Organizational transformation challenges are very well known. Those are primarily described as barriers to cultural shifts and resistance to abandon traditional ways of thinking. When we look into process automation however, we encounter an additional layer of complexity.
One of the primary issues in processes automation is lack of focus when defining project scope. Businesses typically experience a variety of pain points, but it is crucial to address those that are directly aligned with the overall strategy. While it might be tempting to tackle easy-to-solve issues which offer immediate improvements, prioritizing problems that impact strategy goals is far more important.
Another significant challenge is inconsistent solutions. Over time, businesses accumulate various systems that, while initially suited to support individual processes, lack cohesion in terms of overall integration. This fragmentation creates difficulties when attempting to centralize controls in an automated environment. Replacing existing elements typically is not cost-effective, making it extremely hard for solution architects to choose the right bridging technology.
During the design stages of automation, teams often decide to only address immediate issues to save resources. However, it is essential to build processes with scalability in mind. This means ensuring that solutions can accommodate future business growth, such as introduction of new products, expanding customer base, or changing market conditions. Scalable framework prevents the need for frequent redesigns and adjustments, allowing businesses to adapt smoothly as they evolve.
Miscommunication is an underestimated deterrent that can lead to automation projects failure. Various stakeholders, including senior leaders, functional subject matter experts, solution designers, and project managers, have different expectations. To deal with such a variety of work styles, it is essential to invest time in frequent touchpoints and discussions to ensure everyone is aligned on deliverables.
Retaining know-how by solely relying on "tribal" knowledge or inaccurate documentation represents a massive issue. Lack of thorough mapping exercises and limited personnel rotation or knowledge transfer practices does not help to preserve clear understanding of business processes.
Finally, insufficient effort to measure success of transition efforts always leads to a dead end. The absence of tangible, visible improvements between pre- and post- scenarios strips unanimous approval and support for optimization initiatives. To address that issue, we usually don’t just develop business cases, but we also establish post-implementation monitoring plans. That includes specific metrics and benchmarks evaluating quality of automation and demonstrate its value to all stakeholders.
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