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Hi Startup Founder! Hopefully, you’ve already discovered how easy it is to calculate your most important metrics regularly, but you might not know how easy it is to miscalculate the secondary effects of these indicators. How you use, treat and communicate about your metrics is very important.







Your indicators should help you to improve your startup’s performance, but to do that you need to cultivate a data-driven culture where decisions are taken based on scientifically proven hypotheses rather than subjective and potentially biased ideas. Here are three common mistakes that can stop you from reaching your goals.

1. The metrics you measure are not ACTIONABLE


Have you heard of vanity metrics? As a startup founder, you’re often told to avoid vanity metrics, but we don’t read many things on its very useful opposite: sanity metrics. Sanity metrics are actionable. If you measure indicators that don’t connect easily to actions, they are vanity metrics. If you measure indicators that don’t inspire to certain actions, they are also vanity metrics.

To turn vanity metrics into sanity metrics, make them multi-dimensional. What you can do is to add relevant dimensions that are affected by the decisions you’ve taken. For example, total downloads is a one-dimensional metric. Taking the percentage of downloads this month compared to last month is two-dimensional. Taking the percentage change of downloads and creating a ratio to compare it with the percentage change of marketing spend, you have a three-dimensional metrics. This three-dimensional metric will tell you if the actions taken regarding marketing has improved your result from last month. If the ratio has decreased you know that your marketing needs to change, if it has increased you should instead continue to do more of it.

Metrics should always be compared to something, which as seen in the previous example was through comparing to the previous period. It is good since it automatically adds a relevant dimension. The optimal is to compare your results with a set out objective or a benchmark, but it might be tricky for a startup. Startups innovate business models and products, which means that you don’t have any benchmarks to compare with and then comparing your results to previous periods can be a great solution. A tip is to use conditional formatting which makes it clear if your startup is doing well or not compared to your objective or previous period.

2. Your indicators are not considered RELIABLE


When you try to refer to data as an argument for a certain decision someone hesitates on the reliability of the data, claiming that the data cannot be trusted and therefore not support a decision. This reflex is very hurtful if you try to build a data-driven culture and breaks your management loop where the measurements of your actions are supposed to lay a basis for your next plan.

What you need to do according to Bernie Smith, writer of the book “KPI Checklists”, is to have clearly stated definitions of your KPIs that are written down and available for anyone to study. You would optimally create a library of all your used metrics with their definitions and what the correct source is. Each KPI should have a descriptive name and a detailed formula explaining how it is calculated, without giving room to assumptions to avoid the risk of misunderstandings.

Make sure that the data in all your systems checks, if not you need to decide which of the data that you will use officially in your startup. Another important point on this issue is to make sure that your definitions are relevant and don’t leave space for a lot of “buts”. As an example, if you are selling a SaaS and you say that only 50 % of your sold licenses are active users, if you haven’t properly defined what a sold license is people will start making “buts”. “But some of those sold licenses still haven’t received their training!”, “But this includes licensed users who have been experiencing technical issues!”. Every but destroys the reliability of the metric. Make sure to define the bricks of your metrics in a way so no “buts” can appear.

3. The metrics are not ACCESSIBLE for the whole team


The word accessible can be split into two parts, both that your metrics are available to access for anyone in your team and that they are possible to understand by everyone. The data sources that are used to supply your metrics should be available for anyone, call it open source if you like. On top of this, team members should be able to understand what they see and how all data comes together to create the metrics that are important for their work.

A team that knows how to use data to make decisions in a scientific way, will ultimately be an advantage for your startup’s growth. In a concrete way, it means not only that the team understands the dashboard and the typical metrics, but is also able to do ad-hoc searches when having specific questions about their work.

Finding information about your users’ behavior or anything relevant for different tasks shouldn’t be reserved for managers, but rather available to everyone. Metrics should not be a part of top-down communication, but rather be part of communication in all directions.

Test your Skills!

Are you providing your startup with the best possible conditions to succeed? Find out how well you know and use the metrics relevant for your startup to make sure you maximize your startup’s performance. Or if you’re a curious individual you can test your own knowledge. Chose what fits you best with help from the links below to start the test!