Expertise

Process Automation

I find processes that eat time and money, and turn them into managed digital flows.

Automation without rethinking the process is digitizing chaos. The result: the same chaos, just faster. I regularly see companies that spent six months and a serious budget implementing a BPM system, yet employees still work in Excel — because they automated a process that shouldn’t exist in its current form.

My job as an expert is not to choose a tool, but to understand what’s actually happening. Before automating, I break down the process step by step: measuring how long each step takes, who’s involved, where errors occur, where data is entered repeatedly. Often it turns out that of 12 approval steps, 7 are vestigial — they lost their meaning long ago. Removing them alone is a 2× speedup, even before any automation.

The fundamental difference between expertise and implementation: I answer the questions “what to automate” and “why,” not “how to configure the BPM engine.” My work product is a prioritized list of processes with economic justification, a designed TO BE model, and a clear spec for the implementation team. This ensures that automation delivers measurable impact, rather than becoming yet another system nobody uses.

In Central Asia, automation has its own specifics: many companies operate at the intersection of Soviet-era regulations and modern requirements. Processes are overloaded with paper approvals, duplication, excessive control. Here, proper automation delivers multiplicative impact — not 20%, but 3–5× acceleration, because the volume of unnecessary steps in processes is significantly higher than in mature markets.

Target Model

How It Should Work

Automation must start with deconstructing the process: what can be removed, what simplified, what automated. Only then — choosing a tool.

Common Mistakes

Where Companies Typically Go Wrong

Automating chaos — manual process transferred to system unchanged, with all its unnecessary steps

No process owner — nobody is accountable for results after implementation

Automating everything instead of bottlenecks — spreading budget thin

Tool chosen before process analysis — the task is bent to fit the solution

No before/after metrics — impossible to prove the effect

Process exceptions become the rule — system doesn't account for real life

Process automated but manual version runs in parallel — double work

Integration not considered — automated process requires manual data entry from other systems

Approach

What I Do in These Situations

I find 2–3 processes with maximum economic impact from automation. For each: measure current metrics (time, cost, errors), break down AS IS step by step, remove unnecessary steps, design TO BE. Only after the new logic is approved do I automate. Choosing a tool is the last step, not the first.

Team role: The team handles BPM configuration, integrations, testing, and training.

Results