The surprising power of controllable inputs

How do you identify and use controllable input metrics to focus your team, set better targets at work and to guide continuous improvement.
What is the goal of this thought piece and why

The goal of this content is to teach you how to identify controllable input metrics that can guide your teams' focus and strategy.

When we say 'controllable input metrics', what we really mean is - what are the measures of success you directly control. The reason why we focus on the inputs that are within our control is that it helps us set targets and measure success more effectively and investigate the system of how we are working, rather relying on whether we are lucky or not.

A great analogy to explain this concept is something I came from in a book called 'Loonshots' by Safi Bahcall - the concept of a hypothetical lottery.

Imagine you are given the opportunity to enter a lottery where you have a 90% chance of winning 10 million dollars and it costs you $10. Would you enter that lottery?

Of course! It is a no brainer. But now say you enter that lottery, and you loose. Would you enter it again? And what if you enter again and then lose one more time.

If you focus on the outputs out of your control (for example revenue), then you aren't really evaluating if how you are working is right. In our lottery example, you are unlucky, but the inputs you control (the choice to enter the lottery) is absolutely the right choice. In business, we want to figure out what are the inputs we can control that over time will lead to success, not obsess and measure success by the outputs we don't control such as revenue.

Overview of the steps for identifying input metrics

This thought piece is an extension of our resource: "How to set KPIs that guide continuous improvement". We will repeat the steps from this related thought piece - and though both can be read standalone, we recommend reading the prior resource first if some of the next steps aren't fully clear.

The steps we will run through below are as follows:

Step one: define the outputs that matter

We begin our journey with defining the outputs we want to be driving, such as revenue. These are likely already how your targets are being set and what the team key performance indicators ('KPIs') are.

Make a list of all the outputs your team is accountable for delivering and the key performance indicators for these outputs.

For example, if I were running a product team in Alto, I would have some of the following outputs as part of my responsibilities:

At Alto, we use single-threaded teams where there is a single leader accountable for a full business offering. We'll touch on single-threaded teams in a separate thought piece at a later stage - this concept or approach was originally designed by Amazon, but the point is that there are a number of outputs a leader would be accountable for if they want to manage a successful business offering - the above shows a few for brevity's sake.

Step two: identify your output drivers

Next, we use the question: 'what are the factors that drive this output?' to identify what relevant drivers we can focus on improving to improve the output over the long-term.

We'll use a training product and customer experience as an example of how we do this at Alto. This is the kind of data strategy someone owning a training product at Alto would do.

For any professional training, 'what are the factors that drive the customer experience?': 

We find it hard to believe that in 10 years' time, any customer is going to turn around (with respect to any of the factors above) and say: "I love how relevant your training is to my life, but could you make it less relevant?". In other words, if we improve how relevant our training is to our customer, we will improve the overall customer experience score.

For each of your outputs identified in step one, you want to identify the drivers.

Step three: identify your inputs for each driver

Once you have identified your drivers, we can begin brainstorming what inputs can be controlled that influence that driver. Ask: 'what are the things within my control that I can do to increase this driver?'.

If we take one of the drivers from above, how convenient professional training is, here are some of the inputs we can control that we assume improves convenience

These are just a few examples, there are many inputs you might control for just improving convenience. Don't expect these to be static, your inputs should evolve as you learn what actually increases convenience/your relevant driver of interest.

Step four: turn your inputs into metrics

Once you have identified your controllable inputs, turn them into metrics.

For example, if we were turning the introduction of templates into a relevant metric, we would use: % of taught content accompanied by a template for application at work.

Our assumption, the greater % of the taught content that has a template for application, the more convenient it will be apply the learnings and therefore this will not only drive convenience up but relevance (application of content at work) and therefore overall customer experience.

We would seek to measure trends between % templates, convenience and customer experience to be sure that this is true.

Step five: develop your data pyramid

Our final step once we have turned out inputs into metrics we now control is to document them as a data pyramid. In the top box we have the output, below the drivers, below that the input metrics for each driver.

A template data pyramid

Keeping in line with this article about focusing on the controllable inputs, one of the outputs we care about is the audience experience, which is in part driven by relevance and convenience.

So, click on the button below to get a template table you can use to create your data pyramid - same as above except we separate it into a format, which is more conducive to writing lots of inputs than the above example.

Get template

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