With Cynefin, I can justify skepticism about inappropriate approaches and co-create better ones

As testers we need to better understand and be explicit about problems in testing that don’t have known, clear, or obvious solutions. Cynefin can help by transforming the way we, our teams, and our stakeholders think about testing problems.

Ben Kelly and James Christie has written very good blogs about Cynefin and testing. Liz Keogh was one of the first to write about Cynefin in development. At the bottom of this post, I have included a video with David Snowden and a link to an article I found interesting when I read it.

With this blog post I’m sharing elements of my own understanding of Cynefin and why I think it’s important. I think of Cynefin itself as a conceptual framework useful for comprehending dynamic and complex systems, but it is also a multi faceted “tool” which can help create context dependent conceptual frameworks, both tacit and explicit, so that we can better solve problems.

But before diving into that (and in particular explain what a conceptual framework is), I’d like to share something about my background.

Product design and the historic mistakes of software development

I used to study product design in university in the early 90’s. Creating new and innovative products does not follow obvious processes. Most engineering classes taught us methods and tools, but product design classes were different.

We were taught to get into the field, study real users in their real contexts, develop understandings of their problems, come up with prototypes and models of product ideas, and then try out these prototypes with the users.

Discussing an early draft of this post with James Christie, he mentioned that one of the historic mistakes of software development has been the assumption that it is a manufacturing process, whereas in reality it is far more like research and development. He finds it odd that we called it development, while at the same time refusing to believe that it really was a development activity.

SAFe, “the new black” in software delivery, is a good example of how even new methodologies in our industry are still based on paradigms rooted in knowledge about organizing manufacturing. “The Phoenix Project”, a popular novel about DevOps states on the back cover that managing IT is similar to factory management.

What I was taught back in the 90’s still help me when I try to understand why many problems remain unsolved despite hard work and many attempts on the opposite. I find that sometimes the wrong types of solutions are applied, solutions which don’t take into consideration the true nature of the issues we are trying to get rid of, or the innovations we’re trying to make.

Knight Capital Group, a testing failure

The case of Knight Capital Group is interesting from both innovation, risk and software testing perspectives, and I think it exemplifies the types of problems we get when we miss the complexity of our contexts.

Knight Capital Group was one of the more aggressive investment companies in Wall Street. In 2012 they developed a new trading algorithm. The algorithm was tested using a simulation engine, I assume to ensure to that stakeholders that the new algorithm would generate great revenues.

The testing of the algorithm was not enough to ensure revenues, however. In fact, the outcome of deploying to algorithm to production was enormous losses and the eventual bankruptcy of the company after only 45 minues of trading. What went wrong?

SEC, Securities and Exchange Commission of the U.S.A.:

[…] Knight did not have a system of risk management controls and supervisory procedures reasonably designed to manage the financial, regulatory, and other risks of market access […] Knight’s failures resulted in it accumulating an unintended multi-billion dollar portfolio of securities in approximately forty-five minutes on August 1 and, ultimately, Knight lost more than $460 million […]

But let’s assume a testing perspective.

It think it’s interesting that the technical root cause of the accident was that a component designed to be used to test the algorithm by generating artificial data was deployed into production along with the algorithm itself.

This test component created a stream of random data and was of course not supposed to run in production since it was designed to generate a stream of random data about worthless stock.

I find it strangely fascinating that the technical component that caused the accident was designed for testing.

Why didn’t someone ensure that the deployment scripts excluded the testing components?

Was it software testing that failed? It is not uncommon that software testing is entirely focused on obvious, functional and isolated performance perspectives of the system under test.

The component did it’s job: Helped test the new product. The testing strategy (probably undocumented) however, obviously did not consider possible side effects of the component.

I think Cynefin could have helped.

Cynefin transforms thinking

Let’s imagine we’re test managers at Knight and that we choose to use Cynefin to help us develop the testing strategy for the new algorithm. 

David Snowden talks about Cynefin as a ‘sensemaking tool’ and if you engage Knights’ management, financial, IT-operations, and development people in a facilitated session with a focus on risks and testing,

I’m pretty sure the outcome would be the identification of the type of risk that ended up causing the bankruptcy of the company, and either prevented it by explicitly testing the deployment process, or made sure operations and finace put the necessary “risk management controls and supervisory procedures” in place.

I think so because I have observed how Cynefin sessions with their brainstormings are great for forming strategies to deal with the problems, issues, challenges, opportunities etc that we are facing. It helps people talking seriously about the nature of problems and issues, transforming them into smaller chunks that we can work with, and to help escalate things that require escalation.

Cynefin seems to be efficient breaking the traditional domination of boxed, linear and causal thinking that prevent problem solving of anything but the simplest problems.

My interpretation of what is happening is that Cynefin helps extend the language of those participating in sessions.

Decision makers a Knight Capital did not think about possible negative outcomes of the testing software. They had a simplistic view of their business risks. Cynefin could have helped them by extending their ‘sensemaking’ to more complex risks than those they were focusing on.

In the following I’ll dive a bit more into why I understand the sensemaking part of Cynefin to be a language-extending tool.

Language and Conceptual Frameworks

Language is an every-day thing that we don’t think much about.

Yet it is the very framework which contains our thinking.

While we can know things we cannot express (tacit knowledge), we cannot actively think outside the frame language creates.

Many philosophers have thought about this, but here I’d like to refer to physicist Niels Bohr (1885-1962) who in several of his lectures, articles, and personal letters talks about the importance of language in science.

Science is in a way about sensemaking through knowledge gathering and poetically (paraphrasing from my memory) Bohr describes language as the string that suspends our knowledge above a void of endless amounts of experiences.

In “The Unity of Science”, a lecture given at Columbia University, New York in 1954, Bohr introduce language as a “conceptual framework”:

“[it] is important […] to realize that all knowledge is originally represented within a conceptual framework adapted to account for previous experience, and that any such frame may prove too narrow to comprehend new experiences.”


“When speaking of a conceptual framework, we merely refer to an unambiguous logical representation of relations between experience.”

Bohr was the father of quantum physics, which is more than new laws about nature. It introduced new and complimentary concepts like uncertainty, and non-deterministic relations between events. The extension was made for quite practical purposes, namely the comprehension of observations, but has turned out to be quite useful:

“By means of the quantum mechanical formalism, a detailed account of an immense amount of experimental evidence regarding the physical and chemical properties of matter has been achieved.”

The rest is history, so to speak.

This is relevant to software testing and Cynefin because I think that the conceptual frameworks based on the thinking developed during industrialism are far from capable of explaining what is going on in software development and therefore also in testing.

Further, Cynefin seems to be an efficient enabler to create extensions to the old thinking frameworks in the particular contexts in which we use it.

Cynefin and software testing

Software development is generally not following simple processes. Development is obviously a human, creative activity. Good software development seems to me to be much more like a series of innovations with the intention to enable someone doing things in better ways.

Testing should follows that.

But if language limits us to different types of linear and causal thinking, we will always be missing that there is generally no simple, algorithmic or even causal connection between the stages of (1) understanding a new testing problem, (2) coming up with ideas, and (3) choosing solutions which are effective, socially acceptable, possible to perform, and safe and useful.

Experienced testers know this, but knowledge is often not enough.

James Christie added in his comments to the early draft mentioned above that as testers, with Cynefin we can better justify our skepticisms about inappropriate and simplistic approaches. Cynefin can make it less likely that we will be accused of applying subjective personal judgment.

I would like to add that the extended conceptual framework which Cynefin enables with us and our teams and stakeholders further more allow us to discover new and better approaches to problem solving

David Snowden on Cynefin

This video is a very good, quick introduction to Cynefin. Listen to David Snowden himself explain it:


AI personally found this article from 2003 a very good introduction to Cynefin:

The new dynamics of strategy: Sense-making in a complex and complicated world (liked page contains a link to download the article)



Chaos to Kairos – NYC May 1st session on playful testing skills with music and philosophy

Jessica Ingrassellino and I will perform a workshop at the NYC Testers Meetup on Monday May 1st during the Test Leadership Congress. Join the meetup to participate.

The session will be based on the workshop we did at CounterPlay, an international play festival which took place in March in Aarhus, Denmark. Titled “Playful Software Exploration” the topic was value driven improvisation skills in testing. Together with the participants we tested, performed music and formed a philosophical, protreptic circle

The somewhat disturbing background of the workshop is that in a performance oriented and individualized tech industry, we are expected to drive ourselves to be the best in a complex or even chaotic reality. Remaining true to our professional and personal values while staying sane and ready to act and perform every day can be very challenging.

Our CounterPlay workshop was a success. Collaboratively we gained sense of and got to the core of important values in testing. We were even interviewed for the popular show “The Harddisk” on Danish national radio.

This time we would like to playfully explore the significance of Kairos in testing.

Kairos is Greek and means the supreme moment in which the future is transformed to the past with a particularly fruitful outcome. Kairos is important in rhetorics because while there are rules of good communication, there are moments in which speaking and acting is particularly fruitful: There is a time and space for the good talk. And even the best performance will fail if kairos is not considered.

This is an aspect of all improvisation and play, and good testing is in many ways always an improvised, playful act.

We know it when we perform exploratory testing.

But even when testing is turned into a controlled and scripted process, it makes sense to perceive testing in the microscope as a playful exploration and experimentation with potential and actual outcomes – even outcomes beyond the directly observable testing results: E.g. learning points for developers and management.

At the core is that testing makes a difference for people around us, even those who are not directly involved in testing and developing.

So let’s think beyond the processes, and functional and technical perspectives on testing, and explore software testing as a playful and human event with potential to create order in due time.

No prior knowledge or talents are required to join the workshop. But bring curiosity about values in testing, and be ready to play and improvise, introspect and think and reflect abstractly.


Jess and Anders

Kunsten at tvivle: Proptreptisk samtalesalon nr. 8

Det er videnskaben, der bærer vores samfund i dag, og med den følger søgen efter forståelse. Med forståelse kan vi skabe nyt og blive rigere og sundere.

Forståelse indebærer, at vi indtager et standpunkt, altså står ét bestemt sted. Dermed stiller vi os i modsætning til andre standpunkter: Forstår vi noget, kan vi ikke indtage flere modstridende standpunkter om det, vi forstår.
Så med forståelse følger holdning.

Holdning baseret på forståelse virker vigtigere end noget andet, når vi skal tage store beslutninger. Hvordan mon statsministeren eller præsidenten tænker, når han skal sende sit land i krig: Tvivler han og ryster på hånden? Eller har han læst og forstået situationen eksakt og præcist og udmønter derefter forståelsen i handlekraft?

Visheden, der følger med forståelsen, giver sikkerhed og signalerer styrke. Dens modstykke, tvivlen, kan være tegn på uduelighed og svaghed.

Men måske rummer tvivlen alligevel noget godt?

Mange krige har i eftertidens dom vist sig meningsløse og måske mest baseret på rygter og løgne. Vi ved det egentlig godt: Tit søger folk jo ukritisk efter vished og giver måske sig selv og andre indtryk af sikkerhed og styrke men snyder i sidste ende kun sig selv og andre.

Måske findes der en værdifuld, reflekterende tvivl, en dyd, som vi som ledere og mennesker bør kende og opdyrke for at bevare og udvikle kritisk sans og en sans for de sandheder, der rummer nuancer, der ikke kan måles videnskabeligt og sikkert?

Det kræver mod at tvivle, men tvivlen må i alle tilfælde være nødvendig, for at vi personligt og organisatorisk kan mestre de irrationelle psykologiske for-forståelser og mavereaktioner, som alle mennesker trækkes med.

Ja måske er tvivlen ligefrem en forudsætning for at kunne handle empatisk og begavet i det daglige?

I denne ottende samtalesalon vil vi derfor lede efter værdier i og omkring tvivlen, ja dyrke selve kunsten at tvivle.

Tilmelding er obligatorisk – og det er afmelding i øvrigt også, hvis du bliver forhindret. Hvis vi har tomme stole, vil vi nemlig gerne kunne give dem til andre interesserede.

Vi glæder os til at se dig!

Dato: 15. maj 2017
Tidspunkt: 16.00 – 18.30
Sted: Gjesing Coaching, Prinsesse Charlottesgade 31, kld, 2200 København N
Tilmelding til: karengjesing@privat.dk (obligatorisk af hensyn til forplejning)

Kærlige hilsner

Karen og Anders

Playful Software Testing

I met with and enjoyed a very good conversation with Jessica Ingrassellino in New York back in September. Jessica presented a workshop on playful testing during the Reinventing Testers Week (I presented at the conference about “Testing in a Black Swan Domain” which, unfortunately, I have not had time to write about yet).

We talked mostly about philosophy.

Jessica is quite a multi-talent: Plays the violin virtously, is an educated music teacher, has switched career to testing, taught herself Python, authored a book on Python programming for kids, and is teaching Python classes at a local community college, as well as music classes.

She has a vision of making testing playful and fun.

Structured work govern testing in professional settings, work which has nothing to do with play. So why is play important?

Jessica puts it this way:

When the power of play is unleashed in software testing, interesting things happen: The quality of the testing performance becomes noticeably better, and the outcomes of it too. This results in better software systems, higher product quality.

I have a product engineering background and play is important for me too. Engineers have methods, calculations, and procedures, but great engineers know that good solutions to problems are not found by orderly, rational processes. Good solutions depend on creativity and play.

Friday December 9th, I met with Mathias Poulsen in Copenhagen. Mathias is the founder of CounterPlay, a yearly conference and festival on serious play in Aarhus, the second largest city in Denmark.

About three years ago, Mathias got the idea for the conference.

In the first year, 2014, it was an immediate success with more than 20 talks and workshops in 3 tracks on “Playful Culture, Playful Learning, and Playful Business”, and more than 150 participants. This year (2016), the conference had 50 scheduled sessions: keynotes, talks, workshops, mini-concerts and open sessions.

Mathias explains (about 0:30 into the video):

Counterplay is basically an attempt to explore play and being playful across all kinds of domains and areas in society. We are trying to build a community of playful people around the world to figure out, what does it mean to be playful and why do we think it is beneficial?

Processional IT has so far not been represented at the conference, Mathias told me. I found that a bit surprising, as at the moment almost everything in IT seems to be buzzing with concepts promising joy and fun – play.

Sometimes, however, there is an undertone to all the joy. Agile and DevOps have become popular concepts even in large corporations, and to me, both strive to combine productivity with playfulness. That is good.

But is the switch to Agile always done in order to pass power to developers and testers, allowing them to playfully perform, build and test better solutions? No, not always.

Play facilitate change and breaking of unhelpful patterns, but sometimes play is mostly a cover for micromanagement. There is a word for this: In a recent blog post, Mathias talks about playwashing:

Playwashing describes the situation where a company or organization spends more time and money claiming to be “playful” through advertising and marketing than actually implementing strategies and business practices that cultivate a playful culture in said organization.

A question is therefore how we genuinely support play? Are there methods or processes that better accommodate playfulness at work?

I believe there is. Processes need to leave space for exploring context, knowledge sharing and actual interaction with customers, stakeholders and team members.

But processes or methods will not do the job alone. In fact, putting play under the examination of psychology or cognitive sciences will never be able to grasp what play really is.

Play is more like music and poetry, where ideas based on assumptions about order, rational choice, and intention cannot explain anything.

Philosophy and especially the dialectical exploration of what it means being a playful human is much better at embracing what play means to us and how to support it.
Jessica and I are working on a workshop about playful and artful testing. It will combine ideas of playful testing with philosophy.

We are certain that breaking out of patterns will help testers, and breaking out of our patterns, participating in a conference which is fully devoted to play will teach us a lot.

I took this photo in the local forest on a walk with our dog Terry (the black poodle). It is obvious, when dogs play well, that they have fun and learn a lot through play. Play seems a fundamental capacity for mammals.

Why you should do your job better than you have to

Software testers evaluate quality in order to help others make descisions to improve quality. But it is not up to us to assure quality.

Projects need a culture in which people care for quality and worry about risk, i.e. threats to quality.

Astronaut and first man on the moon Neil Armstrong talked about reliability of components in the space craft in the same interview I quoted from in my last post:

Each of the components of our hardware were designed to certain reliability specifications, and far the majority, to my recollection, had a reliability requirement of 0.99996, which means that you have four failures in 100,000 operations. I’ve been told that if every component met its reliability specifications precisely, that a typical Apollo flight would have about 1,000 separate identifiable failures. In fact, we had more like 150 failures per flight, substantially better than statistical methods would tell you that you might have.

Neil Armstrong not only made it to the moon, he even made it back to Earth. The whole Apollo programme had to deal very carefully with the chance that things would not work as intended in order to make that happen.

In hardware design, avoiding failure depends on hardware not failing. To manage the risk of failure, engineers work with reliability requirements, e.g. in the form of a required MTBF – mean time between failure – for individual components. Components are tested to estimate their reliability in the real system, and a key part of reliability management is then to tediously add all the estimated relibility figures together to get an indication of the reliability of the whole system: In this case a rocket and space craft designed to fly men to the moon and bring them safely back.

But no matter how carefully the calculations and estimations are done, it will always end out with an estimate. There will be surprises.

The Apollo programme turned out to perform better than expected. Why?

When you build a system, it could be an it-system or a space craft, then how do you ensure that things work as intended? Following good engineering practices is always a good idea, but relying on them is not enough. It takes more.

Armstrong goes on in the interview (emphasized by me):

I can only attribute that to the fact that every guy in the project, every guy at the bench building something, every assembler, every inspector, every guy that’s setting up the tests, cranking the torque wrench, and so on, is saying, man or woman, “If anything goes wrong here, it’s not going to be my fault, because my part is going to be better than I have to make it.” And when you have hundreds of thousands of people all doing their job a little better than they have to, you get an improvement in performance. And that’s the only reason we could have pulled this whole thing off.