--- title: "Standard Software Is Dead" author: "Daniel Gorld" author_role: "Consulting Director, cbs CX — The cbs Group Salesforce Consultancy" author_url: "https://cx-waves.com/about" publisher: "CX-Waves" canonical_url: "https://cx-waves.com/nodes/standard-software-dies" date_published: 2026-08-12 date_modified: 2026-09-20 language: en --- # Standard Software Is Dead Source: Daniel Gorld, CX-Waves — https://cx-waves.com/nodes/standard-software-dies (published 2026-08-12, updated 2026-09-20) ## Why is the traditional concept of 'standard software' becoming obsolete, and what architectural principle is replacing it? 1. **Cost Argument Collapse**: The primary justification for standard software was its lower cost compared to custom development. With advancements like AI and 'vibe coding,' the cost of custom solutions has significantly decreased, eroding this foundational argument. 2. **Process Rigidity**: Traditional standard software imposed rigid 'process standards,' forcing companies to adapt their unique operational processes to the software's inherent logic. This often led to compromises rather than optimal business practices. 3. **Increased Flexibility Needs**: Businesses increasingly demand the ability to design processes tailored to their specific market logic, customer needs, and competitive advantages, rather than being constrained by generic, pre-defined software templates. 4. **Rise of Technical Standard**: While the 'process standard' is diminishing, the underlying 'technical standard'—focused on data consistency, system interoperability, and reliable integration points—is becoming paramount. This principle emphasizes a stable foundation for flexible process design. ## The Pragmatic Rise of Standard Software The dominance of standard software, exemplified by platforms like SAP and Salesforce, was not predicated on its inherent superiority in process design, but rather on practical economic factors. Historically, custom software development at scale was fraught with challenges: it was often prohibitively expensive, time-consuming, difficult to maintain, and prone to budget overruns and accumulating technical debt. Standard software offered a viable alternative by providing ready-made solutions, even if they required companies to adapt their internal processes to the software's framework. This made standard software the pragmatic choice, not necessarily because it was qualitatively better, but because the alternative was demonstrably worse and riskier for most organizations. The core argument for its adoption was always a cost-benefit calculation, prioritizing affordability and manageability over bespoke process optimization. ## The Costly Compromise of Process Adaptation For decades, companies using standard software invested significant resources into adapting their business processes to the software's predefined logic. This often meant compromising on unique operational methods to fit within the software's capabilities, rather than enhancing their processes for competitive advantage. While this approach sometimes led to genuine standardization and efficiency, it also risked homogenizing business operations, potentially eroding unique competitive differentiators if rivals adopted the same software. The promise of "best practice is built in" was often an oversimplification, as these "best practices" were generic compromises, not perfectly suited to every industry, company size, or market. Despite these limitations, this model persisted because the economic barriers to genuine custom development were too high to overcome, making process adaptation a necessary trade-off. ## AI's Impact on Development Costs The landscape of software development is undergoing a fundamental transformation due to advancements in artificial intelligence. Innovations like 'vibe coding,' AI-driven development tools, and large language models capable of generating process logic are drastically reducing the cost and time required for custom solutions. Tasks that once demanded months of work from entire development teams can now be accomplished in a matter of days. This shift makes what was once prohibitively expensive—tailored software designed precisely for a company's needs—increasingly affordable and accessible. The economic rationale that long underpinned the standard software model is now collapsing; if custom solutions are no longer significantly more expensive than standard offerings, the imperative to adapt internal processes to off-the-shelf software diminishes dramatically. This fundamental change is prompting organizations to reconsider their long-held strategies for digital transformation. ## The Obsolescence of Process Standardization The traditional 'process standard,' which dictated that a company's operations, such as order-to-cash or sales processes, should conform to the logic of platforms like SAP or Salesforce, is losing its relevance. This decline is not a reflection of the software's quality, but rather an outcome of companies gaining the unprecedented ability to design their processes as they see fit. This new freedom represents a significant opportunity, allowing businesses to craft processes that truly align with their unique market demands, customer expectations, and competitive strategies, rather than settling for generic templates. The process standard was always a compromise, a one-size-fits-many solution that rarely perfectly suited any single entity. The ability to move beyond this compromise empowers companies to build systems that genuinely reflect their operational identity and strategic objectives. ## The Enduring Importance of Technical Foundations While the 'process standard' is becoming obsolete, a critical distinction must be maintained: the underlying technical foundation of systems remains more vital than ever. Regardless of how flexibly business processes are designed or iterated, the necessity for systems to communicate effectively, for data to remain consistent across platforms, and for integration points to function reliably is non-negotiable. This is not a process prescription but a fundamental technical requirement that has always existed, often obscured within the monolithic packages of standard software that delivered both process and technical consistency. This technical standard ensures the structural integrity and interoperability of the digital ecosystem. Ignoring this technical foundation in the pursuit of process flexibility leads to chaos, highlighting that beneath individualized processes, robust and consistent technical standards are indispensable for operational coherence. ## Sales Example: Illustrating Technical and Process Standards Consider the example of offer creation in B2B sales to illustrate the distinction between process and technical standards. Sales teams require significant flexibility to address customer-specific configurations, dynamic pricing, and unique agreements, all essential for securing complex industrial deals. Solutions like Salesforce and CPQ (Configure, Price, Quote) tools provide this necessary agility. However, this flexibility operates within non-negotiable boundaries: product catalog governance, price floors, and discount approval workflows must be respected. Critically, every approved offer must ultimately translate into an order in an ERP system like SAP, adhering to standardized structures for materials, condition types, and pricing logic—no exceptions or special formats are permitted. The interface with SAP represents a technical necessity for data consistency, not a process prescription that dictates how sales operates. ## The New Architectural Imperative The core question in digitalization projects has shifted. It is no longer about whether to adapt processes to standard software or build custom solutions, as the traditional concept of "standard" in that sense is evolving. The contemporary challenge lies in consciously defining what constitutes the stable, consistent foundation of a system landscape versus what comprises the flexible "design space" above it. Companies must strategically determine which architectural layers require robust, interoperable consistency to enable genuine flexibility in higher-level processes, and which layers should, or even must, be individually tailored. This represents a move from a binary choice of "standard vs. individual" to a nuanced approach of "conscious architecture." These decisions are critical to prepare for a future where AI capabilities will be integrated, demanding a foundational structure designed to support dynamic and personalized operations rather than rigid, pre-packaged solutions.