Data Centered KPIs for Operations, Finance, and HR

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.

Data Centered KPIs for Operations, Finance, and HR

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 our data also allows us to look at the future and make predictive decisions.

In this article, I’ll cover how ingraining your data within each system of your company will give you a competitive advantage. Also included are examples of how we are doing this at Ladder. To set the table I will share 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.

Data and Operations

Agencies are people businesses, so it’s important we know 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, we also need to ensure we have adequate skills within the team to serve our clients on time.

A large component of this is determining our projected capacity. As we forecast the future, does our Projected Capacity 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.

Another key component is 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 calculates our billables vs non-billables utilization. It is a collaboration between operations and finance. Our financial analysis indicated we need 70% of our hours to be billable to meet our goals. Finance is responsible for creating and maintaining the model and the operations team is responsible for executing our model based plan.

An extremely important key performance indicator ( KPI) we pay close attention to is Churn, the rate at which customers stop doing business with a company over a given period of time. This KPI is shared across all our teams because each employee has a part to play in customer retention, a key to our success.

For more information on Key Performance Indicators visit the library of Bernie Smith.

Data and Finance

Data Centered KPIs for Operations, Finance, and HR

Our main finance KPI is our bottom line but there are other data points we look at to understand our efficiency and overall financial health. These aren’t all we look at, but they’re very important metrics for us:

Revenue Per Head: We can quickly see how many people we have and the average revenue of each. Revenue per Head should be at the lowest point of 7 digits aka $10k

Personal Cost as a Percentage of Revenue: This ratio 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 around or under 60% – it shows our financial efficiency.

Debt and Debt Margin are what we use to keep track of our leverage and make sure this ratio is healthy at all times. Anything between 1 to 1.5 considered on the healthier side for our business

As a cash flow business, Receivables are huge for us. Our benchmark is that 80% should be paid on time, which provides a cash cushion to pay our team and vendors on time and make the necessary investments to grow the business.

Contribution per Department (revenue each department generates against its costs) 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 also maintain the contribution of 60% we need for the business to cover their fixed cost.

Data and HR

Human Resource (HR) is a key system that supports our growth. 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 various data points that indicate how our team is feeling overall and feedback on what we can do to improve. To name a few we gather information around Growth of our people, Recognition they are getting, Engagement and Alignment, all those metrics are ranked from a scale 1 – 5.

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.

How to update and review data for better forecasting

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 – which are 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 Ladder management team internally and the same format is shared annually 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.

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 to get the best results.

2 Real Life Examples of Using Data to Make Decisions:

One way we leverage data and brand it within our company’s systems is our hiring process. We started this model in 2019 and we’re still finding iterations and improving it as Ladder grows. By analyzing our time to hire, we have learned when we reach 70-80% capacity that is the trigger point to start the recruiting process or we will exceed capacity before we can onboard our new teammates.

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 to capture the extra effort required early on in an engagement.

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