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Writer's picturelarryworkson

Deep dive: an in-depth exploration of the Equal way of being and doing.


Know yourself. In a world where the volume of data doubles every two years, creating a sea of information that is nearly impossible to navigate without a compass, the practice of the famous phrase by the Greek philosopher Socrates — "Know yourself" — becomes increasingly necessary.





Looking inward, understanding your values and purpose in depth before analyzing external data, is probably the safest route to embark on this blue ocean journey. This advice applies to both individuals and companies.


So, that was my first action upon joining equal: taking a deep dive to understand the details of this universe called equal BI & Data Engineering. Pleased to meet you, I’m Mayara Rinaldi, the new Marketing Coordinator. I began my journey at the company in July 2024, with the mission of building the marketing department, which until then had been under the responsibility of the CEO, André Azevedo.


Structuring the area is a challenge that motivates me deeply. To begin the work, I sought to understand our value proposition, our market differentiators, and our context. You can tell by the first-person plural possessive pronoun that I’ve already embraced the company, and this was one of the values emphasized by co-founder Vitor Rodrigues: having an ownership mindset. I feel aligned.


In this deep dive I took into equal, I spoke with 10 people. These conversations totaled approximately 15 hours of interviews and 51,000 characters of notes. I could list many other numbers to give the text an air of a "data-driven post," but we know that disconnected information, without data intelligence, is just noise.


The richness of being data-driven lies in knowing how to focus on what really matters and giving meaning to information from a clear business perspective. This perspective is one of equal’s market differentiators in data engineering and business intelligence (BI). This is also one of the insights about the company’s essence that I highlight from my analysis of the interviews conducted.


The data extraction code I applied did not use JavaScript or Python, but rather active listening. Before performing quantitative analyses and looking at numbers, I wanted to hear who equal is from the perspective of those who make up equal. The final result wasn’t a dashboard and charts (although I really like them and strongly believe in data-driven marketing), but this first-person narrative that you are now reading.


I was very excited to see the willingness and collaboration of everyone during the interviews and to notice that there is a lot of alignment among the team members. I was also very enthusiastic about observing the partners’ commitment to creating a pleasant work environment and fostering professional and personal growth for the team. They truly demonstrate this concern, without demagoguery or empty promises, and this is also part of the company’s essence.


The conversations with partners and team members revealed intangible data, information that is difficult to measure. What everyone has at the tip of their tongue is what equal does: "we help companies transform raw data into information that generates business results through technology and data engineering solutions."


But how does this work in practice? What is the impact of a good decision on a business? What sets us apart from competitors in this work with data? What can we improve and evolve in our deliverables?


I went after these answers, and it was interesting to note that many people had never stopped to think about these kinds of questions. The lack of reflection on our day-to-day activities is common. The human brain has its own ETL to automate routines and repetitive activities, so we often execute dozens of tasks without assessing whether they still make sense during the process. I believe that for the team, this moment of pause and self-analysis was beneficial.


Seeking answers to these sometimes difficult-to-materialize questions is essential for communication work. That’s why the step of knowing oneself is so important. This knowledge will enable us to relate well internally as a company and externally with the market.


Speaking of the market, two characteristics of our ideal client are also very clear to everyone at equal: 1. we want to reach mid-sized companies that 2. are aware of the importance of data for professional and efficient management. From there, new questions arise: who are these mid-sized companies in Brazil (and abroad)? Where do they live? What do they feed on?


The dive into the interviews was, in fact, the first meter of a descent into the equal ocean of data engineering and analytics. After looking inward, it’s time to seek new sources, understand market numbers, conduct new research, and benchmarking.


Corporate self-knowledge is a continuous process that requires constant reflection and action. Just as for individuals, for companies, this practice is vital to growing sustainably, innovatively, and resiliently, ensuring relevance and long-term success in the market.


The answers to the intangible questions listed throughout the text will come in the next chapters of this work: the equal brand tone-of-voice manual, blog posts, social media, events. My work in marketing will ensure that equal’s communication is consistent across all channels and brand touchpoints and brings these questions to further reflection.


Communicating our value proposition so that more companies can use data to also know themselves and, with that, professionalize and revolutionize their management, is quite a challenge.


As co-founder Ricardo Siementcoski said, many steps of maturity are needed from complete ignorance of data to using BI’s potential as a competitive advantage.


Even among our clients who came already knowing the importance of BI, the perception of the positive impact of our work was built as deliveries were made, such is the disruption of what we do for our clients' businesses!


How do you measure, for example, the satisfaction and happiness of an employee who no longer needs to spend days on repetitive tasks, now automated by BI? How can the productivity boost of this more motivated employee be measured?


There is a famous phrase in management: "What cannot be measured, cannot be managed." I disagree and dare to suggest another approach: not everything that needs to be managed, such as employee morale, can be easily measured; but everything that needs to be measured, needs to be equal!


This is the message I, as marketing, want to communicate to the market.

 

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