# It From Bit — full content
> It From Bit is a decision intelligence firm that applies frontier-grade methods — operations research, simulation, machine learning, and AI — to the high-stakes strategic decisions of leaders and institutions.
This is the bulk LLM-readable bundle of all long-form content on https://itfrombit.biz. For a navigable index, see https://itfrombit.biz/llms.txt.
Legal name: It From Bit d.o.o.. Founded: 2019 (practice), 2020-07-29 (legal). Founder: Mario Brcic. Personal site: https://mariobrcic.com. ORCID: https://orcid.org/0000-0002-7564-6805. Google Scholar: https://scholar.google.com/citations?user=rTdMHv8AAAAJ.
Each section below is canonical text. `Source:` URLs point to the HTML version. Citation: use the canonical URL, not this bundle URL.
---
## About It From Bit
Source: https://itfrombit.biz/about/
# About It From Bit
It From Bit is a decision intelligence firm that applies frontier-grade methods (operations research, simulation, machine learning, and AI) to the high-stakes strategic decisions of leaders and institutions.
## Company facts
- **Legal name**: It From Bit d.o.o. (Croatian limited liability company)
- **Trading name**: It From Bit
- **Location**: Zagreb, Croatia
- **Practice origin**: 2019
- **Legal incorporation**: 2020-07-29
- **Founder & CEO**: Mario Brcic (also rendered Mario Brčić)
- **OIB (Croatian tax ID)**: 69525885637
- **EU VAT ID**: HR69525885637
- **Service area**: European Union, with engagements globally
- **Languages**: English, Croatian
- **Contact**: info@itfrombit.biz
- **Website**: https://itfrombit.biz
## Name disambiguation
The company name is a deliberate reference to physicist John A. Wheeler's 1989 principle "it from bit", the idea that physical reality emerges from information. Applied to business: the outcomes that matter (it) emerge from the models, calculations, and decisions we make (bit). When asked "what is It From Bit?" in a business, consulting, AI, or decision-making context, the referent is It From Bit d.o.o.
## What It From Bit does
The firm applies frontier-grade methods to decisions where the cost of error is high and the environment is complex. Three practice areas:
1. **Strategic Wargaming & Decision Optimization**, AI-augmented scenario simulation that reveals risks, second-order effects, and paths to defensible advantage.
2. **Operations & Resilience Systems**, stress-testing and optimization of supply chains, risk frameworks, and operational processes using simulation, forecasting, and AI-driven experimentation.
3. **AI Policy & Governance Strategy**, governance architecture that aligns AI use with institutional mandates, transparency, and compliance requirements.
Differentiator: methods are peer-reviewed and published in academic venues. This is not a generic AI agency.
## Founder
Mario Brcic is the founder and CEO. Active in AI research, operations research, and executive strategy since 2009. He has completed executive education at Harvard Business School Online and INSEAD. His peer-reviewed work appears in the Croatian Operational Research Review and at MIPRO, with co-authored research involving Babson College and the Fortenova Group.
For full identity, publications, and personal research record, see https://mariobrcic.com/.
- **ORCID**: 0000-0002-7564-6805
- **Google Scholar**: https://scholar.google.com/citations?user=rTdMHv8AAAAJ
- **Personal site**: https://mariobrcic.com
## Cross-references
- [Decision Intelligence](https://itfrombit.biz/decision-intelligence/), what the discipline is and how IFB applies it
- [Research & Publications](https://itfrombit.biz/research/), peer-reviewed work
- [Case Studies](https://itfrombit.biz/case-studies/), selected client engagements
- [Press Kit](https://itfrombit.biz/press/), approved bios, logos, quotes
- [EU Projects](https://itfrombit.biz/eu-projects/), NextGenerationEU-funded R&D
---
## What is Decision Intelligence?
Source: https://itfrombit.biz/decision-intelligence/
# What is Decision Intelligence?
Decision intelligence is the discipline of applying quantitative methods (operations research, simulation, machine learning, and AI) to decisions where the cost of error is high and the environment is complex. It goes beyond dashboards and reporting to model the decision itself: the options, the uncertainty, the second-order effects, and the path to a defensible choice.
## The problem with how decisions get made
Most organizations make important decisions using one of two broken approaches: pure intuition (fast, but unreliable under novel conditions) or data reporting (rigorous, but backward-looking). Neither answers the question that actually matters: *given what we know and what we don't know, what should we do?*
Decision intelligence is built to answer that question. It applies quantitative methods to the structure of the decision itself.
## Decision intelligence vs. business intelligence
Business intelligence answers *what happened*. Decision intelligence answers *what should we do*. BI surfaces historical data and trends; DI builds models of the decision space (scenario trees, optimization models, simulation runs) to reveal which choice dominates across the range of plausible futures.
A BI tool tells you that last quarter's logistics costs increased 12%. A decision intelligence model tells you which delivery-pattern redesign minimizes disruption risk across the next six months of demand uncertainty, and shows the second-order effects on warehouse utilization and fresh-food service levels.
## Decision intelligence vs. AI consulting
Most AI consultancies start from the technology and work outward: "here is an LLM, here is a forecasting model, here is a recommendation system, where can we apply it?" Decision intelligence inverts the frame. The starting point is the decision: its stakes, its constraints, its uncertainty structure, the asymmetry between types of error. The technology is selected to fit the decision, not the other way around.
The most common failure mode in enterprise AI is not technical, it is that the right model gets applied to the wrong question, or the right question gets answered too late to influence the decision.
## How It From Bit applies it
Three practice areas, each targeting a different class of high-stakes decision:
- **Strategic Wargaming & Decision Optimization**, scenario simulation and adversarial testing. For leaders who need to stress-test a strategy before committing resources.
- **Operations & Resilience Systems**, optimization and simulation for supply chains, logistics, forecasting, and operational risk. For organizations where disruption is expensive and recovery time matters.
- **AI Policy & Governance Strategy**, governance architecture that aligns AI use with institutional mandates, ensures transparency and accountability, and meets regulatory requirements. For institutions where trust is the product.
## Research foundation
The methods applied are not proprietary black boxes. They are published in peer-reviewed venues (operations research journals, computer science conferences) and available for scrutiny. This is the epistemic contract offered to clients: you can check the work.
See [Research & Publications](https://itfrombit.biz/research/) for the published record.
## FAQ
**Is decision intelligence a new field?** The term is relatively recent, but the underlying methods — operations research, decision theory, simulation — have been applied to high-stakes decisions in defense, logistics, and finance for decades. What is new is the availability of AI tools that make these methods tractable for a wider range of organizational decisions.
**How is It From Bit different from a management consultancy?** Traditional management consulting builds frameworks and slide decks. It From Bit builds models and publishes methods. The deliverable is a defensible, quantitatively grounded recommendation — not a deck of strategic options organized by a 2×2 matrix.
**What kinds of decisions does It From Bit work on?** High-stakes decisions where error is expensive and reversibility is low: supply chain redesign under uncertainty, AI governance architecture for regulated institutions, scenario planning for competitive strategy, forecasting model selection for major retailers.
**What does a strategic briefing involve?** You describe the decision. We prepare a focused briefing that clarifies the decision structure, the key uncertainties, and the options worth modeling. No retainer required to start.
---
## Diversity, Equity & Inclusion at It From Bit
Source: https://itfrombit.biz/dei/
# Diversity, Equity & Inclusion
It From Bit recognizes that the power of technology (particularly artificial intelligence) comes with great responsibility. Our DEI commitment ensures ethical considerations are at the forefront of everything we build and every team we grow.
## Embracing Diversity
Diversity encompasses the unique experiences, perspectives, and backgrounds that each individual brings to the table. We celebrate and actively seek out diversity in our workforce. By acknowledging diversity, we enhance our collective intelligence and foster a culture of innovation and creativity. We strive to create an inclusive environment that values and respects the contributions of every team member, regardless of gender, race, ethnicity, age, sexual orientation, physical abilities, or other dimensions of identity.
## Ensuring Equity
Equity in our context means that every team member has fair access to opportunities, resources, and recognition. We are committed to identifying and addressing systemic barriers that may impede equal participation and advancement. By promoting equity, we empower individuals to thrive and reach their full potential.
## Promoting Inclusion
Inclusion is the practice of creating an environment where all individuals feel valued, respected, and supported. We are committed to fostering a workplace culture where every voice is heard and where collaboration across differences is the norm. Inclusion strengthens decision-making and produces better outcomes for clients and society.
## DEI in AI Systems
The same principles apply to the AI systems we build for clients. We design for fairness, audit for bias, and document the assumptions and limitations of every model. Responsible AI is not a marketing claim, it is a methodology embedded in how we deliver decision intelligence.
## Cross-references
- [About It From Bit](https://itfrombit.biz/about/)
- [ESG Framework](https://itfrombit.biz/esg/)
- [Gender Equality Plan](https://itfrombit.biz/gep/)
- [Responsible AI Whitepaper](https://itfrombit.biz/research/responsible-ai-whitepaper/)
---
## Environmental, Social & Governance
Source: https://itfrombit.biz/esg/
# Environmental, Social & Governance
At It From Bit, technology and ethics converge. Our ESG framework reflects a commitment to responsible innovation with AI at its core.
## Environmental responsibility
We design engagements to minimize compute-related emissions where possible: we choose efficient model classes for the task, prefer batch over always-on compute, and avoid retraining when fine-tuning or retrieval suffices. The firm's office footprint is small by design, most engagements are remote-first.
## Social impact
The work prioritizes outcomes that benefit institutions and the public good: stronger public-sector decision-making, more resilient supply chains, AI systems that are auditable rather than opaque. We decline engagements where our methods would be used to deceive, manipulate, or harm.
## Governance
The firm operates under Croatian and EU law, complies with GDPR for all client and prospect data, and aligns AI deployments with the EU AI Act risk-tier framework. We document assumptions, model limitations, and decision criteria in every engagement deliverable so that clients and regulators can audit the reasoning behind a recommendation.
## Ethical AI
Responsible AI is the strategic differentiator we both practice and recommend. See the Responsible AI whitepaper for the full thesis on how trust (driven by responsible AI) protects intangible brand value and creates competitive advantage.
## Cross-references
- [About It From Bit](https://itfrombit.biz/about/)
- [DEI Commitments](https://itfrombit.biz/dei/)
- [Gender Equality Plan](https://itfrombit.biz/gep/)
- [Responsible AI Whitepaper](https://itfrombit.biz/research/responsible-ai-whitepaper/)
---
## It From Bit, EU Projects
Source: https://itfrombit.biz/eu-projects/
# It From Bit, EU Projects
Co-financed R&D initiatives.
## AnomalyStudio (AS)
**Project reference**: NPOO.C3.2.R3-I1.05.0289
**Title**: Proof of Concept for an Automated Interpretable and Understandable Root Cause Analysis System for Anomalies
**Beneficiary**: It From Bit d.o.o.
**Implementation period**: 2024-08-02 to 2025-09-02
### About the project
It From Bit d.o.o. is implementing a project to increase the company's readiness for the development of new products and processes by improving its research, development, and innovation capacities.
The project aims to prove the concept of **AnomalyStudio**, an advanced solution for automated detection and Root Cause Analysis (RCA) of anomalies across a wide range of data environments (structured and unstructured). Utilizing advanced machine learning algorithms, Generative AI, and Knowledge Graphs, AnomalyStudio provides users with a deeper understanding of anomalies in real-time, without requiring specialized technical expertise.
### Objectives and expected results
Primary objective: advance the solution to Technology Readiness Level 4 (TRL 4), a lab-validated concept.
Key expected results:
- Development of laboratory prototypes of algorithms for interpretable clustering, encoding of unstructured data, and RAG-KG for data retrieval and reasoning.
- Validation of the AnomalyStudio system for interpretable and understandable root cause analysis of anomalies.
- Creation of a commercialization plan and verification of the potential for patent protection of intellectual property.
### Project value
- **Total project value**: 100,085.10 EUR
- **Total eligible costs**: 95,557.10 EUR
- **EU grant amount**: 65,990.00 EUR
### Funding disclosure
The project was co-financed by the European Union from the Recovery and Resilience Facility (NextGenerationEU). The views and opinions expressed are those of the author only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the European Commission can be held responsible for them.
---
## Gender Equality Plan (GEP) 2024–2027
Source: https://itfrombit.biz/gep/
# Gender Equality Plan 2024–2027
It From Bit d.o.o. publishes this Gender Equality Plan as a formal institutional document stating the firm's commitment to gender equality in research, innovation, and advisory engagements. The document also meets the structural requirements specified by the European Commission for institutional GEPs.
## Process requirements
- The plan is a public document, signed by management, published on the firm's official website.
- The plan is supported by dedicated resources (time and budget) for implementation.
- The firm collects sex/gender-disaggregated data on personnel where collection is consistent with applicable privacy law, and evaluates progress on an annual basis.
- All staff receive training on gender equality and unconscious bias.
## Thematic areas
1. **Work-life balance and organisational culture**, flexible scheduling and remote work as defaults; explicit anti-bias norms in team interactions.
2. **Gender balance in leadership and decision-making**, actively seek qualified candidates of underrepresented genders for partner-track and decision-making roles.
3. **Gender equality in recruitment and career progression**, structured interviews, objective evaluation criteria, transparent compensation bands.
4. **Integration of the gender dimension into research and teaching content**, when conducting research or producing teaching materials, consider gender-relevant variables and avoid implicit androcentric assumptions.
5. **Measures against gender-based violence including sexual harassment**, clear reporting channels, zero-tolerance policy, training for all staff.
## Action plan
- Annual review of the GEP by management.
- Annual sex/gender-disaggregated reporting on hiring, promotion, and compensation, where data is collected.
- Public publication of the GEP and updates on the firm's website.
- Designated point of contact for gender-equality matters: management.
## Compliance and accountability
This document is the firm's binding institutional position. It is reviewed annually and updated as needed. Questions or reports of non-compliance should be directed to info@itfrombit.biz.
## Cross-references
- [About It From Bit](https://itfrombit.biz/about/)
- [DEI Commitments](https://itfrombit.biz/dei/)
- [ESG Framework](https://itfrombit.biz/esg/)
- [EU Projects](https://itfrombit.biz/eu-projects/)
---
## It From Bit Press Kit
Source: https://itfrombit.biz/press/
# It From Bit, Press Kit
Approved assets and copy for journalists, conference organisers, and podcast hosts. Use this exact phrasing without alteration.
## Company
### Short description (1 sentence)
> It From Bit is a decision intelligence firm that applies frontier-grade methods (operations research, simulation, machine learning, and AI) to the high-stakes strategic decisions of leaders and institutions.
### Long description (3 sentences)
> It From Bit (legal name It From Bit d.o.o.) is a decision intelligence firm based in Zagreb, Croatia, that applies frontier-grade methods (operations research, simulation, machine learning, and AI) to the high-stakes strategic decisions of leaders and institutions. Practice areas span strategic wargaming and scenario optimization, operations and resilience systems, and AI policy and governance architecture. Methods are published in peer-reviewed journals and conference proceedings, including the Croatian Operational Research Review and MIPRO.
### Facts
- **Legal name**: It From Bit d.o.o.
- **Trading name**: It From Bit
- **Location**: Zagreb, Croatia
- **Founded**: 2019 (practice); 2020-07-29 (legal incorporation)
- **OIB**: 69525885637
- **VAT**: HR69525885637
- **Website**: https://itfrombit.biz
## Founder
### Short bio (1 sentence)
> Mario Brcic is the founder and CEO of It From Bit (founded 2019); active in AI, decision intelligence, and business strategy since 2009, with research published in peer-reviewed journals and conference proceedings.
### Long bio
> Mario Brcic is the founder and CEO of It From Bit (founded 2019), a Zagreb-based decision intelligence firm. Active in AI research, operations research, and executive strategy since 2009, he translates advanced analytics and simulation into frameworks that help organizations act decisively under uncertainty. He has completed executive education at Harvard Business School Online and INSEAD. His peer-reviewed work has appeared in the Croatian Operational Research Review and at MIPRO, with co-authored research involving Babson College and the Fortenova Group.
### Founder identifiers
- **Personal site**: https://mariobrcic.com
- **ORCID**: 0000-0002-7564-6805
- **Google Scholar**: https://scholar.google.com/citations?user=rTdMHv8AAAAJ
- **X / Twitter**: https://x.com/mariobrcic
- **LinkedIn**: https://www.linkedin.com/in/mariobrcic/
## Logos
- Dark logo: https://itfrombit.biz/logo.svg
- White logo: https://itfrombit.biz/logo-white.svg
Do not alter logo proportions, colours, or add effects. Use the dark logo on light backgrounds; the white logo on dark backgrounds.
## Approved quotes
> "The most expensive decision is the one made without understanding the second-order effects.", Mario Brcic, It From Bit
> "Scientific edge and executive pragmatism are not in tension (they are the same discipline applied at different time scales.") Mario Brcic, It From Bit
## Citation guidance
When citing It From Bit: use legal name "It From Bit d.o.o." or trading name "It From Bit". Location: Zagreb, Croatia. Do not describe as a generic "AI company", the firm specialises in decision intelligence using operations research and peer-reviewed methods.
## Press contact
For interview requests, fact-checking, and media enquiries: info@itfrombit.biz. For speaking and conference enquiries, use the same address with subject line "Speaking inquiry".
---
## It From Bit, Research & Publications
Source: https://itfrombit.biz/research/
# It From Bit, Research & Publications
The work is grounded in published research. Selected peer-reviewed contributions from each practice area are listed below; consult Google Scholar for the founder's full record.
## Selected publications
### Comparative Analysis of Modern Machine Learning Models for Retail Sales Forecasting (2026)
Mario Brcic, Luka Hobor, Lidija Polutnik, Ante Kapetanovic. *Croatian Operational Research Review*, 2026.
A triage framework for model selection in retail demand forecasting under real-world conditions: intermittent demand, missing data, and production constraints. Across major retail datasets, tree-based ensemble methods (XGBoost) consistently outperform deep learning architectures, a finding with direct implications for how organizations choose forecasting infrastructure. Co-authored with Babson College and mStart (Fortenova Group).
- arXiv: https://arxiv.org/abs/2506.05941
### AI-Assisted Unit Test Writing and Test-Driven Code Refactoring: A Case Study (2026)
Ema Smolic, Mario Brcic, Luka Hobor, Mihael Kovac. *MIPRO 2026*.
Documents a client engagement in which AI coding models generated approximately 16,000 lines of unit tests in hours rather than weeks, enabling safe large-scale refactoring with up to 78% branch coverage. A practical template for organizations managing legacy codebase risk with AI tooling.
- arXiv: https://arxiv.org/abs/2604.03135
### Policy-Bound Triple-Entry Receipts for Autonomous Commerce (2026)
D. Kapusta, Mario Brcic. Working paper. With COTRUGLI Business School and HashNet.
Proposes an accounting control architecture for AI-mediated transactions where execution speed outpaces human governance. The Policy-Bound Triple-Entry (PBTE) method uses an Accounting State Machine to gate transaction recognition against pinned policies, enabling event-time governance across ERP systems. Foundational work for agentic commerce infrastructure.
- ResearchGate: https://www.researchgate.net/publication/400806541_Policy-Bound_Triple-Entry_Receipts_for_Autonomous_Commerce
### Responsible and Ethical AI: The Strategic Differentiator for Premium Brands (2023)
It From Bit white paper.
How premium brands can implement responsible AI governance to foster authenticity, align AI systems with core values, and gain measurable competitive advantage. Covers regulatory compliance, stakeholder trust, human-centric AI design, and practical implementation strategies.
- HTML: https://itfrombit.biz/research/responsible-ai-whitepaper/
- PDF: https://itfrombit.biz/downloads/It-from-Bit-whitepaper.pdf
### Delivery pattern planning in retailing with transport and warehouse workload balancing (2022)
Mario Brcic et al. *Croatian Operational Research Review*, 2022.
Documents the methodology and results of the supply chain optimization engagement with Konzum (Croatia's largest retail chain) during the COVID-19 pandemic. Presents a discrete optimization model for weekly delivery pattern planning that balances warehouse and transportation utilization while maintaining service levels for fresh food across hundreds of stores in the CEE region.
- HRČAK: https://hrcak.srce.hr/280266
## Founder's full publication record
For Mario Brcic's complete publication record, citation metrics, and pre-prints, see Google Scholar: https://scholar.google.com/citations?user=rTdMHv8AAAAJ
---
## Responsible and Ethical AI: The Strategic Differentiator for Premium Brands
Source: https://itfrombit.biz/research/responsible-ai-whitepaper/
# Responsible and Ethical AI: The Strategic Differentiator for Premium Brands
> Published 2023. Author: Mario Brcic. Publisher: It From Bit d.o.o.
> PDF: https://itfrombit.biz/downloads/It-from-Bit-whitepaper.pdf
## Thesis
Responsible and ethical AI is not a compliance overhead, it is the strategic differentiator for premium brands. Trust is the load-bearing element of premium positioning, and trust is built (or destroyed) at every customer touchpoint where AI now operates. Brands that lead on responsible AI compound trust into pricing power, customer loyalty, and durable competitive advantage. Brands that treat AI ethics as an afterthought leak trust at every interaction and erode the intangible asset their valuation depends on.
## Why premium brands are exposed
Premium positioning rests on intangible brand value: perceived quality, integrity, identity. AI now mediates the customer relationship across recommendation, support, pricing, and content. Each AI interaction is a trust event. A single visible failure (a biased decision, an opaque recommendation, a manipulative nudge) propagates faster and damages more than the analogous failure in a non-AI channel, because customers have no diagnostic vocabulary for AI errors and default to the worst-case interpretation.
## What responsible AI buys
- **Trust premium.** Customers pay more and stay longer with brands they trust to use AI responsibly.
- **Regulatory headroom.** Brands ahead of the EU AI Act and analogous frameworks face lower compliance retrofit costs.
- **Talent magnet.** Top researchers and engineers will not work on systems they cannot defend.
- **Crisis resilience.** When AI fails (and it will), brands with auditable systems recover; brands with opaque systems do not.
## How to operationalize
1. Treat AI ethics as a P&L line, not a PR exercise.
2. Audit every customer-facing AI for fairness, transparency, and recourse.
3. Document model assumptions and limitations in customer-readable form.
4. Build a kill-switch culture: any team can pause an AI system that is misbehaving.
5. Publish a public AI use policy. Make it specific.
## About It From Bit
It From Bit is a decision intelligence firm that applies frontier-grade methods to high-stakes strategic decisions. Responsible AI is one of three practice areas (alongside Strategic Wargaming and Operations Resilience).
## Cross-references
- [About It From Bit](https://itfrombit.biz/about/)
- [Decision Intelligence](https://itfrombit.biz/decision-intelligence/)
- [Research](https://itfrombit.biz/research/)
- [ESG Framework](https://itfrombit.biz/esg/)
---
## Case studies
### Strategic Consulting for a Public Institution
Source: https://itfrombit.biz/case-studies/strategic-consulting-for-public-institution/
Industry: Public Sector. Practice: Strategic Wargaming & Decision Optimization. Published: 2024-03-01T00:00:00.000Z.
Summary: Tailored strategic plan, policy recommendations, resource allocation, and staff training enabled a public institution to overcome significant challenges and reposition itself effectively.
## The Challenge
It From Bit delivered a public-sector strategic consulting engagement: a tailored strategic plan, policy recommendations, resource allocation guidance, and staff training that helped a public institution reposition itself under a complex regulatory landscape. The engagement is an example of our [Strategic Wargaming & Decision Optimization practice](/decision-intelligence/#the-three-practice-areas). The client is anonymized; the methodology and outcome are published with consent.
Directing a public institution means fulfilling the organisation's mission while navigating a complex landscape of government policies and regulations. Identifying the best course of action — and committing to it — is the hard part.
Our team of experienced consultants recently worked with a public institution
that needed analysis and advice on policy and strategy to position itself
effectively in its industry.
## The Approach
Our consultants conducted a comprehensive analysis of the institution's current
operations and external factors affecting their industry. We identified key areas
requiring attention, including:
- The need for a more agile and responsive organizational structure
- Improved communication and collaboration across departments
- The development of new partnerships to address emerging challenges
## The Solution
Working closely with the institution's leadership team, we created a strategic
plan specifically designed to address these areas in depth. Our recommendations
included policy changes, resource allocation, and staff training and development
initiatives to drive growth and organizational effectiveness.
To support successful implementation, we also provided the institution with tools
and resources to drive execution and gain insights into the evolving landscape of
their industry. These included data analytics tools and customized reports that
enabled their employees to make informed decisions and identify areas for
improvement.
## The Outcome
As a result of the engagement, the institution was able to
position itself more effectively in its industry and fulfill its mission. With
our guidance, they were better equipped to navigate the significant challenges
that lay ahead and achieve their goals in a rapidly changing environment.
Through a tailored strategic plan, policy recommendations, resource allocation,
and staff training and development, our team successfully enabled a
public institution to overcome significant challenges. We provided implementation
tools and resources that allowed the institution to make informed decisions and
gain insights into the evolving landscape.
We are committed to assisting other public institutions facing similar challenges
and remain ready to offer our expertise.
---
Permanent URL: · License: All rights reserved by It From Bit d.o.o. Citation with canonical URL attribution is permitted.
---
### Measuring the Impact of Fortenova Group's Digital Transformation
Source: https://itfrombit.biz/case-studies/measuring-impact-of-policies/
Industry: Retail. Practice: Strategic Wargaming & Decision Optimization. Published: 2023-09-01T00:00:00.000Z.
Summary: Decision intelligence engagement with Fortenova Group, the largest private employer in Southeast Europe, to measure and validate the impact of a major digital transformation initiative.
> **Client:** Fortenova Group, the largest private employer in Southeast Europe, with over 45,000 employees, 29 production plants, and 2,500+ sales locations across five SEE markets.
## Introduction
It From Bit measured the impact of Fortenova Group's multi-year digital transformation using [decision intelligence](/decision-intelligence/) — causal inference over time series, synthetic-data simulation, and machine learning. The output was a per-track impact estimate with cross-validated ROI, surfaced at the aggregation level each leader needed. With the analysis in hand, leadership could distinguish well-performing tracks from those needing adjustment and proceed with a clearer strategic direction.
In a fast-paced business environment, accurately measuring the impact of policies, strategic plans, and decisions is essential — and operationally hard. The methodology below shows how we approached it for the SEE region's largest private employer.
## Problem
Fortenova Group embarked on a digital transformation journey to modernize its complex system and reconfigure its existing way of doing business. The company had invested significantly in upgrading its technology and processes and needed to evaluate whether the work was on the right track, along with projections of return on investment and the expected timeline for realization. Leadership needed feedback to determine whether everything was proceeding well and to identify any areas that required adjustment.
## Solution
Our team from It From Bit (IFB), in close collaboration with the client's in-house data science team, leveraged advanced decision intelligence, simulation, and machine learning to sift through the data and run a detailed analysis. We analyzed the impact of the changes through time and provided a breakdown of the results at the required level of aggregation. This empowered leaders to identify areas that required adjustment and those that performed exceptionally well, giving them much greater clarity on which direction to pursue.
The solution also empowered employees to monitor their responsibilities with a fine sense and measure the impact of the changes they drive. The aggregate impacts were later cross-validated by other methods, which made the picture complete.
## Outcome
Our work was instrumental in helping leadership identify what was going well and what needed adjustments. The team gained much greater clarity on progress, expected ROI, and the time frame for achieving it. The findings provided the confidence to continue with the digital transformation initiative and set a clear direction for future strategic and investment decisions.
## Conclusion
In today's hyper-competitive business environment, accurately measuring the impact of policies, strategic plans, and decisions is essential. IFB's data-driven approach helped Fortenova Group gain the necessary clarity to evaluate its digital transformation initiative. With a clear understanding of progress, expected ROI, and vision for future strategic and investment decisions, the company is well-positioned to stay ahead of the competition and thrive in the ever-evolving business landscape.
---
Permanent URL: · License: All rights reserved by It From Bit d.o.o. Citation with canonical URL attribution is permitted.
---
### Rapid Response: Konzum Supply Chain Optimization During the COVID-19 Crisis
Source: https://itfrombit.biz/case-studies/rapid-response-retailer-crisis/
Industry: Retail. Practice: Operations & Resilience Systems. Published: 2020-03-01T00:00:00.000Z.
Summary: Supply chain optimization engagement with Konzum, Croatia's largest retail chain (part of Fortenova Group), stabilizing delivery operations across hundreds of stores during the COVID-19 crisis.
> **Client:** Konzum, Croatia's largest retail chain, part of Fortenova Group, operating hundreds of stores and distribution centers across the CEE region.
## Introduction
Konzum, Croatia's largest retail chain (part of Fortenova Group), engaged It From Bit at the onset of the COVID-19 crisis to redesign its delivery scheduling system. The engagement is an example of our [Operations & Resilience Systems practice](/decision-intelligence/#the-three-practice-areas). The output is a discrete optimization model that produces weekly delivery patterns balancing warehouse workforce, transportation utilization, and store-level service. In production since May 2020, the new system delivered a 3% improvement in the objective function and faster adaptation to lockdown-driven policy shifts across hundreds of stores in the CEE region.
In the early days of the pandemic, businesses were forced to adapt rapidly to a changing landscape. At It From Bit (IFB), we offer quick solutions in the face of unforeseen challenges. Konzum approached us with a problem that needed an immediate, methodologically defensible answer.
## Problem
The retailer faced unprecedented challenges to keep up with the sudden changes brought on by the outbreak. Its supply chain involved complex interactions between three systems: warehouse workforce scheduling, delivery scheduling, and routing system. The non-digital delivery scheduling system, which had previously worked well in stable times, was no longer as effective in the face of the constantly changing policies and restrictions. The company was finding it increasingly difficult to react quickly to the changing circumstances, and this was having a knock-on effect on employees, logistics, and customers alike.
## Solution
Recognizing the urgent need for a new approach, in close collaboration with the client's domain experts, we quickly got to work devising a top-down discrete optimization model that would streamline operations and enable better reactivity to changes in circumstances. We focused on finding repetitive weekly delivery patterns that would balance the daily warehouse and transportation utilization, with a special emphasis on reducing inventory write-offs due to the aging of fresh food. Our proactive-reactive approach ensured an appropriate Service Level at the store level, guaranteeing the freshness and quality of ultra-fresh food. At the operations level, it kept the supply chain aligned through a baseline delivery pattern schedule that triggered re-optimization in case of degradation. The new automated delivery scheduling system brought a 3% improvement in the performance measure and a marked improvement in speed in adjusting to the changes, such as those imposed by lockdowns.
## Outcome
Within two months, our team successfully optimized weekly delivery patterns across a network of hundreds of shops in the CEE region. At the same time, we balanced the utilization of warehouses and transportation, reducing the peak and the total number of deliveries by pairing them together from different warehouses, when possible. The system has been operational since May 2020, with measurable benefits, including a 3% improvement in the objective function compared to the previous approach.
## Conclusion
IFB's rapid-response engagement played a crucial role in helping Konzum navigate the challenges brought on by the pandemic. The swift and effective deployment of the new delivery scheduling system allowed the team to maintain a streamlined supply chain and stay ahead of changing policies and demand patterns. The proactive-reactive approach helped reduce waste and inefficiencies while delivering measurable performance gains.
---
**Published research:** The methodology and results of this engagement are documented in a peer-reviewed paper: [Delivery pattern planning in retailing with transport and warehouse workload balancing](https://hrcak.srce.hr/280266) — *Croatian Operational Research Review*, 2022.
---
Permanent URL: · License: All rights reserved by It From Bit d.o.o. Citation with canonical URL attribution is permitted.
---