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Projects kill teams and flow

Given the No Projects definition of a project as “a fixed amount of time and money assigned to deliver a large batch of value add“, it is not surprising that for many organisations a new project heralds the creation of a Project Team:

A project team is a temporary organisational unit responsible for the implementation and delivery of a project

When a new project is assigned a higher priority than business as usual and the Iron Triangle is in full effect, there can be intense pressure to deliver on time and on budget. As a result a Project Team appears to be an attractive option, as costs and progress can be monitored in isolation, and additional personnel can be diverted to the project when necessary. Unfortunately, in addition to managing the increased risk, variability, and overheads associated with a large batch of value-add, a Project Team is fatally compromised by its coupling to the project lifecycle.

The process of forming a team of complementary personnel that establish a shared culture and become highly productive is denied to Project Teams from start to finish. At the start of project implementation, the presence of a budget and a deadline means a Project Team is formed via:

  1. Cannibalisation – impairs productivity as entering team members incur a context switching overhead
  2. Recruitment – devalues cultural fit and required skills as hiring practices are compromised

Furthermore, at the end of project delivery the absence of a budget or a deadline means a Project Team is disbanded via:

  1. Cannibalisation – impairs productivity as exiting team members incur a context switching overhead
  2. Termination – devalues cultural fit and acquired skills as people are undervalued

This maximisation of resource efficiency clearly has a detrimental effect upon flow efficiency. Cannibalising a team member objectifies them as a fungible resource, and devalues their mastery of a particular domain. Project-driven recruitment of a team member ignores Johanna Rothman’s advice that “when you settle for second best, you often get third or fourth best” and “if a candidate’s cultural preferences do not match your organisation, that person will not fit“. Terminating a team member denigrates their accumulated domain knowledge and skills, and can significantly impact staff morale. Overall this strategy is predicated upon the notion that there will be no further business change, and as Allan Kelly warns that “the same people are unlikely to work together again“, it is an extremely dangerous assumption.

The inherent flaws in the Project Team model can be validated by an examination of any professional sports team that has enjoyed a period of sustained success. For example, when Sir Alex Ferguson was interviewed about his management style at Manchester United he described his initial desire to create a “continuity of supply to the first team… the players all grow up together, producing a bond“. This approach fostered a winning culture that valued long-term goals over short-term gains, and led to 20 years of unrivalled dominance. It is unlikely that Manchester United would have experienced the same amount of success had their focus been upon a particular season at the expense of others.

Therefore, the alternative to building a Project Team is to grow a Product Team:

A product team is a permanent organisational unit responsible for the continuous improvement of a product

Following Johanna’s advice to “keep teams of people together and flow the projects through cross-functional teams“, Product Teams are decoupled from project lifecycles and are empowered to pull in work as required. This enables a team to form a shared culture that reduces variability and improves stability, which as observed by Tobias Mayer “leads to enhanced focus and high performance“. Over a period of time a Product Team will master the relevant business and technical domains, which will fuel product innovation and produce a return on investment that rewards us for making the correct strategic decision of favouring products over projects.

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No Projects

Projects kill flow and teams. Focus on products, not projects

Since the Dawn of Computer Time, enormous sums of money and embarrassing amounts of time have been squandered upon software projects that have delivered little or no return on investment, with projects floundering between segregated Business and IT divisions squabbling over overestimated value-add and underestimated delivery dates. Given Grant Rule’s assertion that “studies too numerous to mention show that software projects are challenged or fail“, why are software projects so prone to failure and why do they persist?

To answer these questions, we must understand what constitutes a software project and why its delivery model is incongruent with product development. If we start with the PRINCE 2 project definition of “a temporary organization that is needed to produce a unique and predefined outcome or result at a pre-specified time using predetermined resources“, we can offer a concise definition as follows:

A project is a fixed amount of time and money assigned to deliver value-add

The key characteristic of a software project appears to be its fixed end date, which as a delivery model has been repeatedly debunked by IT practitioners such as Allan Kelly denouncing “endless, pointless discussions about when it will be done… successful software doesn’t have a pre-specified end date” and Marc Lankhorst arguing that “over 80% of IT spending in large organisations is on maintenance“. However, the fixed end date of a software project is invariably a consequence of its requirement for a collection of value-adding features to be simultaneously delivered, suggesting an augmented definition of:

A project is a fixed amount of time and money assigned to deliver a large batch of value-add

Once we view software projects as large batches of value-add, we can apply The Principles Of Product Development Flow by Don Reinertsen and better understand why so many projects fail:

  1. Increased cycle time – a project might not be deliverable on a particular date unless either demand is throttled or capacity is increased, e.g. artifically reduce user demand or increase staffing levels
  2. Increased variability – a project might be delayed due to unpredictable blockages in the value stream, e.g. testing of features B and C blocked while testing of feature A takes longer than expected
  3. Increased feedback delays – a project might incur significant costs due to slow feedback on bad design decisions and/or defects increasing rework, e.g. failures in feature C not detected until features A and B have passed testing
  4. Increased risk – a project might have an increased probability and cost of failure due to increased requirements/technology change, increased variation, and increased feedback delays
  5. Increased overheads  – a project might endure development inefficiencies due to increased requirements/technology change, e.g. feature C development time increased by need to understand complexity of features A and B
  6. Increased inefficiencies – a project might encounter increased transaction costs due to increased requirements/technology change e.g. feature A slow to release as features B and C also required for release
  7. Increased irresponsibility – a project might suffer from diluted responsibilities, e.g. staff member has responsibility for delivery of feature A but is unincentivised to participate in delivery of features B or C

Don also provides a compelling explanation as to why the project delivery model remains prevalent, by explaining how large batches can become institutionalised as they “appear to have scale economies that increase efficiency [and] appear to reduce variability“. Software projects might indeed appear to be efficient due to perceived value stream inefficiencies and the counter-intuitiveness of batch size reduction, but from a product development standpoint it is an inefficient, ineffective delivery model that impedes value, quality, and flow.

There is a compelling alternative to the project delivery model – product development flow, in which we apply economic theory to Lean product development practices in order to flow product designs through our organisation. Product development flow emphasises the benefits of batch size reduction and encourages a one piece continuous flow delivery model, in order to reduce costs and improve return on investment.

Discarding the project delivery model in favour of product development flow requires an entirely different mindset, as epitomised by Grant urging us to “accommodate the ideas of flow production and lean systems thinking” and Allan affirming that “BAU isn’t a dirty word… enhancing products is Business As Usual, we should be proud of that“. On that basis the No Projects movement was conceived by Joshua Arnold to promote the valuation of products over projects, and anointed as:

Projects kill flow and teams. Focus on products, not projects

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Building Continuous Delivery into an organisation requires radical change

While Continuous Delivery has a well-defined value proposition and a seminal book on how to implement a deployment pipeline, there is a dearth of information on how to transform an organisation for Continuous Delivery. Despite its culture-focussed principles and an adoption process described by Jez Humble as “organisational-architecture-process not tools-code-infrastructure“, many Continuous Delivery initiatives fail to emphasise an organisational model in which software is always releasable. This contravenes Lean Thinking and the Deming 95/5 Rule – that 95% of problems are attributable to system faults, while only 5% are due to special causes of variation. Building an automated deployment pipeline can eliminate the 5% of special causes of variation in our value stream (e.g. release failures), but it cannot address the remaining 95% of problems caused by our organisation structure (e.g. wait times between silos). From this we can infer that:

Continuous Delivery = 95% organisation, 5% automation

Establishing a Continuous Delivery culture requires a change management programme more challenging, time-consuming, and valuable than any technology-based efforts. Donella Meadows recommended that to effect change we “arrange the structures and conditions to reduce the probability of destructive behaviours and to encourage the possibility of beneficial ones“, and we can achieve this by using the change patterns of Linda Rising and Mary Lynn Adams within the change management supermodel of Jurgen Appelo:

  • Dance with the System
  • Mind the People
  • Stimulate the Network
  • Change the Environment

To dance with the system, we propose a made to order Continuous Delivery programme, with a Tailor Made business case that emphasises reduced transaction costs and/or increased customer value according to the needs of our organisation. We must identify a Local Sponsor to support our efforts and a Corporate Angel to increase awareness, and we should communicate successful case studies to our stakeholders as External Validation.

To mind the people, we construct a collaborative, bottom-up change programme that encourages participation. We need to Involve Everyone from the outset, and apply a Personal Touch with each individual stakeholder to pitch Continuous Delivery in terms of their incentives. We should use Corridor Politics to promote our change initiative, Just Say Thanks to our contributors, and highlight value stream waste without dispute – as Morgan Wootten said “a lighthouse doesn’t blow a horn, it shines a light“.

To stimulate the network, we emulate the Diffusion of Innovations theory of Everett Rogers and exploit the social network that comprises our organisation. We must encourage Innovators to spark an interest in our change initiative, and then form a group of Early Adopters to offer us early feedback. We need to Ask For Help from Connectors to evangelise to their peers on our behalf, and by Staying In Touch with our supporters we can work towards an Early Majority invested in Continuous Delivery.

To change the environment, we focus upon changing our organisation structure and processes to instil a culture of Continuous Delivery. We need to radiate our value stream In Your Space to raise awareness of cycle time, lead times, and wait times using Just Enough repackaged Lean terminology (e.g. “average time to market” instead of cycle time). We must work as Bridge Builders between different siloed teams to reduce our communications burden, and we should develop our pipeline Step By Step to encourage the good practices and discourage the bad (e.g. enforcing decouple deployment from release in a user interface).

Building Continuous Delivery into an organisation can be achieved by automating a deployment pipeline and implementing a change management programme, but we should remember Jurgen Appelo’s advice that changing people “is hard to do without an expensive operating table“. Our change programme must be tailored to business requirements, personalised for each stakeholder, and focussed upon improving the environment – and we should always remember:

Building a Continuous Delivery pipeline is easy. Building a Continuous Delivery organisation is hard

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Optimise accessible cycle time constraints, radiate the inaccessible

The goal of Continuous Delivery is to optimise for cycle time, so that we can reduce lost opportunity costs and improve our time-to-market. However, how do we construct a cycle time strategy, and how might it be implemented without a comprehensive change mandate? A study of Continuous Delivery experience reports and Lean Thinking suggests some common impediments to optimising cycle time:

  1. Excessive rework
  2. Long lead times
  3. Incongruent organisation structure

From the above we can therefore form an ideal cycle time strategy:

Optimise cycle time = optimise product integrity + optimise lead times + optimise organisation

Optimising product integrity is essential as rework has a pernicious influence upon delivery cadence, highlighted by David Anderson stating that “unplanned rework due to bugs lengthens lead times… and greatly reduces throughput“. By using practices such as Acceptance Test Driven Development and root cause analysis as well as applying Continuous Delivery principles such as Build Quality In and Repeatable Reliable Process, we can trim our defect waste and gradually remove rework from the value stream.

Optimising lead times encourages us to recognise that unreleased product increments are valueless inventory, and that we should accelerate our pathway to production until we obtain a First Mover Advantage over our competitors. By introducing Work In Progress limits to reduce batch sizes and employing the Continuous Delivery principles of Automate Almost Everything and Bring Pain Forward, we can curtail our inventory waste and deliver value-adding features to our customers faster.

Optimising an organisation offers both the greatest challenge and the greatest potential for cycle time optimisations, particularly in siloed organisations. Despite being described by Jez Humble as a “response to the historical expense of computing resources and the high transaction cost of putting out a release [that results in] lower software quality, lower production stability, and less frequent releases“, it remains a prevalent model despite its inherent coordination costs. By restructuring our organisation into product-centric, cross-functional teams and instilling the Continuous Delivery principles of Everybody Is Responsible and Continuous Improvement, we can eliminate our wait waste and obtain a significant cycle time reduction.

At the outset of our Continuous Delivery programme, a value stream mapping and analysis of product defects will likely indicate our expected cycle time impediments, and we should present these findings to our stakeholders along with our ideal cycle time optimisation strategy. However, the ambitious scope of our strategy means that without executive sponsorship our change mandate is unlikely to extend to such radical notions as establishing cross-functional teams. In this situation we should use the confines of our mandate to derive an organisation-specific optimal cycle time strategy:

Optimise cycle time = optimise product integrity + optimise lead times + optimise organisation

Rather than being discouraged by the limitations of our mandate, we can use it to guide our optimisation efforts according to constraint accessibility. If we cannot optimise the organisation, we optimise lead times. If we cannot optimise lead times, we optimise product integrity. After each successful change is implemented, we communicate to our stakeholders both the net gain in cycle time and the larger, inaccessible potential improvements:

Optimise the accessible, radiate the inaccessible

In this manner we can gradually build confidence in our Continuous Delivery programme, until our change mandate is broadened to encompass the comprehensive change required to dramatically improve both our cycle time and our product revenues.

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Continuous Delivery unaccompanied by organisational change will not reduce cycle time

Our Continuous Delivery value proposition describes a goal of reducing cycle time – the average time for a software release to propagate through to Production – in order to improve our time-to-market, saving time and money that can be invested back into product development and growing revenues. However, it is important to bear in mind that like any cross-organisation transformational programme Continuous Delivery is susceptible to Conway’s Law:

Any organisation that designs a system (defined broadly) will produce a design whose structure is a copy of the organisation’s communication structure

This extraordinary sociological observation predicts that multiple teams working on the same problem will produce disparate solutions, and that the structure of an organisation must be adaptable if product development is to remain sustainable. As a Continuous Delivery pipeline will likely traverse multiple organisational units (particularly in silo-based organisations), these are pertinent warnings that were addressed by Dave Farley and Jez Humble in the principles of Continuous Delivery:

  1. Repeatable Reliable Process
  2. Automate Almost Everything
  3. Keep Everything In Version Control
  4. Bring The Pain Forward
  5. Build Quality In
  6. Done Means Released
  7. Everybody Is Responsible
  8. Continuous Improvement

The majority of these principles are clearly focussed upon culture and behaviours, yet some Continuous Delivery implementations are entirely based upon Reliable Repeatable Process and Automate Almost Everything at the expense of more challenging principles such as Everybody Is Responsible.

For example, in our siloed organisation we are asked to improve the cycle time of an application from 28 days to 14 days, with the existing deployment and migration mechanisms manual processes that each take 20 minutes to perform. We introduce a Continuous Delivery pipeline in which we Automate Almost Everything, we Keep Everything In Version Control, and we establish our Repeatable Reliable Process. However, despite deployment and migration now taking only 5 minutes each, our cycle time is unaffected! How is this possible?

To explain this disheartening situation, we need to use Lean Thinking and examine the value stream of our application. While our new release mechanism has reduced the machine time of each pipeline stage (i.e. time releasing an artifact), the process lead time (i.e. time required to release and sign off a artifact) is largely unaffected. This is because process lead time includes wait time, and in a siloed organisation there are likely to be significant handoff periods both during and between pipeline stages which are “fraught with opportunities for waste“. If the deployment and migration mechanisms have each been reduced to 5 minutes but a 3 hour handoff from server administrator to database administrator remains, our Repeatable Reliable Process will never affect our cycle time.

To accomplish organisational change alongside Continuous Delivery, the most effective method of breaking down silo barriers is to visualise your value stream and act upon waste. Donella Meadows recommended that to effect organisational change you must “arrange the structures and conditions to reduce the probability of destructive behaviours and to encourage the possibility of beneficial ones“, and a pipeline containing a Repeatable Reliable Process is an excellent starting point – but it is not the end. Visualise your pipeline, educate people on the unseen inefficiencies caused by your organisational structure, and encourage an Everybody Is Responsible mentality.

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