Introduction

The metrics play a crucial role in assessing progress and steering business decisions. Due to its significance, it is important to clearly define the right metrics that are aligned with the goals of the business. Wrong metrics can lead to teams optimizing the wrong part of the business and may also get wrongly incentivized. Both of these can have detrimental impact on the business goals. Two fundamental types of metrics, input and output, have consistently delivered positive results for teams adopting it. Let’s delve into their significance and how they shape the team’s journey to success.

Input Metrics – Fuel to the engine

Input metrics are those metrics that are completely under the control of the teams. They are the leading metrics that can be acted upon immediately. A simple analogy to explain input metrics is that of baking a cake. To bake a cake, you need a recipe and ingredients that have the impact on how the cake will look and taste. These ingredients are what we call input metrics. They are sort of the fuel to the engine and can be controlled to impact the final outcome i.e. a baked cake. 

The input metrics have a direct relationship to the outputs i.e. business outcomes. They should be designed in such a way that any change in inputs will result in changes in the outputs. Input metrics are also certain activities performed by the teams and have complete control over. For example, at Amazon one of the input metrics was Fast Track In Stock which measures the percentage of products that are in stock and available for shipping within 2 days. Now, the ability to keep products in stock and ship them in completely under Amazon’s control and the better it does, higher is the possibility of the customer purchasing those items. 

Identifying correct input metrics is very important as they would drive actions for the teams who would optimize the metrics. Wrong metrics can incentivize wrong behavior in optimizing those metrics leading to inefficient business results. The input metrics should always be customer centric and always consider its impact on the customer. 

Output Metrics –  Evaluating Success

Output metrics are the results or outcomes that a business strives to achieve. They are not completely under control of the teams and are lagging indicators of success. An output metric measures the business results or user behavior when interacting with the product – all of which are not under direct control of the teams. To take the analogy of baking a cake, the output metric is the final result i.e. a cake.

Output metrics offer a clear definition of success. Whether it is revenue growth, profitability, NPS, etc. they are the metrics that showcase whether outcomes have achieved or not. They are important but leaders should not focus on them too much because they change only after a long period of time and it is better to focus on inputs that impact the outputs. 

Bringing input and output metrics together 

When defining output and input metrics, ensure that there is a direct cause and effect relationship between the two metrics. This means any change in input metrics should have an impact on output metrics as well. This way it is easier to identify potential causes and opportunities to improve by optimizing the relevant input metrics. 

There is a flywheel relationship between inputs and outputs. The input metrics lead to outputs and back again. This can be well explained with Amazon’s flywheel concept where the output is Growth and the inputs are selection, price, and customer experience. Each part of input optimization leads to the growth of the marketplace platform and the flywheel runs faster. For example, low price drives more customers – that drives more sellers to sell on the platform – that drives customers & experience as they come back again on the platform – more customers & sales lead to cost optimization – which again leads to reducing the prices. 

However, getting the inputs and outputs right is an iterative process and most likely the teams will not find the right metrics from the get go. As the teams learn more with experience, the inputs and outputs should evolve over time. Thus, trial and error becomes an important part of defining inputs and outputs but starting is the key component to achieve long term success.