Next month – in just over 3 weeks in fact – I’m running a mini-workshop Masterclass (2 hours) on Writing OKRs. Specifically on making key results measurable and quantifiable. Yes I know targets can mislead, that might be something we will talk about. Its timed for 2pm which should be good for Europe and the East Coast. Sorry far east, Australasia and West Coast.
Tickets are available now but are limited so if you want to don’t delay, book now. Plus, for the next week cheap very early bird are available, and if you use the code “Blog20” you can get an extra 20% off.
Looking across the state of teams today I can clearly see three different styles of agile: Backlog Driven Development, Reactive and Objective Driven Agile. All have their place, all have their uses but the first two of these are a dead end. I’ve been speaking about the third, which I’m calling Objective Driven Agile, for years but in the last few months, since writing Succeeding with OKRs in Agile and speaking to many people about how OKRs and agile fit together, it has become clear to me that ODA allow us the industry, and teams, to address a number of problems that have arisen with agile in recent years.
1) Backlog Driven Development – BLDD. Teams are typically working in a Scrum fashion with a backlog and short sprints. Such teams are sometimes called “feature factories” because they are aiming to “do the backlog” – and the backlog is inevitably a lis of features.
While the Scrum these teams practice is a lot more agile than what came before they haven’t really moved very far from the big requirements documents of old. Backlogs are frequently bottomless pits, the team can never reach done. The loss of change review board might well be making things worse because Product Owners often lack the authority to say “No” or remove items from the backlog.
Still, not only are these teams agile but in many places this is success. The team are churning out stories, customers can see progress and are persuaded to part with cash. If the backlog can be tamed they might even declare done one day. But then, if the team is being operated by a consultancy or other outsourcer for a client the last thing they want to happen is for work to be done.
2) Reactive. Reactive teams gravitate towards Kanban but some are compelled to work in a Scrum fashion which doesn’t match their real work. Such teams may see backlogs are an anathema because they do “what is needed, right here, right now.” Team members here will say “true agility is listening to what customers want and getting it done as quickly as possible.” And in a way they are right.
Again, these teams are a success story, particularly if they are supporting a live system, running DevOps or if customers previously had to wait months for results.
The problem here is that these teams don’t have much capacity for doing the backlog or anything else and yet they are frequently still expect to “do the backlog”. If such a team have been tasked with immediate customer support then that isn’t a problem but frequently these teams face competing demands.
3) Objective Driven Agile, ODA: this is the approach I’m focused on at the moment. With Objective Driven Agile teams have a mission and a higher purpose, something more than “do the backlog” or “keep the system working.” Such teams might be considered “Empowered” and might practice “Dual track agile.” The key thing is, they are not beholden to a prepared list of things to do. The team are responsible for deciding what customers need, what will add value and what will meet team and organisational objectives, and then, delivering that thing.
These teams have “Product Owners” who are more than mere Backlog Administrators – I’ve started calling them “Product Specialists.” These people are tasked with understanding what will add value for customers, users and other stakeholders. Importantly they have the power to decide what gets done and to say “No”. With that power comes responsibility: responsibility to the team, to stakeholders and to other leaders in the organization. That means Product Specialists can explain – in a business case or in a star-chamber – how work on the product adds benefit and how the desired outcome – the objective – is moves things forward.
All three of these styles have their advantages and disadvantages but the real problems occur when the styles are not clearly stated.
Consider the team trying to deliver the backlog BLDD style but who have to “keep the lights on” and support a live system. It is mathematically impossible to make accurate forecasts about delivery when events can derail you. It is also nye on impossible to deny customer requests when they are waiving a large sum of money or escalating their ask through your organization. But again, this can blow up any plan or roadmap.
Nor is is possible to pursue objectives when teams are committed to supporting live or delivering a backlog. At best the objectives duplicate the role of the backlog and at worst increase work-in-progress and add stress to individuals on the team.
So my advice: decide which type of team you are and focus.
In the last few months I’ve been speaking a lot both about objectives and “just in time backlogs”. I’m fired up and want to pursue this idea, if you are interested please let me know and I’ll write more.
Do you count the number of product backlog items in your backlog in tens? hundred? or thousands?
Does your backlog contain many stories which have been there for months, if not years, and yet never raise to the top of the backlog?
Is your success judged on your ability to do the backlog?
Backlogs were a good idea when they were introduced a bit over 20 years ago but today many teams slaves to the backlog – see my posts on the Tyranny of the backlog and Purpose over backlog. One of the benefits I’ve called out for OKRs is the ability to move away from backlog driven development (BLDD).
In Succeeding with OKRs in Agile I ask suggest you either need to prioritise your backlog over OKRs (in which case OKRs are derived from the backlog you intend to do) or OKRs over backlog (in which case OKRs are derived from strategy and the backlog plays a supporting role.) In my podcast with Jenny Herald earlier this year I even say “Let OKRs drive… nuke the backlog.”
Filipe Albero Pomar recently shared his backlog freshness blog which I think is great. Freshness is a great way to think about the state of the backlog that separates the size of the backlog from the relevance of the backlog.
Filipe’s idea is simply to talk about the backlog in terms of freshness – you have a fresh backlog if your backlog items are fresh: written recently, relate to current opportunities, problems and things people currently want.
And of course, the opposite of fresh: stale, stories that have been sitting in the backlog for months, even years, stories that relate to yesterday’s problems and project, stories which people wanted last year. The existence a big backlog of stale stories means the team is seen to be not delivering, the end-date is far off because people still expect all the work to be done.
Filipe suggests backlog freshness can be measured:
1. Set a cut-off date
2. Categorise stories as fresh or stale: fresh stories have been written since the cut-off date, those which are older are stale
3. Calculate freshness as a percentage of fresh from the total: if 25 stories out of 60 have been written in the last month then the backlog is 41% fresh, and 59% stale
Thats a useful metric, I think we can do better, look at the graphic above. I group backlog items into age groups and graphed them. For completeness I added a line to indicate average story age. Clearly this backlog is not fresh – nearly half the stories are over a year old.
I like the idea of graphing backlog freshness because it is easy to understand and makes an impact. In the graph above I’ve categorised backlog items into age groups and added an average line. Clearly this is not a fresh backlog. Whether this is the way to demonstrate backlog freshness I’m not sure – I’m playing with a histogram and quartile ranges.
With some clients I’ve thought of the backlog like a mortgage. There is the principle (the existing backlog), the interest rate (the growth rate of the backlog) and the monthly repayments (stories reaching done). Unfortunately when you do this you sometimes find the mortgage will not be paid for many years, and perhaps never. (Don’t worry about estimating the size of stories, for this sort of analysis the number of stories will get you started, and if your backlog is measured in hundreds of items the small will offset the large.)
I’d love to talk more about this and experiment with some ideas, I think it could be a very useful way of thinking about the backlog.
“Hello Allan , I followed a few of your seminars on OKRs and I am reading your book. I do have one question. I will start a transformation soon. The company has the ambition to move to Scrum and also OKRs; Do you have any advise on where to start? OKRs first or SCRUM first. Thank you a lot !”
This question appeared in my mailbox – or rather my LinkedIn box – a few weeks ago and I thought other readers might be interested in my answer.
My answer is: do both together.
That will sound ambitious if you see Scrum and OKRs as distinct things but I don’t, to me they are synergistic and can be viewed as one change. In the process I see the opportunity to create a simpler form of agile, or simpler version of Scrum if you prefer. Let me describe.
The Scrum Master role remains pretty much the same as regular Scrum. The main change is that in addition to facilitating planning meetings and sprint retrospectives the Scrum Master will additionally facilitate OKR setting sessions and OKR retrospectives at the end of the cycle. They will want to ensure the OKRs are known by everyone and people reference to them during sprints.
Similarly the Product Owner role remains pretty much the same with the additional need for the PO to lead thinking on what OKRs to set. This means the Product Owner needs to do more horizon scanning, talk to more stakeholders and prepare to set objectives that will last several sprints rather than just one at a time.
Simplification comes in that there is no need to build up and administer a product backlog. Set the OKRs, then go straight into a planning meeting and ask “How do we make progress against this OKR?”. Write the stories you need to do that. Use the OKRs as a just-in-time story generator. If you generate stories you cannot do this sprint then put them in a product backlog for the next planning meeting.
In the next planning meeting review progress and ask yourself again: “what do we need to do to make progress on these OKRs?”. It might be that you have some stories from last time to work with, if not write some more. OKRs in effect become the Sprint Goal and you generate the stories from there. (If you are using a Product Goal as well then reference that when setting the OKRs at the start of the cycle.)
Estimation is reduced because you have fewer stories in play and in the backlog. If you want you can use story points and velocity to determine if the sprint is full or you can just ask the team “Is that enough work to keep us busy?” and “Do we have space for more?”
If you want a more sophisticated system then get the stories out on the table, put them in the order they are likely to be done, then go from top to bottom asking “On a scale of 1 to 10, What are the chances we will get this story done in this sprint? – where 1 is unlikely and 10 is almost certainly.” If the probability is below 8 you probably take action, break the story down, reorder the work order or just accept that you probably won’t do everything you would like to.
In the longer term you can count the stories done to build up a record of capacity.
I would aim to do end of sprint demonstrations and better still release to live. The OKR may not be complete but the stories in the sprint can start delivering value early. As usual keep quality high, aim for zero bugs and automate everything that needs testing.
If you are new to both Scrum and OKRs then I would probably run one week sprints and a six or eight-week OKR cycle the first time. Do a retrospective at the end of the OKR cycle, after that you might move to two-week sprints and 12 week OKR cycles but keep an open mind and decide what works for you.
All the way through keep delivering benefit to customers, hitting OKRs is icing on the cake, and there are no prizes for doing perfect Scrum.
I’d like to think I outlined this recipe in Succeeding with OKRs in Agile but I suspect I wasn’t as clear as I could have been. Increasingly I’m seeing OKRs as a means of stripping agile back and simplifying it.
I blogged last week that I had begun work on a new book – How I Write Books which is now a work in progress at LeanPub – signup and be the first to know when the draft is published.
Well a funny thing happened while I was setting up my tool chain to write that book: I found another book! Well, perhaps half a book is a better description.
Succeeding with OKRs in Agile Extra is a companion to last year’s best seller, Succeeding with OKRs in Agile. But it isn’t a complete book in its own right, it isn’t really a sequel, it is a companion. It contains a mix of material. Material which didn’t really fit in the first book, material with was’t needed, ideas which didn’t develop far enough and some unfinished chapters.
As such it is like my Xanpan Appendix, unused material which is still interesting and might appear elsewhere in time.
When I engage with company and teams I’m always keen – nee desperate – to get to meet the engineers and teams who are doing the work. If days, maybe even weeks, go by and I’m not doing that I get very frustrated. More importantly I’m not sure what to believe from those I am talking to.
There was once a bank I spent time with. As soon as I got to the office I discovered almost all the engineers were in a far away country and I wasn’t going to get to visit that country. The few engineers in the London office spent a lot of their time hand-holding those in the far away place. When you looked closely, when you spoke to the engineers far away you found things didn’t add up. One delivered a perfect 10 story points every iteration without fail. Another team increased velocity sprint after sprint. One engineer fell off his moped and broke his arm, the work was still delivered on time – it took all my wiles to discover another engineer had worked all weekend to meet the deadline.
Why am I so desperate to meet the engineers? – well there are several reasons, some more rational than others.
First off, the engineers are where the work happens. In lean parlance they are the gemba, source of truth.
Second, these are the people who will need to change or be changed. There is only so much you can change with an organigram – and to be honest, I’m doubtful reorgs really change much. Sometimes I imagine managers moving their workers around like pawns on a chess board while the reality of work is hand-to-hand combat.
Thirdly, and perhaps most importantly for me: I see my role as helping these people. I am, by profession, by temperament and by ancestry an engineer. I am motivated by the desire to help those who do the work have a more fulfilling life. I still remember the frustrations I faced as a coding software engineer.
Thats why it hurts – really hurts – when engineers tell me “agile is rubbish”, that “agile has nothing to offer”, when they tell me that I’m not helping. Its not that I’m precious about agile, “agile” is just the toolset I’ve found helps. I also know that tool kit allows me to go outside the toolkit.
I was hired by a Californian company to give agile training to their Cambridge team. A few minutes in, one of the engineers told me directly “Agile can’t help us here, we can’t go any lower.” The other engineers in the room were of the same opinion. It turned out the managers had been to Scrum training and come back pumped up about high performing teams and faster-better-cheaper. Sustainable pace, autonomy and quality weren’t on the table.
That hurt and it may have been the toughest training gig I’ve ever had but I think I turned it around. I demonstrated the need for quality and explained the managers were missing essential parts of the puzzle. Unfortunately I didn’t get to meet the managers – they were off playing chess.
But I do engage with managers. Often they are the route to the engineers. Unfortunately some engineers see that as a problem in itself: “our problem is tech debt, sprinting won’t help us” so I’m discounted. In my world – the world of Xanpan – sprinting is a rod you put up your back to make yourself better, if you don’t address quality (e.g. tech debt) issues then you won’t succeed at time-boxed iterations.
(BTW I talk about engineers because most of my work is with engineers, and software engineers at that. I’ve worked a little with other professions and I’m sure most of what I say carries across directly but my experience and empathy is greatest with engineers.)
To deal with managers one needs to understand their concerns, one needs to listen and speak in ways they understand. Engineers may struggle with managers and technical issues but managers also struggle with their managers, organizational debt, customers and the market.
The same is true when I wonder over into the world of product ownership – Product Managers and Business Analysts. Engineers have a bad habit of seeing these roles as “Management” but if you spend time with the “demand side” people you find their concerns are almost identical to coding engineers. BAs worry that what they are being asked to do is unreasonable, that it doesn’t make sense, that something else needs to change first and that people don’t appreciate how things really work. The biggest difference between programmers and BAs is simply that, on average, BAs dress more smartly and are more likely to put on a tie.
One can’t understand a system and one can’t get to the truth if one can’t visit the place where work happens. When manufacturing things that place is the production line, in the digital world that place is the mind. Constructing software is an intellectual exercise that happens in the mind and is only manifested via a keyboard in code. To see the truth one has to speak to engineers.
I’ve seen some awful work environments: a room packed with 28 engineers, very few windows, little fresh air, a development manager on a raised platform at one end, the HR manager at the other end, her desk right by the single door in and out with the clock-in-clock-out cards on the wall.
More recently a large project at a matrix managed organization. The complexity made it difficult to know who was actually on the project and what teams existed. Management existed in its own bubble.
I feel pain simply seeing such places. What it can be like to work there I can only imagine. I assume people become dumb to the pain, switch off to the failing and accept the normalisation of deviance. Or, to put it another way: a culture of failure.
Both of these two examples shared one thing in common: massive Gantt charts which claimed to plan the work. In one case I saw someone scheduled to spend a month writing a manual in two years time. While these charts claim rationality they are so disconnected with the gemba as to be fantasies. I feel cognitive dissonance knowing that the managers who put their faith in such mechanisms are both rational and totally mad.
Encountering such places is painful for me. On the one hand I want to help, I want to make the engineers lives better – that is what I do! The challenge can be great. On the other hand it can be mentally and emotionally draining. Because I am passionate about what I do I feel that. If I switched off, if I treated it as a money paying gig then I too become part of the same culture and loose my efficacy.
On the other hand, when things go right I love it – perhaps because I’m an engineer and I see fixing the organization as a way of fixing the code, its called Conway’s Law.
Confession: I’ve been avoiding the words “agile mindset” for some time because I don’t know what it is. And, completely by coincidence, I’ve recently had a couple of encounters that have caused me to think again. So let me explain…
I repeatedly find myself wrestling with the question “What is agile?” The question came up recently in a new form when I was invited to give a talk on “The Agile Mindset.” I appealed for help on LinkedIn. I got some great answers and the diversity of answers confirmed what I though: it is hard to describe “the agile mindset” in a short or generally agreed form.
The first problem is that to explain “the Agile mindset” one first has to agree what agile is, and is not. I have my own view but I know there is a diversity of opinion so I find it useful to describe “Agile” with the story of the blind men examining an elephant: one feels the leg and says “This is a mighty tree”, another feels the tusk and says “It is a strong sword”, another the trunk and says “It is a strong snake” and so on. Each interprets the part they encounter as the whole yet the whole, to one who has never seen an elephant, can be hard to comprehend.
Illustration from the Natural History Museum, London
The same is true for agile.
The literalist looks in the dictionary and says “Agile is about being fast, reactive and responding to the outside”, the engineer looks at agile and says “It is about doing quality work so we may deliver more”, the Scum aficionado says “It is about high performing teams and alignment”, the Lean thinker says “It is about reducing work in progress and simplifying workflows” and the management consultant says “It is about delivering more with less.”
All are right, none is wrong. And while that is a problem in describing what agile is it is also a strength. Agile is multi-faceted and offers “something for everyone.” While different people emphasis different things it also means the whole is more than the sum of the parts. If you can harness high performing teams, with engineering quality, low WIP and reactive processes then you can deliver the fabled faster, better, cheaper.
But that also makes it hard.
It also goes some way to explaining why “Agile Coaches” never agree: each has their own interpretation of how to put those pieces together to make the whole – to change metaphor, everyone approaches the jigsaw differently.
And again that is right because every jigsaw, every application of agile, exists in a unique context and must be faced on its own terms – to quote Tolstoy: “All happy families are the same, all unhappy families are unhappy in their own unique way.” (And long time readers might notice I just contradicted myself.)
And one important reason why the jigsaw is always different is: in completing the last jigsaw, and since completing it, you, and everyone else as learned, the bodies may be the same but the people – and their minds – are different.
Ultimately, I still claim “Agile” is learning, specifically organizational learning: the thesis I laid out in my first book over 10 years ago Changing Software Development.
Hence I say: The only thing you can do wrong in agile is work the same as you did three months ago. To be agile one should always be learning and changing as a result of that learning.
I should explain that some more in another post, and I’ll have more to say about the agile mindset soon.
I almost despair when I hear people advocate cascading OKRs: the idea that someone, some team, some central planning department, can set OKRs which then flow down the organization with each “lower” group implementing some small part of some “higher” ask. What could be more waterfall like?
I admit, when I started working with OKRs I kind-of-expected to be shown the OKRs of the “above” before my team wrote theirs. But when I thought about it, and the more I thought about it, the more I realised if you did do it that way then it is decided unAgile. How can a team be really autonomous, self-organising and self-managing if they have goals handed down to them?
There was a point when I was wracked with self-doubt: am I interpretting OKRs differently to the rest of the world? How do I reconcile agile and cascading OKRs? What am I missing? – but, when you look around, I am not the only one. In fact, if you read, watch and listen to OKR commentators the majority agree with me: the teams delivering OKRs need the latitude to set their own OKRs.
Reconciling OKRs with agile is far from the biggest problem. In fact there are, at least, two bigger problems, one concerns team motivation. Can a team ever be motivated to do something they have no say in? Perhaps some can, I can’t and I know others who don’t. At the very least team members need to be asked.
Motivation becomes especially problematic if you want OKRs to be stretching. If you set someone a stretching goal and ask them to hit it without involving them then don’t be surprised if they shrug their shoulders.
Still, we haven’t got to the biggest problem.
The biggest problem with OKRs is not the metaphysical issues of motivation and whether one is truly agile or not. The biggest difficulty is simply: cascading OKRs are not practical.
First think about the timetable.
If every team is waiting for the team above them to issue OKRs before they set their own then you have a delay built into the system. And the more levels of hierarchy you have the greater the delay is going to be.
For example, suppose you have an executive team, and middle management team and several delivery teams. Then each cycle the exec team need to set some OKRs, once they have set their the middle management can set theirs, and then the delivery teams can set theirs. At each cascade point there needs to be communication, and each point creates the possibility of misunderstanding and mistakes.
Setting OKRs isn’t instantaneous, I think you need about a week to have a think, reflect overnight, iterate once or twice but, if you are well practices, and don’t hit any delays, you might do it in two days. Either way it is going to take at least a week, and possibly three, to get all three layers set. And if anyone runs late then it has a knock on effect.
I’ve heard it said that the Key Results of higher levels become the objectives of the next layer down. The key results of this layer the become the objectives of the one below them. But that assume that the OKRs themselves are a series of “items to do” and that each objective is made up of several pieces which are themselves things to do.
Sure, it sometimes happens that way. I may even have been guilty of interpreting them that way sometimes. But these days I see Key Results not as small pieces of work which, lego style, build into a bigger objective but as Acceptance Criteria: the parameters which the outcome needs to satisfy.
Now to some degree acceptance criteria can be translated into work items to do, and vice versa, but not always. Consider this:
Objective: Improve overnight batch processing to save 10% of work processing costs Key result #1: Shorten batch processing time by 1 hour so staff do not need to wait for run to complete in the morning Key result #2: Reduce false positive alerts by 100 per day so that staff waste less time
Now these key results could be packaged as individual work to do but perhaps they are the same piece or work. Perhaps a database upgrade could address both issues in one go. Which path you take is a design decision.
Seeing key results as acceptance criteria changes them from work to do into bounding conditions.
In Succeeding with OKRs in Agile I advise against having domino key results: don’t set key results so that failing to hit one makes others impossible to hit. So, for example, if the DB upgrade had been added to that previous example as key result #1 then the team would have been committed to doing it. And if the upgrade had failed then the other key results would have been lost. Leaving it out gives the team the decision on how to proceed: the people doing the work decide the best way of meeting the objective.
That advice is given within teams but it also applies between teams. If, the Middle Management team require three lesser teams to deliver work to build their own objective then, if any one team fail the middle management team will not only miss one key result but will therefore miss their objective.
Done like this the OKRs become fragile and a dependency nightmare. That will have two effects, first more time will be needed when setting OKRs to identify and mitigate the dependencies, then more time will be needed to manage the dependencies. Progress will only occur at the speed of the slowest.
Second, these problems will encourage people to play it safe and not set stretching and ambitious OKRs. Predictability and safety will be prioritised.
Now if we take the alternative approach and each team sets its OKRs independently then the time lag is removed, teams set OKRs in parallel and if someone is late it doesn’t matter. Dependencies may still exist but they have not been baked into the OKRs so teams can put effort into removing dependencies (reducing coupling and increasing cohesion) rather than putting that energy into managing the dependencies.
So, while we might argue about whether OKRs should, or should not, cascade down; and while we might argue about the psychological effects of being given an OKR by another, simply remember: cascading OKRs mean setting OKRs is going to be more complicated and take longer.
