H. James Harrington authored a quote that is so perfect for this blog, that I had to start with it:
“Measurement is the first step that leads to control and eventually to improvement. If you can’t measure something, you can’t understand it. If you can’t understand it, you can’t control it. If you can’t control it, you can’t improve it.”
Measurement is a core component of any business strategy. It is not about the data department, your analyst crunching numbers or the BI tool you’ve installed to display the metrics. It is about the reason for measuring.
What you are measuring;
Why you are measuring it;
How you are measuring it;
And what decisions you will make on the back of it.
In the world where *almost* every act creates a data point, there is so much you can measure. However, there is a risk of drowning in numbers But just because it can be measured, doesn't mean it should.
Equally, not all your metrics can come purely from data. There is a balance between art and science when determining your measurement strategy to ensure you don’t lose sight of the wider context and human perspective.
As Wiliam Bruce Cameron (or some say Albert Einstein) neatly put it “'Not everything that can be counted counts and not everything that counts can be counted'
It is useful to pare back the reason of measurement to the core questions above - the what and why - to understand what metrics are important for your business overall, and how your business will use them to make changes, improve performance and grow.
Yes, different teams in a business will have different needs based on their objectives and targets, but they should all ladder up to the overarching objectives and have consistent measurement methodologies to minimise conflict and confusion with the metrics.
To keep things pragmatic, categorise your metrics into 3 areas:
So what do I actually mean by this? Let’s take an example of business growth through the lens of customer behaviour.
The KPIs may be looking at metrics of customer value, lapsed reactivations, one-timer conversions against the specific task e.g. increase customer value by X%.
The PIs may look at the revenue from the shifts in customer purchasing behaviour, are they purchasing more frequently or buying in different product categories etc.
And the SIs may look at web visitation trends and brand choice measures that give an overall pattern of how your activations are aligning to your strategy.
Once you know what you want to measure and why you can then look at how you are going to measure.
For instance -
Does the data exist or will you need to start collecting it?
Is it in the right format and accessible to collate and standardise metrics?
Is it unique enough to measure specifics?
Do you need to design and establish new processes to collect and use the data?
How are you calculating the metrics and assessing performance?
Do you need to design control cells to demonstrate incremental uplift?
When designing your measurement strategy, consider this practical side of the metrics and put processes in place to capture and manipulate the data if needed.
For instance - when you are setting up your campaigns to track engagement and performance use UTM codes, dedicated phone lines or landing pages? Ensure these are tested prior to campaign deployment and that the data you then have access to for your measurement is accurate.
With using consistent methodologies to calculate metrics across departments, it reduces conflict in the numbers which can lead to confusion and mistrust. You’ll want all departments to be working on the same version of the truth.
Visualising the metrics.
Sounds simple right? It isn’t always. Poor visualisation of metrics can lead to poor interpretation of the numbers and incorrect decision making.
Think about your indicators and the story you want to tell with the metrics, and then use different visualisation techniques to tell your story. For instance, if you are showing a comparison of an AB test against a baseline performance, ensure you are using a clear chart against the recipient's behaviour such as a bar chart. You don’t always need fancy visuals or loads of data points - focus more on how the chart tells an accurate story quickly and easily.
There are some fantastic BI tools on the market that take a lot of the strain away from data visualisation but you still need to put some thought into the best table/chart format to ensure the accurate conclusions are drawn.
Be clear on the purpose of the visualisation (e.g. to drive a decision or next action, or to reflect on past performance)
Identify if it needs to be scalable or added to over time
Know the recipients of it (e.g. how comfortable are they with numbers)
Understand the story you are trying to tell with the numbers (e.g. metrics at a point in time, or a cumulative performance; incremental uplift vs. gross performance)
Decide what would make the meaning in the chart clear and straightforward for the readers
We have helped a lot of businesses to define pragmatic, action-orientated measurement strategies to enable them to learn, understand and improve over time. If you are looking for help in your business, please get in touch via our website or by emailing me at email@example.com