Impact-effort prioritisation
Impact vs effort prioritisation is likely the simplest visual prioritisation technique out there. To me, it certainly is the simplest and the first to try.??
I was way back then managing a small team that was building systems and processes for software delivery. We were doing small-scale software development. It was nothing fancy but coding, backlog items, and priorities were needed anyhow. I had decided that we’d work in the spirit of agile and low overhead. We didn't want to estimate the exact costs of development ideas. We needed a way to structure the backlog items.?
We ended up with an impact-effort board like the one below. The board works on differing levels of items quite the same: for user stories and epics. Let me explain how it worked then.??
After the basics, I dive into 3 advanced topics: focusing on the strategic, iterating to learn, and accepting the limits of our knowledge in the early innovation lifecycle.?
The basic board layout?
First of all, the board is based on the notion that cheap and valuable is great. You will have to define what is valuable. Over time you build a notion of relative value of items in comparison to each other. No exact number for value is needed as we are interested in relative and comparative value. All you need to answer is: item X is more valuable than item Y.?
The second axis is cost. You will take a quick assessment of how much time you guess you will spend the on the item. The less time you believe you'll use to create the solution for the item, the cheaper the item.??
All items on the board are forced-ranked on the two axis: value and cost. You will all the time rank the items against each other. That is: item A is more valuable than item B. And then you do same on the cost side. That’s how you end up with a two-axis forced rank. The green dots on the pictures are your backlog items.?
Once you start doing repeated comparisons, you’ll quickly realize that the comparison is quite doable. For instance a simple bubble sort will put the items where they “belong”. There will be items harder to compare and taking more discussion. Usually, either the value or the cost is clearly differing.??
You can be quite relaxed about the accuracy of your estimates for all items that don't make it to the top 20% for either value or cost. Let's consider the picture below on why that is.??
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The top right corner is “magic” quadrant (the green area). That’s what you want to do next. It is sorted to contain your best options.??
You can quickly trash anything on the bottom-left (the red area), and everyone can see why you did that. After the have emptied the red area of poor investments, we have two quadrants which are not as obvious.??
The left-top (cheap, not that valuable; yellow area) gets also rather quickly trashed or put on hold. You will see that there’s so much better investments on the right side of the board. Again, people are quick to agree on that. If there’s no agreement, maybe you missed some insight in the value-sorting. Revisit the forced rank on value of those items which feel awkward to put on hold.?
The quick wins: the top-right quadrant?
The top right quadrant is the high value and low cost. Intuitively these are the items that we start with.??
I often notice people over-emphasising the value of quick wins. That is: the value is over-rated. When comparing to the more high-value items with high cost, we often notice that strategic and high-punch (with high cost too) items have clearly higher value. I can't put my finger on the cognitive bias at play here, but I presume it is that we always have a number of favourite items. Those items are such that we just want them to bubble to the top of the priority.??
Another phenomenon that I usually see is that quick wins will not take you where you want to go on the long term. There is seldom enough true quick wins to make a true shift in your position. And if you sum up the impact of all your quick wins, you don't usually end up with repositioning your business.??
For finding the big levers in changing your business, go back to the high impact + high cost quadrant.?
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Crack the strategic: high value, high effort?
The right-bottom quadrant (coloured also with green) is the “very valuable, very hard” corner. You’ll want to achieve to deliver those items. You either don’t know how to get those done it yet or you know it is going to be very costly. You know you cannot take on all of the big items at the same time.??
For the high value + high effort category, try splitting the core and essential value out of the item with fractional cost.??
The split out items should bubble upwards on the board as the split out items are cheaper. The split out items should stay rather much to the right (valuable) as you try retain the core value of the original item. For the items where you don't know the right solution, prototype them. Create experiments that teach you how to crack the dilemma. Maybe the cost isn’t as bad as you thought after a bit of knowledge seeking.??
For those items that don’t seem to yield any options with less cost, you’ll end up keeping the items on the quadrant as reminders of the impactful ideas.?
Iterate to learn how to best handle the high cost items. That iteration can also be used to validate the value of the item.??
Feeding the agile iterations and scrumming the big items?
The agile development engine needs to be all the time fed with the smallest possible items.??
I've personally noticed that the short-term selection of items by an agile team becomes biased towards choosing the small items with demonstrable benefit. Maybe it is my personal preference on that, but I think it could be even universal. It is easier to bet on an item that has low cost and some benefit, rather than a larger more undefined item with possibly more benefit.??
The high value + high cost items you want to get done for sure, but you’ll split the items first so well that also the cost side is in control. You gradually build knowledge and the foundational solutions. You chip away from the high original total cost of the item.?
So, you’ll end up:?
Less estimation and analysis. More learning.?
It has been said that:?
As straightforward as this all seems, there are major problems with Impact/Effort prioritisation that cause us to pick the wrong winners. Most importantly Impact/Effort analysis requires us to make somewhat reliable predictions on future events?—?the effort we will require to complete a task and the value that will be delivered to users and/or to the company once completed. As it turns out both are jobs we’re exceptionally bad at.?
We indeed are bad at telling both value and cost of items. We could choose to analyse the items and make more diagrams. I prefer to try and split the items. After a few experiments with the items, we can then iterate and learn.??
The need for estimation and closer analysis of items going on pretty much only in the top-right corner. The rest stay on the board as options for future.??
It doesn’t really matter if the rank on cost (or even value) is precisely right outside of the magic quadrant and the right hand edge. The chosen high value items are not getting to full-scale development without splitting and re-evaluation. The cost estimation is rather simple for items that take a few days to complete. And it doesn’t really need to be accurate again as you’ll end up doing all the items on top-right corner sooner or later.?
To recap. Go for the strategic (high value – even with high cost). Choose 1-2 items. Split the best ones and iterate to learn. Never assume your initial rank was right. The iterations will give you feedback and show if you were right.??
Keep revisiting the board and priorities. The key is to try to be iterating on the 1-2 best big bets all the time. Only learning will tell if your initial ranking holds water.??
Senior Solution Architect at Nitor
1 年This reminded me of the visual activities board in Lucid Spark https://help.lucid.co/hc/en-us/articles/13409960234516-Get-started-with-Visual-Activities#prioritization-activities
Engineering and Leadership Coach at Hand Waving and Holding
1 年I love the follow-up. Both axes have a bias... but when the order is based on relativity, it should not matter. I guess it is one of those things that works well in practice but not in theory :D Choosing one item from the top right corner makes the bias somewhat irrelevant. So, I don't see the point of the adaptations. Especially the negative value is reason enough just to drop them on the floor and forget.