In the ultra-competitive digital era in which we operate, implementing a data-driven culture within your organization makes a difference in the market.
Whether you are a small business or a large company, the ability to collect, analyse and use data effectively can mean the difference between success and failure. To realise the full potential of data, it is essential that it is part of the DNA of the business.
According to a study by the McKinsey Global Institute, companies that make data-driven decisions are 23 times more likely to acquire customers and be profitable. Among other things, documenting your decisions allows you to reduce uncertainty, more hits and fewer misses and, most importantly, to learn faster.
But what exactly is data culture? How can we implement it? In this short guide we offer answers to all your questions.
What is a data culture?
When we talk about this type of “culture”, we are referring to any organisational environment in which the use of data is a key component of decision-making and the way work is done.
In an organisation with a strong data culture, data is valued, shared and used proactively across all areas and levels.
In other words, it is about group beliefs and behaviours of people within an organisation who value and promote the use of data to make a positive leap in decision making.
6 aspects that define data culture in an organisation
When data becomes embedded in a company’s mindset, identity and day-to-day operations, it is due to, among other things, six key issues.
1. Commitment from top management
In other words, the implementation of a data culture starts at the top. Senior management must be committed to the effective use of data and lead by example.
2. Access to quality data
Reliable and high quality data is needed, and this requires investment in data collection, storage and processing.
3. Promotion of training
Training in analytical tools, basic statistics and good data handling practices is essential, as well as training and education of employees.
4. Promoting collaboration
Data culture is based on collaboration and the fluid exchange of information between different departments and teams.
5. Data-driven decision making
Decision-making must be based on data and evidence, and not just rely on intuition alone.
6. Continuous learning
An essential part of an organisation’s data culture is to accept that there is a constant focus on improvement.
Analyse data to learn new information or conclusions about it, implement other strategies and actions, retest it and learn. Again and again. Again and again.
In short, we can affirm that an organisation with these six aspects well integrated into the business has an optimal data culture and adopts data-driven behaviours, aligning this information and its analysis with the results obtained.
Another aspect to consider: teams have a greater ability to prioritise business processes, with an inescapable encouragement of collaboration and participation.
And what good does this do? Increased revenue and a greater competitive advantage are just some of the benefits, but there are many more that you will learn about if you read on.
Benefits of a strong data culture
Understanding the value of data is as simple as appreciating the key benefits of having a strong data culture.
Starting with more informed decision-making, because when data becomes the basis for decisions, the risk of making wrong decisions is reduced.
This means greater operational efficiency, cost savings, and a competitive advantage: we make more, better and faster decisions than our competitors.
At the same time, data can become the seed for innovation and the development of new products or services within the company, enabling significant adaptation to changes in the market and business environment.
In addition, there is the extra facility to retain customers by offering more personalised experiences and adopting a strategic mindset that will have an impact on the future of the organisation.
Steps to implementing a data culture
Now that we know what a data culture is, let’s look at how we can implement it in your organisation.
It should be noted that these steps are a basic and simplified guide to the essential actions that any type of organisation should take to become a data-driven enterprise.
However, our recommendation is that you have a team of data management and business intelligence experts to accompany you in the process. In any case, the steps to follow are:
- Define a clear and measurable vision and goals related to the use of data in decision-making.
- Obtain senior management commitment and assess the data infrastructure to see if there is a need to invest in more technology and resources.
- Train employees (workshops, courses, etc.) and start fostering collaboration between departments and teams.
- Establish a common language, so that everyone speaks the same “data language”, and specify a privacy and ethics policy.
- Start making data-driven decisions at all levels of the organisation, and then measure progress towards your goals.
- Recycling and continuing to learn is the pinnacle of progress.
Useful tools for implementing a data culture
At Bimex we always recommend Power BI (Microsoft) .as one of the most flexible and innovative tools on the market for data analysis, and especially to start implementing data analysis in any company.
In addition to Power BI, we can use complementary tools such as Microsoft Dynamics 365, SharePoint, Teams or Power Platform.
The latter are ideal for managing enterprise resources, managing documents, improving productivity and communication between teams and/or developing applications.
Start building a data analytics culture in your company
Implementing a data culture is a process that takes time, commitment and effort, but the benefits are indisputable.
In any case, remember that implementing a data culture is not a one-off project, but a continuous commitment to improvement and evolution.
In addition, to be on the safe side, it is advisable to have a company that specialises in business intelligence, business analytics and data analytics.