February 7, 2022
One thing we’ve learned at Ladder over the years is how important data is to finding sustainable success and profitability. We’ve always been very data-focused when it comes to our marketing ideology with creative testing and adaptive growth, but we’ve taken it a step forward by truly branding data within our operations, finance, marketing, and HR systems.
Our data strategy allows us to have an understanding of our company’s current health at all times – we’ve built the reports that show us how we’re doing at a glance. But having a good system to manage and learn from your data also allows you to look at the future and make predictive decisions.
In this article, we’ll cover how ingraining your data with every system of your company will give you a competitive advantage and show you how we’re doing this at Ladder. We will start by sharing the main KPIs we track for each system, then how we use them to make accurate forecasting, and, finally, a few real-life use cases of this process.
Agencies are people businesses, so at all times we should grasp where we are with our team’s capacity and make sure we have enough people to service our clients – even when we are growing quickly. Not only do we need the right amount of people, but we also need to ensure we have adequate skills within the team to deliver for our clients and do it on time.
A big part of that is our Projected Capacity. As we look to the future, do we have the capacity to fulfill our growth? Fast growth isn’t sustainable or profitable long-term if our projected capacity doesn’t match it and churn happens because of it.
We also look at our Client Profitability. We have a budget for each client and project, and we know if we follow it, our financial margins will be solid. This KPI shows our efficiency and shows our billables vs non-billables utilization. It mixes both operations and finance – finance created the model where we need 70% of our hours to be billable and the operations team is responsible for making sure that actually can happen.
An extremely important KPI we pay a lot of attention to is our Churn. This KPI is shared across all our teams because they’re involved in doing a great job for our clients. Obviously, this one illustrates our client retention and is extremely important to our success.
Our main finance KPI is our bottom line but there are other data points we look at to see our efficiency and overall financial health. These aren’t all we look at, but they’re very important metrics for us:
Revenue Per Head: this one is important because, at a glance, we can see how many people we have and how much revenue each of them produces – independently of if they directly or indirectly contribute to our top line.
Personal Cost as a percentage: another necessary ratio because it shows how much it costs for the whole team with everything included (payroll, taxes, pension, etc.) against our revenue. Our benchmark for this KPI is for it to be around or under 60% – it shows our financial efficiency.
Debt and Debt Margin are what we use to keep track of our debt integrity and make sure this ratio is healthy at all times.
As a cash flow business, Receivables are huge for us too and our benchmark is that 80% should be paid on time, which illustrates our cash ability to pay our team and the investments we need to make.
Contribution per Department is another data point we look at that falls under the finance engine. This helps us make sure all the departments have the relevant resources, but that they don't maintain the contribution that we need for the business to cover their fixed cost.
HR is a key system that supports our growth, and we leverage data to measure how our team is doing and how we can best support them. These are some of the KPIs we look at:
Employee Happy Index: this includes a variable of data points that tells us how our team is overall feeling and feedback on what we can do to improve.
Time To Hire: this helps us understand how long it’s going to take us to source a position from the time we know we need to hire.
Absent Days: we encourage our team to use their sick days whenever they need them. If at the same time, the number crosses a regular threshold for the team, which is around 4%, we know that there are deeper problems with our team’s happiness we need to figure out.
The past doesn’t foresee the future, but using good data helps us forecast for it. Accurate forecasting isn’t easy, it’s only as good as your assumptions – and they are often not necessarily tied to your data but to your ambitions.
For your forecasting to be as real as possible, I recommend having a thorough process of updating all your databases and making sure the data isn’t skewed.
For example, I look at our cash flow data on a daily basis and all our other financial data on a weekly basis. We also have a monthly presentation to the board where we present all our financial data, our YTD performance, our monthly performance, our high-level KPIs, and our forecasts. Then I present the same findings to our management team internally at Ladder and the same format is annually shared with our shareholders. These all help keep our finances healthy and accurate.
On the operations side, we also look at and update all the KPIs every week with our Director of Growth Operations. We have a quick stand-up every Wednesday that gives us room to rectify some actions as needed like our utilization capacity and other short-term KPIs. At the end of every month, we present all findings to the management team and inform the heads of department if they need to pay attention to something.
And on the HR side, we update our KPIs monthly through Disco on Slack, which anonymously collects all feedback from our team and automatically produces our Happiness Index we discussed before.
That’s what works for us in terms of updating and reviewing our data – I think you have to find your own cadence and process but it’s very important to have a good process for this so you can leverage it best.
One way we leverage data and brand it with all the systems within our company is our hiring process. We started this model in 2019 and we’re still finding iterations and improving it as Ladder grows. Here’s the gist of it: 70-80% capacity is a trigger to start the recruiting process because we use historical data to know how much time we need to hire.
Another example: the KPIs above showed us that, in the first four weeks of working with a client, we tend to have a load period where we over-service them. It’s normal – our team is getting to know the client, building the foundation, creating reports, etc. To help our clients at the level they need while also remaining financially efficient, learning from that data made us change our pricing policy and illustrate that extra allocation.
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