Raise your hand if you agree that “data driven decision making” is one of the biggest buzzwords in data? Not to say it’s not important, but it’s a phrase that has been beaten to death by every marketer and salesperson out there. And even though every company is trying to march to the drum of “data driven decision making”, we still can’t seem to wrangle it like a fish escaping our catch.

In a recent survey, 58% of respondents stated their companies base at least half of their decision-making process on experience or gut feeling. That’s the equivalent of how I decide what I’m having for lunch…based on experience and gut feeling.

So what does it mean to be data-driven? It’s the process of making business decisions based on data, and it involves collecting data, observing patterns, and utilizing facts in decision-making.

Before you can start using data, you need to invest in the technology for collecting, cleaning, hosting, and maintaining that data. Let’s also not forget the salaries of data engineers, scientists, and analysts - they are an investment. Business decision-makers biggest question is: how do I leverage data to turn it into a profit?

The answer? by building a strong data culture within.

A recent article by Harvard Business School suggests that data-driven companies not only take more confident decisions, but also realize significant cost savings. Of all the organizations that used data for decreasing expenses, over 49% have seen major improvement.

That sounds great on paper, but how do you actually build a data-driven culture within your company? We’re going to guide you to a more data-driven culture in four easy steps:

1. Start with business decision making
2. Ensure data quality
3. Democratize data access across departments and people
4. Build your data into processes and products

Start with business decision making

“The fundamental objective of collecting, analyzing, and deploying data is to make better decisions.” (McKinsley: Why data culture matters)

In a data-driven company, data comes second. Yes, you heard me right. The first priority is decision making. Feels backwards, but the goal of building a data-driven culture starts with business decisions first.

These business decisions should align with critical questions to the core decision-makers. What questions should we be asking and answering to give us an edge to not only get ahead of our competitors but maintain the lead? What data would we need to decide what our next product offering should be? How is our product performing in the market?

To drive strategic changes, start by agreeing on common business goals and what metrics are relevant to measure achievement across the whole organization. Turn those metrics into KPIs (Key Performance Indicators), then start measuring and reporting them.

Ensure data quality

Data-driven decisions are only as good as the foundation they are built on.

Data quality promotes trust and gives decision-makers confidence that they can rely on that data. There’s nothing like sitting in a meeting where the numbers don’t match the report. That said, quality can seem an elusive concept.

It boils down to two aspects:

1. Ensure the technical infrastructure supporting data acquisition and consumption is well-engineered.
2. Make data easily available and understandable to decision-makers.

From a technical standpoint, companies must aim to apply the best engineering practices when it comes to data. The entire ETL pipeline must run like a well-oiled machine.

Data sources are smoothly integrated with databases and data lakes. The transformations between data types and flow between different modules are seamless. The entire infrastructure is monitored for errors as well as fault-tolerant. A well-engineered pipeline centralizes different data sources and can flexibly adapt to changes.

In other words, your infrastructure can support your growth and scale with you; this gives you an advantage of scalability.

From a people perspective, make sure to develop an understandable (non-technical) language, spoken across departments and shareholders.

In practice, this involves naming your data in an easy-to-interpret way, agreeing on what the definitions of your core concepts are, and all the other micro-processes, which speed up data interpretation.

Democratize data access across departments and people

Different departments consult different data for their decision-making process; we sometimes sit in our bell jars and forget that people operate from a completely different point of view and set of tools.

Sales rely on their CRM, technical support consults their ticketing system when dealing with requests, and marketing looks at digital platforms to evaluate ad performance.

When crucial information is locked in these data silos, it prevents your company from developing a cross-departmental data-driven culture. Having many sources of truth gives us the advantage of having many different views/perspectives on the same customer, but it also leaves open a wide array of interpretation.

Data being locked in silos is also problematic from a technical standpoint. Multiple data pipelines are harder to monitor and maintain. This can lead to data being stale by the time a department uses it to make decisions.

Break data silos and bring data across departments. Empower everyone to make data-driven decisions on their own by relying on a centralized, single source of truth without the need to rely on others for access or interpretation.

A data-driven culture is about developing a single source of data and a common language to talk about it. Read more about the business best practices when opening silos.

Build your data into processes and products

As Keboola’s CEO Pavel Dolezal puts it: “It’s never enough to put data together and create insights. We need to create new processes.”

This means building processes and products based on data.

In other words, a company does not just use data. Instead, it relies on data for its core offerings and operations.

This can take the form of KPIs and dashboards for regular performance monitoring. But data can also be ingrained in the core of your product and services such as building products using machine learning and AI.

A data-driven culture goes beyond paying lip service to data. It puts data where the money is, at the heart of the company.

Culture is a process, not a state

Building a data-driven culture can take time, but the gains are huge and vital to the growth of a company.

Focus your efforts on these four pillars which are decision-making, data quality, data accessibility, and core-product to reap the benefits of a data-driven culture. Keboola is here to help you out in the process of achieving your company set goals in a faster and efficient way. Hop on a call and let’s discuss your options.

‍