Making OKRs more playful using hill charts(martin.sh) |
Making OKRs more playful using hill charts(martin.sh) |
They're hard to get right though. Its easy to add too much process, make planning too much of a burden, or not regularly check-in.
One concept that's helped lubricate things is "task-relevant maturity", which I first heard about in Andy Grove's _High Output Management_. It's a gross phrase but essentially means to that people who could accomplish a goal in their sleep need less help than someone who is facing something new. Accordingly, I've cut more slack to the former when laying out OKRs.
Its hard to overstate how valuable that is. Senior engineers who've been in the same space for eons chafe at having to do the same pedantic things as a junior engineer, and rightly so--they've seen a million managers and fads come and go.
To the point of the article I _really_ like the concept, but I'm wary of demanding another step for fear that it won't take. Usually I try something out by myself but keep it optional for a year or two---or forever.
1. Beginner: you tell them exactly what to do and how to do it.
2. Novice: you mostly tell them what to do and encourage them to learn and experiment.
3. Experienced: you consult with them on what to do, and they mostly manage how to do it.
4. Expert: you give them the goal and mostly just ask them how they'll approach it and how long it will take.
Am I right that you idea is you're mapping the KRs to different points on the chart? Or is it about progress towards KRs?
It seems hard to decide where a KR lies in terms of uncertainty/certainty when it's just a measure
Simplifying something as complex as an engineering team or a company down to a couple of variables cannot possibly model the real world. You can't say this out loud though, because this goes against established leadership culture. You can't be one of them philosophers. We've got to have achievable goals here!
Example: once upon a time a goal was instituted where tasks were supposed to be assigned to the engineer with the most experience in a particular area. Focus! Faster time to close a ticket! Happier engineers - they work on what they are good at!
See the problem yet? Meeting the goal actually made it so that there were a ton of bottlenecks. If an engineer was out sick the team lost an expert in a particular area. Engineers got bored working on the same thing day in and day out. And because the OKR killed knowledge transfer it became impossible to tackle a problem as a group.
And so the old metric was declared a problem and a new ridiculously limited model of the world was put in its place.
Making your efforts focused on a thing seems like a good idea, given proper research and discovery is done and the metric to improve is measurable and meaningful.
I think the criticism you are voicing is more down to a management style rather than OKRs. I’ve never would isolate my team members in areas and prevent knowledge being focused in one person. Always let the group tackle the problem and let them decide on who is going to work on it. Encourage pair programming and especially during the problem discovery, involve the entire team (when tackling a large, new problem).
Smaller stuff can be picked up by the same engineer. A bug fix here, a small adjustment there. But as soon as you introduce a big chunk of business logic, it’s important to bring along the team. I feel like that’s not what happens to you, but I don’t see this as a fault of OKRs
This is the first time I've seen a "hill chart" and I found it a little confusing to look at - maybe because the shape looks like a normal distribution, where "the sides" are more uncertain and not less uncertain. If one turned a hill chart inside out, you'd get a chart like a dartboard, where as things are more certain you are closer to a bullseye in the middle, and less certain you are further away. I could see looking at OKRs that way.
Hill charts are a great way to keep people informed about a project status. I think they make much more sense than estimates.
It also encourages collaboration over adversarial negotiation.
Then you can have "fun" with it as to find meaningful purpose since their life is missing it elsewhere
But on the other hand i dont fully like them in my work life
First my job forces OKRs amount and treats them equally
So OKR like completing half day training and sharing the learnings has the same value as multi month engineering effort.
My only encounter with OKRs sucked badly, and mismatches like that were one of the reasons.
What we want to incentivise is not success, but the kind of behaviour that leads to success. But that, on the other hand, suffers even worse from Goodhart's law.
Cedric Chin dug deeply into this dilemma[1] about a year ago. His suggestion is to frequently follow up on both behaviour metrics and result metrics to build a tacit understanding of how one is affected by another. This then allows you to focus improvements on behaviour metrics, which are mostly in your control.
I have yet to try putting it to practise, but I like the idea.
Some technical skills increase or personal development objective
And that completion of training or certs is what is measured
The second-biggest problem is that the time horizons of OKRs are often longer than the interval between pivots that cause the old OKRs to no longer make sense.
The bigger problem as I've seen it is engineers that don't see themselves as part of the business, either because of the culture or personal choice around lack of focus on soft skills.
All too often engineers spend zero time understanding the market and customers, and scaled agile, as it's typically implemented and managed, definitely doesn't help.
If you're big enough to have company level OKRs that were written solely by folks that haven't opened a text editor in 10 years simply get out the popcorn and a can of beer. There are going to be some hilarious ones in there.
This concept is something of a breakthrough for me, personally. I have fairly severe ADHD, and it took me about fifteen years in this industry to really find my place in it. My "hill chart" is more of a "valley chart".
In dealing with my own mental abilities, I've found that I've developed a toolset that has resulted in my strengths being in aggressively removing uncertainty and finding the optimal path to implementation - because implementation is the part that I struggle with.
Now I'm wondering if the very effective teams that I've been on have been comprised of people whose "charts" here overlap in a way where someone is always in their "downhill" portion while others encounter the "uphill".
Conversation dies rather quickly then.
Might come handy when you wanna try out that approach https://www.hillchart.co/
It’s short, but high quality and digestible.
"Here comes the airplane!" is a little game that I like to play with PMs so they get to enjoy me punching them in the face. Aren't we all having fun now, how wonderful!
Execs can't do this themselves because they don't have the information they need, and are trying to be predictable and compete in a market. So think about it as an ELI5 exercise where you're infantilizing up, or as it's more commonly and professionally referred to, managing up, or more plainly, helping the business make better decisions.
I often feel the frustration when I'm writing some data-crunching report-extraction thing, of the knowledge that the output of it will be some administrator squinting shrewdly at it and thinking himself better informed. Then he'll do pretty much whatever he would be doing anyway.
And that's the better case. I suspect in many cases they don't look at the information they ask for at all.
Pirates navigating uncharted seas. Explorers finding their way in an abandoned coal mine. Chutes and ladders.
Some people are self motivated and well organized, are great at communicating progress proactively to other stakeholders, an understand the idea of cross departmental alignment. OKRs will not help them.
For everyone else, OKRs are a tool that can help accomplish those things.
PS I actually like OKRs and after a lot of effort, learned how to make them useful. I did not get it at first either.
Cleaning up your code base to accommodate all the gradual accumulation of small fixes/hacks is not something you can put a metric on, at least not without pulling numbers out of your ass. But everyone agrees that you can’t really have quality software without doing this. But OKR’s would say that making nothing but tactical changes to ship features and never revisiting architecture is perfectly great. The incentives always seem to push you towards tech debt.
OKR proponents would say that revisiting architecture and paying down tech debt should be implicit and part of the process of achieving your results, but I’ve never seen it done. Or rather the only time I have seen it done is when someone tries to shoehorn the refactoring work into an OKR in order to justify it, making up bogus metrics, getting the OKR dropped because it’s not meaningful enough, and then just working on it anyway.
Let's just say that I didn't won any popularity awards there for being the rational one.
You mean like Google devs who kill projects faster than they roll them out
I think a new thing is needed at least for smaller teams. Something like adaptive goals. Roadmap a year, vaguely and plan the next 6 weeks. Measure stuff where it makes sense but not everything needs a measure (or things that don’t might be 0 or 1). Plan based on velocity that takes into account that you wont have planned everything.
Measures are useful but also bullshit. There is no correlation between the measure and business success without intelligence. Even revenue is not a measure of success (I could sell half price bitcoins and have a lot of revenue!)
From my perspective the problem is that companies invest zero time in training engineers about the market and companies, and instead just treat engineers like assembly line cogs that produce business value on-demand.
[0] https://dora.dev
I think this is an almost universal caveat.
> OKRs turn measures into something like a sport
No, I don't think that's true. People might do that, but they also do that to things that aren't OKRs. It's great to critique OKRs, but not by comparing them to a hypothetical perfect world.
Right, but please read the first sentence of my post. It’s the “key results” part that’s hard. Because you need to quantify all the benefits you’re targeting, giving them a number, so that you can show whether you completed your goal or not. If you say “productivity will go up”, you have to put a number on the current productivity, then give regular reports on what happens to that number after the refactoring. What do you pick? Number of PR’s merged per day? That’s probably going to go down, because most of the PR’s today are small tactical band-aid fixes. So do you say the number of PR’s merged should go down after the refactoring? That could just as easily be because the refactoring made things worse and everything’s so broken that nobody can make changes. So PR’s merged is a shitty metric. What else? Bugs filed? In a product where you’re growing users you’d probably expect them to go up due to increased usage, so any benefit to refactoring is likely going to be lost in the noise. Line of code count? Please.
More often than not people just pull whatever metric they want out of their ass to make the case for what they’re trying to accomplish, and cherry pick things so that it looks better after the effort. But it’s against the spirit of OKR’s to do this, which is why OKR’s are bad for anything “fuzzy” like refactoring. You have to shoe-horn work that everyone agrees is worth doing, into a framework that isn’t designed for refactoring work, to make the case.
It's not an exact science. You can make pro and con arguments against different things that could conceivably be measured. This is where experience and strategic thinking help.
You can always come up with a risk or a reason why a particular measurement won't affect the desired outcome. You will be more right on some and less right on others. However, throwing out the entire OKR approach because you can not be sure is not correct either.
But it’s really really really hard to quantify it in a measurable way. Which is what OKR’s force you to think about: what is the metric, what is its current value, and what is your goal for the metric, so you know whether you achieved it?
Can you quantify “faster employee onboarding”, reliably? Can you graph it over time? Can you quantify “faster feature implementation” in a way you can actually measure that isn’t sensitive to the fact that all features are different?
I wrote a piece about the common issues that people face creating OKRs. There are a few common mistakes that people make which makes key results unmeasurable: https://koliber.com/articles/top-okr-mistakes
> the gradual accumulation of small fixes/hacks is not something you can put a metric on
I've done it before. On one team, we had a goal to reduce the number of linting errors and warnings from 18,000+ by 50% (while not growing the number of INGORES). The team was reluctant at first, because "it's only linting and it does not matter." But they relented and eventually started fixing things here and there. And the number started going down, albeit slowly. And over time we got the number of linting errors down to 18 (or something close), because people found time here and there to improve things. And the team learned how to use OKRs. And they put in place a style guide and an auto-linter. And they started using it so that the errors did not come back. And there were plans in place to put in more sophisticated style analysis and run another OKR agains that.
They literally matured in the code development practices way beyond just linting, just becuase of the relentless drive on one seemingly insignificant OKR.
This is just one example. You can use OKRs with engineering metrics to improve lots of things:
- fix the top 10 Jira tickets tagged with #techdebt
- reduce linting errors by 20%
- reduce number of functions with a cyclometric complexity of 10+ by 50%
- research 5 static code analysis tools
- increase unit test code coverage from 56% to 62%
You can go many different ways. I've helped engineering teams do this well, starting with deciding what makes sense to improve and getting buy-in, through defining the OKRs, building the system of measuring it, and most importantly, driving the OKR every week.
In the case you cited, with a bunch of hacks, I'd approach it like this:
- Create a OKRs like "Reduce tech debt".
- One of the key results would be "Identify 50 hacky places in code, and create Jira tickets for them" or something similar, by Jan 31st."
- 2nd OKR would be "Refactor XX out of the 50 hacky places identified by Jira tickets, by March 31st"
Pick numbers that work for you.
- Take whatever it is you want to do and break it down into N jira tickets
- Make an OKR saying “solve these N jira tickets by date X”, with the result indicator being “number of those particular jira tickets solved”
- At the end, your OKR percentage is some fraction of N
This works regardless of what the thing you’re trying to do is. It goes against the spirit of OKR’s which is to use metrics that matter to the business (number of users onboarded, page load time, conversion percentage, etc) to justify work. That’s what the “results” in OKR’s are supposed to mean.
It does not go against the spirit of OKRs. Reducing tech debt and making a metric out of the number if Jira tickets can work, and is a workable approach if there is business value from reducing tech debt. If you can align it to "reduce page load time", why would you not use it? Don't conflate business value with how you measure things. OKRs should align to business value. OKRs should be measurable. You can have things aligned to business value that are harder to measure. You can have measurable things which provide little business value.
There is no rule that says that you can not measure the number of tasks that get completed as part of an OKR. It's true that the smaller N gets the less sense it makes, and that N=1 is a binary goal. OKRs are better for larger N numbers, as those show progress better. Going from memory, "Measure What Matters", the OKR bible, has examples of OKRs where the goal
Nothing is stopping you from using OKRs for small N. But I have seen people come up with all sorts of excuses why "it won't work" so your milage may vary. My suggestion is always "try it fullheartedly before you knock it."
The generalization won't work once N is large, or is continuous, or does not make sense as separate Jira tickets. Luckily, it does not need to and you can track such metrics without the help of a ticketing system.
Examples that won't work as Jira tickets but can be good OKRs, if they align to a business goal:
- improve the Core Web Vitals cumulative layout shift (CLS) by 0.3 points. (can align to "reduce bounce rate" as CLS affects the perceived load time and quality)
- increase test coverage by 15% (can align to "reduce churn", if churn is caused by poor product quality, and test coverage can improve quality)
- Improve the time to first byte for the homepage by 500ms.
This one is continuous, because time is continuous. Realistically it will be quantized into milliseconds, but that's nitpicking.
You can get less granular:
- solve 500 linting errors
This one is kind of continuous, but there are 500 distinct steps. Each week it is feasible that you can solve a handful, and can see movement and improvement.
- add 5 unit tests to XYZ module
Now we are getting much less granular. It is a checklist of 5 TODOs. But you can track the progress. Its unlikely each week you will make an improvement, but on some weeks you need to if you want to hit "5" by the end of the quarter.
- hire a new DevOps engineer
This is a binary, checkbox, or hit-or-miss key result. Sometimes they makes sense. It's not great if they make up the majority of the key results on an OKR. The good news is that you can make it more granular. Create a plan for hiring an engineer. Break out the steps, assign a percentage to each step, and track it as a 0-100% key result. This way, as you write a job description, post it, create a pipeline, review resumes, and hold interviews, you can track and share the progress.