How to maximise the work not done

Recently, due to a new exciting engagement, I have been thinking a lot about simple ways to explain the advantages of iterative incremental delivery over big bang releases. When speaking to C-level executives, coaches like me often have very little time, so we need to be able to engage with language they understand to make those few minutes count.

Money and impact on revenue seems to be a topic that is widely understood and accepted, so I have used and will use it during those conversations. My recent musings have brought me to a place where there is a currency that for modern organisations might be more important than revenue itself. Knowledge.

Now, let me expose differences between iterative incremental delivery and bing bang releases in terms of revenue and of knowledge.

Let’s start with revenue.

This picture is probably familiar to most of the agile/lean coaches out there and it is a good one to start the conversation on why releasing often while monitoring our customers behaviours has an immediate positive effect

revenue

From the picture is clear that incremental delivery has an earlier return on investment, while for big bang we have to wait until time t1 to get any return.

This is quite powerful but I don’t think it tells the full story.

Can we express the differences in term of something else?

To look at other aspects of the full story, we need to start visualising a different dimension than the usual revenue or $.

This new dimension is the currency of modern organisations, and it is called knowledge.

Let’s look at what happens with knowledge in a big bang delivery approach:

bigbang

At the start of envisioning and planning we start building knowledge about what the customer wants but at the same time, being humans and fallible, we start building wrong assumptions about it. We will get full knowledge (wisdom) only after the release date t1. At that point we will be able to validate our assumptions and will build the knowledge about what the customer really wants. Isn’t it a bit too late?

Now let’s look at the same dimensions for an incremental iterative delivery

incremental

As we can see, even in our iterative incremental world we build up wrong assumptions about what the customer wants, the difference is that we disprove them very quickly by delivering early and validating them through customer behaviour. This reduces the risk of building assumptions over wrong assumptions but most of all frees our mind to look at how the customer behaves using our product and understand it better. As you can see the assumptions get eliminated and rebuilt often but the knowledge grows continuously. This is very different from our previous graph, what happens if we overlay the two is the following

Maximising the amount of work not done

Every time we deliver a small increment we must ask ourselves 2 questions:

  1. Have we satisfied our customer needs?
  2. Do we still need to do more to satisfy them?

worknotdone

Given K the point at which we can answer one of the 2 questions with a NO then a decision that impacts on the amount of work to be done can be made.

Case A: If at point K i have enough knowledge to decide that I have done enough to satisfy the customer and any other added work will have diminishing return on investment, I can decide to stop.

Case B: It at point K I have enough knowledge to decide that the customers aren’t happy with the product and I am losing revenue, I can decide to stop.

In cases A and B the red area is the work not done as a consequence of my decision. Such decision could not be taken with the knowledge gained with a big bang release if not AFTER the release and all the work had been done.

So, in conclusion, you should use iterative incremental delivery to maximise the amount of work not done. This way, you will save money on work not done, will have the opportunity to spend that money on something your customers really want, obviously through iterative incremental and knowledge seeking delivery.

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From Consulting to Coaching, what’s the difference for the client?

“An expert is a man who has made all the mistakes which can be made, in a narrow field.” Niels Bohr

In order to resolve complex problems, organisations often hire experts for help.

When I am such expert, very early in the engagement I explain how I can help resolve the problem they have in a few different ways.

What I tell them is that I can provide my service at three different levels:

  1. Coaching, where I help the people i coach ask the right questions, find the answers within themselves and resolve the problem.
  2. Mentoring, where I use a combination of coaching, training and also offer some options that might help resolve the problem .
  3. Consulting, where I either solve the problem as individual contributor (doing) or give instructions in order to solve the problem (telling)

The idea is that the paying client will decide what service level he requires, but the decision is not very straight forward if I only provide the three definitions above.

Lately I have found useful using a new approach (new to me) to help my clients make the right choice. With this approach, I show the impact of each of the different levels of service on “things” paying clients care about.

I use three simple visualisations, if you think they can help you, feel free to use them. If you have another interesting visualisation you found useful, please share it with me.

Future dependence on my service

Dependence

Through this view the client will be able to see how one approach is going to create a dependence on my service to be continued in the future, while the opposite is going to remove completely the need for my service. This is useful for clients to verify what fits better with their long term strategy on dealing with problems similar to the ones I am helping resolve.

Time to Resolution:

TimetoResolution

Through this view I highlight the impact of the approach on the time that it will take to resolve the problem I have been hired for. This will help the customer make a decision based on the urgency of the problem. The more urgent the more to the left we will go.

Resistance to Change

ResistancetoChange

This view in my opinion is extremely important because it is not always obvious to my clients but has massive impact on the organisation’s ability to deal with the result of my work.

If I am a specialist working on my own (doing) i won’t have any resistance as I am the one that is changing to resolve the problem. If I have to tell other people how to change to resolve a problem by giving instructions (telling) I am very likely going to be told “go away!”. If I exercise power to apply the change, things won’t be much better as people will do what I say but on a spectrum from unhappy compliant to angry saboteur. If I help people find the right way to change for the better, I will acquire many allies that will be invested in making change happen and most importantly sustain it in the long run.

Are we shifting left or in a continuous loop?

leftI just read a refreshing point of view on a subject I love, from one of my testing heroes, Janet Gregory.

Before proceeding, please take your time to read her point of view.

I use it

I have been using the Shift Left and even Shift Right terminology, as we say in Dublin, for donkeys years. I am not sure who I heard it from, I seem to vaguely recall a conversation with Gojko Adzic, or was it Dan North? I am getting more and more forgetful, whomever I pick I am very likely wrong, so forget about where i heard it from. and let’s move on.

I love it, it’s leaner!

I have to say I love Shift Left, it has helped me and my teams understand where we needed to take our attention to. In my mind it was never only about redistributing testing activities, but it brought great emphasis on prevention over detection, going towards a leaner testing, some people like to call #NoTesting.

I am all for prevention and I was always going to end up with the Shift Left party.

I understand

Now, reading what Janet says, I understand perfectly where she is coming from and there is no denying that the continuous infinity loops models describe the new reality much better than Shift + direction does.

Was it always like this?

Software development today is certainly non linear 100% agree.

Now correct me if I am wrong here, but waterfall is linear.

The water goes in one direction and there is no going back unless we are on some planet with different gravitational laws, which would be pretty cool to see now that i think about it 🙂

The key is “what” are you shifting from?

My take is that, maybe, in the early days, testers suffering with a bad waterfall hungover, would have understood Shift Left with more ease than if presented with the new continuous models (that in fact, didn’t exist yet).

We are improving

Think about being a waterfall tester in the mid late 200x. You are in a room and I talk to you about how to think and use Shift left. Somebody else maybe Janet, talks to you of either of the (excellent) continuous models we have today. What do you reckon you are going to do next?

If I had to guess, I’d say you’d Shift left. It is easier to understand if all you know is waterfall.

There is a left, a right and a centre in waterfall and people get it when you ask them to go left.

It was the first step to move from waterfall to agile, at least for me.

I see the continuous models as the reflection of the growing maturity of modern testers.

We are ready

We are now ready, bring the new continuous models on and let’s leave the shifting to rally drivers.

The models are good now, because testers are ready to understand, embrace and apply them.

Janet, thank you so much for making me think!

 

 


					

The hidden dangers of Process Debt

Most of us involved in software development are familiar with the term “technical debt”.

As a quick reminder, it was introduced by Ward Cunningham to describe the phenomenon that occurs when we use code that is easy to implement in the short run instead of applying the best overall solution we have identified.

It is by definition a conscious decision to take a shortcut for short term gratification (like taking out a new credit card for a holiday) that in thew long term will cost us to spend extra time in development when improving the system (like paying interest on the credit card debt).

Until the capital is repaid in full we will always pay interest when adding features to the system as the debt creates obstacle to adding new code efficiently.

Ward suggests that when we are in a situation of rushing something out we need to be conscious that we will have to pay the capital in the future or the interests will cripple us.

Ward suggests refactoring as a solution to paying off technical debt.

I really like Ward’s vision and I want to expand the metaphor one level up.

Now if we change the word “software” in my description of technical debt above with “processe” we can define Process Debt.

Replacing we get:

Process Debt is the phenomenon that occurs when we use a processes that is easy to implement in the short run instead of applying the best overall solution we have identified.

Let’s look at one example

You notice that lately the system seems to be more unstable than usual. You know this because there are more calls from customer care and more defects get raised.

Option 1: You want to get to the bottom of the situation and believe that a root cause analysis with 5 whys could get you there. If you use this approach you will probably identify a change in your process to help you prevent some defects in the future.

Option 2: You implement a better policy for developers to select the defects to work on reducing the time the defects are in the unresolved queue while maintaining new features creation throughput relatively stable.

You know Option 1 is better in the long run because it will generate a change in the process to reduce the amount of rework. This will mean less time spent fixing and more time spent on new features that as a consequence means higher throughput and lower lead time for new features.

Option 1 requires some investment. You need to hold one or more root cause analysis sessions, identify the problem(s) experiment with solutions until you find a solution that mitigates your problem.

If you are under pressure, because the new product needs shipping and the old defects need fixing, you are likely to choose option 2.

By doing this you have introduced process debt

The capital of this debt is the lack of change in the process  you could have identified if using Option 1.

Oh, yes, I forgot, change is difficult.

The worst part of it is the interest on the debt you will pay forever until you pay the capital. This interest will appear in the form of.
1. bugs keep on coming, we seem to be fixing bugs all the time
2. new features get delayed because now the queue is in the new features to be delivered
3. the lead time of any new feature is expanded by a factor X
4. the customers continue on complaining because of your defects in production
5. your product owner starts being annoyed at the amount of work spent by the development team on defects
6. developers are tired of always fixing defects
7. …
n. need I say more?

This interest will be paid for the rest of your life if you don’t fix the problem.

Months after you are covered in defects, are stressed by your customers and change job.

Is this healthy? Certainly not.

Is there a cure? Oh yes, indeed.

Continuous improvement has the same effect on process that refactoring has on software. It repays the capital of your process debt.

With small changes in the form of experiments you will be able to clearly discuss the problem that the team is having and make small tweaks continuously.

My esteemed colleague and fervid innovator Claudio Perrone presents his continuous improvement model called PopcornFlow saying

If change is hard, make it continuous

I could not agree more.

By making process change a continuous activity, we enable behaviours that will stay with teams forever and we unleash the power of people’s creativity in improving their own way of working.

 

 

Test coach versus test specialist, impact on queues

I recently had a very interesting conversation with a group of skilled testers on whether or not there should always be a test specialist in a cross-functional team.

A lot of people say yes, my personal experience says not.

My personal experience tells me that the most effective and efficient approach uses a test coach that slowly makes himself scarce. My experience focuses on creating competencies for completing an activity (testing) in a collaborative context.

One aspect I am finding difficult to explain is the impact on queues of a test coach approach, I will use a series of Scenarios and pictures to facilitate my reasoning.

If you feel like substituting activity A = development and activity B = testing feel free, but this approach is activity agnostic in my experience as I have applied it to analysis, and development obtaining similar results.

Scenario 1 – Test specialist

In the presence of one specialist on Activity B and many specialists on activity A.
Problem: Long q
ueues form in Ready for Activity B (Case1) or worse specialist multitasks on many activities at the same time slowing down flow of work as per Little’s law (Case2)

Screen Shot 2017-05-29 at 10.40.47

Scenario 2 – Test coach

Stage 1: In the presence of one coach on Activity B and many specialists on activity A
Initially coach pairs on Activity B with people that do activity A. This way we obtain 2 benefits:

  1. Queue in “Waiting for Activity B” is reduced as one person normally performing activity A is busy pairing with coach on one activity B task
  2. By pairing on activity B feedback loops are shortened
  3. Person with activity A acquires new skills to perform activity B from pairing with coach
  4. Quality of activity B increases as it is a paired activity
  5. Flow improves because of 1 and 2

Screen Shot 2017-05-29 at 11.22.49

Stage 2: When cross-pollination of skills required for activity B starts to pay off, we have 2 benefits

  1. Normally some activity A person will show particular abilities with activity B, in this case this person can pair with another less skilled activity A person to perform activity B
  2. Queue in “Waiting for Activity B” is reduced as more people with activity A skills are performing activity B
  3. Flow of value improves lead time decreases
  4. More activity A people get skills on activity B

Screen Shot 2017-05-29 at 10.56.00

Stage 3: All activity A people are able to perform activity B
Activity B Coach can abandon the team to return only occasionally to check on progress. Benefits:

  1. Activity A and activity B can be performed by every member of the team
  2. the WIP limit can be changed to obtain maximum flow and eliminate the queue in Ready for Activity B.
  3. The flow of value is maximised
  4. The lead time is minimised

Screen Shot 2017-05-29 at 10.58.05

WARNING: I have applied this approach to help teams with testing for many years. It has worked in my context giving me massive improvements in throughput and reduction of lead time. This is not a recipe for every context, it might not work in your context, but before you say it won’t work, please run an experiment and see if it is possible.

This is not the only activity that a good test coach can help a team on, there are many shift left and shift right activities that will also reduce the dependency on activity B.

I have been told a million times “it will never work”, I never believed the people who told me and tried anyway, that’s why it worked.

Try for yourself, if it doesn’t work, you will have learned something anyway.

Is agile Alive? Dead? Misunderstood?

Lats Sunday, after reading multiple “Agile is Dead” articles, I posted this short update on linkedIn

screen-shot-2017-03-05-at-11-03-37

As you can see from the stats, in less than 7 days it has received a lot of attention (I am not an influencer and my updates generally do not receive such large feedback)

My contacts in linkedIn include a lot of Agile or Lean Coaches and as expected, initially the message got some positive comments. Soon after some agile detractors joined the conversation and made it much more interesting as generally feedback that comes from different perspectives enriches the conversation adding dimensions that sometimes cannot be expressed by a biased mind.

I noticed 3 interesting trends in the messages.

  1. When agile is not driven by technology, agile fails
  2. When agile is driven by technology and not the business stakeholders, agile fails
  3. Agile is only useful to deliver something nobody wants quickly

The first 2 are extremely interesting, in fact they say exactly the opposite thing but they both come to the same conclusion “agile is dead”. I read and reread those messages and then I saw it

If agile is driven by one part of the organisation, whichever it is, and trust is not built within the whole organisation, it will fail. Do it like this and agile is dead before you even start.

If you try to own something that will change your organisation and run with it, you better make sure you share your vision, your responsibilities and your success with the rest of the organisation. How do you expect people outside your little world to want to follow you in this difficult change if they don’t know, understand, own and help you change. Agile/lean transformations are not driven by a department, they are driven by the whole.

And the result might be that you even stop talking about departments and only talk about the whole.

Now on objection #3.

Agile is only useful to deliver something nobody wants quickly

I have seen this very often and honestly makes me sad. A lot of scrum implementations have a Product Owner that is seen as the heart of the product, the person that understands the vision of the product and that takes the responsibility to take the important decisions for the future of the product in regards to strategy, prioritization and so on.

If you look at it this way, you might think that the PO is a single point of failure, in fact what if he is not able to make good decisions, how about his bias, is he a dictator?

As an agile coach I make sure that any product owner that works with me will have the tools for making good decisions. He in fact will know how to manage flow using WIP limits, he will be aware and become proficient in UX techniques, he will learn how to monitor, gather and use feedback from his customers, he will understand the importance of small experiments, he will be aware of cost of delay and when prioritising his features and user stories will have access to many advanced prioritization techniques.

Being agile does not mean automatically ignoring lean startup, lean UX, research. No that is not being agile, that is being a scrum master after 2 days training.