Sure, no metrics are perfect, but you simply cannot run a successful business without gathering and discussing useful data that provide insights to help you make decisions. Just make sure you start with curiosity when looking at data, and use it to generate questions, rather than taking it purely on face value.
4 x Flow metrics: to measure, analyse, and improve the flow of value to your customers.
Cycle time
This is the amount of elapsed time between 'starting' and 'finishing' an item of work. It increases confidence in forecasts, as you can more accurately predict how long it takes to complete a work item (noting there will always be a range, and this will at best be 85% accurate). It also helps to spot outliers and to ask questions about what caused the variation. This is a lagging indicator of output.
Work item age
The amount of time since any given work item has been 'started', and is not yet 'finished'.
This is a great measure of your current situation at any given point in time. To improve flow, we need to make sure we are tackling the oldest items first (or at least prioritising them when we're confident they're still valid).
This is a leading indicator of output.
Throughput
The number of work items that are 'finished' within a time box.
The higher the better, as this demonstrates you are able to complete more work over a certain period of time. This is good because it typically relates to more products being shipped to customers in order to achieve business outcomes.
This is a lagging indicator of output.
Work In Progress/Process
The number of work items started but not finished. What's tricky here is finding the right balance that allows for smooth, predictable flow. Too much, and everything slows down. Lower is better, but not too low. If your capacity consistently outweighs your WIP your team is probably bigger than it needs to be.
This is a leading indicator of output.
In order to do measure these things, you need to clearly identify the core steps of your portfolio workflow. This allows you to measure the time it takes for work to flow through not just the full process, but also to measure the data and identify bottlenecks in certain stages.
Value Stream Mapping can be of significant help to start to capture these metrics.
Most workflow tools (JIRA, Azure DevOps etc) will have this data and charts available by default.
4 x DORA metrics: to determine the robustness of your DevOps process
Deployment frequency
How often do you release to production? The more often the better, as this indicates you're truly agile in your ability to react to the needs of customers. Be mindful here if you apply thresholds to your releases i.e. only deploying to 50% of customers at a time.
This is typically a leading indicator of output.
Lead time for changes
The time it takes for a code commit to get into production. This is pretty much the same as cycle time but for techies, and for a specific part of the workflow.
Change failure %
The percentage of deployments causing a failure in production. The higher the percentage here the worse, as this indicates poor code quality and lots of defects finding their way through your workflow. DON'T try to increase your deployment frequency if this number is shit.
Mean time to restore service
How long it takes to recover from a failure in production. As long as you're accurately tracking when incidents are created, you should be able to get this data quite easily from incident management systems.
These metrics originate from the Annual state of DevOps report and were beautifully articulated in the book Accelerate.
It outlines the ranges of these measures seen in Elite, High, Medium and Low performing technology companies. I highly recommend it.
4 x Value metrics - to know if your products/services are helping solve the actual problem
Return on Investment - ROI
You need data to know whether to continue or stop allocating funds to a product / project.
The simple calculation of how much are you making (return) divided by how much money you invested (cost) x 100 will give you your ROI%.
If this is a negative number then this is a clear signal to stop investing.
If this is a positive number then you can focus on how to maximise this return, by reducing costs further and running experiments to increase the revenue.
The key issue I see in organisations today is the blind faith in an annual budgeting process. To predict the future and believe that a new project or product will eventually be worth the significant investment, and not to break the investment down in order to prove the hypothesis as quickly as possible. This is where quarterly planning is so much better than annual funding. Those approving the allocation of funds should demand ROI data within 3-6 months, else the risk is simply too high.
Customer retention
This will help you understand how loyal your customers are to your brand.
Repeat customers are essential to reducing costs in your business. Low customer retention significantly Increases the cost and effort of acquiring new customers. This often goes hand in hand with...
Net Promoter Score - NPS
How likely are your customers to recommend your brand to others? Just like eNPS, this is a key indicator of customer satisfaction.
It is determined by posing a single question to customers: “How likely are you to recommend this company/product to a friend or colleague?” and asking them to rate it on a scale from 0 to 10.
Detractors (NPS 6 or lower) are customers who are unlikely to recommend your product to others due to low satisfaction with it.
Promoters (NPS 9 or 10) are enthusiastic, loyal customers that would happily recommend your product to others.
Knowing you have detractors (and who they are) allows you to connect with them and proactively address their issues.
Life Time Value - LTV
This is the amount of money a business earns from one customer over the duration they do business with you.
There are numerous formulae for calculating LTV, but the simplist one is to add up the revenue per customer and subtract the costs of acquiring and servicing them.
NB. If you only have a handful of customers, it will be more important to focus on increasing customer acquisition than reviewing the LTV of the small number you have.
These are often the hardest but the most impactful when it comes to portfolio prioritisation. They basically provide the answer to the question - 'So what?' when someone comes to you with new demand, as they need to be able to articulate how it helps your business i.e. which lever will move as a result of your delivering their demand.
If you use them, linking the metrics to your OKR's is a quick win here. Everything you do should tie back to an objective somehow.
4 x People metrics
Employee net promoter score - to know how likely your employees are to recommend your organsation to others.
eNPS tells you where you are in terms of employee satisfaction and loyalty. Running surveys to gather this data helps your people have a voice and be heard. My go to template here is the Gallup 12. What's important is to share the results and to act on the high priority areas.
NB. Whilst company or department wide surveys are helpful, I generally prefer gathering data in conversation, team by team.
Team health - to help your teams improve
I typically evolve the Spotify Squad health check model to suit the current client and tailor the questions based on what clients wish to understand and improve on.
The key outcome here is having information about how your people feel, and also where to apply interventions to make things better for them. Here's a related article on team performance by Greg Franklin.
NB. Of course it takes more time and effort to gather and consolidate the results across multiple teams. But, it creates a much deeper conversation than a survey. If you needs to create a baseline quickly, a survey may be better.
Autonomy, Mastery & Purpose - to unlock individual high-performance
The secret to satisfaction at work is the deeply human need to direct our own lives, to learn and create new things, and to do better by ourselves and our world. At least according to the book Drive by Dan Pink.
Personally, since reading this book about 5 years ago I'm constantly checking in with myself and the people I work with to see if these 3 elements are present.
Staff Retention / Churn
This one is pretty obvious, but you need to know how many people are leaving and how often. When people leave, in the most part knowledge is lost.
Hiring takes time, and bringing new employees up to speed takes 3-6 months (in my experience) before they really start to add value. As long as the people you're working with are not dicks, it's probably better to retain them than see them leave.
In summary: Data allows you to understand where you are versus where you were previously. It allows you to design and run experiments to see whether you can move the dial.
It removes emotion and opinion in decision making.
Without it, you will simply not reach the heights that you, your teams and your organisation can achieve.
If you want to hear some specific case studies or detailed examples of the metrics referenced in the article, just book a call.