We’re Ellen and Simone. After 36 years in finance, we’re ready to share what textbooks won’t tell you.

💛 Welcome to The CFO Playbook – your practical guide to real-world finance insights. A bi-weekly newsletter we’ll send out every other Thursday. The full read will take approximately 5 minutes. If you’re enjoying the newsletter, we’d greatly appreciate it if you shared it using the “Share the Newsletter” button at the end of this email.

📖 READ OF THE WEEK

This week, we have discussed the topic with and included insights from Bijan Soltani, Founder at Gemmaanalytics and Christopher Brandenburg, Head of Data at Gigs

While finance teams may not be the main players in these areas, they play a critical role in ensuring clean, reliable data flows.

Who hasn’t worked late into the night as part of the finance team before the next board meeting, due diligence, or an important management session, still unsure if the numbers are completely accurate?  

We know your days are filled with the intricate dance of numbers, but it could be smoother. What if numbers out of different tools would reconcile? We’ll help you claim your spot at the table and prioritize data, even with competing team roadmaps.

We want to give you the tools to join these essential conversations and truly make an impact.

Let’s start with the following example…

Imagine you run a platform where customers can book appointments with their hairdressers.

Your revenue model is based on transactions—every time someone books through your platform, you earn money. Additionally, hairdressers pay a basic subscription fee to use the platform.

As a fast-growing business, you haven’t yet invested in automating processes like billing.

Each month, you manually collect transaction data from your platform and import it into a spreadsheet to bill your customers. As your business grows and adds more products, the data volume skyrockets.

The result: Your Excel file now contains over 5,000 contracts and tens of thousands of transactions. It’s become a mess—difficult to maintain, prone to errors, and slow to load. You spend way too much time finalizing customer billing each month, not to mention the headaches with credit notes and reporting on all this data.

Time for a change?

You realize: something needs to change…and your topline growth is at risk

You realize that the company needs better processes and tools. The monthly billing chaos developed into a serious threat: incorrect invoices are sent, which in turn lead to even more work for your team understanding the issues and fixing the model. And it’s actually worse: this blocks further growth into new countries. 

Something needs to change! The company needs a better way to calculate billing amounts and revenues in a more scalable manner. Leaving Excel/Sheets behind and moving to a place where all the data can come together - from customer data to transactions to revenue data.

Your challenge: convincing the company to invest in a new set-up…and get it high up into the priority list.

The company reached the breaking point, the point of no return where an investment in a solid and scalable data platform is needed.  A data platform refers to various components (incl. hardware and software) which enable data loading, storage, processing and consumption. The most common set-ups consists of a

(1) Data loader which helps to move your data from multiple sources into a central location,

(2) a Database where the raw data is being stored (e.g. Snowflake or Google Bigquery)

(3) the Data warehouse where the cleaned and processed is stored and made available

(4) a Reporting tool such as Looker or PowerBI (no, PowerBI is NOT a data warehouse 😊).

Here is where you might hit some roadblocks: 

• In a scale-up environment, everybody is busy with the next big thing. Meaning: You need to get high up into the priority list.

• The finance team needs to proactively campaign for your requirement of better data quality and greater automation on the revenue side - and in our case an investment into data infrastructure.

How to get high on the priority list? Identify a core use case that others can rally behind, in our case, get more transparency on how much revenue you are actually making real time (instead of waiting 20+ days for monthly closing).

If you already have the luxury of a data team, it is now time to team up with them. While finance might be the team with the biggest stake in this project, the data team is responsible for the implementation. If no data team exists yet, this is the point in time where budget for hiring the first data person needs to be freed up. 

Either way you need to team up with the data team. And this is the beginning of a very long friendship.

What’s next?

In our example, the data team will get the transaction data from the engineering team, Go to market team (CRM system such as Pipedrive, Hubspot or Salesforce) and - if existent - from the payment gateway (e.g. Stripe…). All of this data will be pushed into the data warehouse to create one Single Source of Truth (SSoT).

As you can see, this is really a cross-functional collaboration.

Mind the Gap…

However, if you stop there, you will NOT solve your challenges. Why? Different teams might speak a different language when it comes to revenue. There is contextual information in all those tools that needs to be aligned to your business model.

Ever looked into a Sales dashboard that did not make sense at all? 🙂 It’s because functional teams often use their own language and definitions. That’s when data governance comes into play.

Data what…?

At its core, Data Governance is essential for managing the availability, integrity, and security of data within an organization. It involves setting clear policies and standards to ensure data accuracy and appropriate usage while defining specific roles and responsibilities. 

In our example: how do we define revenue? 

• Subscription fee: Revenue is gradually recognized over the service delivery period, even if payment is received upfront.

• Transactions revenue: the revenue is recognized in the month the transaction is taking place. 

Your revenue data needs to reconcile with the data from other sources, e.g. transaction data. While this might be clear to Finance, someone in another team might just be happy to sum up the amounts of all the transactions and all that revenue. 

This requires solid governance around how certain metrics are calculated and defined!

Well, data governance doesn’t sound very agile…

Maybe this sounds more corporate than it actually is in reality. Good data governance is like the ground you build your house on – it needs to be solid. 

It’s like making sure everybody in the organisation speaks the same language when it comes to data.

But wait, is the finance team the owner of this topic? Not really. But you are a key stakeholder and can bring the topic to the agenda of the company and drive it proactively. Especially when you are trying to help steer the company with data!

In practice, keep it simple! Together with the data team and other functional teams you can take three simple steps.

• Develop a concept around who can access which data

• Introduce naming conventions & definitions for your most important KPIs first (again, keep it simple!)

• Create a dictionary and explain where the master data sits and who owns it

Don’t overdo it in the first go. This will grow over time.

Why we should get involved…in a PROACTIVE way

As finance teams, we use a wide range of non-financial and financial data for our modelling, forecasting, reporting. We need to ensure accurate, reliable and consistent data to build and maintain our number one asset: TRUST.

Last but not least - some words to the spreadsheet lovers of this world:

When it comes to investing in proper processes, tools and infrastructure, make sure you don’t miss the tipping point.

Signs that spreadsheets no longer work (in an efficient way):

• Spreadsheets become too large and take A LOT of time to maintain

• Your spreadsheets and formulas get too complex and you realize that only one person in your finance team really understands it 

• Errors become more frequent 

• You cannot control who accesses and changes the data (hint: how would you know if someone has accidentally overwritten the formula in tab 102, line 589?)

• Collaboration becomes impossible

• You don’t sleep well before board meetings 🙂

If at least 2 of these statements are true for you, then it is time to build your data infrastructure. 

In short, spreadsheets have an expiry date when used for calculating metrics and running finance ops  in our view, you should think about investing in a scalable data infrastructure at the latest end of series A or when you have clear product market fit.

Starting too early is not good, but starting too late is neither…

Starting too early means over-investing in people and infrastructure that is less flexible than your Excel file that might not be business critical just yet. Investment that could rather go into your product.

If you start too late, you will need to maintain your patchwork solution. This can be very painful and will cost you a lot of money. The thing is, most people don’t take this into account when they argue against investing in “expensive” tools.

In Finance, it will make you slow and your reports and analysis will have a much higher error rate. And let’s be honest, this will come at a very high price: over time, you risk the trust of your key stakeholders (your CEO, board, investors...).

💡 QUICK INSIGHTS

The Good, the Bad, the Ugly - Shared Learnings

Eliminate busywork—focus on what truly matters!

Finance teams are often overwhelmed, trying to keep up with tasks that don’t always add value. Ask yourself: Are you preparing numbers no one looks at? Here are a few examples:

• Reporting: I've been there! My team and I used to spend days on monthly reports, unsure if anyone even read them. We felt like we were in a PowerPoint competition. My advice: Before diving into detailed reports, ask the bosses if they really need them. Just provide the main points to save unnecessary work.

  Pro Tip: Stop all internal reporting next month and wait who is missing what information. Re-introduce only what’s really needed!

• Automation Over Manual Work: Let's discuss the magical world of finance automation. Breaking old habits is tough, especially for finance teams, but automation saves time by eliminating manual tasks like invoice entry, financial consolidation, and budgeting. Stay tuned for our upcoming newsletters on the Finance Tech Stack 2024 and AI's impact on finance!

Must-Watch Finance Tools and Their Latest Fundings

Cloudpay- Global Payroll Provider

$120 million funding round led by Blue Owl Capital

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• Remote work

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Let’s find your perfect match!

🕵️‍♀️ EASY QUESTIONS - DIFFICULT ANSWERS

READER QUESTION OF THE WEEK

Question: How do you cut costs without killing morale?

Answer: When employees understand the "why" behind changes, they are more likely to support and contribute positively to the initiative. No need to micromanage when the reasoning is clear.

Here are some examples:

• Travel & Entertainment Smarts: Be transparent about why certain policies exist (like booking flights early for long-scheduled meetings or following tax rules—especially in fun places like Germany).

• Trim the Fat, Keep the Muscle: Ditch wasteful spending (unused tools, office supplies), but protect what drives growth.

• Quick Wins: Small changes like renegotiating contracts or automating tasks can save money fast without disrupting day-to-day operations.

Got a burning question? Fill out this form

UPCOMING READS OF THE WEEK

• How can Finance promote data-driven decision making?

• AI in finance teams - now and future

• How does the future Finance Team look like?

• Finance Tech Stack 2025

• …and many more

CLOSING REMARKS

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The CFO Playbook reflects our personal opinions, not professional advice.