In today's world, the frequently used term "data-driven business" often falls far short of what can be achieved with data and proper analytics practice.

For strategic business development and financial accounting to truly be based on analytics and measurable information, the collected data must be absolutely reliable and comprehensible. At the same time, the company must have the capability to interpret the collected data and implement it into practical measures. 

What does being data-driven really mean?

Today's data tools, such as Google Analytics, Looker Studio, Matomo, and PowerBI, are familiar to many. Even if these tools are utilised within an organisation, their data may still go unexploited.

Being data-driven in business is the ability to transform cold numbers into a narrative that engages various stakeholders within the organisation, enabling long-term practical actions based on these insights.

The starting point: data vs. problem

The more an organisation can analyse and truly understand the data it collects, the less it needs to spend time finding problems in the data at hand.

In a nutshell:

• Data should primarily be used to solve identified problems.

• Searching for problems within data can lead to tunnel vision.

• If data is primarily used to find problems, it may indicate a need to develop a more comprehensive understanding of the business.

By way of clarification: It is possible to find problems to be solved within data, but this approach requires the ability to identify issues both from data and the different areas of business. Primarily hunting for bottlenecks in numbers and charts is slow, and lack or distortion of data can lead to prioritising the wrong matters. 

Before lengthy data dives, it is beneficial for a company to know its own products, customer base, business environment, and competitive landscape.

For example:

Company X wants to understand why sales are stalling, even though a lot has been invested in marketing during the peak season. The marketing team has been tasked with uncovering the root causes of the problem.
The table below (imaginary) serves as an example of how decision-making can be supported by data. Note: The analysis can be taken much further.

Properly analysed and presented data can offer decision-makers the opportunity to understand what is actually happening in the business – the next step is to apply development actions based on the collected data.

Next time you find yourself (or your organisation's marketing team) merely staring at charts, remember these.... 

Four Steps to Support Being Data-Driven

1. Problem Identification and Goal Definition: A smart approach begins with identifying the problem (there are many different tools for this, such as SWOT analysis or customer journey mapping) and defining a goal in a way that it can be measured and tracked (read more about SMART objectives)

2. Use Data to Solve the Problem: After defining the problem, data can be used to choose the best approach, for example:

   1. Analysing historical data to identify trends that help understand the root causes of the problem.

   2. Collecting new data to deepen understanding of the problem or validate potential solutions.

3. Focus on Practical Insights: An effective approach is to create ideas based on data analytics that aid in decision-making. Prioritise what helps identify essential actions and avoid getting stuck on irrelevant information.

4. Measure, Measure, Measure: Once a solution is applied, its impact must be assessed based on reliable data. This means measuring the effectiveness of the solution and making necessary adjustments – A/B testing serves as an example. The impact of actions should be communicated to stakeholders to support data-driven decision-making as effectively as possible.

In Summary

When data analytics is correctly applied to problem solving, a strong foundation for informed decision-making is created in business, and practically applicable and measurable development ideas are identified.

Successful data-driven decision-making requires strong data management and analytics skills. In addition to the right tools, a company must ensure it has the proper processes and expertise for collecting, storing, analysing, and visualising data.

If developing your organisation's own skills seems too big of an undertaking, it is possible to rely on the comprehensive expertise of data consultants.

Would you like to hear how being data-driven is practically enabled?