How to Turn Data Chaos into Business Advantage | Insights

AI-Ready Data

The challenges of effectively implementing data management strategies are a daily reality for IT leaders today.

7N's report “The Hidden Complexity Behind Data Ambitions” points out that the key to success is not just investing in technology, but the ability to translate ambitious business visions into concrete operational and technical actions. Only then does artificial intelligence become a true ally of data - and ultimately a growth lever for organizations.

Data as the Foundation of AI and Competitive Advantage

Data is now the most valuable business asset, but in many organizations, it is scattered, inconsistent, and difficult to use. AI can only become a game changer when data is structured and available in real time. As Paweł Konas, Data Solutions Architect with 7N explains:

“Companies don’t lose the AI race because of a lack of technology. They lose because their data doesn’t speak with one voice.”

Five Barriers to Break Before Introducing AI

The 7N report “The Hidden Complexity Behind Data Ambitions” shows that the most significant obstacles don’t lie in technology, but in organization and processes. Key barriers include:

Lack of a common strategy and language between business and IT

Different definitions of key concepts across departments, lack of harmonization

Data silos and lack of system integration

Excessive expectations of “magical” AI platforms without first organizing the basics

Attempts at large-scale deployments without prior “quick wins”

“The greatest value we bring to clients is creating integrity between strategic ambitions, operational processes, and technological reality. AI is the future, but implementing these solutions sometimes requires taking a step back. Only 8% of companies have successfully implemented AI, so without these elements even the best and most ambitious plans can be wasted.”

— Grzegorz Pyzel, Senior Vice President, Poland & India

Key Success Factors:
What Really Works?

Translation, Not Technology

Before deploying AI tools, organizations need an analysis phase—identifying the gaps between business requirements and technical capabilities. Paweł Konas notes:

“Organizations that focus only on technology waste time and money. Success comes when we first focus on understanding the data we will work with. Equally important is understanding the business domain behind it. Only then can you start building and testing a solution in a limited scope - quickly and concretely.”

7N meeting with a male and a female staff member

Building the Foundations

While the temptation is to implement AI immediately, successful companies focus first on data quality, consistency of definitions, and simple integrations.

Without solid foundations, any new technology will only cause chaos. Business impact is achieved through full process transparency. The greatest gains come to companies that can translate strategy into real, clear requirements - because the right questions open the right projects.

Evolution, Not Revolution

Step-by-step implementations work best, where each stage builds trust and demonstrates business value.

“Even small successes at the level of individual teams can trigger a self-reinforcing cascade of change across the organization. The initiators of this approach provide bottom-up inspiration and a real example of value for other teams, which shifts their attitude from natural resistance to proactive willingness to be part of the change,” explains Paweł Konas.

A Long-Term Approach to Developing Data & AI Competencies

The biggest benefits go to organizations that treat AI not as a one-off project but as an ongoing process of continuous improvement. In practice, this means not only implementing technology and organizing data, but also investing in people - their knowledge, analytical skills, and ability to work with data every day.

That is why, alongside technological foundations, a long-term educational program is needed. 7N responds to this challenge through 7N Academy, offering dedicated development paths and training in the Data and AI domain. This way, organizations not only implement modern solutions, but also build an internal pool of experts who can maintain, scale, and translate those solutions into measurable business outcomes.

Business Impact and Long-Term Advantage

Companies that invest in organizing their data gain tangible benefits: faster decisions, fewer errors, better business forecasts, and readiness for advanced AI solutions. The key, however, is an iterative approach and investment in competency development.

“Companies that invest in data discover new business opportunities they had never considered. That’s when AI stops being seen as a flashy technological novelty and becomes a tool of real change—one that supports everyday decisions, increases efficiency, and builds lasting competitive advantage,” says Grzegorz Pyzel.

A data strategy in IT cannot be just a vision - it must be a proven methodology that avoids common pitfalls and builds value step by step.

We encourage you to read the full report “The Hidden Complexity Behind Data Ambitions,” which includes concrete success stories, checklists, and in-depth analyses of transformation challenges. Then, contact our team of experts to discuss practical solutions for your organization.