3 things I learned from “The Art of Business Value”

art of businessI am trying something new with this blog post – providing a mix of book review and a summary of what I learned about a book I really like. Waiting for Mark Schwartz to release his latest book “War and Peace and IT” I thought I re-read his earlier works. And as I was reading “The Art of Business Value” again I noticed that I am reading it with fresh eyes and that I appreciate this book even more than a few years ago.

Spoiler alert – the answer the book provides is a bit of a cop out: “…Business value is what the business values, and that is that.” But reducing this book to the final response to the question does not do it justice. The book artfully explores different angles of business value and why they are challenging when it comes to driving Agile delivery on the basis of this: ROI, NPV, Shareholder Value.

This is must read for all product owners to understand why there is not one answer to the question of business value and why Mark’s final response is unsatisfying yet completely appropriate. The book is also small enough that you don’t have to feel bad to recommend the book to the product owners you work with. I have recommended my favorite book of all time “Goedel, Escher, Bach” to many people fully knowing that only very few people would work their way through this fascinating but challenging book. “The Art of Business Value” is a book you can recommend without such thoughts on your conscience.

What I found even more useful in Mark’s book is that he explores the space around business value and three key learnings stand out for me:

  1. That the language of Agile can lead to a new command and control paradigm – this time by the product owner or Agile coach as Only Person you can listen to (OPYCLT)
  2. That the product owner as interface to the business requires a special kind of organisation and having X-teams are a better approach
  3. That the bureaucracy and governance we encounter is codified business value of the past

Let’s explore each of these a little further:

Agile as a new command and control paradigm

This one hits close to home. For a while I have been complaining about the Agile coaches out there who evangelise their methods without being able to explain why calling something a “PBI” is better than “User Story” or why we will only provide documentation in code. Mark adds another interesting dimension to this, if the product owner is the Only Person You Can Listen To for the team then how is this different to the project manager assigning work. Mark argues in a similar vein that the prescription of technical practices is a similar command and control rule – I recently spoke to an organisation that does not do automated testing and rather does production monitoring in full knowledge that they can respond quickly enough if something breaks. So I think we need to all be vigilant to not let Agile drift into just another command and control world this time run by the agilists instead of the project managers.

Product Owner vs. X-Team

In traditional Agile thinking the product owner represents the business and he presents the business problems to be solved to the Agile team which go off and solve them. Mark compares this with a loosely coupled system where the details of implementation is up to the team as long as they fulfil the contract that the product owner has made with the business. I am with Mark that this too simplified. We have plenty of experience that shows that the product owner needs help to manage the backlog and to work with the rest of the business. Mark introduces a new term “X-Team” from another book as guiding principles that teams need to work internally and externally. It is amazing how much more productive teams can be when they have rich context. For one of my Agile teams we arranged recordings of customer calls and visits to call centers so that the team got a better understanding of the business problem rather than relying on the product owner. The levels of innovation immediately increased when we started doing this.

The value of bureaucracy

This one is probably the one that requires the most consideration and came out of nowhere for me in re-reading the book. I think I had dismissed this point last time I read it. Mark argues that the processes you encounter were at some stage codified business value in many cases. And that we would be at risk of losing tacit knowledge of the value if we just throw it all out. Rather we should understand what the underlying value was and whether or not it is still applicable. You can then decide whether there is an alternative way to create that value or whether you continue with the established process. A good example is transparency as a value which might require you to do certain things that might not on first view provide value of itself like additional documentation or reviews.

There you go – I really enjoyed the second time I read his book and hope you will too.

The Anti-Transformation Transformation of Agile and DevOps

Organisational transformations have been part of organisational life for many years. There are reorganisations, big IT transformations and nowadays Agile, Cloud, Digital or DevOps transformations. These transformations used to follow a familiar pattern: an organisation is going through a major transformation and invests significant amounts of money over a 3-5 year horizon into the transformation. At the end of the transformation when the “end-state” was achieved, the level of investment got reduced and focus shifted to stabilisation and cost reduction. Over time the requirements changed more than the current level of investment allowed us to adapt for. Technical debt and the gap between needs and system functionality increased until this reached a level that required significant reinvestment or a new transformation to the next trend.

The cycle repeated every few years. While far from ideal it seemed to work okay, it was good business for technology companies and consultancies, it provided a level of comfort for organisations as they executed their 3-5 year roadmaps of transformation. The duration was not really a problem as the environment changed slowly enough for organisations to catch-up with each cycle. The level of change in the environment has increased and competitors are increasingly coming from digital startups that move very quickly. This means that the traditional transformation cycle is too slow to react. We cannot afford 3-5 year cycles any longer and rather need to create an organisational capability to continuously adapt to the environment. If you do one more transformation in your organisation it needs to be the anti-transformation transformation. The idea of this transformation is to transform not with a specific technical capability in mind but rather to transform to an ever improving, a learning organisation and to build the organisational capability that allows you to drive this ongoing process in a sustainable pace and process.

anti-transformationThere are obviously a few things different with this transformation and the most obvious yet confusing thing is that there is no end-state. There is no end-state technology architecture, there is no end-state organisational structure and there is no end-state delivery methodology. But if there is no end-state how do we know when we are done? This is the bad news, we will never be done. We have to create capabilities that make it easier and easier to adapt incrementally and we need mechanisms to guide each improvement even in the absence of an end-state.

Having this discussion with my clients makes me feel like a GP who is telling the patient that is coming to the office that there is no pill that I can give to reduce his blood pressure and shortness of breath, but rather that the patient needs to eat healthier and do more sports. It is not going to be easy and each day will present a new challenge. Furthermore as his consultant I cannot do this work for him, I can only guide and support, but the patient has to do a lot of the work himself. The exact same is true for organisations neither Cloud, Robotic Process Automation, AI or any other technology will magically solve the problems. We need our organisations to change to a healthier lifestyle to remain fit and survive.

Enough of the analogy, but I hope you get the point. So what can we do to guide the anti-transformation transformation? First of all our view of technology architecture needs to change, as highlighted in this blog post there are 3 architectures we are dealing with and each one of them needs to be adaptable: our business systems architecture, our IT tools architecture and our QA and data architecture. We also need to have a guiding system to show us where our technical debt is and where systems are highly coupled – these need to reduce to remain adaptable. Last but not least we need to find ways that allow us to continue to evolve organisational structure and methodology in a way that does not disrupt the business – it is not about moving from the Spotify model to SAFe or vice versa, but rather its about running small experiments with your own contextual methodology or org structure to be able to evolve and continuously improve. If you are still in the beginnings of the anti-transformation then you might want to adopt one of the more common methodology frameworks to get yourself started, but if in 2-3 years you are either still doing the same things or feel the need to adopt another model then you have a problem. Neither of those two extremes should be correct, you should feel like you are working with a methodology and org structure that is truly your own and that has been optimized for your context over time.

One last thing to note – larger disruptions in business or technology will still cause more challenging needs for change and require you to increase investment, but it should not require another transformation. It should rather require a larger incremental change that is easier to manage because we decoupled our architectures and methods.

The transformation is dead, long live the anti-transformation transformation.

The modern IT architect needs to manage 3 architectures to enable Agile and DevOps ways of working

3 architecturesI have been a technology architect for a long time and have worked with many different technologies. And there is something satisfying about coming up with “the architecture solution” for a business problem. The ideal end-state that once implemented will be perfect.

Unfortunately I had to come to the realization that this is not true. There is no end-state architecture anymore and there never was. All those diagrams I drew with the name end-state in it – they are all obsolete by now.

Knowing that architecture will continue to evolve (just look at the evolution of the architecture of Amazon (or many other internet companies) over the years) means as architects we need to think differently about architecture. We need to build architectures that before even implemented are already considering how parts will be replaced in the future. No stone will remain unturned over time no matter how good they seem at the moment. So rather than spending time on defining the end-state we need to spend more time understanding and defining the right principles of architecture for our organisations and manage the evolution of the architecture – how technical debt is paid down and systems are being decoupled for the eventual replacement.

This would be difficult if we had to deal just with the architecture of business systems. Reality is that in the current IT world we have to deal with three different architectures: the business systems architecture, the IT tools architecture and the QA and Data architecture.

Let’s quickly define these:

  • Business Systems Architecture – this is usually well defined in organisations. How do your CRM, ERP and billing systems work together to achieve business outcomes
  • IT Tools architecture – this is the architecture of all your tools that make IT delivery possible: configuration management, container management, deployment, defect management, Agile lifecycle, etc
  • QA and Data architecture – how do we validate that systems are working correctly both in production and in new development and how is data flowing across systems and environments

All three of these architectures need to be managed with the same rigor and focus on continuous evolution as the business systems architecture. This will make the job of architects a little bit more complicated. At the moment I see many organisations not having architects focused on all three architectures as they are not perceived as being of similar importance.

Let me give you some examples from my past to highlight why that is foolish:

  • One of my clients was already pretty mature in their automation so that all deployments to production were fully automated. Unfortunately their deployment architecture was basically a single Jenkins server that was manually maintained. When this server was wiped out by mistake it took weeks to get the capability back to deploy to production – in the mean time very risky manual deployments had to be performed by people who had not done this in months
  • Another client of mine had built a test automation framework that was too tightly coupled so that it took a lot of effort to replace one of the components and maintenance had become so expensive that they had stopped using it – ultimately there was too much technical debt in the tests and the QA and data architecture

The answer of course is that all three architectures need to be managed by architects in similar ways (e.g. failover and availability need to be considers for IT tools and QA tools too) and that the principles of decoupling and continuous evolution need to be aspects of all three.

The architect function is one that will see a lot of change as we come to terms with managing three interconnected architectures and the evolving nature of architecture. But I think it will make the job more interesting and will allow architectures to climb down from the proverbial ivory tower to engage with the Agile delivery teams in a more meaningful way.

DevOps Enterprise Summit Las Vegas 2018 – The best yet?

DOES18Its already over again – the annual get together of the brightest DevOps minds (well the brightest who could make it to Vegas). And in this instance I want to make sure that what happens in Vegas, does not stay in Vegas by sharing my highlights with all of you. It was a great event with a slightly higher focus on operations than last time.

The four trends that I picked up on:

  • Self service operations are considered an good answer to the “DevOps Team” problem
  • The prevalence of Dunning Kruger (Link) when it comes to self-assessments -> We are “DevOps”, we use the “cloud”,…
  • Minimum Viable Compliance as a new term
  • DevOps for AI – I did not see much AI for DevOps yet, perhaps next time

This year the conference focused much more on operations which is great, for next year I hope that we bring in some of the end-to-end business stories. How have we used DevOps practices to drive business – thinks like instrumentalization of software features to understand the business impact.

The top 3 talks

Andrew Clay Shafer

Andrew spoke in his typical eccentric style (with tie on his head) about Digital Transformations and doing DevOps. He made it clear that there is no real end to this transformation and compared it with getting fit (something he took on successfully since the beginning of the year). All the external help you can get will not make you fit, it’s the work you put in yourself. The same is true for this DevOps/Digital transformation. He also made a good point that some message can be dangerous if they are given before the recipients are ready.

J Paul Reed

I admit that I went into “5 dirty words about CI” expecting a talk about Continuous Integration like many others , something John humorously took on in the beginning. The talk focused on Continuous Improvement instead and stood out for me. Key learnings:

  • Root causes are a social construct for the point where we stop looking further, more appropriately we should call those “proximate causes”
  • A great story from Amazon, who used an outage caused by “human error” to look for the weaknesses in the systems rather than finding fault with the person who made a mistake
  • That incidents are not deterministic – there are many parallel universes where the incident might not have happened in the same circumstances, our systems are too complex to be deterministic. The Swiss Cheese model to analyse incidents was a great take away for me.
  • Human error is not the cause, it’s the effect. It’s the start of the investigation.

Damon Edwards

Okay, okay he usually is in my top list of talks because I like his style and approach. This time he told a great case study of how all the new fancy technologies and techniques did not prevent the opps problems. Which was a) funny and b) educational to move us away from all the techno-optimism. He then described the self-service operations model which I prefer myself as well, so this was good to see discussed, which is also called out in the latest puppet state of DevOps report.

 

Some other nuggets from other talks

Courtney Kissler

  • First mention of “Minimum Viable Compliance”
  • I loved the phrases “Geriatric stack” and “PTSD caused by legacy apps”
  • Great story on how compliance can calculate negative ROI to justify investment

Scott Prugh

  • Great case study where he showed the results over the years
  • Showing how Agile and DevOps work together to achieve huge results
  • Aligning teams to Value streams not projects and even using the platform as a product with product owner
  • Some interesting aspects on lean portfolio management that is run through several “tanks” like sharktank
  • I loved the metric – “% of things releases outside of release cycle”

Jeffrey Snover

  • Super inspiring to hear from someone who stood up for what he believed in and that careers can be a bit like snakes and ladders (it took him 5 years to come back from a demotion)
  • Insightful to hear about organisations and/or leaders having a list of people who are moving the company forward and of course those are the people that get well rewarded
  • How transitions transformations can push your career – introducing the terms stair job vs elevator jobs
  • Loved the point that when you are really good at something that doesn’t matter anymore that it will be bad for you (either as organisation or in your career) – great example from DEC which was excellent at something that didn’t matter anymore a and missed the move from vertical integrated to horizontal systems
  • He made a point that he believes the pendelum is swinging back to vertical integrated (like Azure and AWS)
  • “Build what differentiates you, buy what doesn’t”

Thorsten Volk

  • Reiterated the point I have heard a few times now that AI is still similar to the 90s just more accessible and powerful
  • Understand what AI and human understanding is good for and when to use what
  • Start with a narrow problem and extend it once you have a useful answer
  • Treat AI as code – Parameters, training set, data transformation pipeline, etc
  • Use public data – there is heaps that you can use to teach your algorithms
  • AI is a virtual reality as you can only see what is in the data and that data can be biased

Mik Kersten

  • He introduced his new framework to help with the transition from project to product which is described in his new book, which was available at the conference for the first time (I will review it in a blog post in due course)

Rob England

  • How some of the new material in the DevOps world has forgotten the old and sometimes is even reinventing it
  • Interesting anecdote that the SRE book comes to the conclusion that key metric is unplanned downtime – something the ITSM community has already know
  • How DevOps has not covered everything that ITSM covered like user training/Desktop management,… – there is some benefit in review the more rigorous material from ITIL
  • Gave us hope that ITIL 4 will be more relevant and easier to consume vs ITIL 3 being a bit of mixed bag

Jez Humble, Nicole Forsgren

  • Only 22% of people who say that they use the cloud are following the 5 characteristics of NIST – most hands went down at “OnDemand Self Service”

Cornelia Davies

  • Difference between functional and imperative programming
  • Why functional programming allows us to do get systems to do more for us and are less error prone because there is no state embedded
  • The term “Repave environments” – refreshing every part of the environment which we should do regularly
  • Introduced the concept of “Sidecars” – a container next to another container in a Kubernetes pod that deals with cross cutting concerns like security

 

Another brilliant conference is over and I am already looking forward to next year.

Something is missing in the Agile manifesto

As Agilists we keep using the Agile manifesto and are pretty much beyond questioning the exact words on the page. One key one is:

Working Software over comprehensive documentation

And over the years we had the arguments that this does not mean that there is no documentation, what exactly the definition of working software is and many other aspects of this. Yet I failed to pick up on a very important nuance for all those years.

The other day I was running an Agile training and someone with less of an IT background called out to me that she disagrees with the statement “working software over comprehensive documentation”. I was shocked initially until she explained that working software means terribly little when no one uses it (for example due to poor documentation or change communication) or if the software does not solve a business problem.

Wow – how had I not noticed this clear miss before. Of course, we are not about just building software and the Agile manifesto came from people who were thinking about creating software in a better way. But more than decade after I started to run Agile trainings, why had I never noticed this clear gap in the manifesto for our modern context.

A few weeks earlier I was at an Agile conference in Germany and someone spoke about Agility rather than Agile and pointed out how much of the language in the Agile principles behind the manifest are software specific (e.g. “The most efficient and effective method of conveying information to and within a development team is face-to-face conversation.”) How have we not updated this material to be more relevant by changing all the wording to be inclusive of business and other parts of the organisation that need to enable success? See below for references to software development in more than half of the principles.

principles

Of course, the manifesto has its relevance as historic document, but whenever we talk about it, it is worthwhile calling out that we do have a broader understanding of this now which goes way beyond IT and software development. I for one will call this out more clearly whenever I run training going forward. We are using Agile to solve business problems and creating better software is only a small part of the solution. Thank you Jane for calling out a blind spot that I have had for years!

UPDATE: Thanks to Phil i found this tweet which discusses a solution:

tweet

 

The need to change our mental models – A core idea behind DevOps for the Modern Enterprise

I always loved this quote: “Nothing is more dangerous than using yesterday’s logic for today’s problems” which shows you that you just cannot afford to get lazy and do the same thing again and again. This causes larger problems when you scale it up. Gary Hamel summarizes the problem our organisations face as follows: “Right now, your company has 21st century Internet enabled business processes, Mid 20th century management processes all built atop 19th century management principles.”

One of the main reasons for me to write “DevOps for the Modern Enterprise” was to help address this mismatch between the work we need to do, creative IT based problem solving, and the management mindset many managers still have, that of IT being managed just like manufacturing.

I like to use the term mental model to describe what having the wrong mindset means for the every day job of managers and other executives. Let’s take a very practical example to show you how your mental model shapes your view of reality. Look at the vase on the picture below. What do you see?

Bottle1

Depending on how your brain has been shaped up to this day, you will see different things on the vase. Children predominately see 9 dolphins (see further below to help you see them). I guess that you saw something different, didn’t you? What does that say about your mental model of reality and your preferences 😉 What this exercise hopefully shows you is that each persons view on reality is not exactly the same and that the mental model you use makes an important difference in how you perceive reality and act.

Perceiving IT as being similar to manufacturing leads to management processes that are inappropriate, you are looking for productivity measures where there are none (more about that here), you expect people to be replaceable resources, you think that fixing the process will fix the end-product and that you can upfront plan for projects. Pretty much all of those have been shows to be incorrect.

As a starting exercise for changing your mental model, I recommend watching Dan Pink’s video on motivation (Watch it here). I leverage his idea extensively in my book and think it is a perfect match for Agile delivery where we provide purpose by providing the agile team with the context of the problem they are solving, we allow them to achieve mastery through quick feedback cycles and we created cross-functional teams that are reasonably autonomous. Once you understand Dan Pink’s mental model you can easily diagnose some of the common problems with Agile projects that don’t provide those three motivators.

This shift in mental model is exciting stuff and goes much further in areas of operations and working with vendors/partners, you can read more about it in my book. For now I hope I was able to motivate you to look further into the topic and for you to try to be more conscious of your own mental model. It is worth challenging the model you have and perhaps you are then able to see those dolphins too 😉

bottle2

It’s time to make Application Management Sexy Again

app maintenanceA few weeks ago I was in group of people and someone made a statement that application management (AM) is commodity and most people in the group agreed. I didn’t say anything but I think application management is one of the most exciting places to be today. There are so many technology trends that apply to AM: Agile, DevOps, Artificial intelligence, etc.

When I say application management I mean some level of operations (e.g. level 3 support and code fixes) and some level of application development/maintenance (smaller changes that don’t require projects). The nature of those activities are that they are frequent and smaller, which means we have a lot of opportunity to learn and improve. It’s the ideal testbed to showcase how successful modern engineering practices can be assuming the volume of work is large enough to justify investment.

Let’s look at two dimensions of this: the code changes and the platform services

The product team making the actual code changes should have responsibilities for making changes for both new scope and production defects. This team needs to reserve some capacity for urgent production defects, but the bulk of production defects get prioritised against new scope and are just forming part of normal delivery. This is possible because the release frequency is high (at least monthly) and the team can leverage platform services like CI/CD, feature flags, automated environment provisioning and monitoring services. The team collaborates with the platform services team in many ways and focuses on the application they own. Both Kanban and Scrum are possible methodologies this team can use, making this a great Agile working space.

The platform team provides the services which make life easier for the product teams. They also provide the first levels of support in a centralised fashion to protect the product team from too many distractions. There are two goals for this team: to provide platform services to the product team (like CI/CD, environment provisioning, monitoring) and to keep improving the customer experience for end-users. Fast ticket resolution is not the right measure for this aspect, but rather how to reduce the tickets overall. Advanced monitoring of performance, functionality and infrastructure is being used to find problems before the customer finds it. Each user created ticket is an opportunity to improve the monitoring for next time. Chatbots and self service are used to provide the fastest service for standard requests and AI/ML is learning from tickets to make more and more requests become standard and to route tickets to the best team/person. Analytics on all aspects of the platform allows to find patterns and reconcile them against issues. The platform team collaborates with the product team to make sure the application related services keep being improved. Over time this team becomes a small team of automation experts rather than a large team of operators for manual tickets.

Seriously if you look at the above, how are you not super excited about this space?If you do this right you get to use a lot of super modern engineering practices to improve the delivery capability of your organisation. The amount of money/capacity that frees up once you have implemented the first improvements can then be used to make more and more meaningful changes to the products and services. You can do this with a focus on the creative tasks rather than the fire fighting and repetitive manual work that consumed application management teams in the past.

I am working with a couple of organisations now that are as excited as I am about this space and have a similar vision. I am very much looking forward to see what results we will achieve together.