2,5 minute read

The role of intuition and data in the decision-making process

Since the beginning of time, human beings have made decisions based on intuition and data (empirical experience). Logically, the weight of each one of them has varied and the experience (and the data) have taken the protagonism away from intuition with time. In reality, each hemisphere of the human brain is more inclined to one side:

  • The left hemisphere contains the rational part of the brain and is related to analytical thinking
  • The right hemisphere contains the most creative part of the brain and is related to intuitive thinking

Most people have one hemisphere that dominates more than the other; this means that there are people who are able to make intuitive decisions more easily and vice versa. Undoubtedly, teams that have talent in both capacities will be able to contribute more value overall.

The importance of data in companies

Having said all this, surely you’re thinking that data is not so important and intuition alone can be enough to make good decisions, right? Data is tremendously important and the obsession of any company, digital or not, should be to measure and analyse results. Data shapes an unequivocal reality and does not give rise to debate. If we choose to  analyse data, then meetings can be focused on how to improve that data and what decisions should be made from that point forth. This way, we avoid standard phrases such as ‘I think it’s working’ or ‘This data is not correct’.

The path to data driven company

Currently, there is a tendency towards the use of data in decision making. In future articles we will talk about this trend and how to face this challenge. But if organisations do not see the value of data, it is very difficult to change this trend. 

The 5 key factors for a company to start becoming a data driven company are:

  1. Data culture: for each decision that is made, always ask which KPIs will be taken into account to assess the impact, and for each action implemented, always ask for the results and determine what the ROI (return on investment) is.
  2. Poor analysis of data: Currently, there is a lot of data we can analyse. Success is knowing what data is relevant.
  3. Data hierarchy: each level of the organisation should be set to some KPIs and not all should analyse them. Organisations need to be able to synthesise data as it rises.
  4. Consistency with data: the analysis of data helps us draw conclusions and make decisions. It is important to be consistent in this virtuous cycle of analysis and action.
  5. Belief in data: large organisations always have a problem and that is that data is often incongruent and inconsistent. It is important to ensure that the data is correct in order to avoid the skepticism that is often generated and, in a way, the excuse that many teams use when they don’t like the results.

Qualitative analyses to understand data

Of course, data is not everything; data reflects the result, or the result of actions or decisions that have been taken, but they do not take into account team motivation, customer insights or competition… It is important to listen and perform qualitative analyses that complement data: field observations, focus groups, benchmarks, mystery shopping… there are many techniques that help interpret the data correctly.

Jirada and Jelliby wants to bring this added value by combining teams that are a combination of both analytical thinking and creative expression.

Summarizing data in inspiring phrases

If you were a data skeptic, I hope this article has helped you understand the importance of data. Here are six inspiring sentences that reflect and summarize the importance of data. 

  • “What gets measured, gets managed” – Peter Druker.
  • “Those who not remember the past are condemned to repeat it”- George Santayana.
  • “Errors using inadequate data are much less than those using no data at all” – Charles Babbage.
  • “A point of view can be a dangerous luxury when substituted for insight and understanding” – Marshall McLuhan
  • “Not everything that can be counted counts, and not everything that counts can be counted” – Albert Einstein
  • “The goal is to turn data into information, and information into insight” –  Carly Fiorina, Former CEO of HP