When BA means B∪<<$#!t Artist

BA typically means Business Analyst, but what makes for a good BA?  When do you have a good BA and when don’t you? Many projects fail at the beginning due to incomplete, inconsistent, and overly verbose analysis produced by BAs.

Are your BAs any good?  The success of many projects depend on the ability of the BA do correctly identify the problem you are trying to solve.  If your BA is not competent then you are doomed before you start.

RubiksCubeBusiness analysis consists of all facets of solving business problems. Business analysis is a role executed by project, product, and engineering managers.  However, there are people that do business analysis as their main role and we simply label them as business analysts or product managers. We shall stick to the term business analyst for simplicity.

Business analysts perform a range of tasks including:

  • Gathering requirements
  • Writing business cases and project charters
  • Performing gap analysis between products and corporate processes

Ever suspect that the people responsible for performing business analysis for you are not up for the challenge?  Here are three simple questions; good business analysts will get all three correct and not take longer than 20 seconds.

  Context Question
#1  MullerLyerLines Which of these two lines is longer?
#2  paris_spring_puzzle What does this sign say?
#3 I have two products whose prices add up to $1.10 and one product is $1 more than the other. How much is the more expensive product?

The answers are:

  1. The lines are the same length
    1. Take a ruler if you are not convinced
  2. Paris in the the spring
    1. Notice that the occurs twice
  3. The more expensive product is $1.05
    1. If the more expensive one had been $1 then the cheaper one would be $0.10 but then the expensive one would only be $0.90 more expensive than the cheaper one.

Jumping+to+conclusionsThese three questions illustrate that the mind can jump to conclusions that are often wrong.  The mind can be tricked because it assesses things quickly and only some people have the instinct to double check their results.

Most BAs are well educated; however, the interesting thing is that studies show that educated people are less able to see their biases and they jump to conclusions more readily than other people.1

A good business analyst realizes that during analysis there will be situations where the mind will jump to conclusions.  Many business analysts are asked to resolve conflicting requirements, recognize missing requirements, and deal with biases coming from many different sources.  Unless you have the reflex of checking facts for consistency and eliminating bias then you won’t make a good business analyst.

So what is the quality of your BAs?

Other articles

Bibliography

West, Richard F. and Meserve, Russel J. Cognitive Sophistication does not Attenuate the Bias Blind Spot. Journal of Personality and Social Psychology.

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No Business Case = Failed Project

A business case comes between a bright idea for a software project and the creation o that project. Project Timeline, Business Case

  • To – idea to have a project is born
  • Tcheck – formal or informal business case
  • Tstart – project is initiated
  • Tend – project finishes successfully or is abandoned

Not all ideas for software projects make sense.  In the yellow zone above, between idea and project being initiated, some due diligence on the project idea should occur.  This is where you do the business case, even if only informally on the back of a napkin.

The business case is where you pause and and estimate  whether the project is worth it, i.e. will this project leave you better off than if you did not do it.

For those who want precise definitions the project should be NPV +ve.  In layman’s terms, the project should leave the organization better off on it’s bottom line or at least improve skill levels so that other projects are better off.

Projects that do not improve skills or the bottom line are a failure.

Out of 10 software projects (see Understanding your chances):

  • 3 are successful
  • 4 are challenged, i.e. over cost, over budget, or deliver much less functionality
  • 3 will fail, i.e. abandoned

This means that the base rate of success for any software project is only 3 out of 10.

Yet executives routinely execute projects assuming that they can not fail even though the project team knows that the project will be a failure from day 1.

Business cases give executives a chance to stop dubious projects before they start. (see Stupid is as Stupid Does)

Understanding how formal the business case needs to be comes down to uncertainty. There are three key uncertainties with every project:

  • Requirements uncertainty
  • Technical uncertainty
  • Skills uncertainty

When there is a moderate amount of uncertainty in any of these three areas then a formal business case with cash flows and risks needs to be prepared.

Requirements Uncertainty

Requirements uncertainty is what leads to scope shift (scope creep).  The probability of a project failing is proportional to the number of unknown requirements when the project starts (see Shift Happens).

Requirements uncertainty is only low for two particular projects: 1) re-engineering a project where the requirements do not change, and 2) the next minor version of a software project.

For all other software projects the requirements uncertainty is moderate and a formal business case should be prepared.

Projects new to you have high requirements uncertainty.

Technical Uncertainty

Technical uncertainty exists when it is not clear that all requirements can be implemented using the selected technologies at the level of performance required for the project.

Technical uncertainty is only low when you have a strong understanding of the requirements and the implementation technology. When there is only a moderate understanding of the requirements or the implementation technology then you will encounter the following problems:

  • Requirements that get clarified late in the project that the implementation technology will not support
  • Requirements that can not be implemented once you improve your understanding of the implementation technology

Therefore technical uncertainty is high when you are doing a project for the first time and requirement uncertainty is high.  Technical uncertainty is high when you are using new technologies, i.e. shifting from Java to .NET or changing GUI technology.

Projects with new technologies have moderate to high uncertainty.

Skills Uncertainty

Skills uncertainty comes from using resources that are unfamiliar with the requirements or the implementation technology.  Skills uncertainty is a knowledge problem.

Skills uncertainty is only low when the resources understand the current requirements and implementation technology.

Resources unfamiliar with the requirements will often implement requirements in a suboptimal way when requirements are not well written.  This will involve rework; the worse the requirements are understood the more rework will be necessary.

Resources unfamiliar with the implementation technology will make mistakes choosing implementation methods due to lack of familiarity with the philosophies of the implementation libraries.  Often after a project is complete, resources will understood that different implementation tactics should have been used.

Formal or Informal Business Cases?

An informal business case is possible only if the requirements, technical, and skills uncertainty is low.  This only happens in a few situations:

  • Replacing a system where the requirements will be the same and the implementation technology is well understood by the team
  • The next minor version of a software system

Every other project requires a formal business case that will quantify what kind of uncertainty and what degree of uncertainty exists in the project.  At a minimum project managers facing moderate to high uncertainty should be motivated to push for a business case (see Stupid is as Stupid Does). Here is a list of projects that tend to be accepted without any kind of real business case that quantifies the uncertainties:

  • Change of implementation technology
    • Moving to object-oriented technology if you don’t use it
    • Moving from .NET to Java or vice versa
  • Software projects by non-software companies
  • Using generalists to implement technical solutions
  • Replacing systems with resources unfamiliar with the requirements
    • Often happens with outsourcing

Projects with moderate to high risks and no business case are doomed to fail.

Related articles

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Enhancements don’t belong in the bug tracker

Not my faultAs development progresses we inevitably run into functionality gaps that are either deemed as enhancements.

These issues often get captured by QA in the bug tracker and assigned to a developer.

Enhancements should not be managed from the bug tracker

The life cycle of a defect and the life-cycle of a enhancement are two entirely different things.  A defect is a difference between a stated requirement and the code. If there is no documentation there is no code defect (see It’s not a bug, it’s…) — in fact, most enhancements will eventually be coded by some developer; they just should not be managed from the bug tracker.

Defect Life-cycleDefectLifecycle

The defect life-cycle is well known:

  • Defect is identified as a departure from the requirements
  • Defect is assigned to a developer
  • Defect is corrected
  • Correct is verified
    • If not corrected re-open and re-assign to developer
  • The defect is closed

This is the incorrect way to manage enhancements.  When a functionality gap is determined by QA and it is not covered by the requirements then we have an issue.  It is rarely the case that the issue can be resolved by the developer.

Enhancement Life-cycle

If enhancements are assigned to a developer then they are likely to try to resolve the issue. The problem is that “enhancements” determined at the QA level may be phantom problems caused by either:

  1. Insufficient requirements
  2. Correct requirements but incorrect test plans

Enhancements may or may not become code changes.  Even when enhancements turn into code change requests they will generally not be implemented as the developer or QA think they should be implemented.

Enhancements are really requirement defects. Enhancements should be logged as such in the bug tracker and assigned to the person in charge of requirements (business analyst or product manager).  Those individuals should be responsible to track down how these issues should be handled.

If the requirements are correct and the test plans are defective then it should be logged as a test defect.  This is tricky because QA often controls the bug tracker and will not log errors that they have made.

At a minimum, the implementation of requirements and test defects can do several positive things for you:

  1. It removes the responsibility to find a solution from development.
  2. It makes it clear how many defects are in the requirements or test plans.
  3. It reduces stress; no developer wants to be blamed for an issue that is not his.
  4. Many enhancements call for updated project plans and pushing back the deadline.

Put Responsibility Where it Belongs

The creation of requirements and test defects in the bug tracker goes a long way to cleaning up the bug tracker.  In fact, requirements and test defects represent about 25% of defects in most systems (see Bug Tracker Hell and How to Get Out!).  The percentages break down as follows:

  • Requirements defects: 9.58%
  • Testing defects: 15.42%

The creation of requirement and test defects in the bug-tracker alleviate pressure on the engineering department and redirect it  to either the product manager or QA. Eventually enough data will accumulate in the bug-tracker to get management’s attention.

At a minimum, these categories should help reduce the amount of fire-fighting in late projects (Root cause of ‘Fire-Fighting’ in Software Projects)

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It’s not a bug, it’s…

When does a bug become a bug?
Who decides that it is a bug?

Caution, BugHow many legs does a lamb have if I say the tail is a leg?  The answer is 4, just because I say the tail is a leg does not make it a leg!

Bugs should be obvious, but we say It’s not a bug, it’s a feature because often it isn’t obvious.  Watson Humphrey felt that we should use the term defect and not bug because most people don’t take bugs seriously, so let’s use the term defect instead.

So when does a defect become a defect?

  • When quality assurance tells you that you have a defect?
  • When product management says that it is a defect?
  • When the customer says that it is a defect?

The answer is: none of the above.

Now it might turn out that there is a problem and that code needs to change, but a defect only exists if:

code behaves differently than the requirements specification

This is important because most systems are under specified (if they are specified at all) and so when code misbehaves it is only a defect if the code behavior differs from the specification.  We call defects undocumented features because we know that the problem is that the requirements were never written.

Incomplete and Inconsistent Requirements

Many organizations do not create sufficiently complete requirements before starting development, either because they don’t know how to capture requirements properly or because they don’t have resources capable of capturing complete requirements. Incomplete (and inconsistent) requirements and unrealistic deadlines often force developers into making decisions about how to implement features.  The end result is that developers are regularly told that they have defects in their code.

While this process is common, it is destructive.  When requirements are under specified and inconsistent developers end up needing to perform serious rework. The rework will can require dramatic changes that will impact the architecture of the code.

The time required to find a work around (if it is possible) is rarely included in the project plan. Complicating matters is that the organizations that are reluctant to spend time creating requirements also tend to underestimate their projects.  This puts tremendous pressure on the engineering department to deliver; this promotes the 5 worst practices in software development (see Stop It! No… really stop it.)

Only 54% of Issues are Resolved by Engineers

The attitude that all defects must be resolved by the engineering department is severely misguided.  Analysis by Capers Jones of over 18,000+ projects shows that only about 54% of all defects can be resolved by the engineers! (only the 3 highlighted rows below)

Defect Role Category Frequency Role
Requirements defect 9.58% BA/Product Management
Architecture or design defect 14.58% Architect
Code defect 16.67% Developer
Testing defect 15.42% Quality Assurance
Documentation defect 6.25% Technical Writer
Database defect 22.92% Data base administrator
Website defect 14.58% Operations/Webmaster

This means that precious time will be wasted assigning issues to developers that they can not resolve.  The time necessary to redirect the issue to the correct person is a major contributing factor to fire-fighting

Getting Control of the  Defect Process

For most organizations fixing the defect process involves understanding and categorizing defects correctly.  Organizations that are not tracking the different sources of defects probably have a bug tracker that has gone to hell.  Here is how you can fix that problem, see Bug Tracker Hell and How To Get Out!

At a minimum you need to implement the requirements defect, once you identify issues that are caused by poor requirements it will shine the white hot light of shame onto the resources that are capturing your requirements.  Once you realize how many requirements defects exist in your system you can begin to inform senior management about the requirements problem.

Reducing Fire-Fighting

Fire fightingThe best way to reduce fire fighting is to start writing better requirements (or writing requirements 🙂 ).  To do so you need to figure out which of the following are broken:

  1. Not enough time is allocated to the requirements phase
  2. Unskilled people are capturing your requirements

In all likelihood both of these issues need to be fixed in your organization.  When requirements are incomplete and inconsistent you will have endless fire-fighting meetings involving everyone (see Root cause of ‘Fire-Fighting’ in Software Projects)

Stand your ground if someone tells you that you have coded a defect when there is no documentation for the requirement.

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Stupid is as stupid does

StupidIsAsStupidDoesSenior management does not set out to have a failed project, however, when the failure rate is 7 out of 10 projects you wonder what the problem is.

As Ma Gump stated, “stupid is as stupid does“, that is, smart people sometimes do stupid things.  The collective IQ of a project is reduced by the number of managers involved in the project.

Now from a human perspective, something very interesting is going on here.  For example, suppose you were give the following choices:

  1. An 80% chance of making $100
  2. A guaranteed $40

If people behaved according to expected value then everyone would choose the first choice.  However, because humans are risk averse, almost everyone will choose the second alternative with guaranteed money.

Now out of 10 software projects:

  • 3 will succeedExecutives, Understanding your chances, PedestriansCrossingStreet
  • 4 will be challenged
  • 3 will outright fail

To put that in perspective, if you were watching people cross the street at an intersection:

  • 3 cross the street successfully
  • 4 get maimed
  • 3 get killed

How interested would you be in crossing that street?

You can Google “software project failure rates” to see that this has been demonstrated by multiple reliable institutions over every industry.  Challenged projects are generally projects which go over budget and under deliver a software solution that can be declared a moral victory by management.

So if human beings are risk averse and the odds of project success are so low then:

Why does senior management ignore risks on software projects?

Damn the torpedoes, full speed aheadThe only possible conclusion is that senior management can’t conceive of a their projects failing. They must believe that every software project that they initiate will be successful, that other people fail but that they are in the 3 out of 10 that succeed.

This inability to understand the base rate of failure in software development is systemic. There are so many software projects that are started by senior management where the technical team knows that the chance of success is 0% from the start.

Senior management is human and is risk averse, you just need to find a way to remind them of this. One way to get senior management to think twice about projects is to make sure that there is a meeting before launching the project where management is asked the following question:

Assume that this project will fail, why would it have failed? What will the consequences be?

This exercise (if done seriously) may have the effect of causing senior management to realize that the project can indeed fail. With luck, the normal risk aversion that every human being is endowed with will kick in and the project may get re-evaluated.

Related Articles

Bibliography

Kahneman, Daniel. Thinking, Fast and Slow.

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Are we there yet?

Are We There YetWe associate “are we there yet?” with kids asking incessantly if a long trip is almost over.  It is generally funny, however, it is less funny on a project that should be complete.

Projects follow distinct phases:

  1. Basic requirements are collected
  2. Project plan and end date are established
  3. Development starts
  4. Projects track to the project plan

Often, tasks start off well until they all level off at 90-95% complete and get stuck.  Management was satisfied with progress until progress stall, they see frantic activity picking up and they wonder “are we there yet?.

Like a family vacation, this trip is sometimes not even close to being finished.  You  expect that if 9,000 hours have been spent on a project estimated at 10,000 hours that you would be 90% done.  Surprisingly this is not the case for 7 projects out of 10 — have you ever worked on a project where a 90% project plan meant the project was 90% done?

Project PlanUsing a project plan to estimate completion is useful if there is a direct correlation between the project goal and the project plan. You often discover that the goal and the plan differ late in a project. Project plans and results differ because

  • Requirements and tasks are missing
  • The project is incorrectly estimated
  • Work is performed on tasks that do not advance the project

Requirements and Tasks are Missing

Clearly missing requirements mean that more work will be necessary to get to the goal, but the time for this work is rarely added to the project deadline.

A relative of missing requirements is missing tasks, this occurs when the work breakdown structure is incomplete and more subtasks are necessary to complete a task than estimated.

In both cases, if there are 2,000 hours of missing requirements and tasks then a project initially forecasted for 10,000 hours should move the deadline to 11,000 hours.  Therefore if 9,000 hours are done then you are only 75% complete.

OverbearingUnfortunately, weak IT leadership, internal politics, and embarrassment over  poor estimates will not move the deadline and teams will have pressure put on them by overbearing senior executives to get to the original deadline even though that is not possible.

The Project is Incorrectly Estimated

There is much literature about how accurate estimates are possible and necessary to successful projects.  Weak and uniformed IT leadership will cave in to senior management demands for project deadlines without formal estimates.  A typical interaction looks as follows:

CEO: We need feature X, how much will it cost and how long will it take to built?

VP Engineering: Well we need to define feature X properly, see how it will be implemented, determine if we have the necessary skill sets, and see what the impact to our other operations will be.  It will take time to do do this work.

CEO: We don’t have time for formal estimates.  How hard can it be to add feature X?  But next Friday, I will need a ballpark estimate for time and cost.

VP Engineering: I’ll see what I can come up with for next week.

Weak IT executives allow themselves to be bullied all the time by other executives that have no idea what is involved in IT projects.  The end result is an underspecified project that will be underestimated in time and cost (see Why Executive Declared Deadlines lead to Disaster)

The more inaccurate the requirements the more extra work there is to do to get to the target.  That is why short requirements processes lead to strongly shifting requirements and cancelled projects (see Shift Happens).  In fact, the degree of requirements shift is equal to the chance of a project being cancelled.

Work is Performed that Does Not Advance the Project

Even if a project is correctly specified, there are several activities that will be performed that will not advance the project:

  • Some requirements can not be implemented as specified and time will be spent researching and implementing work arounds
  • Some requirements will be ambiguously specified and be implemented incorrectly and need to be redone
  • Some requirements will be inconsistent and require time and analysis to establish consistent requirements
  • Infrastructure might need to be refactored when you discover that it will not support the code created later

ReworkWork executed on these activities will not advance your project and should not be counted in the total of completed hours.  So if 2,000 hours have been spent on activities that don’t advance the project then if 9,000 hours have been done on a 10,000 hour project then you have really done 7,000 hours of the 10,000 hour project and you are only 70% done.

Not Changing the Deadline Leads to Bad Practices

Whether a project is off course because of missing activities or non-productive activities, not changing the project end date will lead to schedule pressure as the project advances and people slowly start to realize that you are not going to make it.

HopeIsNotAStrategy

When it becomes clear that a project can’t make it’s original deadline many organizations will start common but deadly practices.  Excessive schedule pressure often leads to the following bad practices (see Stop It! No… Really stop it.):

  • Friction within the team
  • Friction amongst the managers
  • Inadequate communication with  stakeholders
  • Layoffs of key personnel

Solutions

There are only a few cures for the ‘Are we there yet?‘ problem:

  1. IT management with the intestinal fortitude to hold out for the creation of proper work breakdown structures and formal estimates
  2. Proper requirement processes that yield complete, consistent, and concise requirements
  3. Proper change management processes to alter the project deadline when missing tasks and non-productive activities are encountered

Failure to comply with these 3 principles means that you will continue to be subject to chaotic environments where 7 out of 10 projects fail (see Executives: Understanding your Chances of a Successful Project)

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SR&ED and Eligibility

Most Canadian corporations know that the Canada Revenue Agency (CRA) gives out tax credits for Scientific Research and Experimental Development (SR&ED) work done by technical companies. This tax credit works out to 35% of the qualifying work and can be as high as 68% when overhead is factored in.

The Scientific Research part of the name makes some organizations assume that unless you are curing cancer, building rockets, or building a better mouse-trap that they must be engaged in rocket science to qualify for the tax credit — nothing could be further from the truth.

For organizations involved in software development the key to claiming SR&ED is the Experimental Development part of the title.  Assuming that you have a project which has technical uncertainty then you will qualify for the tax credit.

So what qualifies as technical uncertainty?

Technical uncertainty occurs when you face a business problem that is well specified with skilled resources and it is unclear how to proceed.  Examples of technical uncertainty would be needing to:

  • double the number of transactions that you currently process
  • increase the efficiency of an compression algorithm
  • implement a security model that does not exist

Experimental development occurs when you hit a fork in the proverbial development road and it is unclear which direction to take.  

Sometimes you will know that there are multiple design alternatives and have to create prototypes for the different alternatives to determine the best solution. Sometimes you will choose a design alternative and have to abandon the choice and back-up and take another path.  In both cases there is a clear decision point where code needs to be tested for multiple alternatives.

There is actually an easy way to know if you are facing technical uncertainty and facilitate applying for SR&ED tax credits.  Most developers do not like reinventing the wheel; when faced with a requirement that is technically challenging most developers will Google it to see if there is a solution to the problem.  If your developers are regularly looking for technical solutions odds are that you have SR&ED eligible work.

Saving technical searches is the easiest way to figure out how much SR&ED eligible work you have.

If you search for a technical solution to a challenge and discover:

  1. There is a solution for the problem but it is proprietary
  2. There is an available solution that would cost too much to acquire

Then this work will be SR&ED eligible if it leads to experimental development.  The CRA does not require that you be the first to solve a technical problem, only that you search for public solutions before executing experimental development.

What isn’t technical uncertainty?

There are a few issues which can masquerade as technical uncertainty and the CRA will not pay SR&ED credits for them:

  • Training
  • Poor requirements

If a COBOL programmer starts to develop software in Java then you will end up with quite a bit of experimental development as the programmer learns the new language.  However, the CRA will not pay for you to train developers.   Experimental development only occurs when developers who are familiar with the technologies that you are using (language, O/S, IDE, API) and then engage in experimental development.

To be explicit, the following would not qualify:

  • Language, Java developers needing to do C#
  • O/S, Developers familiar with Windows development developing on Android tablets
  • IDE, Developers familiar with Eclipse needing to use Sun’s NetBeans
  • API, Developers familiar with one SQL database switching to the API of another SQL database

Only competent developers that hit technical uncertainty and face experimental development qualify for SR&ED.

The CRA will not pay for you to figure out what your requirements are.  While you are working out your “business rules” you may look like you are resolving a technical challenge as you attempt multiple alternative paths.  However, creating code to solve a business problem does not qualify for SR&ED.

Changing requirements because of a technical challenge does qualify

How do I know if I did Experimental Development?

The CRA gives you up to 18 months from a fiscal year end to claim your tax credits.  The problem is that if you wait this long none of your developers will remember what they did!

If your year end was March 31, 2011 then as of today (August 27, 2012) you can still claim your tax credits from 2011.  The problem is that your developers will have trouble remembering what they did from March 31, 2010 to March 31, 2011.

Frankly speaking, you would be lucky to have your developers recall what they did last month. When looking back over time, there are two kinds of development that easily qualify for SR&ED:

  1. Work abandoned for a technical reason
  2. Building multiple prototypes to solve a technical problem

If you were trying to accomplish something, let’s say implementing a fine grain security model in a database and were forced to abandon the work for a technical reason then this will qualify for SR&ED.  If you abandoned the work because you no longer had the requirement, i.e. a business reason, then the work would not qualify for SR&ED.

If you ran up against a technical challenge and there were multiple design alternatives that lead to multiple prototypes being tried, then the work qualifies for SR&ED.  Even if the multiple design alternatives involved 3rd party software, as long as there were multiple prototypes and you had to write code then this work should qualify.

Document your technical challenges right away!

How do I Simplify the SR&ED Process?

The easiest way to simplify the SR&ED process is to track experimental development as it happens.  Once your developers solve a problem and use that solution for a few months then they will forget how difficult it was to solve the problem.

There are several techniques to help in the documentation of your SR&ED claim for the next year:

  1. Save your technical searches
  2. Tag your tasks in your project management system
  3. Train project managers to recognize SR&ED tasks
When the developers search for technical solutions and find none have them save the search (PDF, web page, etc).   If you work on several projects simultaneously then create a directory under each project where the developer will save the search.  In your project management system then have the developer document this information.

In your project management system (JIRA, Redmine, etc) have a tag for SR&ED so that tasks can be tagged for SR&ED.  As the developer or project manager discovers SR&ED tasks you can tag these tasks so that computing the hours for SR&ED next year will be easy.

Train your project managers to look for SR&ED tasks.  Inevitably, if a developer has a task that expands for a technical reason then he will have to notify the project manager about the event.  That will be the best time for the project manager to recognize SR&ED tasks and update the project management system.

Summary

All companies should make sure to have SR&ED trained people help you to make your claim.   The number of companies making SR&ED claims has increased strongly in the last few years and the CRA is more strict with regards to which projects qualify.
Do not be afraid to claim your SR&ED tax credits, if you have technical challenges that involve experimental development then they are yours.  Also, keep in mind that the earlier that you document your technical challenges the easier (and cheaper) it will be to make your SR&ED claim.

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Uncertainty trumps Risk in Software Development

Successful software development involves understanding uncertainty, and uncertainty only comes from a few sources in a software project.  The uncertainties of a software project increase with the size of the project and the inexperience of the team with the domain and technologies.The focus on this article is on uncertainty and not on risk.  In part 1 we discussed uncertainty and in part 2 we discussed risk, so it should be clear that:

All risks are uncertain, however, not all uncertainties are risks.

For example, scope creep is not a risk (see Shift Happens) because it is certain to happen in any non-trivial project.  Since risk is uncertain, a risk related to scope creep might be that the scope shifts so much that the project is canceled.  However, this is a useless risk to track because by the time it has triggered it is much too late for anything proactive to be done.

It is important to understand the uncertainties behind any software development and then to extract the relevant risks to monitor.  The key uncertainties of a software project are around:

  • requirements
  • technology
  • resources
  • estimating the project deadline

Uncertainty in Requirements
There are several methodologies for capturing requirements:

  • Business requirements document (BRD) or software requirement specification (SRS)
  • Contract-style requirement lists
  • Use cases (tutorial)
  • User stories

Regardless of the methodology used, your initial requirements will split up into several categories:

The blue area above represents what the final requirements will be once your project is completed, i.e. the System To Build.  The initial requirements that you capture are in the yellow area called Initial Requirements.

With a perfect requirements process the Initial Requirements area would be the same as the System To Build area.  When they don’t overlap we get the following requirement categories:

  1.  Superfluous requirements
  2. Missing requirements

Superfluous initial requirements tends to happen in very large projects or projects where the initial requirements process is incomplete.  Due to scope shift the Missing requirements category always has something in it (see Shift Happens).  If either of these two categories contains a requirement that affects your core architecture negatively then you will increase your chance of failure by at least one order of magnitude.

For example, a superfluous requirement that causes the architecture to be too flexible will put the developers through a high learning curve and lead to slow development.

If scalability is a requirement of the architecture but it is missing during the initial architecture then you will discover that it is difficult and costly to add later.


The physical equivalent would be the apartment building here on the right.  The foundation was insufficient to the needs of the building and it is slowly collapsing on one side.  Imagine the cost of trying to fix the foundation now that the building is complete.

I’ve been in start-ups that did not plan for sufficient scalability in the initial architecture; subsequently, the necessary scalability was only added with serious development effort and a large cost in hardware. Believe me, throwing expensive hardware at a software problem late in the life cycle is not fun or a practical solution :-(.


The overlapping box, Inconsistent Requirements, is to categorize known and missing requirements that turn out to be in conflict with other requirements.  This can happen when requirements are gathered from multiple user roles all of whom have a different view of what the system will deliver.

It is much easier and faster to test your requirements and discover inconsistencies before you start developing the code rather than discover the inconsistencies in the middle of development.  When inconsistencies are discovered by developers and QA personnel then your project will descend into fire-fighting (see Root cause of ‘Fire-fighting’ in Software Projects).

The physical equivalent here is to have a balcony specified to one set of contractors but forget to notify another set that you need a sliding door (see right).  When the construction people stumble on the inconsistency you may have already started planning for one alternative only to discover that rework is necessary to get to the other requirement.

Note, if you consistently develop software releases and projects with less than 90% of your requirements documented before coding starts then you get what you deserve (N.B. I did not say before the project starts 🙂 ).   One of the biggest reasons that Agile software development stalls or fails is that the requirements in the backlog are not properly documented; if you Google “poor agile backlogs” you will get > 20M hits.

Requirements Risks
Some risks associated with requirements are:

  • Risk of a missing requirement that affects the core architecture
  • Risk that inconsistent requirements cause the critical path to slip

Uncertainty in Technology
Technical uncertainty comes  from correctly using technology but failing to accomplish the goals as outlined by your requirements; lack of knowledge and/or skills will be handled in the next section (Uncertainty Concerning Resources).  Team resources that don’t have experience with technology (poorly documented API, language, IDE, etc) does not constitute a technical risk it is a resource risk (i.e. lack of knowledge).

Technical uncertainty comes from only a few sources:

  • Defective APIs
  • Inability to develop algorithms


Unforeseen defects in APIs will impact one or more requirements and delay development.  If there is an alternative API with the same characteristics then there may be little or no delay in changing APIs, i.e. there are multiple choices for XML parsing in Java with the same API.

However, much of the time changing to another API will cause delays because the new API will be implemented differently than the defective one. There are also no guarantees that the new API will be bug free.

Mature organizations use production APIs, but even then this does not protect you against defects.  The best known example has to be the Pentium bug from Intel discovered in 1994.  Although the bug did not seem to cause any real damage, any time you have an intermittent problem the source might always be a subtle defect in one of the APIs that you are using.

Organizations that use non-production (alpha or beta) APIs for development run an extremely high risk of finding a defect in an API.  This generally only happens in poorly funded start-ups where the technical team might have excessive decisional control in the choice of technologies.

The other source of technical uncertainty is the teams inability to develop algorithms to accomplish the software goals.  These algorithms relate to the limitations of system resources such as CPU, memory, batteries, or bandwidth concern, i.e.:

  • Performance
  • Memory management
  • Power management
  • Volume of data concerns

Every technical uncertainty is associated with one or more requirements.  The inability to produce an algorithm to satisfy a requirement may have a work-around with acceptable behavior or might be infeasible.

If the infeasible requirements prevents a core goal from being accomplished then the project will get canceled.  If affected requirements have technical work-arounds then the project will be delayed while the work-around is being developed.

Technical Risks
Some risks associated with technology are:

  • Risk that a defective API will cause us to look for another API
  • Risk that we will be unable to find a feasible solution for a core project requirement

Uncertainty Concerning Resources
When using the same team to produce the next version of a software product there is little to no resource uncertainty.  Resource uncertainty exists if one of the following are present:

  • Any team member is unfamiliar with the technology you are using
  • Any member of the team is unfamiliar with the subject domain
  • You need to develop new algorithms to handle a technical issue (see previous section)
  • Any team member is not committed to the project because they maintain another system
  • Turnover robs you of a key individual

Resource uncertainty revolves around knowledge and skills, commonly this includes: 1) language, 2) APIs, 3) interactive development environments (IDEs), and 4) methodology (Agile, RUP, Spiral, etc).  If your team is less knowledgeable than required then you will underestimate some if not all tasks in the project plan.

When team members are unfamiliar with the subject domain then any misunderstandings that they have will cause delays in the project.  In particular, if the domain is new and the requirements are not well documented then you will probably end up with the wrong architecture, even if you have skilled architects.

The degree to which you end up with a bad architecture and a canceled project depends on how unfamiliar you are with the subject domain and technologies being used.  In addition, the size of your project will magnify all resource uncertainties above.

The majority of stand-alone applications are between 1,000 and 10,000 function points.  As you would expect, the amount of the system that any one person can understand drops significantly between 1,000 and 10,000 function points.  The number of canceled projects goes up as our understanding drops because all uncertainties increase and issues fall between the cracks.  N.B. The total % of the system understood by a single person drops precipitously between 1,000 and 10,000 function points.

When there are team members committed to maintaining legacy systems then their productivity will be uncertain.  Unless your legacy system behaves in a completely predictable fashion, those resources will be pulled away to solve problems on an unpredictable basis.  They will not be able to commit to the team and multi-tasking will lower their and the teams productivity (see Multi-tasking Leads to Lower Productivity).

Resource Risks
Some risks associated with resources are:

  • The team is unable to build an appropriate architecture foundation for the project
  • A key resource leaves the project before the core architecture is complete

Uncertainty in Estimation
When project end dates are estimated formally you will have 3 dates: 1) earliest finish, 2) expected finish, and 3) latest finish.  This makes sense because each task in the project plan can finish in a range of time, i.e. earliest finish to latest finish.  When a project only talks about a single date for the end date, it is almost always the earliest possible finish so there is a 99.9% chance that you will miss it.  Risk in estimation makes the most sense if:

  • Formal methods are used to estimate the project
  • Senior staff accepts the estimate

There are numerous cost estimating tools that can do a capable job.  Capers Jones lists those methods, but also comments about how many companies don’t use formal estimates and those that do don’t trust them:

Although cost estimating is difficult there are a number of commercial software cost estimating tools that do a capable job:  COCOMO II, KnowledgePlan, True Price, SEER, SLIM, SoftCost, CostXpert, and Software Risk
Master are examples.

However just because an accurate estimate can be produced using a commercial estimating tool that does not mean that clients or executives will accept it.  In fact from information presented during litigation, about half of the cases did not produce accurate estimates at all and did not use estimating tools.  Manual estimates tend towards optimism or predicting shorter schedules and lower costs than actually occur.   

Somewhat surprisingly, the other half of the case had accurate estimates, but they were rejected and replaced by forced estimates based on business needs rather than team abilities. 

Essentially, senior staff have a tendency to ignore formal estimates and declare the project end date.  When this happens the project is usually doomed to end in disaster (see Why Senior Management Declared Deadlines lead to Disaster).

So estimation is guaranteed to be uncertain.  Let’s combine the requirements categories from before with the categories of technical uncertainty to see where our uncertainty is coming from.  Knowing the different categories of requirements uncertainty gives us strategies to minimize or eliminate that uncertainty.
Starting with the Initial Requirements, we can see that there are two categories of uncertainty that can addressed before a project even starts:
  1. Superfluous initial requirements
  2. Inconsistent requirements

Both of these requirements will waste time if they get into the development process where they will cause a great deal of confusion inside the team.  At best these requirements will cause the team to waste time, at worst these requirements will deceive the team into building the architecture incorrectly.  A quality assurance process on your initial requirements can ensure that both of these categories are empty.

The next categories of uncertainty that can be addressed before the project starts is:

  1. Requirements with Technical Risk
  2. Requirements Technically Infeasible

Technical uncertainty is usually relatively straight forward to find when a project starts.  It will generally involve non-functional requirements such as scalability, availability, extendability, compatibility, portability, maintainability, reliability, etc, etc.  Other technical uncertainties will be concerned with:

  1. algorithms to deal with limited resources, i.e. memory, CPU, battery power
  2. volume of data concerns, i.e. large files or network bandwidth
  3. strong security models
  4. improving compression algorithms

Any use cases that are called frequently and any reports tie up your major tables are sources of technical uncertainty.  If there will be significant technical uncertainty in your project then you are better off to split these technical uncertainties into a smaller project that the architects will handle before starting the main project.  This way if there are too many technically infeasible issues then at least you can cancel the project.

However, the greatest source of uncertainty comes from the Missing Requirements section.  The larger the number of missing requirements the greater the risk that the project gets canceled.  If we look at the graph we presented above:

You can see that the chance of a project being canceled is highly correlated with the % of scope creep. Companies that routinely start projects with a fraction of the requirements identified are virtually guaranteed to have a canceled project.

In addition, even if you use formal methods for estimation, your project end date will not take into account the Missing Requirements.  If you have a significant number of missing requirements then your estimates will be way off.

Estimation Risks

The most talked about estimation risk is schedule risk.  Since most companies don’t use formal methods, and those that do are often ignored, it makes very little sense to talk of schedule risk.

When people say “schedule risk”, they are making a statement that the project will miss the deadline.  But given that improper estimation is used in most projects it is certain that the project will miss its deadline , the only useful question is “by how much?“.

Schedule risk can only exist when formal methods are used and there is an earliest finish/latest finish range for the project.  Schedule risk then applies to any task that takes longer than its latest finish and compromises the critical path of the project.  The project manager needs to try to crash current and future tasks to see if he can get the project back on track.  If you don’t use formal methods then this paragraph probably makes no sense 🙂

Conclusion

The main sources of uncertainty in software development comes from:

  • requirements
  • technology
  • resources
  • estimates

Successful software projects look for areas of uncertainty and minimize them before the project starts. Some uncertainties can be qualified as risks and should be managed aggressively by the project manager during the project.

Uncertainty in requirements, technology, and resources will cause delays in your project.  If you are using formal methods than you need to pay attention to delays caused by uncertainties not accounted for in your model.  If you don’t use formal methods then every time you hit a delay caused by an uncertainty, then that delay needs to be tacked on to the project end-date (of course, it won’t be 🙂 ).

If your project does not have strong architectural requirements and is not too big (i.e. < 1,000 function points) then you should be able to use Agile software development to set-up a process that grapples with uncertainty in an incremental fashion.  Smaller projects with strong architectural requirements should set up a traditional project to settle the technical uncertainties before launching into Agile development.

Projects that use more traditional methodologies need to add a quality assurance process to their requirements to ensure a level of completeness and consistency before starting development.  One way of doing this is to put requirements gathering into its own project.  Once you capture the requirements, if you establish that you have strong architectural concerns, then you can create a project to build out the technical architecture of the project.  Finally you would do the project itself.  By breaking projects into 2 or 3 stages this gives you the ability to cancel the project before too much effort is sunk into a project with too much uncertainty.

Regardless of your project methodology; being aware of the completeness of your requirements as well as the technical uncertainty of your non-functional requirements will help you reduce the chance of project cancellation by at least one order of magnitude.

It is much more important to understand uncertainty that it is to understand risk in software development.


Appendix: Traditional Software Risks
This list of software risks courtesy of Capers Jones.  Risks listed in descending order of importance.

  • Risk of missing toxic requirements that should be avoided
  • Risk of inadequate progress tracking
  • Risk of development tasks interfering with maintenance
  • Risk of maintenance tasks interfering with development
  • Risk that designs are not kept updated after release
  • Risk of unstable user requirements
  • Risk that requirements are not kept updated after release
  • Risk of clients forcing arbitrary schedules on team
  • Risk of omitting formal architecture for large systems
  • Risk of inadequate change control
  • Risk of executives forcing arbitrary schedules on team
  • Risk of not using a project office for large applications
  • Risk of missing requirements from legacy applications
  • Risk of slow application response times
  • Risk of inadequate maintenance tools and workbenches
  • Risk of application performance problems
  • Risk of poor support by open-source providers
  • Risk of reusing code without test cases or related materials
  • Risk of excessive feature “bloat”
  • Risk of inadequate development tools
  • Risk of poor help screens and poor user manuals
  • Risk of slow customer support
  • Risk of inadequate functionality
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Uncertainty and Risk in Software Development (2 of 3)

[Part 1 of 3 is here.]

Defining Risk and its Components

There are future events whose impact can have a negative outcome or consequence to our project. A future event can only be risky if the event is uncertain. If an event is certain then it is no longer a risk even if the entire team does not perceive the certainty of the event, e.g. individuals know that the project is late even though the project manager and senior staff do not.

Risks always apply to a measurable goal that we are trying to achieve; if there is no goal there can be no risk, i.e. a project can’t have schedule risk if it has no deadline.

Once a goal has been impacted by a risk we say that the risk has triggered. The severity of the outcome depends on how
far it displaces us from our goal. Once triggered, there should be a mitigation process to reduce the severity of the possible outcomes.

Before looking at software project risks tied to these goals, let’s make sure that we all understand the components of risk by going through an example.

Risk Example: Auto Collision

Let’s talk about risk using a physical example to make things concrete. The primary goal of driving a car is to get from point A to point B. Some secondary goals are:

  • Get to the destination in a reasonable time
  • Make sure all passengers arrive in good health.
  • Make sure that the car arrives in the same condition it departs in.

There is a risk of collision every time you drive your car:

  • The event of a collision is uncertain
  • The outcome is the damage cost and possible personal injury
  • The severityis proportional to the amount of damage and personal injury sustained if there is an accident
    • If there is loss of life then the severity is catastrophic

A collision will affect one or more of the above goals. Risk management with respect  to auto collisions involves:

  • Reducing the probability of a collision
  • Minimizing the effects of a collision

There are actions that can reduce or increase the likelihood of a collision is:

  • Things that reducethe chance of collision
    • Understanding safe driving techniques
    • Driving when there are fewer drivers on the road
    • Using proper turn signals
  • Things that increasethe chance of collision

By taking the actions that reduce a collision while avoiding the actions that increase it we can reduce the probability or likelihood of a
collision.

Reducing the likelihood of a collision does not change the severity of the event if it occurs. The likelihood of an event
and its consequence are independent even if there are actions that will reduce the likelihood and consequences of an event, i.e. driving slowly.

If an auto collision happens then a mitigation strategy would attempt to minimize the effect of the impact. Mitigation strategies with respect to auto collision are:

  • Wear a seat belt
  • Drive a car with excellent safety features
  • Have insurance for collisions
  • Have the ability to communicate at all times (i.e. cell phone, etc)

Having a mitigation strategy will not reduce the chance of a collision, it will only lessen the severity.

Goals of a Software Project

The primary goals of a software project are:

  • Building the correct software system
  • Building the system so that its benefits exceed its costs (i.e. NPV positive)

Building the Correct Software System

What is the correct software system? Cartoons similar to this one are easily found on the Internet:

The correct system is shown in the last frame of the cartoon; so let’s define the correct system as what the customer actually needs. To build the correct system we will need to have correct requirements.

How Long Will The Project Take?

Let’s assume we have complete and consistent requirements for a correct system. How long will it take to build this system? One approach is to take a competent team and have them build out the system without imposing a deadline. Once the system is built we would have the actual time to build the system (Tbuild) .

Tbuild is theoretical because unless you are using an Agile methodology you will want to estimate (Testimate) how long it takes to produce the system before you start. Nonetheless, given your resources and requirements Tbuild does exist and is a finite number; as one of my colleagues used to say, “the software will take the time that it takes“.

Most executives want to know how long a project is going to take before the project starts. To do this we take the requirements and form an estimate (Testimate)
of how long the system will take to build. The key point to note here is that the actual time to build, Tbuild, and the estimated time to build the system, Testimate , will be different. The key thing to keep in mind is that Testimate is only valid to the extent that you use a valid methodology for establishing an estimate.

Building the System so that its Benefits Exceed its Costs

Building a system so that its benefits exceed its costs is equivalent to saying that the project puts money on the organization’s bottom line. We hope that an organization will do the following:

  • Define the system correctly (project scope)
  • Assess the financial viability of the project (capital budgeting)
  • Establish a viable project plan

Financial viability implies that the available resources will be able to produce the desired system before a specific date (Tbuild < Tviable then the organization will have a financial failure.

The problem is that we don’t know what financial failure. We need to have a reasonable expectation that the project is viable BEFORE we build it out. Therefore we use a proxy by estimating the time (Testimate) it will take to build the software from our project plan.

Once we have a time estimate then we can go forward on the project if Testimate, for a project can be done in multiple ways:

Software Project Risks

There are several primary risks for a software project:

  • Schedule risk
  • Estimation risk
  • Requirements risk
  • Technical risk

We often confuse schedule risk and estimation risk. Schedule risk is the risk that the tasks on the critical path have been under estimated and the project will miss the end date (i.e. Testimate). A project that takes longer than the
estimate is not necessarily a failure unless Tviable.

You can only talk meaningfully about schedule risk in projects where:

  • formal estimation techniques are used
  • proper task dependency analysis is done
  • project critical path is identified

Most of us do not work for organizations that are CMM level 4+ (or equivalent),
so you are unlikely to be using formal methods. When the project end date is arbitrary (i.e. method 2 or 3 above) it is not meaningful to talk about schedule risk, especially since history shows that we underestimate how long it will take to build the system, i.e. Testimate<<< Tbuild. When formal methods are not used (i.e. method 2 or 3 above) then the real issue is estimation risk and not schedule risk.

The real tragedy is when an IT departments attempt to meet unrealistic dates set by management when a realistic date would still yield a viable project (below). Unfortunately, unrealistic deadlines will cause developers to take short cuts and usually cripple the architecture. So that when management gives you additional time after their date fails, the damage to the architecture is terminal and you can’t achieve the initial objective.

Requirements risk is the risk that we do not have the correct requirements and are unable to get to a subset of the requirements that enables us to build the correct system prior to the project end date. There are many reasons for having incorrect requirements when a project starts:

  • The customer can not articulate what he needs
  • Requirements are not gathered from all stakeholders for the project
  • Requirements are incomplete
  • Requirements are inconsistent

Technical risk is the risk that some feature of the correct system can not be implemented due to a technical reason. If a technical issue has no work around and is critical to the correct system then the project will need to be abandoned.

If the technical issue has a work around the:

  • If the technical issue prevents the correct system from being built then we have requirements risk
  • If the technical work around takes to long it can trigger schedule risk

Last part (3 of 3):

  • Discuss other risks and how they roll up into one of the 4 risks outlined above
  • Discuss how risk probability and severity combines to form acceptable or unacceptable risks
  • Discuss risk mitigation strategies
  • Discuss how to form a risk table/database
  • Discuss how to redefine victory for informal projects
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Uncertainty and Risk in Software Development (1 of 3)

To develop high quality software consistently and reliably is to learn how to master complexity. You master complexity when you understand the different sources of uncertainty and the different risk characteristics of each uncertainty. Uncertainties introduce delays in development as you attempt to resolve them. Resolving uncertainties always involves alternative designs and generally affects your base architecture. Poor architecture choices will increase code complexity and create uncertainty as future issues become harder to resolve in a consistent manner.

Confused? Let’s untangle this mess one issue at a time.

Uncertainty

The key principle here is that uncertainty will introduce delays in development. Let’s look at the average speed of development. The Mythical Man Month conjectures that an average developer can produce 10 lines of production code per day regardless of programming language. Let’s assume for the sake of argument that todays developers can code 100 lines of code per day.

Development speed is limited because of meetings, changed and confused requirements, and bug fixing. Suppose we print out all the source code of a working 200,000 line program. If we ask a programmer to type this code in again, they are likely to be typing at least 2,000 lines of code per day. So to develop the program from scratch would have taken 2,000 man days, but to type it in again would only take 100 man days.

The time difference has to do with uncertainty. The developer that develops the application from scratch faces uncertainty whereas the developer that types in the application faces no uncertainty.

If you have ever done mazes you discover that to do the maze from the entry to the exit point involves making decisions, and this introduces delays while you are thinking. However, try doing a maze from the exit back to the entry, you will find there are few decisions to make and it is much faster. Fewer decisions from resolving uncertainty faster leads to fewer delays.

It is always faster to do something when you know the solution.

Sources of Uncertainty

The major sources of uncertainty are:

  • Untrained developers
  • Incomplete and inconsistent requirements
  • Technical challenges

We use the term “learning curve” to indicate that we will be slower when working with new technologies. The slope of the learning curve indicates how much time it will take to learn a new technology. If you don’t know the programming language, libraries/APIs, or IDE that you need to work with this will introduce uncertainty.

You will be constantly making syntax and semantic errors as you learn new languages, but this should pass rather quickly. What will take longer is learning about the base functionality provided by the libraries/APIs. In particular, you will probably end up creating routines only to discover that they are already in the API. Learning a new IDE can take a very long time and create serious frustration along the way! Incomplete and inconsistent requirements are a big source of uncertainty.

Incomplete requirements occur when you discover new use cases as you create a system. They also occur when the details required to code are unavailable, i.e. valid input fields, GUI design, report structure, etc. In particular, you can end up iterating endlessly over GUI and report elements – things that should be resolved before development starts.

Inconsistent requirements occur because of multiple sources of requirements as well as poor team communication. Technical challenges come in many forms and levels of difficulties. A partial list of technical challenges includes:

  • Poorly documented vendor APIs
  • Buggy vendor APIs
  • Interfacing incompatible technologies
  • Insufficient architecture
  • Performance problems

In all cases technical challenge is resolved either by searching for a documented solution in publications, on the Internet, or by trial an error. Trial and error can be done formally or informally but involves investigating multiple avenues of development, possibly building prototypes, and then choosing a solution.

While you are resolving a technical challenge your software project will not advance. A common source of uncertainty is insufficient architecture.

Insufficient architecture occurs when the development team is not aware of the end requirements of the final software system. This happens when only partial requirements are available and/or understood by the developers. The development team lays down the initial architecture for the software based on their understanding of the requirements of the final software system.

Subsequently, clarified requirements or new requirements make developers realize that there was a better way to implement the architecture. The developer and manager will have a conversation that is similar to:


Manager: We need to have feature X changed to allow Y, how soon can we do this?

(pause from the developer)

Developer: We had asked if feature X would ever need Y and we were told that it would never happen. We designed the architecture based on that. If we have to have behavior Y it will take 4 months to fix the architecture and we would have to rewrite 10% of the application.

Manager: That would take too long. Look I don’t want you to over engineer this, we need to get Y without taking too much of a hit on the schedule. What if we only need to have this for this screen?

(pause from the developer)

Developer: If we ONLY had to do it for this one screen then we can code a work around that will only take 2 weeks. But it would be 2 weeks for every screen where you need this. It would be much simpler in the long run to fix the architecture.

Manager: Let’s just code the work around for this screen. We don’t have time to fix the architecture.


The net effect of insufficient requirements is that you end up with poor architecture. Poor architecture will cause a technical challenge every time you need to implement a feature that the architecture won’t support.

You will end up wasting time every time you need to work around your own architecture.

Management will not endorse the proper solution, i.e. fixing the architecture, because they have a very poor understanding that every work around that is made is pushing the project closer and closer to failure. Eventually the software will have so many work-arounds that development will slow to a crawl. It is interesting that the project will probably fail, yet, soon enough the organization will attempt to build the same software using the same philosophy.

There is never enough time to get the project done properly, but there will always be enough time to do it again when the project fails.

http://www.geekherocomic.com/2009/06/03/clever-workaround/

Summary

  • Uncertainty comes from several sources
    • Untrained personnel (language, API, IDE)
    • Inconsistent and incomplete requirements
    • Technical challenges

Next part (2 of 3)

  • Defining and understanding risk
  • Matching uncertainties and risks
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