Management for Data 101 — Operational Strategy
Preface: This article is the first in a series that talks about things we’ve learnt while trying to organise the data team at Aircall. Hence it goes without saying that some of the things we talk about will have a certain SaaS flavour to them. However, these articles are not meant to serve as a guide but more like examples that we hope will help you structure your ideas.
Know your stage
One of the first things you need to do to develop an effective data team is to understand the role your team plays in the development of your organisation. As your organisation progresses through different stages of development, the data team will need to adapt its role to respond to the changing needs.
Broadly, we like to look at the stages of this growth journey and the roles of the data team during those stages as follows:
- Start up — Measuring the main KPIs of the company
- Scale up — Providing the right information to the right team at the right time
- Maturity — Understanding and predicting the impact of strategic actions, driving personalisation of the product
Data in a Scale-up
Today, I would like to talk about the second stage — Scale up. An interesting stage, as this is usually when companies start growing in size and begin organising themselves into different departments. These departments have their own data needs which must now be addressed by a real data team.
Such a development gives rise to the necessity for proper management and organisation in order to ensure that the data team is able to contribute effectively to the organisation.
If you’re doing this for the first time, the task may seem a little daunting. At Aircall, we use a simple process to help us understand how we can support the various departments of our company and drive growth.
Our Process
Define your North Star metric
We begin by deciding on a North Star metric for our organisation. In most organisations, this should be quite evident — simply follow the metric(s) your investors ask about during the board meetings. Some of the more common examples of such a metric could be your Monthly or Annual Recurring Revenue (MRR/ARR), your Gross Merchandise Volume (GMV), Stock Keeping Units (SKUs) moved, Net Promoter Score (NPS) etc.
Frame your Objectives
As a scale up your priority is to grow quickly and as the data team, we want to help the organisation achieve that goal.
Hence, the first step is to define growth in clearer terms. The AARRR framework is a simple and common way to do just that. The letters stand for Acquisition, Activation, Retention, Referral, Revenue respectively.
Layout the structure of your Organisation
Next, we list out the different departments of our company. For the sake of this example, we’ll consider a few generic departments like Marketing, Sales, Success, Product and Support. Additionally, we’re going to take the MRR as the main metric as this is what we follow at Aircall and these definitions should resonate with most SaaS companies.
Now we make a table with the five parts of AARRR on the Y axis, and we take all our departments and lay them along the X axis. With this done, you can mark a X if a department contributes to the corresponding stage of AARRR.
You should end up with a table like:
- Marketing: Acquisition (inbound)
- Sales: Acquisition (outbound, partnerships)
- Success: Activation (customer on-boarding); Retention (customer care); Revenue (up-selling)
- Product: Activation (trial, on-boarding); Revenue (product/service sold), Referral (client satisfaction)
- Support: Retention (customer care), Referral (customer satisfaction)
This table serves as a simple point of reference to help you understand which part of the chain a certain department needs to stay informed about, in relation to your North Star metric.
For example, your marketing team needs to be able to study how the various acquisition channels contribute to the MRR. Your success team should be informed about how well they’re able to convert trials into paying customers, or up-sell to existing customers. The product team could benefit from having funnels that help them optimise the sign up or on-boarding processes etc.
This way you’re not only providing raw reporting to the teams you work with, you are also enabling them to improve their roadmap and organisation by helping them identify their key issues.
Adding more depth
While these examples look at data from a bird’s eye view, you can take them further by adding more levels of granularity. Let us take the example of sales and break it down further into Outbound and Partnerships, then our metrics could be something like:
- Level 1 Metrics → global KPIs like MRR acquisition, growth, churn
- Level 2 Metrics→ breakdown of MRR growth by region, segment
- Level 3 Metrics→ performance reports of individual sales executives, partner performance reports, targets/bonuses, commission payouts etc.
Once you know what information you need to provide to each department, you need to figure out the order of priorities for the company for the given quarter (or any other time period). Let us say the company wants to give the top priority to Acquisition activities and second to retention for this quarter, you will follow the same prioritisation.
That means that for the departments that work on Acquisition, you should target to provide all the levels of metrics. Then for the ones that work on retention, you could work on only L1 or L2 and so on.
Now that you know the kind of data points you need to work on during this quarter and how their relative priorities are, you should be able to draw yourself a roadmap that is aligned with the objectives of the company. Depending on how mature your organisation is, you might even have some visibility on the next few time periods — which you can use to ensure you’re prepared to face the upcoming challenges in terms of people, skills, infrastructure etc.
As a data team, your job is to help the rest of your company do better and if you know what to focus on, hopefully you should be able to do yours.
Hello reader, glad to see you made it all the way to the bottom! I hope you found something useful. Check back in right here next week for the next article in the Management for Data 101 series when we talk about prioritising issues.
If you enjoy reading about such things, do consider following Aircall on Medium or Twitter, we try our best to share our learnings as often as we can.
