agile

Pull, don’t push: Why you should let your teams set their own OKRs

Agile / / / ,

There is a divide in the way Objectives and Key Results (OKRs) are practiced. A big divide, a divide between the way some of the original authors describe OKRs and the way successful agile teams implement them. If you haven’t spotted it yet it might explain some of your problems, if you have spotted it you might be feeling guilty.

The first school of thought believes OKRs should be set by a central figure. Be it the CEO, division leadership or central planning department, the OKRs are set and then cascaded, waterfall style, out to departments and teams.

Some go as far as to say “the key results of one level are the objectives of the lower levels.” So a team receiving an OKR from on high take peels of the key results, promotes each to Objective status. Next they add some new key results to each objective and hand the newly formed OKR to a subordinate team. The game of pass the parcel stops when OKRs reach the lowest tier and there is no-one to subordinate.

The second school of thought, the one this author aligns with, notes that cascading OKRs in this fashion goes again agile principle: “The best architectures, requirements, and designs
emerge from self-organizing teams.” In fact, this approach might also reduce motivation and entrench the “business v. engineer” divide.

Even more worryingly, cascading OKRs down could reduces business agility, and eschew the ability to use feedback as a source of competitive advantage and feedback.

Cascading OKRs

Cascading OKRs are handed down from above

We can imagine an organization as a network with nodes and connecting edges. In the cascading model information is passed from the edge nodes to the centre. The centre may also be privy to privileged information not known to the edge teams. Once the information has been collected the centre can issue communicate OKRs back out to the nodes.

One of the arguments given for this approach is that central planning allows co-ordination and alignment because the centre is privy to the maximum amount of information.

A company using this model is making a number of implicit assumptions and polices:

  1. Staff at the centre have both the skills to collect and assimilate information.
  2. That information is received, decisions made and plans issued back in a timely fashion. Cost of delay is negligible.

However, in a more volatile environment each of these assumptions falls. Rapidly changing information may only be known to the node simply because the time it takes to codify the information — write it down or give a presentation — may mean the information is out of date before it is communicated. In fact the nodes may not even know they know something that should be communicated. Much knowledge is tacit knowledge and is difficult to capture, codify and communicate. Consequently it is excluded from formal decision making processes.

The loss of local knowledge represents a loss of business agility as it restricts team’s ability to act on changing circumstances. Inevitably there will be delays both gathering information and issuing out OKRs. As an organization scales these delays will only grow as more information must be gathered, interpreted and decisions transmitted out. Connecting the dots becomes more difficult when there are more dots, and exponentially more connection, to connect.

This approach devalues local knowledge, including capacity and ambition. Teams which have no say in their own OKRs lack the ability to say “Too much”, they goals are set based upon what other people think — or want to think — they are capable of.

Similarly, the idea of ambition, present in much OKR thinking, moves from being “I want to strive for something difficult” to “I want you to try doing this difficult thing.” Let me suggest, people are more motivated by difficult goals that they have set themselves more than difficult goals which are given to them.

Finally, the teams receiving the centrally planned OKRs are likely to experience some degree of disempowerment. Rather than being included and trusted in the decision making process team members are reduced to mere executers. Teams members may experience goal displacement and satisficing. Hence, this is unlikely to lead either to high performing teams or consciences, responsible employees.

Any failure in this mode can be attributed to the planners who failed to anticipate the response of employees, customers or competitors. Of course this means that the planners need more information, but then, any self-respecting planner will have factored their own lack of information into the plan.

Distributed OKRs

Distributed OKR setting

In the alternative model, distributed OKRs, teams to set their own OKRs and feed these into any central node and to leaders. This allows teams to factor in local knowledge, explicit and tacit, set OKRs in a timely fashion and determine their own capacity and ambitions.

One example of using local knowledge is how teams managing their own work load, for example balancing business as usual (or DevOps) work with new product development. As technology has become more common fewer teams are able to focus purely on new product development and leave others to maintain existing systems.

Now those who advocate cascading OKRs will say: “How can teams be co-ordinated and aligned if they do not have a common planning node?” But having a common planner is not the only way of achieving alignment.

In this model teams have a duty to co-ordinate with both teams they supply and teams which supply them. For example, a team building a digital dashboard would need to work with teams responsible for incoming data feeds and those administering the display systems. Consequently, teams do no need to information from every node in the organization — as a central planning group would — but rather only those nodes which they expect to interact with.

This responsibility extends further, beyond peer teams. Teams need to ensure that their OKRs align with other stakeholders in the organization, specifically senior managers. In the same way that teams will show draft OKRs to peer teams they should show managers what they plan to work on, and they should be open to feedback. That does not mean a manager can dictate an OKR to a team but it does mean they can ask, “You prioritising the French market in this OKRs, our company strategy is to prioritising Australia. Is there a reason?”

A common planner is but one means of co-ordination, there are other mechanisms. Allowing teams the freedom to set OKRs means trusting them to gather and interpret all relevant information. When teams create OKRs which do not align it is an opportunity not a failure.

When two teams have OKRs which contradict, or when team OKRs do not align with executive expectations there is a conversation to be had. Did one side know something the other did not? Was a communication misinterpreted? Maybe communication failed?

Viewed like this OKRs are a strategy debugger. Alignment is not mandated but rather emerged over time. In effect alignment is achieved through continual improvement.

These factors — local knowledge and decision making, direct interaction with a limited number of other nodes and continual improvement — are the basis for local agility.

Pull don’t push

Those of you versed in the benefits of pull systems over push systems might like toes this argument in pull-push terms. In the top down approach each manager, node, pushes OKRs to the nodes below them. As with push manufacturing the receivers have little say in what comes their way, they do their bit and push to the next in lucky recipient in the chain.

In the distributed models teams pull their OKRs from their stakeholders. Teams ask stakeholders what they want from the team and they agree only enough OKRs to do in the coming cycle.

This may well mean that some stakeholders don’t get what they wanted. Teams only have so much capacity and the more OKRs they accept the fewer they will achieve. Saying No is a strategic necessity, it is also an opportunity to explore different options.

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It’s the workflow, stupid

Agile / / / , ,

Sausages making illustrates workflow brilliantly! – For years I used this picture of sausages makers to describe the way teams work: meat goes in, sausages come out.

If you put pork in you get pork sausages out

If you put chicken in you get chicken sausages out

If you put beef in you get… in the aftermath of the 2013 horse meat scandal I used to joke “You out horse meat in you get beef sausages out.”

What comes out bears a strong relationship to what goes in.

If you put project A meat in in you get project A sausages out

If you put project B meat in in you get project B sausages out

Sure it works best if you have a dedicated team and you only put project A requests in. When A is finished the team switches and focuses exclusively on project B. But you know what it? It still kind of works if you mix as you go along.

When a team works on multiple different projects in parallel it is not so productive – reduced focus costs, switching between things costs too. It will be a damn site harder to make forecasts about what will be done when, answering the “when will it be done” question will be tougher. But it still works, you can still make forecasts just they will be even less reliable.

By extension, if you put business as usual meat in you get business as usual sausages out. If you put DevOps meat in you get DevOps sausages out. If you put company admin in you get company admin sausages out. Get the picture?

While it is great advice to “focus on just the project/product” the vast majority of teams I’ve ever worked with are not in a position to do that. Turning work down is above their pay grade.

Seeing the whole

In Xanpan I called this “Team centric”. The project you are doing is less relevant than the workflow you are operating. Xanpan explicitly discusses how to integrate “urgent but unplanned work” with planned “project” work, I’ve extended the thinking with OKR Zero.

When things go wrong teams become like a saturated sponge. People can’t see the correlation between what goes in and what comes out. Trust is reduced, more reporting and even policing is added. The workflow becomes more complicated, less predictable and more costly.

It is no use looking at the project. Each project is only part of the picture. Neither will looking at the BAU, DevOps or urgent but unplanned work help either. They are only pieces.

You need to look at the whole: the workflow, the sausage machine that makes the sausages.

It is of little use looking at the pork sausage project and asking how many pork sausages will come out next week if the team is also doing BAU and making some chicken sausages on the side.

Nor is it any use talking about the pork sausage project if every time the team turn the handle they have to stop. Check with accounts, check with the security team and check customers – all of whom have their own workflow. Customers who just want the team to “get on and deliver it.” Every time a team needs to interact, get permission, get feedback or anything else with another team, things slow down and grind to a halt. Other teams are most likely struggling with similar things so they all block one another.

Often when this happens, because people have the best intentions, and because they want to be productive, they start doing something else. Pork sausage production stops while they wait feedback on sausage sales. So they start producing chicken sausages. Then just as chicken sausages start coming out the pork feedback comes in and everything must switch back. But now the chicken meat is unwrapped and getting warm. By the time they get back chicken sausages it has gone off.

It’s the workflow, stupid. Let me suggest again: watch Stockless Production.

No one person

Everyone, and every team, is linked together in workflow so it is difficult for one alone to make a difference. Working harder, producing more often makes things worse not better. Individually people are pretty helpless.

Such workflow streams are full of work-in-progress, WIP, they are overloaded. This is really “work hopefully in progress” (WHIP). It is bad when one team is overloaded but when it is excess strategic wip the whole organization struggles. It is difficult to know where to begin fixing thing. You still have to start fixing it at the team level but until multiple teams start fixing there is not much improvement to show.

No one person can fix this. No single technology can change it. Maybe not even a single team. Everyone is connected. Only by looking at the whole can things be fixed.

Unfortunately this is where project warriors come along. They insist that everything is a project – which increases administration. One or two projects get expedited and are forced through but everything else deteriorates.

Saddest there are know solutions: work to completion, reduce workpiece size, operate a pull system not a push, work within capacity, allow for shit to happen (unplanned but urgent work) and don’t overload the team – in fact don’t load them more the 76%.

That is workflow management. The devil is in the detail, there are no big easy solutions – if there were they would have been applied already. Workflow management cuts across projects. Managers have a role to play here but not project managers. Project management is too narrow.

It’s the the workflow, stupid.

So finally, an advert: I’d love to help, call me, e-mail me, LinkedIn, WhatsApp, whatever medium you like, just ask.

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Is all management bad? Or is it just bad management?

Agile / / / ,

There is an interesting piece in this week’s Economist about the poor quality of management in the UK, “For Britain to grow faster it needs better managers” (paywall). It suggests bad management is a large part of the productivity gap between the UK and other developed nations. Living in the UK, and having seen inside many British companies this rings true with me. I’ve long thought it was less a case of “In search of excellence” and more a case of “In search of mediocracy.”

Now that said, I don’t have an objective point of view: I’ve been involved with many “project rescues” or “turn arounds” (actually I quite enjoy them, call me!) in the UK but my clients abroad are normally more stable. I suspect this is selection bias: because I’m UK based it is easy to ask for help. Flying someone in from abroad is a barrier so only the better managed companies in Europe and the USA would do it. So while I might think UK management is bad it is entirely possible that it is bad everywhere. Indeed, I am sure there is bad management everywhere, and there is good management too; but in the UK the ratio of bad to good is higher.

The international agile movement doesn’t do much to encourage management to improve. All the anti-manager talk (“self managing teams”, “no project managers”, etc.) creates a barrier. It has long been my view that such anti-manager talk is largely a reaction to bad management and it is entirely possible that “no management” is better than “bad management.”

Simultaneously, “good management” can be value adding, people don’t push back on “good management” (even if it gets branded as bad just because it is management). Sometimes, making things better for the many means being unpopular with a few. The few will voice their complaints more loudly than the many will voice their praise, and often it is hard to attribute success to managers anyway.

What we miss

The common agile view of management as “a bad thing” misses two points:

First off: removing the managers will remove some management work but will leave a lot. Removing managers does not remove management work. The work which remains either doesn’t get done (worse still) or is spread around those who remain so everyone’s work gets disrupted. On the whole these people don’t want to be managers, so they are unhappy and don’t have management skills. They do have other skills – business analysis, Java, support desk, whatever – so now they are not using their most productive skills and are unhappy with it.

Second, and more importantly: removing managers does’t do anything to improve the skills of those who do management work. Whether this is managers in place or people who have to step up when managers are fired. In other words, all this talk of “no managers” stops us from improving management skills one way or another.

Yes, I think workers and teams should have a voice in the work they do.

Yes, I think we should make group decisions and take into account diverse opinions.

Yes, managers sometimes need to use authority but good managers spend more time nudging, enthusing, guiding, structuring. Occasional use of authority can help, over use undermines.

Yes, I think people can take more responsibility. Some of what passes for management work is admin that could be dropped, information sharing which could be automated, or managers making work for other managers.

But I happen to think good management recognises all those things and respects the expert workers.

Bad management ignores all those things and subscribes to the “Action Hero model of management”: you do this, you do that, I’ll siege the bridge, if I’m not back in 10 blow it all to kingdom come, move it!

The irony is, those who subscribe strongest to the “no management” meme will say “Let the engineers (or doctors, or designers, or whatever) run things” but when you do that you find a management style cadre arises who are experts in their own field. Being a senior engineer (or whatever profession) often means being a type of manager, they need their original skills but they also need some management skills. If they don’t learn new skills those people become bad managers.

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Why don’t people Test First?

Agile / / / , / 1 Comment

In my last blog I describe two potential silver bullets: working test first and reducing work in progress. I finished by promising to discuss why they aren’t used more. This post briefly discusses why people don’t work test first, the second one, looks at why it is hard to reduce WIP, work in progress.

It is easy to understand why people don’t work test first: we (humans) are optimistic. Test first is hard and historically test comes at the end of a process. Because testing is traditionally (almost) the last thing that happens moving testing requires change which is counter intuitive and often perceived as risky. (That risk is very really for when work is sub-contracted: there is an incentive for the supplier to delay testing to make it harder for clients to change suppliers.)

The thing we call “Testing” has several parts. The first, should, involve working out what tests to do: test writing. Later those tests are executed (manually or automatically) against the candidate solution. If the candidate does not pass there is more work to do. While the test execution cannot occur until the is a thing has been created the tests themselves can be decided in advance. This is what I call test first: decide what tests you intent to perform. Thinking about the tests up front is an act of learning and informs the work of creating the solution.

Working test first requires thinking and it requires thinking about something we would rather not happen. Since we are optimistic we see this as waste, or something that should be done by people paid less than us. So it requires discipline to do it. You need to be able to project yourself into the future and ask “What will the result look like?” Thinking test first is often better done with others, e.g. pair programming or “power of three” analysis sessions, so keep each other disciplined.

While it is relatively easy to work test first when programming the skills required to write automated test first require some time to master. This skill still isn’t taught at most schools or colleges so people need to learn it later in their career. Since people are optimistic, they often lack the motivation to learn to write tests first so they never master the skills. Since they are always on the learning curve test first coding takes longer and they often give up before they master it. If they stay the course, if they master the skills then they will find that while coding may still take longer the elapsed time is less because they no longer need to fix things afterwards (“debug later”.)

(As an aside, I’ve long been of the opinion that when we get AI technology to write programs (which is now starting to happen) writing tests will become more important than code. While machines will write more code which executes and doesn’t crash there is still a need to test the code does what is wanted. If we have a good test set then machines can be left to iterate and mutate code until it passes the tests.)

Outside of code the testing skillset is less well defined and people are less accustomed to thinking about tests anyway. Consequently working test first is more difficult. Add to that the fact that there are many more parameters to consider, and people are more forgiving than machines and it become more difficult still.

So, while test first working might be a silver bullet it is not easy to adopt. But then, because it is hard to do it is also hard for your competitors to do which means test first can be the source of competitive advantage.

Next Why is it hard to reduce WIP?

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Two unspeakable Silver Bullets?

Agile, OKRs / / / , ,

“There are no silver bullets” wrote the late, great, Fred Brooks. Consequently most writers and evangelists avoid claiming they have a silver bullet even when it sounds like they are claiming just that. I’ve cautioned against silver bullets several times in this blog. I often find myself telling clients “The devil is in the detail.” Meaning: there are lots of things to address and no single big fixes.

Anyone claiming to have found a silver bullet deserves to be faced by scepticism. Still…

I find myself coming back to two solutions again and again. They are the closest thing to silver bullets I know. Even if these are not silver bullets in their own right applying either makes it easier to work the detail and tackle problems.

Yet these silver bullets dare not speak their name. To do so risks endless debate and damaging your own leverage.

Keep reading for the Silver Bullets

Writing this I’m avoiding naming the potential silver bullets because I even feel many readers will stop reading the moment I name them. Please, keep reading.

Both are widely discussed by the agile cognoscenti but both are controversial. Suggesting either may lead people to think you fail to comprehend the situation or are just stupid. Thus in both cases you are likely to end up in long discussions.

Both are disliked by opposite ends of the organizational hierarchy. Both ends are optimistic, and prefer to believe people should be able to rectify problems themselves (the people problem problem again.)

Both bullets are rarely applied with vigour. Perhaps because of the previous points. When I raise the points people plea helplessness, “My boss doesn’t understand.”

Both bullets scale: in the small and large, although they manifest themselves in different ways at different scale points.

Neither is an instant fix but both start to deliver returns relatively quickly. The problem with both is you need to keep the faith and keep applying them for weeks to see a difference. In both cases, people often give up before they see the benefit.

Bullet #1: work Test First

Specifically in technical teams applying Test First coding; whether Automated Unit Testing (e.g. TDD, test driven (first) development), Behaviour Driven Development (BDD) or some other form of Acceptance Test Driven Development (ATDD). Away from code, at team and organizational levels OKRs are implement the test first principle.

Test first will not fix all problems but it will remove a substantial number of problems. That makes managing the remaining ones easier. And as to where the “extra time” comes from, that is easy: the time you don’t spend fixing defects and misunderstandings. Test first is faster than debug later.

I’ve written a lot about test first so I won’t say more just now.

Bullet #2: reduce Work in Progress (WIP)

Most commonly WIP limits are applied through limited columns on a Kanban board or limiting the work taken into a sprint. Done right OKRs limit WIP too. However, reducing WIP requires discipline.

At the higher levels companies and Government entities seem quick to reduce staffing numbers but slow to reduce work. Accepting new “projects” is easy but resourcing them difficult. Rather than prioritise, say “No” and push back on work, everything is taken on. Individuals who push back as seen as pessimists, “not team players” and “obstacles.” Pushing back does not help your chance of getting promoted so leadership ranks tend to be populated by those who accept.

The result is salami sliced people and slow progress across a broad front rather than rapid progress across a narrow range. But, reducing WIP also seems to be the hardest medicine to administer. In fact, I sometimes find myself hiding WIP reduction measures.

As an aside, I feel WIP has gotten worse since the pandemic struck, the move to remote working means every conversation is now a meeting in the diary. Our diaries are now overrun with “Meeting WIP”. An ad hoc 10 minute conversation at the coffee machine is now a 30 minute Zoom call planned days in advance.

WIP reduction is applicable at all levels: reduce the number of pieces of work the individual is switching between, reduce the number of pieces of work teams are tackling, reduce the number of projects a department has in flight, and most of all: reduce strategic WIP.

Next time

There are lots of benefits of reducing WIP so let me ask: why is WIP so difficult to reduce? – that is the question I’ll address next time. So too is Why don’t people Test First?

Finally I’ll just note: I sometimes wonder why I stop being an OKR-cynical to learned to like them. The thing is, I see OKRs as a tool to address both these problems: OKRs are test first, and limiting OKRs is WIP limiting.

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Why OKRs require a strategy rethinking

Agile, Digital business, OKRs, Strategy / / / , , , / 2 Comments

OKRs offer a way to connect strategy – high level abstract goal type things – with delivery – low level concrete detailed task level things. OKRs offer a middle level planning. They are replanned often enough to be flexible while lasting long enough to give enough stability to take on bigger, more ambitious work.

As with so much else about OKRs there is a more agile way of going about this and a less agile way of going about it. Connect strategy to OKRs in the less agile way and you end up back at command and control. The give away sign is that OKRs cascade down the company so teams don’t control their own destiny, ambition is neutered and motivation is lost.

Which approach you take will largely depend on the seemingly academic question: “what is strategy?”

Many people see strategy as a one way street. Strategy making and execution is hierarchal with decisions made at the top are passed down. Alternatively strategy can be seen as emergent property of a cooperating network. Strategy is a two way street, each node both informs strategy making and execution is guided by the resulting strategy.

Depending on how you view strategy you are going to implement OKRs very differently.

Is strategy a kind of planning?

Sad to say, the predominant view of strategy is that it is some sort of grand plan. The plan sets out the “place” the company aims to get to (price, position, etc), plus the route for getting there. Anyone who has studied a little strategy will recognise this as the “Porter view of strategy.”

Strategy as planning inherently sees strategists as master planners, all the relevant information is fed into the strategy/planning department. Experts analyse the data and rationally decide what needs doing. The plans are sent out.

This is inherently hierarchical so it natural to use cascading OKRs as the implementation mechanism. But because teams have little say in setting their OKRs motivation is lost and ambition is neutered.

The is a machine like view of organizations, inherently top-down, deviation from the plan, the strategy, is an error. When OKRs do not directly support strategy OKRs need to be changed.

Study a bit more strategy and you will find that while Porter’s view has appeal it is not the only view. There are in fact many different schools of thought on what strategy is.

Emergent strategy is more agile

To my agile mind the “emergent view of strategy” fits better. Strategy emerges over time from the activities of the organization, part planned, part reactive and part backward looking to explain the past. Professor Henry Mintzberg describes strategy as “a pattern of behaviour over time” which chimes with my pattern thinking.

Strategy is a two way street, teams are edge sensors: detecting technology changes, production techniques, putting products in the hands of customers and gathering feedback. This allows learning and adaption. The organization as a whole is a learning entity: discovering customer need and mastering new capabilities. Teams have the authority to act in the best interests of the company and customers. Over time strategy emerges.

When OKRs do not reflect stated strategy it is a learning opportunity. Ask: why do team OKRs deviate from strategy?

Is the team seeing something which the strategists do not? – in which case the OKRs are signalling back from the edges to the centre.

Is the team able to follow strategy? – maybe it lacks skills or capacity, or maybe it is overloaded with “business as usual.”

Has the intended strategy has been clearly communicated? Or maybe there is no explicit strategy?

Strategy, OKRs and agility

OKRs, like other agile tools, are problem detectors exposing opportunities for improvement.

Perhaps obviously, the “Strategy as a plan” view is going to limit agile to a back-room delivery thing because it passes over the opportunities for feedback and centralises decision making. Conversely, the “Emergent strategy” view entirely compatible with devolved authority, independent teams, experimentation and “the agile mindset”.

When teams act on their own initiative the organization will be more agile. When teams wait for instructions everyone is less agile. There may be a price for agility: teams may repeat work, teams may pursue the “wrong” goals but the price of that efficiency is lost agility which costs in missed opportunities and improvements.

If you want high levels of efficiency and believe in planned strategy you will look to decide strategy and align OKRs with the strategy before you do anything else. However, that results in less agility.

If you want to using OKRs and maximise agility then you need to take an emergent view of strategy. In many ways, we back to the Theory X or Theory Y question.

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New year resolutions & improvement days

Agile, Agile Process / / / , , ,

Happy new year!

Traditionally new year is the time for making new resolutions. We resolve to change our ways, try new things, give up bad habits and make an effort to do things differently, for the better.

So why not try that in your work? Why not try that with your team?

A few years back I organised a “New Years Resolution” session at the company I was working for. Engineers gathered, we suggested ideas, we talked them through and we resolved as a group to do some new things. The fact that everyone was still fresh from a break and had been hearing about, and perhaps deciding on their own, new year resolutions, gave it an extra boost.

Yes, it was a bit like a retrospective and you could set it up as a retrospective on the past year.

Which leads me nicely on to: Agile Improvement Days – maybe I can help you?

Last year I visited Scandinavia several times to run a series of improvement day workshops for a client. The days were based around a series of well tested exercises, group discussion, reflection and action planning. Most of the days focused on teams but one of the days was specifically for product owners and another for business representatives.

These workshops came to mind when I was reviewing the survey I ran a few weeks ago: over 27% of respondents said their agile initiative “needs a reboot”. (Another 27% said it was early days and 33% said they were “in search of great.”) In thinking about how I could help these teams I realised I had a ready made, tried and tested answer: the improvement days!

As much as we talk about kaizen and continuous improvement it doesn’t always happen. Teams need reminding sometimes. I’ve long been a fan of the lesser know kaikaku – also called a “kaizen-blitz”. Even the best teams can benefit from trying something different. In fact, the best teams probably need something different simply because they have tried everything else.

So, I’m now offering my Agile Improvement Days workshops in their own right. You can have a single one off day, a package of days for multiple teams, different days over several weeks or have the days customised to your own need.

Feel like rebooting your team? Help your team move from good to great? Or deal with a specific issue? Have a look and let me know what you think,

And please, forward this on to anyone who you think might benefit from such days.

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Objective Driven Agile, BLDD & Reactive styles of development

Agile / / / , , ,

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.

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How fresh is your backlog?

Agile / / / , , , / 1 Comment

Do you struggle with an overwhelming backlog?

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.

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How fresh is your backlog? Read More »

Scrum or OKRs, which comes first?

Agile / / / ,

“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.

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