Data strategy expert interview: data-driven start-ups

How is data used in start-ups? 

As a start-up, you cannot start with a data strategy right away. You are still fleshing out many processes and do not yet know exactly how it will turn out. You also have little time to do everything, but if you want to know how your company 'works', you cannot ignore your data. This takes place at various levels. It all starts with your culture, a data-driven mindset, and clear processes. You determine which metrics are important, when to look at your figures, and course-correct based on what you see.

Every quarter, you look at what you are doing from a business perspective. In the long term, you become more strategic and learn from your data what you can optimise and eventually automate. This makes your organisation scalable.

Data plays an essential role in this, for example, when you are working on financing your company. You must then be able to support your commercial model with data. You cannot only start working on this one week in advance: your key processes must be data-driven from the beginning to optimise and support your model with figures.

A fundamental difference between start-ups and corporations is that as a start-up, you do not start with one use case or department. The way you handle data immediately affects several parts of your company. As a start-up, you can switch gears much more quickly: the organisation is less hierarchical, the founding team almost always thinks in a data-driven manner and has a better overview. This way, you can make progress on all those parts simultaneously.

For Maarten, working in a data-driven manner is part of the daily routine. He explains how the vision on data became increasingly strategic within the organisation.

What is your own experience in terms of working strategically with data?

We started Deeploy with four people and have been using insights from data from the get-go. We started by analysing the usage of our product and focusing on certain metrics. Other things, such as commercial activities, have always been logged, but not optimised based on data from the start. We first focused on finding the product-market fit.

My experience is that you should not start developing a strategic vision on data too early. Characteristic of a start-up is that you try things out and experiment. You should approach this in a structured way, but not necessarily data-driven. In this phase, you have to be careful not to optimise locally without knowing what you are doing globally. If the focus of your company can still shift, you may need different processes, metrics, and dashboards.

Only after making those choices can you start optimising. For example, we are currently renewing our commercial strategy. Data is an important component in this, but I am glad we did not start optimising based on data from the start. That would probably have been optimisation in the wrong direction.

On the other hand, if we hadn't had a data-driven mindset from the beginning, we might not exist anymore. Start-ups that do not utilise their data effectively have no chance of succeeding. Creating scalability is essential and this can only be achieved with good, complete insight, so that you can adjust quickly and make informed decisions.

It is also much easier to assign responsibilities to other people if you have clear metrics with corresponding targets. An additional advantage: this makes internal meetings a lot more efficient. Thanks to the insights from your data, you as a founder can make good adjustments and it is clear to everyone what the expectations are.

What tips do you have for people who want to get started with their data strategy?

1. Make sure you develop your own vision of data before hiring someone to help you.

Without your own vision, a data strategy project will almost always end up in disappointment.

2. Involve all layers of the organisation in strategic decisions.

Do this for both your long-term vision and the operationalisation of use cases.

3. Develop a vision for the coming years, but also think concretely about what you need to implement now to make that vision a reality.

What does this mean for everyone? What impact does it have on your current tools, processes, and methods?

4. Do not get stuck in the process of designing your data strategy or implementing tools.

Make a roadmap, determine your scope, and start implementing. You can always refine it as needed.

5. Focus on application.

Start-ups are very good at this because they have limited budgets. I have seen many organisations create an entire data platform before working on use cases. The risk here is that the platform does not align with the use cases, or has already become outdated before it can be used.

Being surpassed by new, innovative players in the market is something that many C-level managers worry about. Maarten explains why he thinks this fear is justified.

To what extent is data strategy now on the agenda of starting and established companies?

Many corporates ultimately see data and technology as an afterthought. Data, technology, and innovation are considered interesting, but often become the last item on the agenda of the board meeting, which hastily has to be discussed in just 5 minutes. What I find fascinating is that many corporates do not even have a CTO. However, without technical knowledge at the highest level, you cannot make a good assessment of the long-term impact of technology.

In my opinion, you really need your own vision on data and you need to be working on it at a strategic level. Otherwise, you will not get very far and you will end up losing market share. The fear of being surpassed by scale-ups is, in my view, justified. You can already see it happening in banking and retail.

Start-ups think more strategically about their data and technology from the start. Growing pains are the biggest risk here. Some companies grow from 100 to 400 employees in a year, but hire people without a good cultural fit or clear job profile. You have to grow fast to be relevant, but it really is an art in itself. Data helps to achieve controlled growth.

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