Lean Data‑Driven
Management
16 steps to structured data-driven management
Specialist methodologies abound. For the executive who needs results, control, and repeatability — there are almost none. We built a 16-step guide and added an AI Mentor that accelerates implementation 3‑5x.
70%
of BI projects fail
Due to management, not tech errors
6–12
months typically wasted
On traditional implementation
3–5x
overspend
On unnecessary capabilities
2–4
weeks to first results
With our methodology
Evolution or Extinction
Data-driven management is no longer an advantage. It is about survival.
Competitive Advantage
Data-driven gave leaders an edge over competitors. “We see more” meant more profit.
Resilience & Survival
Those who can't see, lose. Decisions “by intuition” are like flying through fog without instruments.
The problem: most attempts at data-driven management fail. Not because of technology, but because of management mistakes.
Anatomy of Failure: 5 Traps
Why data management projects stall, cost 3x more, and never deliver the expected results
The solution is looking for a problem
Companies build massive data warehouses hoping insights will emerge. Like buying a gym membership and expecting muscles from the purchase.
The perfectionism trap
Trying to create a single perfect version of the truth from day one destroys ROI. While you align reference books, the business moves on.
The 10/90 rule
Success depends 10% on algorithms and 90% on process change: psychology, habits, rituals. But everyone focuses on the 10%.
Death of dashboards
A dashboard not tied to a concrete meeting becomes digital trash in three months. No link to rituals or decision cycles.
No owner
Metrics exist, but nobody knows who is responsible or what to do when numbers are bad. If "everyone" owns it, no one does.
Common denominator
All these mistakes are managerial, not technological. Yet management methodologies for executives are almost nonexistent.
Why Specialist Methodologies Don't Help Executives
DAMA-DMBOK, Data Governance, DWH/BI playbooks — all built for technical teams, not decision-makers
Too engineering-focused
Data architectures, frameworks, terminology. A CEO needs a translator, not a textbook.
Too slow
Months of study, alignment, and preparation. By the time the document is ready, the business context has changed.
Too far from decisions
Focus on infrastructure and tools, not the management cycle: Decision → Metric → Ritual → Action.
Not embedded in processes
No link to rituals and employee KPIs. Result: beautiful diagrams, zero adoption.
A management framework, not a tech manual
Confidence in results first, then data and automation. 16 steps that an executive can walk through with their team without becoming a data-engineering specialist.
What Is It?
A management methodology of 16 steps that starts from risks and decisions, not from data and code.
Steps 1–4
Design & Diagnosis
What are we improving and why, before spending money on development?
Concrete outcomes:
- 1Decision Map — what to improve and why
- 2Launchpad scenario — choose starting point
- 3Metric formulas and calculation rules
- 4Data diagnosis — existence and quality assessment
Steps 5–8
Prototyping & Validation
Proof of value without capital expenditure. Manual prototype in real management rhythm.
Concrete outcomes:
- 1Testable hypothesis — from idea to test
- 2Team and roles — who participates
- 3Manual prototype — Excel/paper in action
- 4Results evaluation — scale or stop
Steps 9–12
Embedding & Industrialization
Turn discovered value into a sustainable system. Analytics becomes part of process.
Concrete outcomes:
- 1Management rituals tied to meetings
- 2Roles and ownership — who answers for what
- 3Industrial automation — manual to code
- 4Lifecycle control — metrics about metrics
Steps 13–16
Scaling & Institutionalization
Multiply success and make data culture self-sustaining.
Concrete outcomes:
- 1Next growth point — where to replicate
- 2Internal case studies and practice leaders
- 3Social scaling through champions
- 4Data office and CDO — institutionalization
Not lectures — results
Each step produces a concrete artifact you can use at work. Not theory — a practical toolkit for management.
The 16 Steps
Click on any step to learn more about its purpose, key insight, and the concrete artifact it produces.
AI Mentor — Your Personal Guide
Walks you through the steps, provides guidance, and helps create artifacts. 3‑5x faster implementation.
Navigation through 16 steps
The AI analyzes your situation and suggests what to do next specifically for you. No generic advice.
Artifact drafts
Decision Map, metric ownership matrix, ritual plans, reporting requirements — the AI creates drafts tailored to your company.
Personalization
Takes into account your industry, business scale, and context. Examples and templates adapt to your reality.
Eliminates getting stuck
Accelerates the transition to action. Instead of weeks of deliberation — a concrete plan in an hour.
How It Works
Create an initiative
Enter your company info, goals, and constraints. More quality input → better recommendations.
Start from Step 1
The AI Mentor gives you personalized recommendations and creates the first draft of the artifact.
Refine and iterate
Discuss with your team, add clarifications. The AI rebuilds documents until you say "good enough."
Move forward
The AI remembers all previous steps. Each next step becomes faster and more precise.
AI Mentor
Your personal methodology guide
Real-Case Library
Built-in library of real cases from data-driven practitioners. The AI suggests relevant fragments for your current step, or you can search for the most relevant moments in experts' stories.
Important clarification
The AI Mentor does not replace an executive or their team. It accelerates and disciplines the process. Decisions are still yours — the AI helps you avoid getting stuck and losing focus.
Who Is This For
And who it is definitely NOT for
This is for you if
Owners & CEOs
Need transparency and control. Tired of decisions "by intuition" and unpredictable results.
C-level Executives (COO, CFO)
With KPIs on profit, growth, and efficiency. Need tools for operational management.
Scalable Businesses
From startup to corporation. Tools differ, but the nature of management mistakes is the same everywhere.
This is NOT for you if
Looking for "a Power BI or SQL course"
Expecting a "magic pill" without changing anything
Not ready to change rituals and accountability
Important: The methodology requires changes in management culture. If you are looking for just a “tool” without changing processes — it won't work.
What Executives Say
Results from beta testing the methodology
“Finally a methodology that speaks the language of business, not IT. In 3 weeks we built a Decision Map and understood where we were losing money.”
Alex M.
CEO, e-commerce | 50+ employees
“The AI Mentor really accelerates things. Instead of months of deliberation, we got a concrete plan in a few days. Already implementing first automations.”
Maria K.
COO, manufacturing | 200+ employees
“The key discovery: you don’t need to buy expensive BI right away. We started with Excel and rituals. Results in 2 weeks, not 6 months.”
Dmitry P.
Owner, retail chain | 15 locations
Note: Names changed per confidentiality agreements. Full case studies available to waitlist members.
Author of the Methodology
Experience from hundreds of implementations, structured into a practical system
Ivan Vakhmyanin
Managing Partner, Visiology
Co-founder and Managing Partner at Visiology, responsible for strategic development
Participated in 100+ complex BI implementation and data-driven culture projects at major companies
Evangelist of data-driven management; lecturer and expert in executive education programs
MBA graduate, SKOLKOVO School of Management
Author of the business novel "KPI"
Why this methodology?
“After years of implementing data-driven management, I became convinced: the key problem is almost always the same — the gap between business value and technical solutions.”
“That is why, combining the experience of top analytics, management, and data-driven experts, we created this methodology. Light enough to start quickly, deep and proven enough to deliver results consistently.”
Frequently Asked Questions
Answers to the most common questions about the methodology
Ready to manage with data,
not drown in it?
Join the waitlist and be the first to get access to the AI Mentor