Nikolai Potapov | Product & Data Leader
Product and Data leader with 20+ years of experience. Responsible for Data Strategy & Governance at TIMOCOM, reporting to Board Members and co-shaping AI strategy. Based in Berlin.
Product · Data · AI
I build the path when there isn’t one yet.
I help companies decide what to focus on next across Product, Data and AI, then turn those choices into products, governance and operating models that work in practice.
Board-facing. Hands-on. From hypothesis to operating capability.
Scope
Product
Strategy
Management
Data
Governance
Readiness
Credibility
20+ years
Across software, data, product and enterprise transformation
Board-facing
Working directly with senior leaders and decision-makers
Hands-on
From hypotheses and strategy to products, operating models and implementation
Why initiatives stall
The hard part is rarely the technology.
Companies rarely lack ideas or technology. They struggle to make a clear choice, establish ownership and turn it into something people can use.
Signals without a decision
Customer needs, data and strategic goals exist, but no clear priority has been set.
Strategy without ownership
A direction exists, but nobody owns the path from intent to implementation.
AI without foundations
Tools exist, but trusted data, company context, governance and reusable capabilities do not.
Clarity is not a workshop output. It becomes real when teams can act on it.
From signal to system
Find the signal. Test the bet. Build the system. Make it stick.
Four connected stages. Skipping one usually creates problems later.
Read the reality
Understand customer problems, market shifts, company strengths, available data and operational constraints.
Frame the bets
Turn evidence into hypotheses, compare options and choose where the organization can create a real edge.
Build the capability
Shape the product, workflow or AI-supported system around the outcome, the decisions involved and the organization’s real constraints.
Make it operational
Set ownership, access, human review and measures so the capability can run, learn and improve.
A strategy is useful only when the organization can act on it.
What I build
Not another strategy deck. A capability the organization can use.
Strategic direction and next bets
Which customer problems matter, where the market is moving and what the company is uniquely positioned to build.
Product Management and internal products
Products led from discovery and prioritization through delivery, adoption and improvement, including data products and AI-enabled internal tools.
Data and AI governance operating models
Ownership, decision rights, permissions, human review and measurement that make data and AI reliable and scalable.
Selected work
Evidence across strategy, products and implementation.
View all work
TIMOCOM
Defining company-wide Data Strategy and Governance and putting them into practice
Leading company-wide Data Strategy, Data Governance and data quality, reporting to Board Members, and advancing Microsoft Purview and the Enterprise Data Map.
From company-wide direction to practical implementation in data foundations and AI readiness.
Data Strategy · Data Governance · Data Quality · AI Readiness
Publicis, for a global automotive brand
Global analytics product across 41 markets
A BI product on Microsoft Dynamics, rolled out across 41 markets.
Product rollout and enablement across 41 markets.
Product Management · Data Product · Global Rollout · Adoption
Bringmeister
Modern BI capability from team to architecture
Co-founded the BI team and shaped its product direction and priorities.
BI team, product direction, architecture modernization and one delivery model.
Product Management · Product Leadership · Cross-functional Alignment · Data Architecture
What I believe
Good strategy turns evidence into a choice the organization can execute.
Start with customer needs, business priorities and execution constraints.
Governance should improve decisions, not create paperwork.
Create clear ownership, trusted information and processes teams can use.
AI strategy and AI governance should be designed together.
Define where value is created, who decides, where human review is needed and what evidence is required.
Senior leadership should stay close to the work.
Align leaders and teams, then stay involved through implementation.
Experience
More than 20 years from software engineering to Product and Data.
My career spans software development, data engineering, BI, Product Management, Data Strategy and enterprise transformation. I still stay close to implementation.
Former national-team athlete and Junior World Championship medalist.
An important question, but no clear path yet?
Let’s identify the right bet and turn it into something your organization can execute.