SUCCESS STORIES

Beyond reporting.
Measurable transformation.

iatro does more than turn data into reports. It simplifies complex data collection, makes organizational capacity visible and helps institutions implement their own transformation roadmaps.

ScaleDistributed public-sector data management across 200+ units and an architecture adaptable to different organization types
AccessibilityGuided data collection and reporting even with limited initial expertise
VerifiabilityA workflow extending from carbon calculation and reporting to outputs taken through verification processes
TransformationTurning analysis outputs into operational improvement and digital transformation actions

Challenge: organizational complexity, not the standard itself

GRI Standards define the reporting framework, but they do not provide a ready-made data collection model for the multi-layered structures, diverse responsibilities and public-sector processes of municipalities. At metropolitan scale, the real challenge is collecting the right data from the right unit, in the right scope and format.

Under a manual approach, this structure means many files, emails, meetings, reminders, data checks and repeated coordination tasks.

Bring the data request to the right user—not the full standard

iatro mapped responsibilities and activity areas within the organization to GRI requirements and distributed questions and data requests to the relevant units. Instead of seeing the full standards set, participants received only the questions, tables, numerical fields, options and explanations related to their own activities.

“Without requiring every user to be a GRI expert, structured data can be produced at source within the organization.”

Distributed, parallel data collection across 200+ units

Data collection from more than 200 units and departments within İzmir Metropolitan Municipality was managed in a distributed model. Instead of sequential tasks waiting on one another, different units could enter their data at the same time.

Incoming information was incorporated into the reporting structure while data collection was still underway, so data collection and report construction were no longer two completely separate phases.

Outcome: approximately 90% less operational reporting effort

Compared with the previous manual approach, the operational effort required to distribute data requests, follow up, consolidate responses and transfer them into the reporting structure was assessed to be approximately 90% lower with iatro.

When parallel activities by different users were normalized as a single linear workload, total active operational processing on the platform—from the start of data collection through reporting—was approximately three hours.

Making deep GRI knowledge unnecessary as a prerequisite

For the İzBB sustainability team, the process became easier to manage with less coordination burden than the previous manual cycle. Distributing question structures and data types by activity area allowed participants to contribute data without needing detailed knowledge of the technical structure of the standards.

A scalable structure from one municipality to a municipal ecosystem

In the 2026 implementation, reporting scope was limited to the core municipality; subsidiaries and affiliated organizations were outside the scope. The experience demonstrated that the same architecture can be extended hierarchically from the parent institution to affiliates, subsidiaries and their sub-units.

≈ 3 weeksProject period from kickoff through completion of data collection and reporting
FLAGSHIP MUNICIPAL CASE · GRI + CARBON

Bornova Municipality — integrated reporting with limited initial expertise

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At Bornova Municipality, GRI reporting and carbon footprint work were carried out within the same project flow despite limited initial sustainability expertise. iatro’s guided data structure enabled participants to produce data directly for their own activity areas.

01 · Starting pointLimited sustainability expertise
02 · iatroGuided data collection + GRI + carbon
03 · OutcomeIntegrated process completed in approximately three weeks
One platform, two workstreamsGRI reporting and carbon footprint work were managed together in the same project period.
Low knowledge barrierExpert-level knowledge of the standards was not a prerequisite for participants.
Data across the organizationCollecting data at source and from relevant activity units improved visibility of the actual situation.
Faster coordinationRouting question sets by activity area reduced coordination complexity.
FLAGSHIP TRANSFORMATION CASE · KYA + DMA

Baymob Design — from analysis to measurable operational improvement

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The Corporate Structure Analysis and Digital Maturity Assessment carried out under a South Marmara Development Agency technical assistance project did more than produce a current-state report. Recommendations, action plans and the strategic roadmap were implemented as lean management and digital transformation initiatives.

01 · AnalysisCorporate Structure + Digital Maturity
02 · Implementation5S · OEE · Preventive maintenance · Capacity planning
03 · TransformationDigitalization of processes from design through final customer use
+68%Improvement in committed delivery performance
+43%Increase in production process performance

Performance rates are based on internal comparisons within the starting conditions and implementation period of the Baymob project.

Analysis → ActionA measurable transformation case in which iatro outputs were carried into operations through lean management tools and digital transformation applications
EVIDENCE 03 · VERIFIABLE OUTPUT

Lowering the knowledge barrier in carbon management.

The Aykim Aluminium and Mirza Textile cases show that the same core approach can work across sectors and starting points: collect data in the right structure, calculate it and move it into verification without leaving the user alone with complex methodology.

ALUMINIUM · CARBON

Aykim Aluminium — managing carbon with limited starting expertise

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Despite limited carbon management expertise, the organization collected emissions data and managed its carbon process through iatro, producing a report that went through a verification process. The user experience specifically indicated that managing the process on the platform did not present significant usability difficulty.

Limited carbon expertise→Guided data entry→Calculation + reporting→Verification
Report taken through verificationAbility for an internal corporate user to manage the carbon process on the platform
TEXTILES · CARBON

Mirza Textile — from short training to in-house reporting

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After a short, application-focused training, the company was able to manage its own carbon calculation and reporting through iatro. The resulting report went through a verification process.

Short training→In-house use→Carbon calculation→Verification
Internal capabilityPractical evidence that reporting can become an internal capability rather than an activity dependent only on external expertise
Taken together, these two cases show that iatro’s value is not only calculation; it turns methodology into manageable data steps and makes it easier for the organization to manage its own process. During independent verification, an authorized verifier can use the iatro verifier workspace to review the report, supporting evidence and process records and manage findings through a traceable workflow. iatro provides the supporting digital infrastructure; the verification opinion remains with the independent verifier.
EVIDENCE 04 · SCALABILITY

Same core.
Different organizational realities.

A metropolitan municipality, a district municipality and a multi-company program across different sectors do not share the same structure. iatro’s scalability comes from adapting data and analysis flows to each organization rather than forcing the same assessment model onto everyone.

Metropolitan municipalityİzBB · 200+ units
District municipalityTorbalı · GRI adapted to organization scale
Multi-organization / sectorMARKA · Sakarya MÜSİAD companies
DISTRICT MUNICIPALITY · GRI

Torbalı Municipality — the same reporting capability in a different municipal structure

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Although the district municipality’s organizational structure and data ownership differ from those of a metropolitan municipality, the same iatro platform architecture was adapted to its scale to manage GRI data collection and reporting.

Different organization scale→Unit mapping→Distributed data→GRI reporting
Scale-independent architectureAbility to adapt the methodology used at metropolitan scale to a district municipality
MARKA · SAKARYA MÜSİAD

A shared analysis architecture across sectors and maturity levels

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In a project financed by the East Marmara Development Agency, companies in wholesale trade, building materials, textiles, food, machinery, agricultural machinery, apparel and other fields were assessed for institutional capacity and competitiveness. Businesses with very limited digital infrastructure and those with more advanced systems were analyzed within the same program.

Multi-sector→Different maturity levels→Corporate analysis→Tailored roadmap
Not a one-size-fits-all resultEach company identified its own improvement areas, priorities and development roadmap

Four components of scalability

For iatro, scalability is not simply about adding more users. It is the ability to reconfigure organization, data, question sets and reporting scope around the institution.

OrganizationParent organization, unit, sub-unit, subsidiary or different business structures
Data ownershipDetermine who should provide which data based on activity area
Knowledge levelDifferent maturity levels, from first-time users to organizations with advanced digital infrastructure
OutputReports, action plans and roadmaps tailored to organizational needs rather than a standard output

What problem does your organization’s success story start with?

We can assess your current position in GRI, carbon management, corporate structure or digital maturity and show how the data collection and reporting model can be adapted to your organization.

Request a Demo  →
EVIDENCE / METRIC METHODOLOGY

How do we
measure the numbers?

We present success-story metrics within a common methodology framework. For each indicator, the measured variable, comparison basis, scope and interpretation are defined so the measurement basis behind time, effort and performance outcomes is visible.

İzBB · Effort≈ 90%

Lower operational reporting effort

MetricOperational workload required for data requests, follow-up, consolidation and reporting preparation.
Comparison basisİzBB’s previous manual reporting workflow compared with the iatro-supported process.
ScopeIdentifying data owners, distribution, follow-up, data structuring and reporting flow.
InterpretationThe indicator expresses the operational effort difference between the manual reporting approach and the iatro-supported process.
İzBB · Active workload≈ 3 hours

Normalized active processing workload

MetricNormalized total workload of active operational processes on the platform.
Comparison basisParallel activities by different users normalized into a single linear workload.
ScopePlatform activities from the start of data collection through reporting.
InterpretationThe indicator represents normalized total active processing workload across parallel activities, independently from calendar elapsed time.
Bornova · Duration≈ 3 weeks

From project kickoff to reporting

MetricPeriod from project kickoff through completion of data collection and reporting.
Comparison basisProject timeline for Bornova Municipality’s GRI + carbon work.
ScopeGRI reporting and carbon footprint work carried out within the same project period.
InterpretationThe indicator represents the approximate calendar period from project kickoff through completion of data collection and reporting.
Baymob · Delivery+68%

Delivery performance improvement

MetricImprovement in committed product delivery performance.
Comparison basisInternal performance comparison before the project and after implementation.
ScopePeriod in which lean management and digital transformation applications were monitored after KYA + DMA.
InterpretationThe outcome was measured within the starting conditions and implementation period of the Baymob project.
Baymob · Production+43%

Production process performance increase

MetricInternally measured increase in production process performance.
Comparison basisComparison between pre-project performance values and post-implementation results.
ScopePeriod in which 5S, OEE, preventive maintenance, capacity planning and digitalization steps were implemented.
InterpretationThe outcome reflects an internal performance comparison of the transformation program implemented after KYA + DMA.
Aykim + MirzaVerification

Report taken through verification

MetricIt indicates that the relevant carbon report went through an independent verification process.
Comparison basisThe independent verification experience in the Aykim and Mirza carbon reporting projects.
ScopeThe scope of the relevant carbon report and its independent verification engagement.
InterpretationThe indicator reflects that the relevant carbon reports were reviewed through an independent verification process.
Metrics are evaluated within the scope, starting conditions and comparison period of each project. This methodology makes the data and comparison basis behind each result visible. Outcomes are specific to the relevant project and organizational conditions.

Transparent evidence through measurement methodology.

Time, effort and performance indicators in these success stories are based on the scope, starting conditions and comparison period of each project. Each metric is presented together with its measured variable, comparison basis and scope to support transparent, traceable and accurate interpretation.

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