How to become data-driven? Disclaimer: it is not related to internal tooling

A lot of companies are wondering how to “become data-driven”? You often think that by buying some advanced platform you might reach this unmeasurable state. Unfortunately, you don’t become good at selling by buying Salesforce nor do you become fit by buying a pass to a gym club. Those are prerequisites but not ways of becoming data-driven. This article is about what we observed at companies that became data-driven.

Draft your ideal metric and its breakdown

The journey starts by knowing what you want to track. One cannot grow what one cannot measure. Since you’re in business to grow your revenue, you will need to find a metric related to it. Then you can break it down into your different teams. Here are couple of examples about key KPIs to follow depending on your business model

• E-commerce, Marketplace, Consumer : Monthly Recurring Revenue, Gross Merchandise Value or Total Sales over the period
• B2B SaaS: Monthly Recurring Revenue
• Hard tech, hardware, life science: LOIs, Prebooked contracts
• Open source: github stars, active contributors, community active users

For us, a B2B SaaS, we track the MRR and broke it down between two metrics

• Sales: net new MRR per month
• Product: Weekly Active Users and Retention

Every business is different but you get the idea. A data project and culture evolves. So don’t over engineer this part. Start on launching a first version fast. As you grow you will obviously start segmenting and going in more details of each team KPIs to keep on measuring and improving.

Pick a data champion in your organization

If nobody owns the data topic, you’re failing by design. Whatever your size or domain, you need to appoint someone that will be the data champion internally. It does not have to be a tech person. What makes a good data champion?

• Clearly identified internally: they are appointed by C-levels as data champions or evangelists
• Time allocation: they have 20-50% of their time dedicated to that mission
• Communication: they can communicate clearly on metrics and changes with different teams
• Analytics skills: they know how to structure analysis like sales, financial, marketing analysis
• Curiosity: they like understanding how and why metrics are following a certain trend. They use data as a mean for improvement and for everyone
  

We noted that it is rarely a question of personal skills and capabilities. There are always resources to ask technical questions or help either internally or externally. The key success factor lies in identifying the data champion and making room for her/him to perform well.

Start measuring things manually

Yep. You read it right. Automating comes when you know what you want to do and measure. So the best companies that thrive with data are generally the ones that start first by committing time and practice to data not a budget for a fancy platform.

Tracking your metrics manually will force you to appoint someone that will be responsible for that and start to implement a data culture with the organization. The first step to that is to define one key metric per team and dedicate time (weekly or monthly reviews) as to why each metric is improving or deteriorating.

This manual exercise can be done for a couple of weeks or months. It will help your team and data champion get used to working with metrics, choose the right one from the right data sources, etc. In short, you choose the metrics you want to track and then implement a tool to automate the tracking, not the other way around, and starting doing things manually is the best way to do that.

Run each team operations with numbers

As you start measuring things for each team, the goal is to use these metrics in your everyday life. It could be done during meetings, sprint plannings, performance reviews. Find a dedicated moment to get people used to that. Make it a fun team effort. Working with data is hard. People generally don’t like having measurable objectives and targets. It’s human. The goal here is to make it a collective effort to improve the organization as a whole and not just point out who underperformed. During each performance review, ensure the top management or team leaders are here and committed. There is nothing worse than trying to implement something without C-level support to show that the topic is serious for everyone.

As you can see, data is more about defining things and making it adopt by the company, just like it is hard to go to your Gym Club or make sales people use a CRM, commit time and resources to it and you definitely have made 70% of the job.