Automation Pitfall: When Systems Amplify Chaos Instead of Creating Order

The Situation

When considering automation, employees and management don't always consider the state of their current processes. Everything seems under control: data exists, reports are compiled, and approvals — though manual — are being completed. Excel files are sent around, metrics are discussed on calls, and managers personally verify calculations. Everyone is used to it, perceiving it as a normal workflow.

Even when employees notice discrepancies in reports or inconsistent methodology interpretations, it doesn't raise concerns. There’s a common belief that once a system is in place, things will fall into place — simply transferring the current logic to a platform will make everything easier.

The uncomfortable truth that processes are far from streamlined, data is fragmented, and calculation rules are undocumented often goes unspoken. Neither within the team nor in discussions with contractors. The project launches essentially in a state of uncertainty, although on the surface everything appears organized: teams are formed, a project plan is developed, and a kickoff meeting has been held.

Yet there's no shared understanding of how the process should actually work. There's no comprehensive picture or established rules — just different versions of the truth in reports and hope that the system will fix everything.

The Core Issue

Implementing a financial system doesn't solve process and data problems if these issues aren't resolved before the automation project begins. If a company lacks order, clear rules, and unified calculation approaches, the system doesn't simplify work — it scales existing chaos.

When processes aren't documented and data is fragmented, automation becomes not a tool for simplifying work but a means to rapidly propagate errors across reports, data sets, and departments. Instead of saving time and resources, the company ends up with even more manual work: constantly reconciling data, building endless mappings, and requesting one custom fix after another — just to keep the new system barely running.

Automation cannot create order where none exists. For a system to work and benefit the business, you must first establish processes, align on rules, and standardize data. Only then can these clear, manageable processes be automated.

The Consequences

1. Metrics are inconsistent — the same indicators in different reports don't match.
2. Employees don't understand how to use the system and continue working as before — in Excel, messaging apps, private chats, and email.
3. The system requires significant modifications because no one considered methodology and design beforehand.
4. Error correction costs increase, but the system provides no benefit.
5. The team becomes disillusioned with automation and begins to resist it.

Problem Indicators

1. No common understanding of how business processes should function: who is responsible for what, and what should happen in what order.
2. Users constantly adjust data manually and clarify details via correspondence or calls.
3. Data is manipulated to achieve desired results.
4. No one on the team can explain how processes interconnect.

How to Avoid The Mistake

For automation to truly work rather than create new problems, several steps must be taken before the project starts:

1. Formalize and document processes Record who does what, in what order, in which system, and why. If a process doesn't work on paper, automation won't help.
2. Conduct a data audit Standardize metrics, align methodology and reports, determine a "single source of truth" for data. Without this, automation merely transfers chaos from Excel to the system.
3. Align calculation methodology All departments must have identical approaches to calculating financial metrics.
4. Assign process and data owners Each business process and dataset must have a designated responsible party who monitors its quality, comparability, and relevance.