Is manual data processing making your organization error-prone?

Manual data processing leads to three critical risks: processing errors costing organizations an average of $12.9M annually, team inconsistencies creating data silos, and delayed insights that undermine decision-making. Automated data pipelines using platforms like CloverDX eliminate these risks while freeing teams from repetitive work.

In McKinsey’s vision of the “data-driven enterprise of 2025”, automation plays a vital role. By automating recurring decisions and “basic day-to-day activities”, employees will be “free to focus on […] innovation, collaboration, and communication.”

Yet despite this appealing image, even the most ambitious organizations continue to rely on manual data processes. Even in advanced analytics projects, 80% of company time is spent on repetitive tasks like data preparation.

The first step to securing the benefits of automation is understanding the true cost of your manual data processes. Read on to find out the 3 critical risks you can't ignore, and just how significant their impact can be — and how modern data platforms can help.

The risks of manual data processing

1. Processing errors

Processing errors are the most obvious risk of manual data processing — but it’s easy to understate their impact.

If your data processing tasks are time-consuming and repetitive, mistakes are inevitable. Performing the same simple tasks week after week makes it virtually impossible to avoid momentary lapses of concentration or slips of the finger. And that’s all it takes for errors to find their way into your datasets — and potentially impact your decision-making.

With poor-quality data costing organizations an average of $12.9 million each year, it’s not something you can afford to ignore.

2. Inconsistencies between teams

Manual processes are often reactive solutions — a job needs to be done, and this is the quickest way to tackle it.

But this means your processes will lack consistency. Each of your teams will face different challenges. And if their day-to-day data demands aren’t the same, their manual data processes will likely diverge, too.

They might:

• Adopt different tools to store or process data
• Take different approaches to data validation and cleansing
• Develop different ways of formatting key fields

And when business teams (who are often closest to the data) aren't able to easily collaborate with technical teams, they're more likely to resort to shadow processes or workarounds.

As a result, your organization’s datasets can quickly become inconsistent. This makes it easier for data silos to emerge, as sharing data becomes more time-consuming. And without alignment on best practices, it’s harder to guarantee your data is error-free.

3. Delayed insights

Your business insights are where your data truly delivers value for your organization. But to be effective, these insights need to be timely. Having a clear view of your performance three months ago won’t help you make effective decisions today.

Unfortunately, manual processes mean your insights will be subject to significant delays. This is partly a result of the issues mentioned above. Poor-quality data means you spend more time validating your datasets and correcting errors, and less time drawing conclusions. Meanwhile, inconsistencies between teams make it harder for you to build an integrated view.

But there are deeper issues that can arise from an over-reliance on repetitive manual tasks. By spending more time on manual work, staff are more likely to feel stressed and disengaged. This makes it harder for them to develop critical insights or identify innovative solutions.

How CloverDX eliminates manual data risks

CloverDX's data integration platform helps data teams overcome many of the risks and problems that come with manual data processing.

Eliminate manual data processing errors

• Automated validation built into workflows catches errors before they flow downstream
• Built-in data quality rules ensure consistency across pipelines
• User-friendly interfaces help domain experts review and correct data

Standardize across teams

CloverDX Business Tools enable both technical and business teams to work together on the same platform.

• Engineers build robust data pipelines in CloverDX Designer
• Business users handle data quality reviews, mappings, and approvals through user-friendly interfaces
• No more Excel back-and-forth or shadow IT processes
• Complete audit trails maintain governance and control

Accelerate time to insight

• Free up time from engineers by offloading work to business users, eliminating bottlenecks
• Schedule jobs to run on autopilot, reducing the need for manual input
• Automated alerts notify you of issues immediately, reducing downtime

Case study: Ortec Finance automated data processes, and reduced error-prone manual work by up to 90%

Thomas Hage

Senior Consultant, Ortec Finance

“It's really the click of a button and we run the system. Instead of having typically a 4 or 5 day process of people preparing the data, running the models, checking the results and building the reports to send to the clients, we’ve reduced that to half a day or less.”

Manual vs automated data workflows: A comparison

A real-world example

A CloverDX customer receives data from multiple clients daily, each with different formats requiring transformation before warehouse loading.

The manual approach:

Downloading files from FTP, opening in Excel, visual inspection, cleanup, column manipulation, data import wizards. Impractical at scale.

The scripted approach: 

Multiple scripts handling each step. Still error-prone, opaque, time-consuming.

The CloverDX automated  approach:

A single automated pipeline that:

• Detects file arrival automatically
• Identifies format and layout
• Transforms and validates data with built-in quality rules
• Any records that need review are loaded into Data Manager for domain expert correction and approval
• Loads records to target system
• Logs every step with full error visibility

Result: Fully automated, transparent, scalable process requiring zero or little manual intervention.

Start automating your data processes today

Manual data processes are time-consuming, difficult to manage, and prone to errors. By automating your data processes, you can deliver higher-quality insights at a faster pace — all while reducing the burden on your teams.

Of course, we don’t want to undersell the challenges of automating your data processes. It requires coordinated effort and ongoing investment to deliver results. But the risks of sticking with the status quo are far greater.

A key first step to automating your data processes is ensuring you have the right tools in place to support your efforts.

Or perhaps we should say tool. By adopting a single solution, you can avoid the extra cost and effort associated with an over-elaborate tech stack. You’ll be able to develop a coordinated approach to data automation that links up every part of your organization.

To kickstart your data automation journey, look for a platform that:

• Enables you to develop complex data workflows with ease and manage them all from one place
• Allows business users to automate their own data preparation processes
• Gives your IT team full visibility over your data pipelines
• Supports automated validation checks and error handling

If you’d like to see how CloverDX’s data integration platform delivers all these features, and many more, book a demo today. It’s time to move on from manual data processes — and we’re here to help you.