The Art of Simplifying How to Effectively Embrace Complexity Managing and even siezing opportunities associated with complexity is increasingly critical to business success! And, yet, traditional methods for navigating change are fundamentally siloed and, hence, flawed and incapable of addressing the full range of complexity. Business Complexity - Changes in demands or expectations of customers, changes in nature of projects or services to be rendered based on these needs. Technical Complexity - Applying domain skills, emerging technologies, production capabilities to meet current and future business challenges. Social Complexity - Synergizing sustainability and greening of energy -- both in terms or production and use -- with business objectives. Digital Complexity - Assuring that powerful and existing digital capabilities -- AI, analytics, graph, cloud -- are applied in cohesive, synergistic manner to one’s business and technical missions. Digital Fatigue - Overcoming the challenges of climbing yet another implementation challenge in the wake of all other challenges! Simplexity leverages a team of multi- disciplinary experts to help our customers develop and implement cohesive, foward- leaning technology and IT strategies that align to business opportunities and production capabilities. Contact us for further details.

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-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. .

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. .

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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.