Over the past weekend, I pondered heavily on the notion that we tend to see what we want to believe. It is the epitome of cognitive bias and how life’s fast pace creates unintentional ignorance. Sometimes the fast pace of life brings us to focus on the wrong things.
A friend of mine had shared with me about a sanitation project in India funded by a prominent, global influencer, which had failed to be adopted by locals. I was shocked to learn this was the same influencer whom I had recently admired on television, broadcasting the successes of the very same project. The ambitious project set out to create self-sustaining toilets for rural parts of India in an effort to reduce hygiene issues. What they did not highlight was that some of the villagers from rural areas had refused to use a man-made toilet as they believed that it was better to be outside when nature calls. After many months with no follow up and maintenance, the toilets eventually became unusable — nothing more than an abandoned feat.
Was it a success? More than often, organisations deem success as the moment the solution is delivered into the hands of the user. It is easy to miss the last mile in facilitating the change we seek to create and measuring what happens afterwards- the things that really count.
It’s everywhere
Lack of follow-through on outcomes happen everyday to organisations of all shapes and sizes. Take the healthcare industry for example. Activity based funding has fuelled the lifeblood of health services— each seeking to show long lists of numerous activities undertaken that highlight demand and warrant the request for more funds. In reality, the question we should be asking is — “Has it improved health outcomes?”
Why does this happen?
I started to question why this happens, even to the best of organisations. Ask any individual and they would agree. Surely, it makes sense if we are delivering a service or solution, that we seek to understand the outcome of it?
Over the years, I have learnt that time pressures can sometimes blur the finish line and unknowingly change a mindset to “Deliver fast and move on”.
Additionally, measuring output is often easier than outcomes — as it’s faster and easier to attain activity data. As an example: “How many people have downloaded an app” vs “How many people got value from it” or “How many people saw our awareness campaign ad” vs “How many people changed their mindset after as a result of it”.
Becoming outcomes focused
Measuring outcomes is an art. There are dedicated professionals whose job is to help organisations define, gather and measure the right outcomes. But everyone can take a step in the right direction. Here’s some learnings I’ve developed along the way:
- Start with a clear finish line in mind. Why are we doing this? What does success look like?
- Know your capabilities. Knowing what is within your control will help shape desired outcomes. As an example, if you are selling a blender…how often the blender is used is largely not within your influence. However, being the experienced quality is within your control. In many cases, we have to remember we are operating in an ecosystem with many factors at play. Setting smart expectations helps ensure you are not set up for failure.
- Have metrics with a meaningful purpose. Otherwise, it is just another surface number. Understanding what each metric will be used for beforehand is crucial. Is it a learning metric or a success metric or both? Is there a process and follow up plan accounted for?
- Gather the right data. Identifying how you measure outcomes has a large impact on the insights you will attain. Often, the data we collect and how we collect it can be full of biases. There is a whole stream of studies and methodologies on this which I will not delve into here. At the top level, we have to clearly outline the sample target characteristics, key assumptions and potential limitations.
- Get stakeholders on board. For many reasons — it helps drive a data-driven culture, outcomes focus and better decision making. It also helps attain the appropriate resources and support for follow up and measurement activities.
- Be adaptable. Every organisation is going to be different. From large scale data analytics teams to lean startups on tight budgets— be ready and able to work with what you have.
- Lastly, have a growth mindset. The first insights you attain from your metrics may not always be what you wished for. An experiment that didn’t go as well as anticipated? A site that had little to no views? Rather than getting disappointed — it is important to reframe it as “What can I learn from this?”
If we have already made it 99% of the way to deliver something amazing — why stop before the last mile.
