Being a skilled coder, building algorithms, or analyzing data sets alone isn’t sufficient. In order to create value, data must be implemented into actions that are in tune with the organization’s objectives.
A data scientist, for example, can develop a perfect model for making predictions in a given context. However, that model’s true worth is realized when it can influence choices, such as optimizing customer acquisition, minimizing operational loss time, or changing the pricing structure.
Could this be the reason that those who understand data and business strategy have a competitive advantage? It is something that has to be analyzed on your part.
Data Literacy for Business Professionals
Of the many tasks involved in developing this dual approach, one of the most difficult is explaining your findings to non-tech-savvy people. In other words, do not overwhelm your stakeholders with complicated mathematical models or terminologies; rather, consider the “so what” aspect. For example,
- If you are able to identify customer churn, connect it with its probable revenue loss, and outline measures to correct this matter.
- Get the message across using visualizations such as dashboards or simpler data story tools like Tableau or Excel.
Why Do I Need a Business Mindset When I Work for a Core-Tech Role?
No matter whether one works in a purely technical or managerial position, it is necessary to think like an entrepreneur to become a problem solver rather than a task-doer. It’s not simply about understanding the mathematics that underpins machine learning models but about the market in which they’re being used.
- Understand how one can determine which KPIs are relevant to the business.
- What factors have a material influence on the existing and potential state of the market?
- Which barriers affect revenue sources and customer behavior?
- To what degree is geopolitics going to influence your business?
It is equally important for a manager who demands quantification of work to be able to determine what requires measurement. Integrate your analytics with customers, opportunities, and business issues so that your value is clear at every organizational tier.
Career Pathways
Preparing for roles like Data-Driven Product Manager, Business Intelligence Analyst, or Chief Data Officer is noteworthy. These positions require a balance of both worlds: people who understand the technical side of data but can also lead teams, drive strategy, and make high-impact decisions. For instance,
- A data-driven Product Manager uses data insights to refine products or services based on customer feedback and market trends.
- A Chief Data Officer, meanwhile, is responsible for a company’s entire data strategy.
The Best Time for Upskilling is Now
The European School of Data Science and Technology (ESDST) MBA in Data Science, Machine Learning & AI is designed to equip learners of all levels with both the technological mastery and business sense to become data-driven leaders.
Courses such as Transformational Management and Data Analysis for Managers teach you how to apply data science in a business context, while integrated labs like the Entrepreneurship & Innovation Lab ensure you have a space to nurture your ideas at the intersection of tech and strategy.
Do strive to be double-skilled at the earliest because leadership today is not only about people but also about using data to create margins and value.