April 9, 2025 | 5 min read

How to capture clean data that drives better process analytics

Business processes are made up of complex, interrelated subprocesses and tasks. To have a crystal-clear picture of how business processes actually run and make them manageable, companies adopt process transparency tools. They help businesses track how processes actually work, identify tasks causing inefficiencies and target them for automation.

Companies use a variety of methods to uncover inefficiencies hidden in day-to-day tasks. In the article we reveal how to go beyond surface-level analytics and collect clean data that drives smarter automation.

Traditional manual methods of capturing data

Interviews and surveys

One of the most popular ways to understand how the work is getting done is to ask employees what tasks they perform and how. Such interviews can be conducted in the form of a real-life interview or in written form (e.g. surveys or questionnaires). But regardless of format, these methods rarely provide complete accuracy or objectivity. The range of reasons for this differs:

1. Human errors
Considering the volume of routine manual tasks employees have, mistakes arise from time to time and create inefficiencies

2. Knowledge gaps
Insights that employees share during an interview might be limited due to unclear task scope or difficulty explaining how work is done on the spot

3. Intentional omissions
Some employees may hide their mistakes on purpose, as getting punished can affect their image

Document and SOP review

When conducting business process analytics, analysts first things first get to documents like policy manuals and SOPs. These documents typically describe the happy path – the ideal version of how processes should run. It’s important to have such documents, as they help to familiarize teams with ‘should-be’ processes. But unfortunately, without a relevant clear picture of ‘as-is’ business process it’s virtually impossible to benchmark against the happy path.

Process observation

This method includes watching a specific business process. A business analyst observes each step of their processes and takes notes on how the process unfolds in reality, measuring how much time each step takes. After observing, they interview employees to better understand what challenges they might experience. Based on the information collected, they make reports and build maps to help generate automation ideas.

Challenges of manual data collection

All the methods listed above are widely used to get a picture of what business processes are like. However, they have their own disadvantages due to the manual nature of data collection. Because these methods rely on humans, they’re inherently less objective and more prone to errors and hiccups. What’s more, since there are far more employees than analysts, collecting data manually becomes slow and inefficient. And consequently, if data on an employee’s business process is not collected in real time, by the time data is analyzed, some of it may outdated or irrelevant.

Task Mining – a modern approach to data collection

Living in the era of technological developments, it’s hard to deny existing tools for achieving operational efficiency much faster and easier. They have the upper hand when it comes to data collection and processing. As they conduct it automatically, ensuring 100% success of potential business process optimization (BPO), because automatic nature of the method guarantees data accuracy and relevancy.

What is Task Mining?

Unlike other methods of analytics, Task Mining drills down to the task layer, so you can have granular picture of business processes. The data it collects is not limited to any informational system and can show what’s beyond the human eye can see.

How Operavix Task Mining works

Task Mining is a technology that helps to understand how employees get the work done at the task level. Traditionally, companies used manual methods for data collection and extraction that were quite time-consuming. Operavix takes an automated, data-driven approach that eliminates manual work. Let’s explore how it works based on a real customer story.

Operavix case study: procurement optimization

A pharmaceutical company didn’t understand how procurement process ran and turned to Operavix team to illuminate hidden inefficiencies at the task level.

First, Operavix collected user interaction data from employees’ PCs. This method provided the full picture of what’s happening in the business process. Then, Operavix extracted tasks and grouped them into logical categories. As a result, we found around 10 areas for optimization or automation. Among them we identified key zones with the highest potential for automation: payment request creation, filling out contracts with counterparties and supplier price registration.

Operavix optimized the areas and accelerated the procurement cycle by 17%.

Key benefits of using Operavix

1. Automated task analytics
Operavix captures user interaction data, extracts business tasks and identifies automation potential without data analyst involvement

2. Process agnostic approach
The system is not tied to a specific process, it works across all business processes and departments

3. Full transparency into tasks
With Operavix you’ll see what’s really going on in your business processes, as it provides visibility into employees’ tasks step-by-step.

Want to see how Operavix collects data for quality business analytics?

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