Delphi Documentation

Explore the inner workings of the Delphi Platforms through our  documentation and gain insights into the methodology that powers our cloud-based intelligence solution for the green hydrogen market.

Basics

Hydrogen Dashboard Methodology

Welcome to the heart of Delphi Data Labs' Hydrogen Dashboard. In this documentation section, we unveil the methodologies that form the backbone of our groundbreaking cloud-based intelligence solution for the green hydrogen market. Understanding the processes behind our dashboard is key to harnessing its full potential.

1. Research Process Overview
Embark on a journey through our research process, where precision and thoroughness converge to gather the most relevant and up-to-date information. Explore how we meticulously curate data to ensure the highest quality insights for your strategic decision-making.

2. Methodology for Market Sizing and Segmentation
Delve into the methodology that underpins our market sizing and segmentation strategies. Discover how we analyze and categorize data to provide a clear understanding of the size and dynamics of the hydrogen market, offering you a strategic edge.

3. Forecast Methodology
Gain insights into the future with our forecast methodology. Uncover the science behind predicting trends and developments in the hydrogen market, empowering you to proactively shape your strategies based on informed projections.

4. Search Methodology
Navigate through our search methodology, highlighting the precision and comprehensiveness with which we scour data sources. Learn how we ensure that no valuable information is left undiscovered, contributing to the depth of our insights.

5. Geodata Classification
The precision of coordinates within our hydrogen project database is classified using a system of indicators that define the quality of geodata modeling crucial for various analytical tasks, such as calculating localized green hydrogen production costs, determining industrial clusters, and generating forecasts.
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6. Delphi Hephaistos Framework for Technology &Manufacturing Readiness
The Delphi Hephaistos Framework simplifies theassessment of technology and manufacturing readiness by combining them intofive practical levels, from concept formulation and initial feasibility toautomated mass production and full supply chain integration.

7. Value Chain Classification
One of the key pillars of our Classification Methodology is the comprehensive mapping of value chains within the hydrogen sector. By tracing each stage of the value chain, we offer unparalleled insights into the activities and value addition at every critical juncture.

8. Assessment Methodology
Witness the meticulous assessment methodology used to evaluate market and competitive landscapes. From understanding growth potential to analyzing competitive dynamics, gain a nuanced perspective that forms the basis for informed decision-making.

Each page provides a gateway to understanding the processes that elevate our intelligence solution to the forefront of the industry.

The Delphi Research Process

At Delphi Data Labs, we are reimagining the landscape of cleantech market intelligence by embracing the digital revolution and the vast ocean of data it provides. Where conventional market research leans heavily on expert interviews, often treating data as a secondary asset, we reverse the paradigm.

Our groundbreaking approach leverages data to inform 80% of our research process, utilizing expert interviews for the remaining 20% for cross-validation and data integrity.

In an era that’s drowning in information yet starved for wisdom, Delphi Data Labs serves as the compass for navigating the cleantech market. With an almost symphonic interplay between cutting-edge technology and human expertise, we offer not just data, but data with depth, direction, and purpose. Welcome to the future of market intelligence.

Market Sizing & Segmentation

In the current digital epoch, the abundance and granularity of data have transcended traditional confines. Recognizing this transformation, Delphi Data Labs is resolute in leveraging online and digitally available data. This approach allows for a comprehensive synthesis of global market metrics, defined precisely as the aggregated sum of production and sales of a specific commodity across the globe.

Data Tracing & Participant Monitoring
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With advancements in web scraping tools, machine learning algorithms, and big data analytics, it's now feasible to trace virtually all market participants.

By continuously monitoring digital footprints, product listings, and online transactions, we can achieve an almostreal-time understanding of market dynamics. However, we also utilize the human element of insight gathering, as we are convinced that a fully automated solution does not result in a sufficient data quality as of yet.

Comparative Methodology Evaluation
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‍The richness of the internet-derived data, while invaluable, is best understood & utilized when evaluated with insights from time-tested traditional methodologies.

— Surveys & Interviews: Grounded insights from direct stakeholder interactions, whether they be industry leaders, consumers, or intermediaries, provide the nuanced context that pure digital data might miss.

— Macroeconomic Modeling: Traditional macroeconomic models, which consider variables like GDP growth rates, gross capital formation and inflation rates, offer a macro lens to view market trends, complementing the micro insights the digital data yields.
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— Trade Data Analysis: Scrutinizing international trade data, including imports, exports, and tariffs, offers pivotal insights into market dynamics, especially for commodities with significant cross-border flows.

By employing a harmonized approach, wherein online data is meticulously vetted and complemented with findings from these traditional methodologies, Delphi ensures a holistic, accurate, and layered understanding of market dynamics.

Benchmarking & Refinement
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— With Other Market Data Suppliers: Regularly, our data sets and findings are benchmarked against other leading market data suppliers. This exercise not only validates our results but also reveals potential areas of improvement or overlooked data niches.

— Market Sizing and Segmentation Refinement: The aforementioned benchmarking, combined with our internal analytics, continually refines our market sizingtechniques. Through this iterative process, our segmentation efforts are sharpened, revealing more nuanced market subdivisions and trends.

By integrating these methodologies, Delphi Data Labs is at the vanguard of market research, harnessing the power of the digital age while respecting the depth of traditional research methodologies.

Forecasts

Methodology

We have formulated three distinct scenarios (base, bear, bull) all of which aregrounded on the following fundamental indicators:
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Demand Indicators
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— National hydrogen strategies
— Public policy considerations
— Hydrogen production targets from over 200 multinational corporations
— Announced project initiatives: > 2.300 hydrogen projects in Delphi’s databases

Supply Indicators
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— Growth projections for more than 230 electrolyzer vendors

Global Macroeconomic Data

— Forecasts sourced from esteemed institutions such as the World Bank and the International Monetary Fund (IMF)

Primary Influences Driving the Dynamic forecasting algorithm

— 2023-2026 fully based on existing project pipeline
— 2026-2032 additionally taking into account hydrogen production targets by countries and corporates  
— Dataset linked and constrained with electrolyzer manufacturing capacity dataset  

The dynamic scenario is continuously updated with every project addition or project status change The algorithm enables a very granular view of the data. Over 200 countries worldwide are tracked and can be viewed individually.

Scenario Development:
Hydrogen Market Forecast

1. Literature Review and Data Collection
‍Acomprehensive literature review was initiated to collate data from authoritative sources. Publications from international bodies, such as theInternational Energy Agency (IEA), World Bank, Goldman Sachs and other relevant institutions, formed the backbone of our initial dataset.

2. Econometric Modeling
‍Econometric models were developed to understand and predict variables central to the hydrogen market:

‍2.1. Data Aggregation and Econometric Normalization
‍Comprehensive Econometric Data Pool: Collation and standardization of green hydrogen projectdata, encompassing diverse variables such as project lifecycle, capacity, geopolitical location, and developmental stage.
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Integrationof Production Targets: Methodical assimilation of national and organizationalhydrogen production objectives, adjusted for geopolitical and macroeconomicvariables.

‍2.2. Temporal Adjustment Using Econometric Distribution
‍Application of Right-Shifted Normal Distribution: Adjustment of project timelines with astatistical approach to account for standard deviations typically observed in energy project completions.

‍2.3. Project Valuation Adjusted by Developmental Stage
‍Stage-Specific Weighting Protocol: Application of a weighted average approach to project data based on developmental stage, grounded in empirical research (Concept: 0.18, Feasibility/Feed: 0.5, etc.).

‍2.4. Supply-Demand Equilibrium Analysis
‍Market Capacity Threshold Assessment: Analysis of electrolyzer industry’s manufacturing capabilities as a determinant of market supply potential.
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Demand Forecasting Model: Econometric modeling of market demand, incorporating factors like policy frameworks, technological evolution, and shifts in global energy paradigms.

3. Scenario Analysis and Modeling
‍Econometric Scenario Construction: Development of multiple market scenarios throughadvanced econometric modeling techniques, addressing a spectrum of potentialmarket evolutions.

4. Stakeholder Engagement
Interviewsand surveys were conducted with key stakeholders, including policy makers, industry leaders, and academic experts. Their insights ensured that our models not only were statistically rigorous but also had a pragmatic grounding.

5. Sensitivity and Stress Testing
Each scenario was subjected to sensitivity and stress tests. These tests ensured the robustness of our models by analyzing how changes in key variables affected outcomes.

6. Expert Review
Draft scenarios were presented to a panel of external experts for validation. Their feedback and insights were instrumental in refining our scenarios to ensure they were both scientifically robust and practically relevant.

7. Scenario Refinement
Each scenario (Bull, Base, and Bear) was revisited and refined based on the insights derived from the models, stakeholder input, and expert reviews.

8. Continuous Monitoring and Quarterly Updates
Post initial development, all scenarios are subject to continuous monitoring. Updates are introduced on a quarterly basis, accounting for global macroeconomic shifts, geopolitical events, technological advances, and any other significant market influencers.

Base Scenario

In the context of our scenario analyses at Delphi Data Labs, we have carefully crafted the 'Base Scenario'.

This scenario reflects a comprehensive interpretation of recent geopolitica levents, with particular attention to the dynamic market shifts occurring in China. Notably, the Base Scenario adopts a more prudent stance compared to the 'Bull Scenario'. The latter is predominantly anchored in the ambitious projections set forth by electrolysis manufacturers. 

In case only one forecast scenario in any of Delphi’s visualizations is applied, this is in general based on the 'Base Scenario’, unless otherwise noted. 

Primary factors prompting a more conservative outlook in the Base Scenario include

— Input Costs: An observed escalationin the prices of essential input materials.
— Economic Recovery: A protracted economic revival pace.
— Private Investment: A tempered enthusiasm among private investors in hydrogen ventures. 

Key Assumptions Underlying the Base Scenario
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— Political Backing: Robust politicalendorsement is anticipated across all major economies.
— Economic Outlook: A medium weighting is assigned to the trajectory of global economic forecasts.
— Private Market Entry: From 2025 onwards, the participation of private entities in the market is expected to beautonomous, not necessitating public funding support.
— Growth Phase: A pronounced surge in growth is projected between 2025 and 2030.
— Project Completion: It is anticipated that over 50% of the announced projects will reach fruition. 

Bear Scenario

In our analysis, the 'Bear Market Scenario' heavily draws inspiration from the IEA's Announced     Pledges Scenario as featured in their Global Hydrogen Review 2021. This scenario underwent meticulous refinement in Q2 of 2023, integrating and updating the latest macroeconomic trends to ensure accuracy and relevance.

Key Assumptions Underpinning the Bear Market Scenario:

— Adoption Pace: A measured; deliberate pace characterizes the adoption of new projects.
— Economic Landscape: A prolonged sluggishness in global economic growth is anticipated to persist until 2025.  
— Economic Forecasting: High emphasis is placed on global economic outlooks, making them pivotal in shaping hydrogen market dynamics.  
— Policy Implementation: Both the US and Europe display a delayed momentum in embracing pro-hydrogen policies, potentially tempering the sector's growth in these regions.
— Financial Climate: A sustained inflationary atmosphere is anticipated, with interest rates maintaining their elevated stature.  

Given these assumptions, stakeholders should approach the hydrogen market with caution,     understanding the potential hurdles and slower-than-expected growth.

Bull Scenario

At Delphi Data Labs, our 'Bull Scenario' envisions a dynamic future landscape dominated by a global competition — a veritable “race for hydrogen leadership". This scenario is buoyed by expectations of significant growth rates and unwavering policy support across the globe.

Primary Influences Driving the Bull Scenario

— Political Commitment: Unwavering political support is anticipated in every major economy, emphasizing their commitment to hydrogen as a key energy vector.  
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— Economic Trajectory: Global economic prospects play a less critical role in this optimistic scenario, allowing hydrogen markets to thrive even in less-than-ideal global economic conditions.

— Private Sector Investments: An influx of investments from private entities is expected, reducing the relative importance of national hydrogen strategies.  

— Accelerated Momentum: The period between 2025 and 2030 is marked by an exceptionally rapid growth pace in hydrogen initiatives.  

— Mega-Projects: The commencement of multiple gigawatt-scale projects every year from 2025      signifies the sector's ambition and capability.  

— Economic Revival: The global economy is expected to embark on a substantial recovery trajectory from Q2 2024.  

In this scenario, the collective emphasis on hydrogen leadership across nations is unmistakable. The combination of governmental willpower, market dynamics, and private enterprise push positions hydrogen at the forefront of the global energy agenda.

Search Methodology

Company Identification

Initially a detailed Value Chain Mapping of the h2-industry was created. The mapping currently stands at over 50 value Chain positions.

In a second step relevant industry codes were utilized to create an initial company pool. This task was performed in a global financial database & company register.

We utilized different AI driven search tools to trim down an initial set of 3 Million companies to around 50,000 with relevant technology offerings:  

For news research, we utilized a news API with over 80,000 Sources  
Key databases used: IEA Hydrogen Project Database, various financial databases, UN Comtrade  

Those companies are manually screened and analyzed and attributed to the relevant value chain Positions in the Map.

This is an ongoing process and new companies are added to the Value-Chain Model on a regular basis. Core hydrogen technologies are given a higher prioritization at this stage. Less focus on  peripheral value chain positions such as end-users and solar energy companies at this point.

Geodata Classification

The precision of coordinates within our hydrogen project database is classified using a system of indicators that define the quality of geodata modeling crucial for various analytical tasks, such as calculating localized green hydrogen production costs, determining industrial clusters, and generating forecasts.

These indicators are as follows:

‍A (Exact Location): The plant's precise geographic coordinates are identified, providing the most specific location details possible, including latitude and longitude.

‍B (Close Proximity): The location is identified within the bounds of a municipality, which means the town or city where the plant is located is known, but its exact coordinates are not specified.

‍C (Regional Proximity): The plant's location is determined at the provincial level, indicating a broader area that encompasses the specific region within a country, without pinpointing the municipality.

‍D (State Proximity): This indicator reflects that the plant is located within a certain state or equivalent administrative division within a country, which is broader than the provincial level and does not provide a specific city or region.

‍E (National Proximity): The plant's location is known only at the country level, suggesting that the precise state, province, or municipality is not determined.

‍X (Various Project Locations): This denotes projects that are not tied to a single geographic location but are spread across multiple, unspecified locations.


This categorization allows for a standardized approach to communicate the degree of locational detail available for plant sites, ranging from the most specific (A) to the least specific (F), with X indicating a non-fixed or multi-location scope.

Delphi Hephaistos Framework

Technology & Manufacturing Readiness

The Delphi Hephaistos Framework simplifies the assessment oftechnology and manufacturing readiness by combining them into five practicallevels, from concept formulation and initial feasibility to automated massproduction and full supply chain integration. It simplifies enhances the traditional TRL scale by including manufacturing stages to better illustrate commercialization:   


Level 1:  Research & Technology Development 

— Technology: Technology concept and application have been formulated. Feasibility studies and initial development are underway.
— Manufacturing: Initial assessment of manufacturingrequirements and constraints. Basic production methodologies identified, butnot yet developed. 

Level 2: Experimental Validation and Pilot Production 

— Technology: Active R&D efforts to validate experimental proof of concept in a controlled environment. Key functional prototypes developed.
— Manufacturing: Outline of the production process defined with more details. Prototyping methods are used to evaluate manufacturability and to begin addressing production issues. 

Level 3: System Integration and Small Scale Production 

— Technology: Technology validated in a relevant environment. Integration into larger systems begins.
— Manufacturing: Pilot production established to refine production capabilities and address scale-up issues. Quality assurance processes are initiated and tested. 

Level 4: Full Scale Production (Non-Automated) 

— Technology: Technology fully integrated and operational inits final form under real-life conditions.
— Manufacturing: Full-scale production capabilities are established and operational. Production processes are optimized for volume and efficiency, but not fully automated. This stage focuses on ensuring the technology can be produced at scale reliably and consistently. 

Level 5: Automated Mass Production and Deployment

— Technology: Final technology adjustments completed to enable mass production.
— Manufacturing: Advanced manufacturing processes implemented, including automation and high-efficiency production lines. Systems fully optimized for mass production, with complete supply chain and logistics integration.


The Delphi Hephaistos Framework provides a systematicapproach to assessing and communicating the maturity of a technology frominitial development through to fully automated mass production. This framework is designed to assist stakeholders in making informed decisions about technology investment, development, and deployment, ensuring a smooth transition through each phase of readiness.

Value Chain Mapping

One of the key pillars of our Classification Methodology is the comprehensive mapping of value chains within the hydrogen sector. By tracing each stage of the value chain, we offer unparalleled insights into the activities and value addition at every critical juncture. This approach not only sheds light on industry dynamics but also empowers organizations to identify opportunities for efficiency improvement and value creation.

Screenshot, Delphi Hydrogen Dashboard (September 2023)

Precision in Classification
‍Our commitment to precision ensures that each company is accurately classified based on its role and contribution to the hydrogen value chain. This approach goes beyond surface-level categorization, providing you with a detailed understanding of each entity's function in the broader ecosystem.

‍Extensive Company Tracking
‍We currently track and classify over 3.000 companies within the hydrogen sector. This expansive coverage ensures that our insights are not only comprehensive but also reflect the dynamic nature of the market, giving you a real-time pulse of industry movements.

‍Adaptive and Evolving
‍The Classification Methodology is not static. It evolves in tandem with industry changes, ensuring that our classification remains relevant and reflective of the ever-shifting dynamics within the hydrogen market.

Competitive Assessment Process

Within the complex dynamics of the hydrogen market, assessments serve as beacons, guiding strategic decision-makers through the industry landscapes. Our Assessment Methodology is an immersive process designed for evaluating both market and competitive dynamics. It goes beyond conventional analysis, providing nuanced insights that empower organizations to make strategic choices with confidence.

Our assessment process transcends data provision; it unfolds a holistic view of the strategic implications associated with the assessed landscapes. By understanding the intricacies and potential strategic moves within the hydrogen market, organizations gain foresight to navigate and thrive in this dynamic environment.

In-Depth Market Dynamics
‍Our assessment methodology goes beneath the surface, unraveling the dynamics of the market. This includes a comprehensive analysis of competitors, strategic moves, and the identification of key opportunities and threats.

‍Future-Ready Growth Exploration
‍Beyond current conditions, our assessments venture into the realm of future growth potential. Organizations receive insights into emerging trends, allowing them to position strategically for upcoming opportunities and challenges.

‍Adaptive Excellence
‍The Assessment Methodology is not a static entity; it evolves in tandem with the ever-shifting landscape of the hydrogen market. This adaptability ensures that the assessments provided remain relevant and aligned with the pulse of industry changes.

The Delphi Competitive Assessment process is a standardized strategic tool for competitive assessment of industrial technology companies.

Currently, the Methodology is employed  for four different markets
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Electrolyzer
Waste to value & carbon compound based H2-Generation
Fuel Cells (in development)
Synthesis technology (in development)
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While the seven classification criteria remain the same, the calculation and methodology of each criterium might vary
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Classification is relative and compareswith industry peers  -  not absolute. It is thus not possible to compare scores from two different assessments.

Scoring Classes & Sample

Currently the score for the 7 key categories is based on a set of attributes, which can unambiguously be attributed to a certain score.

To obtain the required information, a different set of research methodologies was used:

Expert interviews
Quantitative data analysis
Surveys
Qualitative literature analysis

Ourscores are currently calculated through an attribution to a certain range.

Example: A start-up which received a funding of 7 MUSD achieves the same score (3) as a start-up that received funding of 12 MUSD. A start-up that received 22 MUSD would score higher (4).

Scoring Table with Categories

At Delphi Data Labs, our commitment to precision extends to the heart of our assessment process, embodied in the Scoring Table with Categories. This comprehensive framework employs seven key categories, each meticulously crafted to provide a holistic evaluation of companies within the hydrogen market. The combination of these categories offers a nuanced understanding of their strengths, positioning, and potential for strategic collaboration.

The Seven Categories:

‍Financial Resources
‍The financial capabilities of a firm are ranked based on received funding, cash at hand, corporate revenues and the strategic commitment to invest in the assessed segment.

‍Supply Chain Capacities
The classification is based on current manufacturing capabilities, announced scale-up plans, roadmaps and the global setup of manufacturing operations.
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‍Market Share and Experience
‍Companies are ranked based of their market experience (time in the market) and their market share in the previous years, as well as on awarded orders. The weight of announced orders is based on the project stage of the announced order, ranging from 1. Concept (lowest value) to 5. Operational (highest value).

‍Partner Network
‍The ranking is based on a network analysis of the connections & collaborations in the market segment. The connections are mainly derived from news publications and are stored in a database. Important connections (e.g. Joint Venture partners with multinational corporations) result in ahigher scoring compared to unimportant connections (manufacturing partnership with a small local SME).

‍Global Setup
‍Based on the extend of global sales activities, locations and manufacturing plants.

‍Technology
‍Analysis of the technological portfolio. The score is influenced by the TRL, scalability, efficiency and the number of different technologies within acompany's portfolio.

‍Strategy
The strategy score is a function of the other 6 categories, extended with a score adjustment in the range of -2.0 to+2.0, which includes factors that are not covered in the other 6 dimensions (Current Performance, Focus, Marketing, Special Routes to Market).

Note: The Delphi Market assessment model is an evolving & dynamic tool, Feedback is continuously integrated to advance the classification algorithms.

This structured approach ensures that our evaluation goes beyond surface-level assessments, providing you with a nuanced understanding of companies' capabilities and positioning within the hydrogen sector. Whether you are exploring potential partners, assessing competitors, or identifying collaborators, our scoring offers a comprehensive framework for strategic decision-making in the dynamic world of hydrogen.

Scoring Quadrants

The score on each axis is calculated by a weighted average of the currently 7 research categories.

Execution Capabilities: Strongly weights financial power and already realized strategic initiatives, such as thecurrent market share and the established strategic partnerships.

Strategic Vision: Strongly weights technology and the general business strategy.

Note: The exact formula and weightings are a business secret of Delphi Data Labs and are not published.