Digitizing Paper-Based Processes in Physical and Identity Access-Management

While the primary objective of these systems is to manage badges and tokens for every individual, the complexity arises when these systems must integrate with multiple external and internal processes. From self-service applications where employees update their profiles (including badge photographs) to approval workflows that require validation from both internal stakeholders and external authorities, the scope is vast. This expansive functionality underscores the need for a consolidated software solution that not only digitizes but also standardizes these processes.

The Challenge of Digitizing Paper-Based Processes

Despite the clear benefits of digital transformation, many organizations continue to rely on paper forms for gathering applicant information and manually processing badge requests. Although the turnaround time for receiving a badge might not be a critical factor in every context, the inability to fully audit, track every event, and implement robust role-based access control presents significant risks. The challenge lies not just in the speed of execution but in ensuring that every digital interaction is secure, traceable, and compliant with both internal policies and external regulations. In this post we want share our experience where in digitizing paper-based processes in PIAM system following challenges put the project at risk:

• Process Modeling: Transitioning from Paper to Digital
• The Critical Role of Standards
• Overcoming Expertise Deficits
• Managing Project Scope and Change

And how we have successfully overcome them.

Process Modeling: Transitioning from Paper to Digital

One of the most daunting aspects of digitizing paper-based systems is rethinking and modeling existing workflows. In many large organizations, the teams tasked with defining these digital processes come from a system administration or IT background rather than from process engineering. Consequently, they tend to recreate paper processes using basic block diagrams that depict step-by-step workflows (flow of work) without considering the nuances of digital data management.

When transitioning to a system that leverages role-based access control and transactional databases, a superficial replication of paper-based processes quickly reveals its limitations. Critical questions about data storage, retrieval, and the interaction between various roles are often left unaddressed. The challenge is to move beyond the legacy mindset, recognizing that a digital process must account for data normalization, indexing, and the rigorous structural design inherent in robust software architecture.

The Critical Role of Standards

Frameworks such as ITIL, ITSM, and methodologies like RUP have long been used to standardize processes across IT environments. In the realm of software design, however, the use of advanced modeling techniques—such as Unified Modeling Language (UML)—becomes essential. UML provides a concrete, visual representation of processes, which can be communicated clearly to both technical teams and clients.

Unfortunately, the steep learning curve associated with these standards often means that clients and some internal stakeholders are not conversant with their principles. This gap leads to a scenario where initial process definitions are drafted without sufficient expertise, resulting in a model that is a biased extension of paper-based workflows rather than an optimized digital process. Moreover, without comprehensive standards, any attempt to incorporate critical features later on might necessitate a significant architectural overhaul, thereby introducing risk and compromising system quality.

Overcoming Expertise Deficits

A lack of specialized expertise further complicates the transition. In many organizations, the team responsible for digitizing processes may not have the in-depth understanding of advanced process modeling and data design required to foresee and mitigate potential conflicts. This deficit can lead to missed opportunities in capturing essential details, ultimately resulting in accusations of mismanagement or a lack of conviction regarding the project’s execution. The morale of the project team and the overall success of the digital transformation can suffer as a result.

Managing Project Scope and Change

Scope creep is another persistent challenge. When features are defined without a rigorous standard or a team of experts to guide the process, constant changes and additional requirements become inevitable. Development teams may initiate implementation based on incomplete or evolving specifications, only to discover that certain requirements conflict or that critical functionalities have been overlooked. Frequent revisions and the necessity for additional meetings—often involving project managers rather than the developers themselves—create an environment where continuous scope adjustments add layers of complexity to the project.

A Pragmatic Approach: Embracing Domain-Specific Languages (DSL)

After years of experience with PIAM systems and the digitization of paper-based processes, one promising solution has emerged: the use of a Domain-Specific Language (DSL). A DSL is essentially a tailored subset of a programming language, crafted to describe the specific variables, processes, and interactions within a given domain. This approach offers several compelling advantages:

• Simplicity and Clarity: By defining a limited set of operations, the DSL makes it easier for clients and non-technical stakeholders to understand the underlying processes. When the language mirrors the client’s business logic—such as describing an approval process with its corresponding approvers and applications—the communication between stakeholders becomes nearly code-like and inherently clear.
• Rapid Adoption: Unlike comprehensive standards like UML or ITIL, a well-designed DSL has a much gentler learning curve. This enables all parties involved to quickly grasp the process definitions and contribute to refining them.
• Early Detection of Contradictions: The DSL’s structured nature forces explicit definitions of data interactions and process flows. This rigor helps in identifying any critical contradictions between different requirements early in the development cycle.
• Iterative Implementation: With the DSL as a common language, teams can implement processes iteratively, offering routine demos that showcase incremental progress. This iterative methodology helps align expectations and facilitates agile adaptations to evolving requirements.

Weighing the Advantages and Limitations of the DSL Approach

While the DSL approach addresses many of the challenges associated with digitizing paper-based processes, it is important to recognize its limitations. For projects with a broader scope—where the digital transformation goes beyond replicating existing processes and ventures into entirely new business domains such as payments—the constrained nature of the DSL might become a hindrance. In our experience, even though the DSL has proven powerful for modeling business processes, it is not universally applicable to all system functionalities. For instance, automated processes like GDPR compliance routines or email notifications for certificate expirations often fall outside the DSL’s remit.
Therefore, while the DSL is an effective tool for a specific subset of process digitization, it must be used judiciously. Its power lies in its domain-specific focus, and misapplying it to larger or unrelated domains could inadvertently expose the project to new risks.

Further Developments and Future Directions

In the spirit of continuous innovation, our journey did not stop at adopting a DSL. Last year, we embarked on an ambitious project codenamed “GRID” (Grammar-Railed Decoding) and “forms”—a patent-pending technology designed to empower IT professionals to develop PIAM systems with greater ease and precision (learn more). Initially focused on crowd applications, this technology evolved to embrace the full potential of digital process automation.

By integrating the DSL with our GRID-based framework, we are now able to generate tailored business processes that meet the specific needs of an organization. This integration enables the deployment of intelligent agents that can execute approval processes automatically, thus enhancing operational efficiency. Unlike general-purpose code generators or agents that often struggle to grasp context, our DSL-informed agents possess the domain knowledge required to execute commands accurately. This synergy between domain-specific modeling and advanced automation promises a drastic improvement in the overall quality and robustness of the final digital service.