Agile

3 ideas until you nuke the backlog

Agile / /
  1. Lead with goals
  2. Write an “use by” expiry date on new backlog items
  3. Keep an ideas list, maybe

When I deliver “Honey, I shrunk the backlog” and when I tell people “Nuke the backlog” there are a few questions and talking points which come up again and again. So, if you read my last post and have been asking yourself how you live with a backlog you want to nuke… read on…

Lead with goals

“My boss won’t stand for me deleting the backlog” I empathise. I know it happens.

At the same time I wonder: does your boss really care? – I’m sure some of them do, I see many Product Owners who are really “Backlog administrators.” Their boss is certainly leaning over their shoulder checking on what being done. If this is your case then your boss is the real Product Owner, sorry to say this but you are really a goffer.

In this case you want to educate your boss, you want to start having discussions about a better way. This is going to be a long and hard path. There is no sure fire advice I could give you here, except to suggest you give me a call.

Assuming your boss give you some leeway then go and start a conversation about your bigger goals. Beyond “delivering backlog items” what are the goals your goals? More specifically, what are driving at for the next 10 weeks?

Start to have a conversation about goals bigger than backlog items. Build a routine, a super cycle, around your sprints with the boss and team to discuss bigger goals. Then, during the cycle drive with the goals. If there is a suitable backlog items that contributes towards the goal(s) then do it. If not, write it out and do it immediately.

Either way, whether you are doing this to work around a boss or as a mechanism to tradition to a backlog-less world the same idea applies: create a super cycle, set goals every 10 weeks (approximately) and then drive through the goals rather than the backlog.

Drive with the goals and put the backlog in the back seat, it is secondary. The aim is to avoid nuking the backlog by letting it fad into irrelevance.

Write an “use by” expiry date on new backlog items

For any item you do add to the backlog make sure it has an expiry date. That is: a date after which it will be removed from the backlog. Giving every backlog item a life expectancy won’t help you today, but it does mean that in the months ahead some items will “self delete” from the backlog.

After a while you might want to visit older items in the backlog and (if you can’t delete them immediately) assign them “use by” date.

I am sure a few people will say “O this need will live for ever.” In which case you can put a long date on it, say 10 years. But that also tells you: there is no urgency. You can do this item anytime in the next 10 years and add value, it can wait.

Better still, write a “best before” and a “use by” date on the item

The best before date will tell you the date by which an item should be done to maximise benefit. After that date the benefit will decline, it might still be worth doing but it is not as beneficial. The “use by” date now tells you the date on which it has no benefit.

Now when you are reviewing the backlog you can see which items can be pushed back and which items need doing sooner. This is a little bit of a double edged sword for the requester, if they say “If I don’t have it in 2 months it will start loosing value” then it is more urgent, but also if it doesn’t make the cut soon then it can be removed soon.

Keep an ideas list

When you have a great idea, or when someone suggests something you could do add it to an ideas list – not the backlog. In fact, don’t show the list to people, don’t promise anything to anyone. This is your list for things you don’t trust to your memory.

Some people operate their backlog like this already but many people assume that if an item is in the backlog it will be done one day. Others measure the backlog and forecast dates. But ideas may never be done so they complicate this thinking.

Personally I like to think that great ideas will either get remembered or rediscovered. That said, I also write down lots of ideas. However, I frequently throw my ideas lists away. So if at 11pm I think of something I’ll write it down, three weeks later if it is just moving from one list to another I’ll cross it off. I rewrite my “todo” and “priorities” lists regularly.

If it helps then just keep ideas some other place. One team I worked with created a “Sprint 99” – a sprint so far off in the future it was never going to done. They parked all the good ideas there so they had them for reference and if they needed them but there was no suggestion they would ever be done.

You will also want to think carefully about what you tell people when they say “I’ve got a great idea, can you add it to the backlog?” You want to be honest, but you don’t want to create a long conversation. So you might want to say something like “Great, thanks, I’ll add it to our ideas list, if it becomes a block please come back to me and we can talk some more.” In other words, put the ball back in their court to show the value of the idea.

I’ll admit I’m nervous about this suggestion. Part of me things it will inevitably become to be seen as a backlog. I think important things will get remembered, and things which aren’t important can just as easily get lost when put among 1000 other things. Still, I know some people will take comfort in this idea so give it a try and let me know.

This piece was originally published on Medium.

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Nuke your backlog?

Agile / / / , ,

When I deliver “Honey, I shrunk the backlog” and when I tell people “Nuke the backlog” there are a few questions and talking points which come up again and again. So, if you read my last post and have been asking yourself how you live with a backlog you want to nuke… read on…

Lead with goals

“My boss won’t stand for me deleting the backlog” I empathise. I know it happens.

At the same time I wonder: does your boss really care? – I’m sure some of them do, I see many Product Owners who are really “Backlog administrators.” Their boss is certainly leaning over their shoulder checking on what being done. If this is your case then your boss is the real Product Owner, sorry to say this but you are really a goffer.

In this case you want to educate your boss, you want to start having discussions about a better way. This is going to be a long and hard path. There is no sure fire advice I could give you here, except to suggest you give me a call.

Assuming your boss give you some leeway then go and start a conversation about your bigger goals. Beyond “delivering backlog items” what are the goals your goals? More specifically, what are driving at for the next 10 weeks?

Start to have a conversation about goals bigger than backlog items. Build a routine, a super cycle, around your sprints with the boss and team to discuss bigger goals. Then, during the cycle drive with the goals. If there is a suitable backlog items that contributes towards the goal(s) then do it. If not, write it out and do it immediately.

Either way, whether you are doing this to work around a boss or as a mechanism to tradition to a backlog-less world the same idea applies: create a super cycle, set goals every 10 weeks (approximately) and then drive through the goals rather than the backlog.

Drive with the goals and put the backlog in the back seat, it is secondary. The aim is to avoid nuking the backlog by letting it fad into irrelevance.

Write an “use by” expiry date on new backlog items.

For any item you do add to the backlog make sure it has an expiry date. That is: a date after which it will be removed from the backlog. Giving every backlog item a life expectancy won’t help you today, but it does mean that in the months ahead some items will “self delete” from the backlog.

After a while you might want to visit older items in the backlog and (if you can’t delete them immediately) assign them “use by” date.

I am sure a few people will say “O this need will live for ever.” In which case you can put a long date on it, say 10 years. But that also tells you: there is no urgency. You can do this item anytime in the next 10 years and add value, it can wait.

Better still, write a “best before” and a “use by” date on the item.

The best before date will tell you the date by which an item should be done to maximise benefit. After that date the benefit will decline, it might still be worth doing but it is not as beneficial. The “use by” date now tells you the date on which it has no benefit.

Now when you are reviewing the backlog you can see which items can be pushed back and which items need doing sooner. This is a little bit of a double edged sword for the requester, if they say “If I don’t have it in 2 months it will start loosing value” then it is more urgent, but also if it doesn’t make the cut soon then it can be removed soon.

Keep an ideas list

When you have a great idea, or when someone suggests something you could do add it to an ideas list – not the backlog. In fact, don’t show the list to people, don’t promise anything to anyone. This is your list for things you don’t trust to your memory.

Some people operate their backlog like this already but many people assume that if an item is in the backlog it will be done one day. Others measure the backlog and forecast dates. But ideas may never be done so they complicate this thinking.

Personally I like to think that great ideas will either get remembered or rediscovered. That said, I also write down lots of ideas. However, I frequently throw my ideas lists away. So if at 11pm I think of something I’ll write it down, three weeks later if it is just moving from one list to another I’ll cross it off. I rewrite my “todo” and “priorities” lists regularly.

If it helps then just keep ideas some other place. One team I worked with created a “Sprint 99” – a sprint so far off in the future it was never going to done. They parked all the good ideas there so they had them for reference and if they needed them but there was no suggestion they would ever be done.

You will also want to think carefully about what you tell people when they say “I’ve got a great idea, can you add it to the backlog?” You want to be honest, but you don’t want to create a long conversation. So you might want to say something like “Great, thanks, I’ll add it to our ideas list, if it becomes a block please come back to me and we can talk some more.” In other words, put the ball back in their court to show the value of the idea.

I’ll admit I’m nervous about this suggestion. Part of me things it will inevitably become to be seen as a backlog. I think important things will get remembered, and things which aren’t important can just as easily get lost when put among 1000 other things. Still, I know some people will take comfort in this idea so give it a try and let me know.

This pieces was first published on Medium, Nuke the backlog.

Nuke your backlog? Read More »

Comments, off, sorry

Agile / /

I’ve always enjoyed the comments people leave on this blog – even when people disagree.

Unfortunately, for the last few months the vast majority of comments I am receiving are spam – people trying to add links to their own websites and such. The same comments are made again and again, sometimes a dozen in a day.

So, with a heavy heart I’ve switched comments off for now. I’m happy to receive your comments, please e-mail me allan AT allankelly.net.

Of course, as I’m experimenting with Medium at the moment most of my content is appearing there and you can comment there. So please follow me over there.

Comments, off, sorry Read More »

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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Nuke the bug list when you nuke the backlog

Agile / / /

“Nuke the backlog” originally a quick comment in a podcast about OKRs it summed up what I had come to believe. “Honey, I shrunk the backlog” presentation expands on that idea and outlines why I think teams should replace backlogs with just-in-time story generators – powered by OKRs or some other goal setting technique.

So I shouldn’t have been surprised when this question arrived in my mailbox:

“Throw away the backlog, is that for old bug tickets too? How does that work?”

The short answer is “Yes, throw away the bug list too.”

What do you mean, “Bug” ?

Basically the things we call bugs can be divide in two. Some are actual defects – things the system should never have done and quite possibly are detrimental to the running of the system. Everything else might be considered an enhancement. Logical right? Only where do you draw the line?

If I hit return 50 times and the system crashes the machine that is clearly a bug, the machine should not crash. But then again, how likely is someone to press return 50 times? Let me suggest not very often. And if they do, what are the chances of them doing it again? After all, there is a very easy work around. So while this might be a bug it might also be considered an enhancement request.

Ultimately, where you draw the line between bug and enhancement is subjective. This becomes really clear when you can count known bugs in single digits, 5 instead of 500. Until then calling a “change request” a bug is little more than an attempt to exert leverage and prioritise work. Calling it a bug might also have some other beneficial effect: apportioning blame might further another argument and moving a change from CapEx to OpEx column might help balance the books.

Consider all bugs from a priority point of view instead. While many different scales are used there are basically 3 categories: #1 must be done and done soon, #2 really should be done but not right now, and #3 should done but can be put off indefinitely.

Categories #1 and #3 are easy: the first are just done, the third are ignored forever but we kid ourselves that one day we’ll do them (right after we fix climate change, famine, war and pestilence.) Still, it is relatively easy to close all #3 reports over 12 months old. And next month close those over 10 months old. And so on. By all means keep a list of them somewhere but don’t pretend they will be fixed.

The only real debate are around category #2. We keep these on file in the hope that the Bug Fixing Fairy will fix them one day. In the absence of the fairy any work will require time and people to fix. That means they need to fight against all the other #2s and all the new shiny stuff. It is the same people who fix bugs as make shiny new things. It is a choice. A choice made probably by someone with the title Product Owner or Product Manager.

Which means if that fix isn’t more valuable than everything else then it won’t be done. This is the same argument I use when I say “Nuke the backlog.” If the fix isn’t valuable enough to justify being done, then it waits in a queue. The longer it waits the less important it is, leave any #2 bug there long enough and it will transform into #3.

What do I do?

The whole “is it a bug or is it a change request?” discuss is an utter waste of time. Whatever you call it work is needed, it s work to do, that work costs, that work creates benefits – the cost and the benefits are independent on what you call it. Benefit should the overriding criteria.

So

1) Fix the bugs you think need fixing

2) Don’t pretend you will fix the others, throw the bug list away

Of course, throwing away the records does not fix the “bugs”, they still exist – the same way cockroaches seem to survive everything. But we are recognising that, like cockroaches, the cost of action is not justified. This is simple honesty, a list of 100 items that we pretend will be done one day is dishonest. If that honesty creates a debate then good.

I have more advice – and more subtle advice in my “Bug management strategies” which outlines six strategies for addressing bugs and can be found in my lesser known “Xanpan appendix: Management and Team“.

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Announcing the Succeeding with OKRs in Agile 2nd edition

Agile / /

The rumours are true, I’ve been working on a second edition of Succeeding with OKRs in Agile.

Now I’m ready to share, the content is stable, some polishing to do (mainly copy edit).

You can buy it now on LeanPub with free updates as they are ready.

In addition there is an OKR bundle available with give you the second edition and the first edition plus the unfinished Succeeding with OKRs in Agile Extra addition which contains additional chapters, journal articles, blog posts and Q&As. Buying the bundle will get you free updates to both the second edition and Extra as they progress.

No time scale for finishing Extra but I hope to have the second edition done by the end of the summer.

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AI will undermine offshore & WFH programers first

Agile / /

A postscript, continuing from AI might effect the world of software engineering and programming. I’m supposing the power of AI real and it can replace the people we now call programmers. What next?

Spoiler alert: This post if going to upset a lot of people, who like working from home or work as offshore.

Where will the first job losses come? – let me suggest the Indian IT industry has the most to loose from AI.

In past technology cycles the first jobs to go are usually the low end jobs. The jobs which are more easily replaced are the jobs which require less skill and knowledge. Initially new technology is far from perfect so it is applied narrowly to the simpler bits of work. For example, the co-pilot feature now appearing in programmers tools which can write part, but not all, of the function.

These are often the low wage jobs (that is not always true, sometimes low wage jobs survive because the cost means they aren’t worth replacing.) So, assuming AI programming starts at the low end and works its way up market who has the most to fear? The low wage coders, who are the low wage coders? – overwhelmingly the offshore, and often outsourced, jobs.

So, expect to see India’s tech sector hit before the USA and Europe, more generally, anyone who competes on price.

For similar reasons expect to see Stackoverflow and engineers who cut-and-paste code to be hit early.

Next, recall from my last post I said that Business Analysts and others who are tasked with understanding what is needed will benefit even as programming jobs are hit (assuming AI is true). That extends to programmers, again, many programmers actually spend a lot of their time working with customers, users – and even BAs – to understand what is needed. Such programmers, like BAs, will be safer than those who code-to-order.

Such roles are less transactional in nature. The problem, the solution, and even the role itself is vaguely defined. Understanding what is needed often requires understanding to turn a vague request into something much more specific. It requires empathy, it requires background information, it requires trust and a willingness to explore together.

Let me suggest that those things are still better done in person. Doing them online is possible but in general a much greater degree of communication and understanding is needed. Nuance can be important. For that reason I believe they are better done face-to-face, in the same location, time zone and even culture. Even if some work can be done remotely having a bond which comes from physical interaction can help.

Human’s will still have a role to play in working through vagueness. That is best done face-to-face so there is a premium for working in the office. If it isn’t vague then an AI can do it.

Again, offshore programmers will loose out here. Onsite engineers will be valued more. But also, engineers who work from home will loose out, especially those who work from home every day.

It is true, you can code from anywhere: the office, a coffee shop, your house. But acquiring deep understanding, empathy and trust requires you to be there. Right now is the worst time to stay at home.

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Winners and looses when AIs program

Agile / / / ,

I feel guilty, the rest of the world has gone AI mad and I’ve said nothing about it. I’ve been hiding. Part of me feels sad and threatened, is AI going to wipe out the world I knew?

So here is my take. Since I come from a programming background, and since this is where a lot of the AI opportunities are supposed to be I’m going to talk about this. To those of you from elsewhere, let me ask: can you apply my logic to your world?

We’ve been here before, once upon a time code generators were gong to replace programmers, another time it was “programming in pictures”, another time it was 4GLs. Is this time different?

The term “AI” has been applied over the last 20 years to many systems which are little more than rules engines. These may not require programming but they do require configuration. Configuration which can be complicated – more than selecting Preferences/Edit/… and click. Instructing computer how to work, whatever the metaphor, is called programming. Anyone who says “With this tool I replace the programmers” just become a programmers themselves.

Many of those code generators, and programming by clicking systems replace one set of problems with another set.

A thought experiment

So, a thought experiment: lets suppose AI can write code as good as a human. Your programmers are replaced. What happens then?

First: do you trust what the AI writes? Or do you still need testers?

There have always been companies out there who forego testers and testing, undoubtedly many will. But in general you will want to test what the AI creates. Just because an AI says 2+2=5 does not make it right. There are already documented cases of AI exhibiting biases in things like identifying criminals.

In fact you probably need more testers for two reasons: programmers used to do some testing, while AI will not make silly syntax errors it will still make logic errors. Additionally if AIs writes more code faster than before there is simply more work in need of testing.

Second: how do you actually know what you want? – many programmers and testers spend most of their time actually understanding what customers want. Think: when you use travel planning software you may reject the first suggestion because it uses buses not trains, the second because there is too much walking, the third because you prefer connecting at one station over the other.

If the programmers are gone then testers might take on that work as part of testing (trial and error cycles). Or you might turn to Business Analysts and Product Managers. There are the specialists who understand what is wanted.

BAs and Product Managers have another role to play: post evaluation. Now it is cheaper to produce solutions there will be more solutions and someone needs to see whether they actually solve the problem you set out to solve.

In fact, there is more work to do in choosing the problems to solve in the first place. After all, building and deploying a new system is only part of the problem. What about training people to use it? What about changing the processes around it?

In fact, if we are introducing more technology and solutions faster than we are going to need more change managers analysts and consultants to advise on workflow improvements. One day your entire company may be machines working seamlessly together but until then you need to accommodate the people. Which means someone, be they BA or consultant, needs to look again at the workflow.

And if we know anything from the agile and digital movement of the last 20 years it is that changing our approach to work takes time. The technology is the easy bit. It takes years, decades even, for processes to change.

While there are still humans in the system there will still be interfaces which will need designing. Interface, UXD or experience design, is not an entirely logical processes. You need to look at how people respond. With more systems you have more interfaces and more need of interface designers.

And because adding features to your product is now so cheap you suddenly have an explosion of extra features which makes the interface more complicated and may even detract from your product value – remember how the iPod won out over other, more feature rich, competitors? So now you need you analysts and designers to limit the features you add and ensure those you do are usable.

So far we have removed programmers but increased the number of Testers, BAs, Product Manager and Designers.

In one form or another all these people will be telling the AI what to do, as I said this is call programming. So many of those new hires will be doing some form of programming. The programming paradigm has changed, perhaps its more high level, but it is still there.

If AI follows the pattern of past technology change (and why shouldn’t it?) then:

The full benefits of technology are not realised until the rest of the system, particularly processes, change to take advantage of the technology. This can take decades.

Programming isn’t going away

New technology is often billed as replacing previous technology and/or workers. It might do that in time but it also expands the market. Electricity did not eliminate candles, more candles are produced today than ever before but we don’t use them for lighting (so much.)

I don’t see AI programming bots replacing programmers in many detailed roles, perhaps ever. The ins and out of something like Modbus, and at the other extreme enterprise architecture, will make that hard. But there are domains were AI will dominate.

Finally, as we adopt new technology and processes we give rise to new innovations, we find new markets we can address and new ways of addressing existing problems. That generates work and new roles.

So I am sad to think the joys of youth spent writing ‘Writeln(“Hello world.”)’ are coming to an end, and my children will probably never experience the joy of feeling a machine perform their wishes (LDA#0, JSR OSWord, anyone?) those days are already gone.

Rationally I know AI is not something to fear (at least in the jobs context) but emotions are not always rational.

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What do you mean by “initiatives and OKRs”?

Agile / / /

A few weeks ago I had a conversation with a potential client about OKRs. They started talking about “initiatives.” In fact, they talked about “initiatives” as a standard part of OKRs, one of those moments when self-doubt set in. I started wondering “What do they mean?” And more worryingly, “How do I not know about initiatives?”

When I did some digging it turns out that one, or possibly more, OKR consultancies talk about “initiatives” as a third level of OKR. For these consultants there is a hierarchy, Objective at the top, Key results below that and then initiatives as the “things you will do to deliver the key results and therefore the objective.”

Umm, maybe

In one way, I like the thinking. I agree that “what we will do” is not part of the objective and it’s not the key results. (A common mistake with OKRs, one I made myself years back, is seeing them as the to-do list.) So I can see why they label the things to do as another level. At the same time, I see two problems.

First is the hierarchical decomposition. Again, the idea that an initiative builds towards one key result which builds towards one objective. Once you start viewing key results as acceptance criteria which describe the post-objective world, this breaks down – the key results become cross-cutting. If your key result is “Customer receives their order within 48 hours”, for an objective of “Satisfied customers”, there is probably not just one thing to do. That goal may cut across lots of other pieces of work.

Is an initiative big or small?

Second, and perhaps more importantly, the word “initiative” is already widely used and means different things to different people, creating a recipe for confusion.

Specifically, although the #NoProjects community never standardised on the word, it is widely used as an alternative to “project” to describe a stream of work, an endeavour, a mission, a programme, or an ongoing effort. So for many of us, an initiative is not a small piece of work sitting below key results, but rather a big stream of work sitting above objectives.

This also hints at the reason why “initiative” was never agreed on. For many of us “initiative” has overtones of “beginning” – indeed my Apple dictionary uses words like “originate”, “before” and “fresh” when defining “initiative.” (In Dungeons and Dragons players roll “initiative” at the start of a fight to see who goes first).

So what do you think? Am I too sensitive? Have I missed something critical? – let me know in the comments or drop me a mail.

Still, there is most definitely a need to decide what actions are needed to deliver OKRs. When and how to do that will be in future posts, stay tuned. In the meantime, if you use the word initiative make sure you clearly tell people what you mean by the work.

What do you mean by “initiatives and OKRs”? Read More »

Why does agile need OKRs?

Agile / /
Why does agile need OKRs?

The comment I get again and again about my presentations and workshops, OKRs and others, is “passionate.” And it is true, I’ve been passionate about this thing which gets called “agile” for over 15 years. Now I know “agile” has become a dirty word in some circles, all I can say is “That’s not my agile.” My agile is about engaging everyone, about engineers doing quality work, a more orderly and effective work environment. This type of agile creates benefits like meeting deadlines, satisfying customers, a more orderly work environment and ultimately happier workers and an improved return on investment.

When I stand in front of people and talk I’m talking to my former self, the coder I was 20 years ago who struggled with all the same problems engineers struggle with today: unclear requests, too much work, weak management and yes, technology frustration. That’s why I’m passionate.

So why do I get excited about OKRs? And why did I write a book about them? – especially odd when know I was originally an OKR skeptic.

Let me honest: I’m not really passionate about OKRs. I’m passionate about what they can do for agile and how they can help those doing the work. OKRs are more than a very useful tool to add to the agile toolkit. Sure it is a very useful tool but they also address problems in agile.

First off OKRs are big, not small. Agile works best in small – remember diseconomies of scale? – small teams, small stories, small releases, … this is great for effectiveness but it looses track of the big things. The outer Matroska. Well, OKRs give us a mechanism for thinking bigger.

Second, standard agile (e.g. Scrum, XP and even Kanban) has no widely accepted solution to mid-range planning. We used to talk about “release plans” but since the arrival of continuous delivery that doesn’t make sense. People struggle to produce mid-range plans that are accepted by others. OKRs can plug that hole.

These two issues intersect when it comes to backlogs, in particular Scrum Product backlogs. All those small things clog up a backlog and without some planning mechanism merely obscure the truth. Put simply, backlogs don’t scale. Backlogs are useful when we are thinking days in advance and counting product-backlog-items (PBIs) in single digits but they fail when they contain hundreds of PBIs and extend years into the future. Again, OKRs can help here.

Third, OKRs provide a framework for elevating the conversation to more senior leaders and executives. These people lack their own agile context, their time is scarce and they don’t want to be bothered with small things which last a few days. But without their involvement and affirmation teams lack “air cover” from above and struggle to escalate issues upwards.

Not only do OKRs provide a communication interface to the senior team but the same mechanism facilitates communication and co-ordination with other teams. Done right OKRs create an API for the team and can push more authority down to the teams furthering self-organization.

When teams set their own OKRs we create a powerful feedback mechanism, a strategy debugger. (Conversely, cascading OKRs down a hierarchy destroys their power and undoes many benefits of agile working.)

In other words: OKRs allow agile to grow up.

That in a nutshell is why I think why agile needs OKRs, and why I’ll be writing more about OKRs.

Why does agile need OKRs? Read More »