CASE STUDies

Our Customers

See how companies are using Causal to automate manual processes and democratise financial planning in their orgs.

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consolidation, headcount planning, board reporting
Causal pulls and consolidates actuals across 5 entities from Xero, saving me 2 days per month and giving the management team more confidence in our numbers.
Zack Topuzov, Head of Finance
Automatic consolidation turns 2 days into 2 minutes

Smarkets has 5 legal entities across different countries, which need to be consolidated into a single view. This took days of manual work in Excel, and was highly error-prone. Causal has automated the entire consolidation workflow, and removed the chance of human error in the process. Finance spends less time double-checking numbers, and stakeholders can trust that the integrity of their data.

The management team use Causal dashboards to explore scenarios in real-time during meetings, and are more actively engaged with the financial model than before.

Re-forecasts in hours, not weeks

Wagestream operates in 4 countries, and needed both country-level and consolidated P&Ls, each tracking budgets against actuals. In Excel, this led to a lot of formulas and duplication — a monthly re-forecast would takes days.

Causal incorporated the multi-country structure into Wagestream's model. Updating the P&L in one place now updates it across all countries, and Causal automatically tracks budgets vs actuals at a granular level.

consolidation, headcount planning, board reporting
Causal has let us easily model across multiple countries separately and at a consolidated level. Re-forecasts take hours instead of weeks, so I can spend more time on strategic initiatives.
Eoin Weeks, Financial Controller
consolidation, headcount planning, board reporting
We implemented Causal in 3 weeks, including integrating with NetSuite. With Causal’s visual dashboards, the management team are more engaged with finance than ever before.
Nicola o'farrell, Head of Finance
3-week implementation to automated reporting

After Duffel implemented NetSuite, they needed a tool that could pull historicals directly to perform rolling forecasts and present engaging visuals to the management team and board.

Implementing Causal took 3 weeks from start to finish, and Duffel have embedded live Causal charts and tables into their Notion documents to share with the rest of the company. The charts update automatically with new data — no more time spent preparing reports each month.

Learn more about Causal's data integrations.

5 entities consolidated and more engagement

Like most SaaS businesses, Taxdoo needed to model multiple products on a cohort basis, incorporating historical data into their forecasts. This led to a tremendous complexity in Excel — dozens of tabs and thousands of formulas made it hard to audit and make changes.

Causal’s advanced modelling features reduced all this complexity into a single model with a readable set of formulas. Adding 10 different scenarios took just a few minutes, and the company now presents live dashboards to investors with no ongoing reporting effort.

consolidation, headcount planning, board reporting
I replaced our Excel financial model almost overnight with Causal. Building our cohort-based revenue model was ridiculously easy, and my investors love the charts + dashboards.
Christian Königsheim, CEO
consolidation, headcount planning, board reporting
Our Excel model was complex and hard to maintain. With Causal, we can easily keep our financial model up-to-date and the company has a much more transparent insight into our business.
Jack Morrisson, CEO
Greater transparency + automated board reporting

Scythe wanted to provide financial visibility and transparency to the whole company, via a single source of truth. This wasn't possible in Excel without sharing sensitive salary data or an enormous amount of manual work.

After switching to Causal, Scythe now has a single, shared source of truth. Anyone in the company can view and understand the financial model, and granular permissions protect sensitive salary data.