Consulting and Advisory Services
GSS Consulting assists customers and business partners in developing and deploying innovative and advanced peformance reliability, and planning solutions. Solutions leverage unique combinations of technology, domain knowledge, algorithms, and processes to optimize physical systems performance outcomes and address critical technology transition and sustainability missions. GSS Consulting works in support of our newly formed and innovative technology and solutions company, Intessellate Inc.
Decision Intelligence In Practice
Identifying Actions and Decisions that Hold Under Real Conditions
Organizations often pursue optimization as the primary means of improving performance. However, most real-world environments are dynamic, with changing
constraints, evolving objectives, and interdependencies that are not easily captured in static models. As a result, solutions that appear optimal at a point in time
frequently degrade as conditions shift.
Decision intelligence extends beyond traditional optimization by focusing on how decisions perform over time within interconnected systems. It emphasizes the ability to
sustain outcomes under variability rather than achieving a one-time analytical optimum.
In this approach, decision-making activities involve both evaluating individual actions and understanding how those actions interact across the broader system. Analytics
plays a critical role by enabling continuous assessment of conditions, dependencies, and outcomes. More specifically:
•
Identification and representation of interdependencies across decisions, assets, and constraints
•
Continuous evaluation of decision effectiveness as conditions evolve
•
Integration of operational, financial, and risk perspectives into a unified decision context
•
Recognition of second- and third-order effects that impact system performance over time
•
Structured approaches for maintaining alignment between decisions and organizational objectives
GSS Consulting applies these principles in alignment with the decision frameworks developed by Intessellate [www.intessellate.com] to support more resilient and
effective decision-making.
Contact us for further details.
Outcome-Driven Asset Management
Target Actions and Investments to Drive Bottom-Line Results
Outcome-driven asset management focuses on achieving desired outcomes or objectives of an organization through the effective management of assets. It goes
beyond simply managing assets and emphasizes the value that assets can provide to the organization., or more precisely - outcomes that result in successful
accomplishment of organizational goals and objectives.
Outcome-driven asset management involves systematic and risk-informed decision-making processes to optimize the return on investment generated from assets. It
also involves coordinating management actions to ensure the alignment of asset management activities with organizational objectives. By adopting an outcome-driven
approach, organizations can generate value and maximize the benefits derived from their assets.
In this approach, asset management activities involve both managing assets and coordinating actions to ensure the best possible outcomes are realized. Analytics plays
a critical role by enabling timely, accurate assessment of situation and options. More specifically:
•
Data- or model-derived baseline or ground truth to assure that asset management and investment strategy assessments are based on current state of condition and
understanding of asset roles/usage.
•
Risk models and frameworks to assess and quantify nature of risks (consequence, likelihood, … )
•
Data-driven and/or domain-expert generated, quantitative process for determining outcomes for target investments, over time, by business or technical objective.
•
Situational- and policy-driven investment scoring framework that enables investment outcomes to be (re)calculated as a function of changes to objectives, external
factors, or policies.
•
Rigorous, scenario-driven, exploration, and optimization functions to analyze asset portfolio readiness by objective, over time, as a function of planned or projected
asset management and investment activities.
GSS Consulting is partnering with Jack Dempsey co-founder of the Asset Management Partnership to develop and implement leading edge process-
and analytics-driven methodologies to improve outcomes through better asset management.
Value Realization
Value-Based Deployment of Technologies and AI
With all of the hype and promise of AI and particulary generative AI, it’s critical to understand how AI and analytics match business and technical objectives-- i.e., to not
treat this topic in isolation but to tailor one’s approach to the composition of the business, physical assets, and digital assets (data, math, existing AI systems.), the overall
asset portfolio composition, and business/political/physical environments.
Methodologies and frameworks must be able to both evolve morph over time. This means that one must be prepared to shift/extend or fundamentally re-assemble
digital assets to continue to match or support business objectives and needs. This is where our approach to implementation of analytics and scenario-based
optimization tools needs to be very pragmatic and aligned to business processes.
•
As policy and processes are re-envisioned, the means for assessing how to characterize and quantify specific objectives/need, must be refactored as well.
•
Frameworks – combinations of structure, analytics, and outcome driven applications – must be capable of delivering business value -- i.e., they must be constructed
to assure that insights to be generated can truly drive organizational capabilities and, as a result, expected outcomes, over time.
Different circumstances may dictate a need for bold versus measured steps, as well as fundamentally different definitions what success is … but, it’s extremely difficult to
consistently make superior decisions without achieving excellence within analytics and strategy realms.
.
Strategic Advisory
Bringing Domain Knowledge and Critical Thinking to Strategy
We are seeing dramatic changes to the makeup of industry, technologies applied, and impacts of sustainability and decarbonization; we are also facing significant
immediate challenges in addressing declining profit margins, volatile demand, and aging asset issues. … and we are seeing substantial differences among asset owners
and operators as to the nature of or level of risk or opportunities resulting from these changes!
Thus, the need to tailor the approach and composition of both physical and digital (data, math, AI, …) asset portfolios … and to realize that one must be vigiliant in efforts to
adapt to changes in technical needs as well as business context;. To accomplish this, its critical that one’s asset management and technology strategies are properly
informed by all aspects of domain knowledge required:
•
Technology/Business: e.g., Technology/systems, Market/business, Finance and Capital, and Risk Management
•
Externalities: e.g., Policy, Market formation/transitions
•
Process Methodologies: Asset Management practices (e.g., ISO 55000, 55001, 55002 …), AI, Modelling and Simulation, IT/OT infrastructure including sensors, IIoT,
historians, cloud compute environments,
Our Strategy and Advisory practices focus on adoption of critical business processes, technology, and fundamentally critical changes to business or operations models.
We seek to build trust by first demystifying and validating solution elements that have the most impact on success, recommend actions or approaches required to
tackle those first, and then systematically extend the solution and functionality. This is particularly critical as customers embark on the application of new and extremely
promising technology realms such as generative AI.
Target opportunity areas we address include:
•
Portfolio or asset performance and optimization – how to maximize or optimize performance in the context of the market/financial as well as technical performance
objectives.
•
Asset health, reliability, and risk – applying models, AI, and diagnostics tools within reliability and maintenance practices.
•
Capital commitments across asset portfolios to fund new projects and support existing installations.
•
Flexibility and agility to achieve changing priorities, address new/emerging customer needs or expectations.
.
© Copyright 2026 GSS Consulting | All Rights Reserved
Contact Us: info@gssconsults.com
Driving innovation and agility into asset intensive industries
through unique combinations of technology, domain knowledge,
and methods to optimize physical systems and address critical
technology transition and sustainability missions.
Graph-Based Thinking for Real Systems
Structuring Complex Systems for Better Decisions
Traditional analytical approaches decompose problems into components and address them individually. While effective in well-defined contexts, this approach does not
fully capture the interconnected nature of most operational systems, where relationships between elements often drive outcomes.
Graph-based thinking provides a structured way to represent systems as networks of interconnected elements. This allows organizations to move beyond simplified,
linear models and better reflect how decisions, assets, and constraints interact in practice.
In this approach, system representation becomes a critical enabler of analysis and insight. Analytics supports not only the evaluation of individual elements, but also the
relationships that connect them. More specifically:
•
Representation of assets, decisions, and constraints as interconnected nodes and relationships
•
Explicit modeling of dependencies, tradeoffs, and flows across the system
•
Ability to trace how changes propagate through interconnected elements
•
Identification of leverage points that are not visible in isolated analyses
•
Unified evaluation of impacts across operational, financial, and risk dimensions
By structuring problems in this way, organizations can achieve a more complete and actionable understanding of system behavior. GSS Consulting applies system-level
modeling capabilities developed by Intessellate [www.intessellate.com], the customer, and others..
Contact us for further details.
Adaptive Planning vs. Static Optimization
Sustaining Performance in Changing Environments
Planning efforts often focus on identifying an optimal solution based on current assumptions. In dynamic environments, however, those assumptions change, and plans
that are highly optimized for a specific point in time can quickly become misaligned with reality.
Adaptive planning shifts the focus from static optimization to continuous alignment. It recognizes that effective plans must evolve alongside changing conditions and
that decision processes should incorporate feedback and iteration as core elements.
In this approach, planning activities involve ongoing evaluation and adjustment rather than one-time analysis. Analytics enables this by supporting continuous insight
into system performance and emerging conditions. More specifically:
•
Continuous monitoring of key variables, constraints, and system conditions
•
Iterative adjustment of plans based on updated information
•
Integration of feedback loops into planning and decision processes
•
Evaluation of alternative scenarios as conditions evolve
•
Maintenance of alignment between plans, actions, and organizational objectives over time
This approach improves resilience, reduces reliance on reactive adjustments, and supports sustained performance. GSS Consulting applies these adaptive planning
principles in alignment with methodologies advanced by Intessellate [www.intessellate.com],.
Contact us for further details.
Explainability as a Strategic Asset
Enabling Decisions that Can Be Trusted and Acted Upon
Advanced analytical models can generate highly sophisticated outputs, but their value is limited if those outputs cannot be clearly understood and trusted by decision-
makers. In many organizations, lack of transparency is a primary barrier to adoption and effective use of analytics.
Explainability ensures that analytical results can be interpreted, validated, and communicated across stakeholders. It enables organizations to move from theoretical
insight to practical implementation.
In this approach, analytics is designed not only to produce results, but to make those results accessible and actionable. More specifically:
•
Clear linkage between inputs, assumptions, and resulting outputs
•
Traceability of decision logic and underlying model structure
•
Visibility into tradeoffs and key drivers of outcomes
•
Ability to validate, challenge, and refine analytical results
•
Support for cross-functional understanding and alignment
By embedding explainability into analytical processes, organizations can increase trust, accelerate adoption, and improve decision quality. GSS Consulting
incorporates these principles consistent with the explainable analytics approach developed by Intessellate [www.intessellate.com] and for asset management
constructs, AMPS [see Outcome-Driven Asset Management section below].
Contact us for further details.
Incremental Transformation Approach
Delivering Measurable Value Through Structured Progression
Large-scale transformation initiatives often encounter challenges when attempting to move directly from concept to full implementation. Without sufficient validation,
these efforts can introduce risk, complexity, and uncertainty.
An incremental approach focuses on building understanding and demonstrating value in stages. It enables organizations to validate assumptions, refine methods, and
scale with confidence. This is particularly critical in today’s world where trust and confidence in AI-enabled systems and processes must be earned.
In this approach, transformation is treated as a progression of structured steps, each designed to produce actionable insight and measurable outcomes. Analytics
supports this progression by enabling focused analysis and rapid evaluation. More specifically:
•
Definition of a clear and bounded problem space aligned to organizational objectives
•
Development of structured system representations to support analysis
•
Creation of targeted testbeds to evaluate concepts and approaches
•
Validation of insights through iterative refinement and feedback
•
Expansion of scope based on demonstrated results and validated understanding
This approach reduces implementation risk, accelerates time to value, and strengthens stakeholder confidence. GSS Consulting employs this staged methodology that
is aligned with maturity and evolution of relevant business practices and technical processes, to ensure that systems and methods are holistically connected to real-
world needs and activities. We have built and continue to build integrated technology and process maturity solution pathways in concert with AMP, intessellate, and
other business partners.
Contact us for further details.
Consulting and Advisory
Services
GSS Consulting assists customers and business partners in developing and deploying innovative and advanced peformance reliability, and planning solutions. Solutions leverage unique combinations of technology, domain knowledge, algorithms, and processes to optimize physical systems performance outcomes and address critical technology transition and sustainability missions. GSS Consulting works in support of our newly formed and innovative technology and solutions company, Intessellate Inc.
Decision
Intelligence In
Practice
Identifying Actions and
Decisions that Hold
Under Real Conditions
Organizations often pursue optimization as the
primary means of improving performance. However,
most real-world environments are dynamic, with
changing constraints, evolving objectives, and
interdependencies that are not easily captured in
static models. As a result, solutions that appear
optimal at a point in time frequently degrade as
conditions shift.
Decision intelligence extends beyond traditional
optimization by focusing on how decisions perform
over time within interconnected systems. It
emphasizes the ability to sustain outcomes under
variability rather than achieving a one-time analytical
optimum.
In this approach, decision-making activities involve
both evaluating individual actions and understanding
how those actions interact across the broader system.
Analytics plays a critical role by enabling continuous
assessment of conditions, dependencies, and
outcomes. More specifically:
•
Identification and representation of
interdependencies across decisions, assets, and
constraints
•
Continuous evaluation of decision effectiveness as
conditions evolve
•
Integration of operational, financial, and risk
perspectives into a unified decision context
•
Recognition of second- and third-order effects
that impact system performance over time
•
Structured approaches for maintaining alignment
between decisions and organizational objectives
GSS Consulting applies these principles in alignment
with the decision frameworks developed by
Intessellate [www.intessellate.com] to support more
resilient and effective decision-making.
Contact us for further details.
Outcome-Driven
Asset Management
Target Actions and
Investments to Drive
Bottom-Line Results
Outcome-driven asset management focuses on
achieving desired outcomes or objectives of an
organization through the effective management of
assets. It goes beyond simply managing assets and
emphasizes the value that assets can provide to the
organization., or more precisely - outcomes that result
in successful accomplishment of organizational goals
and objectives.
Outcome-driven asset management involves
systematic and risk-informed decision-making
processes to optimize the return on investment
generated from assets. It also involves coordinating
management actions to ensure the alignment of asset
management activities with organizational objectives.
By adopting an outcome-driven approach,
organizations can generate value and maximize the
benefits derived from their assets.
In this approach, asset management activities involve
both managing assets and coordinating actions to
ensure the best possible outcomes are realized.
Analytics plays a critical role by enabling timely,
accurate assessment of situation and options. More
specifically:
•
Data- or model-derived baseline or ground truth
to assure that asset management and investment
strategy assessments are based on current state
of condition and understanding of asset
roles/usage.
•
Risk models and frameworks to assess and
quantify nature of risks (consequence, likelihood, …
)
•
Data-driven and/or domain-expert generated,
quantitative process for determining outcomes for
target investments, over time, by business or
technical objective.
•
Situational- and policy-driven investment scoring
framework that enables investment outcomes to
be (re)calculated as a function of changes to
objectives, external factors, or policies.
•
Rigorous, scenario-driven, exploration, and
optimization functions to analyze asset portfolio
readiness by objective, over time, as a function of
planned or projected asset management and
investment activities.
GSS Consulting is partnering with Jack
Dempsey co-founder of the Asset Management
Partnership to develop and implement leading
edge process- and analytics-driven
methodologies to improve outcomes through
better asset management.
Value Realization
Value-Based
Deployment of
Technologies and AI
With all of the hype and promise of AI and particulary
generative AI, it’s critical to understand how AI and
analytics match business and technical objectives--
i.e., to not treat this topic in isolation but to tailor one’s
approach to the composition of the business, physical
assets, and digital assets (data, math, existing AI
systems.), the overall
asset portfolio composition, and
business/political/physical environments.
Methodologies and frameworks must be able to both
evolve morph over time. This means that one must be
prepared to shift/extend or fundamentally re-
assemble digital assets to continue to match or
support business objectives and needs. This is where
our approach to implementation of analytics and
scenario-based optimization tools needs to be very
pragmatic and aligned to business processes.
•
As policy and processes are re-envisioned, the
means for assessing how to characterize and
quantify specific objectives/need, must be
refactored as well.
•
Frameworks – combinations of structure, analytics,
and outcome driven applications – must be
capable of delivering business value -- i.e., they
must be constructed to assure that insights to be
generated can truly drive organizational
capabilities and, as a result, expected outcomes,
over time.
Different circumstances may dictate a need for bold
versus measured steps, as well as fundamentally
different definitions what success is … but, it’s
extremely difficult to consistently make superior
decisions without achieving excellence within
analytics and strategy realms.
.
Strategic Advisory
Bringing Domain
Knowledge and Critical
Thinking to Strategy
We are seeing dramatic changes to the makeup of
industry, technologies applied, and impacts of
sustainability and decarbonization; we are also facing
significant immediate challenges in addressing
declining profit margins, volatile demand, and aging
asset issues. … and we are seeing substantial
differences among asset owners and operators as to
the nature of or level of risk or opportunities resulting
from these changes!
Thus, the need to tailor the approach and composition
of both physical and digital (data, math, AI, …) asset
portfolios … and to realize that one must be vigiliant in
efforts to adapt to changes in technical needs as well
as business context;. To accomplish this, its critical
that one’s asset management and technology
strategies are properly informed by all aspects of
domain knowledge required:
•
Technology/Business: e.g., Technology/systems,
Market/business, Finance and Capital, and Risk
Management
•
Externalities: e.g., Policy, Market
formation/transitions
•
Process Methodologies: Asset Management
practices (e.g., ISO 55000, 55001, 55002 …), AI,
Modelling and Simulation, IT/OT infrastructure
including sensors, IIoT, historians, cloud compute
environments,
Our Strategy and Advisory practices focus on
adoption of critical business processes, technology,
and fundamentally critical changes to business or
operations models. We seek to build trust by first
demystifying and validating solution elements that
have the most impact on success, recommend
actions or approaches required to tackle those first,
and then systematically extend the solution and
functionality. This is particularly critical as customers
embark on the application of new and extremely
promising technology realms such as generative AI.
Target opportunity areas we address include:
•
Portfolio or asset performance and optimization –
how to maximize or optimize performance in the
context of the market/financial as well as technical
performance objectives.
•
Asset health, reliability, and risk – applying models,
AI, and diagnostics tools within reliability and
maintenance practices.
•
Capital commitments across asset portfolios to
fund new projects and support existing
installations.
•
Flexibility and agility to achieve changing priorities,
address new/emerging customer needs or
expectations.
.
Driving innovation and agility into asset
intensive industries through unique
combinations of technology, domain
knowledge, and methods to optimize
physical systems and address critical
technology transition and sustainability
missions.
Graph-Based
Thinking for Real
Systems
Structuring Complex
Systems for Better
Decisions
Traditional analytical approaches decompose
problems into components and address them
individually. While effective in well-defined contexts,
this approach does not fully capture the
interconnected nature of most operational systems,
where relationships between elements often drive
outcomes.
Graph-based thinking provides a structured way to
represent systems as networks of interconnected
elements. This allows organizations to move beyond
simplified, linear models and better reflect how
decisions, assets, and constraints interact in practice.
In this approach, system representation becomes a
critical enabler of analysis and insight. Analytics
supports not only the evaluation of individual
elements, but also the relationships that connect
them. More specifically:
•
Representation of assets, decisions, and
constraints as interconnected nodes and
relationships
•
Explicit modeling of dependencies, tradeoffs, and
flows across the system
•
Ability to trace how changes propagate through
interconnected elements
•
Identification of leverage points that are not visible
in isolated analyses
•
Unified evaluation of impacts across operational,
financial, and risk dimensions
By structuring problems in this way, organizations can
achieve a more complete and actionable
understanding of system behavior. GSS Consulting
applies system-level modeling capabilities developed
by Intessellate [www.intessellate.com], the customer,
and others..
Contact us for further details.
Adaptive Planning
vs. Static
Optimization
Sustaining Performance
in Changing
Environments
Planning efforts often focus on identifying an optimal
solution based on current assumptions. In dynamic
environments, however, those assumptions change,
and plans that are highly optimized for a specific point
in time can quickly become misaligned with reality.
Adaptive planning shifts the focus from static
optimization to continuous alignment. It recognizes
that effective plans must evolve alongside changing
conditions and that decision processes should
incorporate feedback and iteration as core elements.
In this approach, planning activities involve ongoing
evaluation and adjustment rather than one-time
analysis. Analytics enables this by supporting
continuous insight into system performance and
emerging conditions. More specifically:
•
Continuous monitoring of key variables,
constraints, and system conditions
•
Iterative adjustment of plans based on updated
information
•
Integration of feedback loops into planning and
decision processes
•
Evaluation of alternative scenarios as conditions
evolve
•
Maintenance of alignment between plans, actions,
and organizational objectives over time
This approach improves resilience, reduces reliance
on reactive adjustments, and supports sustained
performance. GSS Consulting applies these adaptive
planning principles in alignment with methodologies
advanced by Intessellate [www.intessellate.com],.
Contact us for further details.
Explainability as a
Strategic Asset
Enabling Decisions that
Can Be Trusted and
Acted Upon
Advanced analytical models can generate highly
sophisticated outputs, but their value is limited if
those outputs cannot be clearly understood and
trusted by decision-makers. In many organizations,
lack of transparency is a primary barrier to adoption
and effective use of analytics.
Explainability ensures that analytical results can be
interpreted, validated, and communicated across
stakeholders. It enables organizations to move from
theoretical insight to practical implementation.
In this approach, analytics is designed not only to
produce results, but to make those results accessible
and actionable. More specifically:
•
Clear linkage between inputs, assumptions, and
resulting outputs
•
Traceability of decision logic and underlying
model structure
•
Visibility into tradeoffs and key drivers of
outcomes
•
Ability to validate, challenge, and refine analytical
results
•
Support for cross-functional understanding and
alignment
By embedding explainability into analytical processes,
organizations can increase trust, accelerate adoption,
and improve decision quality. GSS Consulting
incorporates these principles consistent with the
explainable analytics approach developed by
Intessellate [www.intessellate.com] and for asset
management constructs, AMPS [see Outcome-Driven
Asset Management section below].
Contact us for further details.
Incremental
Transformation
Approach
Delivering Measurable
Value Through
Structured Progression
Large-scale transformation initiatives often encounter
challenges when attempting to move directly from
concept to full implementation. Without sufficient
validation, these efforts can introduce risk, complexity,
and uncertainty.
An incremental approach focuses on building
understanding and demonstrating value in stages. It
enables organizations to validate assumptions, refine
methods, and scale with confidence. This is
particularly critical in today’s world where trust and
confidence in AI-enabled systems and processes
must be earned.
In this approach, transformation is treated as a
progression of structured steps, each designed to
produce actionable insight and measurable
outcomes. Analytics supports this progression by
enabling focused analysis and rapid evaluation. More
specifically:
•
Definition of a clear and bounded problem space
aligned to organizational objectives
•
Development of structured system
representations to support analysis
•
Creation of targeted testbeds to evaluate
concepts and approaches
•
Validation of insights through iterative refinement
and feedback
•
Expansion of scope based on demonstrated
results and validated understanding
This approach reduces implementation risk,
accelerates time to value, and strengthens
stakeholder confidence. GSS Consulting employs this
staged methodology that is aligned with maturity and
evolution of relevant business practices and technical
processes, to ensure that systems and methods are
holistically connected to real-world needs and
activities. We have built and continue to build
integrated technology and process maturity solution
pathways in concert with AMP, intessellate, and other
business partners.
Contact us for further details.