What Does it Mean to be Data-Driven? (and Why Does it Matter?)

Believe it or not, there is a lot of meaning behind the popular "data-driven" buzzword, and now more than ever, it's important for you and your business to use data to improve your organisation. According to 90% of analytics experts, many businesses are hesitant to commit to a data-driven approach as they are unsure of the benefits of adopting a data-driven approach.

The Information Age

Through the information age, we have entered a data-driven era as a result of the expansion of data analytics technologies. Data is being used by businesses to improve and expedite decision-making. Statistics demonstrate that data is enabling businesses to grow and expand more quickly than before. The difficulty of gaining access to insights is further diminished by the fact that non-technical employees may now more easily use data analytics tools.

What does being data-driven mean?

When a company uses a "data-driven" approach, it means that it makes strategic decisions based on data.

A data-driven organisation might have a mindset of "continual improvement." This may involve optimising core processes over and over again, such as improving process efficiencies or lowering the cost of operations. This is done by carefully analysing data, building mathematical or statistical models, and running simulations.

To be data-driven, you need to utilise various tools and skills. Most importantly, you need to work on embedding a culture that responds and reacts to data.

A culture that is based on data starts at the very top. Companies with strong data-driven cultures tend to have leaders who make it clear that decisions should be based on data and that this is not unusual or new. They lead by what they do. Data can enable businesses to make decisions based on facts. These habits trickle down because employees who want to be taken seriously by senior leaders have to talk to them on their terms and in their own language.

How can I be data-driven?

A company that is driven by data usually forms hypotheses and conducts tests regularly. User testing, in which you work directly with real customers or users to get feedback on products and new features, is just one way a business may conduct a test.

A data-driven organisation might also use predictive modelling to make predictions about sales, retention, or revenue. It's important to feed incorrect predictions and other learnings back into your models to improve them.

A data-driven organisation will almost certainly use a set of weighted variables to choose between options or actions for the future. To make a data-led decision, one should collect data for each of the sets of variables that are significant or relevant. Then, one should figure out how much each of those variables matters.

Be considerate of the various functions in your business when it comes to utilising data. Different parts of your business, such as finance, customer relations, or HR, face different and unique challenges.

What are the benefits of being data-driven?

Data-driven decision making often, if not always, outperforms guesswork. A data-driven approach helps businesses look at and organise their data in order to improve their products or services for their employees, customers, or consumers.

Using data to make decisions has many benefits, such as:

1. Utilizing a single source of truth

When colleagues and different functions in your business have access to the same data (with the right levels of governance), they are able to work from a single source of truth.

2. Enabling collaborative working

Most of the time, the data you see is the same data that someone else is looking at from a different angle. When your data can be associated and discovered, people in different parts of your business can use their insights to take actions that are driven by the data.

3. Creating opportunities

When people share insights, it leads to new opportunities and real change. Your business can be more agile if you can see what is happening under the hood. Without capturing data and modelling it for insights, most of what you try to change will be guesswork.

4. Saving or making money

Manually processing and storing data costs money, particularly when it isn't automated. It is best to limit the number of different teams spending their time analysing the same data from disparate datasets. Data as a product and data products are also great ways of generating additional revenue streams for your business.

5. Employee retention

Promoting data literacy throughout your company can also lead to more employee engagement and teamwork, which can help keep people from leaving. A study done by Forrester Consulting for Tableau showed that almost 80% of the employees they talked to said they were more likely to stay at a company that gave them the training they needed to be good with data.