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Guideline to data thinking shift

Updated: Jul 7

One of the main purposes of data mining is to find new hidden patterns in a dataset that can be useful and support the decision-making process.


Any organisation with, for example, access to huge historical datasets, and with the business core in sales (most of them fit this profile), should manipulate data to create information so that useful insights can be generated to accomplish the company's goals and mission.


Developing a data-driven mindset is crucial for these organisations, and turning them into a data-driven culture isn't easy and has many obstacles that need to be overcome. This change can be extremely hard, mainly because what we do not understand, we do not accept.


So, the success ladder for data-driven thinking is top to bottom:


1. Executive leadership aligned and on board with the change, their impact on decision making and the most important resource: BUDGET allocation. They must understand the benefits and have a data-driven mindset.

2. Have a Data Department, to establish clear data definitions supported by updated documentation and to define who and what should be available.

3. Engage all employees in a data thinking mindset, and develop an insight culture throughout the organisation.

4. Uplift data to the asset level

From my personal working experience (20 years) I can say that I have already faced many different scenarios, some more positive than others. In my opinion, to be a data-driven organisation, it's fundamental to have a roadmap that includes all initiatives to be developed, data availability and granted access to it (data quality mindset is mandatory), hierarchy commitment and understanding where we are and where we can go (expectation level management).



by Pedro Veiga

Data Analyst Consultant @ Passio Consulting

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