Process Automation 1 min read

From process discovery and pilots to continuous improvement: Managing automation projects

Why traditional process maps doom IT projects to failure and how to build effective automation based on real logs, BPMN 2.0, and DMN decision tables.

Organizations frequently struggle with automation initiatives because they design workflows based on idealized, subjective employee interviews rather than actual operational practices. This reliance on theoretical "happy paths" ignores how work is truly executed on the ground.

Consequently, up to 49% of pilot projects stall halfway, and only 13% scale successfully. Automating these undocumented, chaotic workarounds leads to bloated, hard-coded IT systems that are incredibly expensive to maintain and prone to user sabotage.

To overcome this, modern enterprises utilize objective process mining of digital footprints alongside standards like BPMN 2.0 and DMN to isolate decision logic. Platforms like Scriptum and UnityBase enable rapid, flexible deployment. This structured orchestration ensures continuous, data-driven optimization without developer-heavy code rewrites.

From an environmental perspective, transitioning to precise digital orchestration is highly impactful. Eliminating operational chaos and redundant processing directly minimizes energy consumption in data centers and accelerates the transition to paperless, resource-efficient digital workflows.

Sources & materials

C-ECO Consulting practices and materials referenced in this article.

  1. UnityBase — unitybase.info
  2. Scriptum.DMS (з AI-центром) — inbase.com.ua
  3. Megapolis.DocNet — inbase.com.ua
  4. Scriptum (low-code платформа) — inbase.com.ua
  5. Scriptum.Repository — inbase.com.ua
  6. А5 Персонал — inbase.com.ua