog
  • The New Nature of Dependency Management
  • New Story Format
  • “Not Reaching the Mainstream” Patterns
  • More Than an Obsoleted Process

Part IV: What’s Next?

  • From Contents per Profile to Features per Profile
  • No Temporal Anchor
  • A Mere Matter of Emergence

Part V: It Takes Multiple Levels of Agility

  • Agile as a Software Method
  • Agility at the Enterprise Level
  • Agility as a Continuous Improvement  Philosophy

Written by israelgat

August 4, 2011 at 7:03 am

Posted in Events, Trends

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Code2Cloud: Bigger than a Disruption in ALM

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Update, October 22, 2010: Watch this excellent demo of Code2Cloud!

 

 

http://en.wikipedia.org/wiki/File:ALM.svg

Figure 1: A Representation of the Application Lifecycle Management Concepts

VMware’s Code2Cloud announcement a couple of days ago is intriguing. According to this announcement, the whole development infrastructure is delivered as a service with no setup, no hardware or software to manage. The tedious and time consuming task of setting (and as appropriate modifying) the environment within which coding is carried out is done by Code2Cloud, not by the programming/testing team. As pointed out by colleague and friend Michael Cote, Code2Cloud might have the potential to be quite a disruption in Application Lifecycle Management (ALM):

“The software development tool chain has always been tedious to setup and integrate,” said Red Monk analyst Michael Cote. “While cloud-based development promises to make application delivery, deployment, and use easier, I haven’t seen excellent unified application management approaches that take full advantage of cloud. VMware’s SpringSource Code2Cloud is an ambitious step towards moving much of the development management stack into the cloud and hopefully vacuuming up those tedious application management tasks. It’ll be fun to watch this idea evolve as more and more people and applications start taking advantage of cloud computing.”

Important that such a disruption in the ALM space might be, I believe the main significance of the Code2Cloud announcement is in demonstrating so vividly how powerful the Everything as a Service (EaaS) paradigm could be and probably will be. IMHO Code2Cloud is another proof point to the power of the confluence of Agile, Cloud, Mobile and Social. It is a virtuous cycle of unprecedented impact – in technology delivery, in the structure of markets, in society and in the patterns of living we are accustomed to.

© Copyright 2010 Israel Gat

Figure 2: The Virtuous Cycle of Agile, Cloud, Mobile and Social

The Code2Cloud announcement is primarily about the {Agile –> Cloud} link in Figure 2. The {Cloud –> Mobile}, {Mobile –> Social} and {Social –> Agile} are just as powerful. For example, the {Social –> Agile} link, in conjunction with Cloud and Mobile, opens the door for highly efficient Testing as a Service.

Think of the Code2Cloud as a great example of Everything as a Service. Many other examples of such services are forthcoming. The common denominator of all these examples to come is their transformative power. Not in the tactical sense of “transformative”, but in the deep strategic meaning of the word.

Action item: Start a pilot to evaluate Code2Cloud. Expand rapidly if it meets your development needs. Tie at the earliest point in time to your plans for application delivery, deployment and use in the cloud.

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Wrestling with governing your software from a lifcycle perspective? Let me know if you would like assistance in implementing a simple yet highly effective software governance framework that can be used by both technical and non-technical members of your staff. Click Services for details and contact information.

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Written by israelgat

October 21, 2010 at 7:19 am

A New Chasm is Forming

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http://www.flickr.com/photos/96483949@N00/192144459/

Recently I had frustrating experiences with the bureaucracies of two companies: a company who is bringing me in to consult on continuous value delivery and another company who is interested in a seminar on the consumerization of enterprise software. While the two companies could not be more different, good-hearted engagement managers in both companies cautioned me in advance that their bureaucracies would drive me nuts. Based on my experience to date they were not kidding…

It is a striking contrast between the ease with which I can get precious data from my social network anytime I need it versus the unbelievable waste of time answering the very same question in two or three redundant forms used to screen me as a supplier. This contrast leads me to conclude we are witnessing the formation of a new chasm. It is between companies who stick to their old bureaucratic patterns with respect to suppliers versus those that realize that a supplier these days is a “prosumer.” He/she might provide services one day, consume (other) services the other day.

The business opportunity this chasm presents is providing efficient marketplace infrastructures. Anyone who can collect my data once and provide it as needed to multiple companies I interact with as a supplier will be doing me, and countless number of social networking aficionado, a huge service. Time is simply too precious to be wasted typing in the maiden name of my mother multiple times.

The distinguished economist Ronald Coase perceived reduction of transaction costs as the essence of the firm. His thoughts of more than 70 years ago are right on these days. The bar for transaction costs is “fill in the details only once”. Once in this context means “once in your lifetime.”

Recommendation: Examine the  way your company acquires new customers versus the way it brings aboard suppliers. Something is wrong if your company’s procurement folks routinely tell suppliers “we know you have already given this information, but ‘they’ would not accept it from ‘us’ if you don’t fill this extra form as well.” This being the case, you need to rethink your approach to composite value chains.

Written by israelgat

October 13, 2010 at 7:40 am

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.

Footnotes:

[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 Supply Side of the Consumerization of Enterprise Software

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Source: http://www.flickr.com/photos/bertboerland/2944895894/

In my recent post about the consumerization of enterprise software I discussed two factors that are likely to accelerate the pace toward such consumerization:

  1. Any department/business unit that can get a service in entirety from an outside source is likely to do so without worrying about enterprise software and/or data center considerations. This is already happening in Marketing. As other functions start doing so, more and more links in the value chain of enterprise software will be “consumerized.” In other words, these services will be carried out without the involvement of the IT department.
  2. Once the switch-over costs from legacy code to state-of-the-art code are less than the steady state costs (to maintain and update legacy code), the “consumerization” of enterprise software is going to happen with ferocious urgency.

In this post I would like to add a third factor – the buying pattern. My contention is that the buying pattern for micro-apps will spread to enterprise application. Potential demand for buying in this way is huge. Supply for buying enterprise software as micros-apps is not quite there yet, but it would take only one smart vendor to start transforming the traditional pattern how enterprise software is chunked, offered and sold.

Think about your recent experience downloading an application to your smart mobile phone. You did not go through a six-month evaluation period; you did not do a comprehensive competitive analysis; you did not check how well the seller does customer support in Sumatra. You simply paid something like $7.99 and downloaded the application. You are more than happy if it fulfills your needs in a reasonable manner. If it does not, you simply buy another application with the functionality you desire. Maybe you are a little more cautious now and ask a friend or send an inquiry to your Twitter followers before you pick the new application. Whatever you might choose to do, the fundamental facts are: A) you can afford to lose $7.99; and, B) your time is more precious than the sunk cost of the application. You simply move on.

This buying pattern is not something that you are going to forget when you step into your office in the morning. It makes perfect sense to you and it would be good for your company. You would rather concentrate on your business than on the tricky language of clause number 734 in the contract that your department’s attorney prepared for licensing yet another piece of enterprise software.

The ‘$7.99 experience’ you and zillion other folks like you had over the past week or the past month makes enterprise software vendors extremely vulnerable. The “high-touch; high-margin; high-commitment” [1] business design is not sustainable once the purchase model changes.  The expensive machinery of professional services, system engineering and customer support is not affordable at the face of competition that constructs modular chunks of enterprise software and sells them at a price the customer can afford to write off (if they do not perform to satisfaction). Maybe the ceiling in the enterprise to ‘forget about this application and move on’ is no higher than $1,000 (instead of ‘no higher than $7.99’ for the private citizen), but a smart vendor can still make a lot of money on selling at one thousand dollars a pop to the enterprise.

The growing gap between “this lovely application on my iPhone” and the “headache of licensing traditional enterprise software” is an immense incentive for up-and-coming software vendors to use the ‘$7.99 experience’ as the heart of a new business design. This new business design can be simply summarized as “low-touch; low-margin; low commitment” [2]. And, yes, it is very disruptive to the incumbents…

My hunch is that the IT Service Management (ITSM) industry will be the first to crumble. The premise of “service delivery” sounds a little hollow in a cloud computing world characterized by “everything as a service” [3]. Would a buyer be really willing to pay for “service for the service” from a vendor who does not actually provide the underlying service?! It sounds like paying a Fidelity or a Vanguard investment manager to manage a portfolio of their own mutual funds for you…

All it takes for this shift to start – in ITSM or in another part of enterprise software –  is one successful vendor.

Footnotes:

[1] I am indebted to Annie Shum for this phrase.

[2] Ibid.

[3] I am indebted to Russ Daniels for this phrase.

How to Break the Vicious Cycle of Technical Debt

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The dire consequences of the pressure to quickly deliver more functions and features to the market have been described in detail in various posts in this blog (see, for example, Toxic Code). Relentless pressure forces the development team to take technical debt. The very same pressure stands in the way of paying back the debt in a timely manner. The accrued technical debt reduces the velocity of the development team. Reduced development velocity leads to increased pressure to deliver, which leads to taking additional technical debt, which… It is a vicious cycle that is extremely difficult to break.

Figure 1: The Vicious Cycle of Technical Debt

The post Using Credit Limits to Constrain “Development on Margin” proposed a way of coping with the vicious cycle of technical debt – placing a limit on the amount of technical debt a development team is allowed to accrue. Such a limit addresses the demand side of the software development process. Once a team reaches the pre-determined technical debt limit (such as $3 per line of code) it cannot continue piling on new functions and features. It must attend to reducing the technical debt.

A complementary measure can be applied to the supply side of the software development process. For example, one can dynamically augment the team by drawing upon on-demand testing. uTest‘s recent announcement about securing Series C financing explains the rationale for the on-demand paradigm:

“The whole ‘appification’ of software platforms, whether it’s for social platforms like Facebook or mobile platforms like the iPhone or Android or Palm, or even just Web apps, creates a dramatically more complex user-testing matrix for software publishers, which could mean media companies, retailers, enterprise software companies,” says Wienbar. “Anybody who has to interact with consumers needs a service to help with that testing. You can’t cover that whole matrix with your in-house test team.”

Likewise, on-demand development can augment the development team whenever the capacity of the in-house team is insufficient to satisfy demand. IMHO it is only a matter of little time till marketplaces for on-demand development will evolve. All the necessary ‘ingredients’ for so doing – Agile, Cloud, Mobile and Social – are readily available. It is merely a matter of putting them together to offer on-demand development as a commercial service.

Whether you do on-demand testing, on-demand development or both, you will soon be able to address the supply side of software development in a flexible and cost-effective manner. Between curtailing demand through technical debt limits and expanding supply through on-demand testing/development, you will be better able to cope with the relentless pressure to deliver more and quicker than the capacity of your team allows.