Too Much Work Is Still Manual and Hard to Scale
Routine work still depends on people reviewing, routing, checking, and following up by hand.
As volume grows, teams still rely on manual review, data entry, routing, follow-up, and error correction to keep work moving. Even with digital tools in place, too many processes still depend on people interpreting inputs and pushing stalled work forward by hand.
Where Manual Work Breaks Down
Where are you feeling this?
- Multiple people or teams are involved in routine work just to keep it moving
- Work slows down or backs up as volume increases
- Headcount has to grow just to maintain current service levels
- Processes still rely on review, routing, follow-up, or exception handling by hand
What This Looks Like in the Real World
This shows up differently depending on how far the environment has modernized. DataBank helps organizations reduce the manual work required to keep routine processes moving.
In more manual environments:
- Work moves one step at a time as teams review documents, check data, and pass tasks along
- Staff open emails, download attachments, rename files, and enter data before the system can process anything
- Teams spend time opening files, checking documents, entering data, and routing work before processing can begin
- Throughput depends on how many people are available to review, route, and clear backlog
In hybrid environments:
- Some steps are digitized, but work still stalls between systems and requires manual follow-up
- Teams chase updates across inboxes, spreadsheets, shared queues, and multiple systems
- Information is copied between systems because platforms do not share it cleanly
- Turnaround times slow as volume grows because more follow-up and queue management is required
In more modern environments:
- Platforms and automation are in place, but work still pauses at approvals, exceptions, or missing information
- Teams monitor queues, fix exceptions, reroute work, and restart stalled tasks
- Shadow processes are created to handle workflow and system gaps
- Throughput varies because too much work still depends on people making decisions step by step
Across all of these, the pattern is the same:
Routine work still depends on people reading, checking, routing, fixing, and following up to keep it moving.
Why This Happens
Incoming work is not consistent enough for systems to handle on its own
Requests, forms, records, invoices, claims, and other work arrive through different channels and in different formats. When what comes in is incomplete, inconsistent, or hard to interpret, teams have to review, classify, check, and prepare it before processing can begin.
The information needed to continue work is not consistently available
Teams lose time searching for files, checking details, correcting errors, and re-entering information across systems. Even when the work itself is predictable, the information around it is not reliable enough for systems to move it forward without help.
The workflow still depends on people coordinating the work
Approvals, handoffs, exception handling, and follow-up often happen outside the system or rely on local workarounds. That leaves people chasing updates, routing work, fixing issues, and keeping tasks moving between teams and tools.
What this leads to:
- Processing slows as volume increases
- Headcount grows just to keep up with volume
- Backlogs build faster than teams can clear them
- Turnaround times and quality vary across teams and shifts
- The business cannot scale work predictably even after investing in digital tools
How We Help Reduce Routine, Manual Work
We help reduce the reading, checking, routing, and follow-up, that slows work down every day.
Step 1
Clean Up Intake
Reduce manual review at the start.
What this looks like:
- Capture data automatically
- Reduce manual entry
- Standardize incoming work
Step 2
Reduce Rework
Less time checking and fixing work.
What this looks like:
- Reduce corrections and re-entry
- Validate information automatically
- Reduce time spent searching
Step 3
Keep Work Moving
Reduce routing and follow-up delays.
What this looks like:
- Automate task routing
- Reduce queue monitoring
- Eliminate extra handoffs
Step 4
Scale the Work
Handle more work without more staff.
What this looks like:
- Reduce backlog growth
- Improve turnaround times
- Support higher work volumes
Ways We Support
We don’t clean up data; we make it usable, connected, and ready for automation.
Make incoming work usable from the start
We help reduce the manual work before processing begins.
What Changes:
- Manual work often begins before the real process even starts. Teams open emails, review forms, sort documents, enter data, and decide what something is before it can move. We help capture incoming work, classify document types, extract key data fields, and standardize formats so systems can process items without manual review and preparation. This is often the right place to start when teams spend time checking or preparing work before it can enter the process.
Our Technology
Organize and govern the information the work depends on
We help reduce time spent searching, checking, and re-entering information.
What Changes:
- Work stalls when the next step depends on finding the right document, validating details, or reconciling data across systems. We help structure and centralize information, connect it across platforms, and ensure systems can access what they need without manual searching, checking, or re-entry. This matters when work slows down not because the task is difficult, but because teams spend too much time locating and validating information.
Our Technology
Help workflows run without constant follow-up
We help keep work moving without constant monitoring and routing.
What Changes:
- The goal is not just to automate tasks. It is to reduce the amount of routine work people still have to manage manually. We help define workflow rules, automate routing decisions, reduce unnecessary approvals, and eliminate manual handoffs so work moves forward without constant queue monitoring and follow-up. This becomes critical when growth increases workload, but efficiency does not improve with it.
Our Technology
Real World Example
A healthcare payor was processing growing volumes of claims-related documents and service requests across multiple teams and systems.
The Challenge:
Digital tools were already in place, but staff still had to review submissions, enter data, route work, follow up on missing information, and monitor queues before items could move forward.
What this leads to:
Growing Backlogs
Queues built faster as volume increased and more items required manual review.
Slower Turnaround Times
Processing slowed because staff had to keep work moving step by step.
Headcount Growth
Additional staff were needed to manage review, routing, follow-up, and exception handling.
The Impact:
Reducing manual review, routing, and follow-up helped the organization process more work without proportional staffing increases.
Faster Turnaround
Work moved through the process more quickly as volume increased.
Less Manual Review
Teams spent less time checking, routing, and correcting routine work.
Reduced Queue Backlogs
Fewer items stalled waiting for review and follow-up.
Frequently Asked Questions
Why is routine work still so manual even after we added digital tools?
Because many processes were digitized without making the work itself consistent enough for systems to handle. If inputs vary, information is hard to trust, or handoffs still happen outside the workflow, people still have to review, check, route, and follow up on work manually.
Where should we start if we want to scale without adding more staff?
Start where teams are spending time preparing, checking, routing, correcting, or following up on repeatable work. If the issue starts with inconsistent intake or manual data entry, that is where improvement needs to begin.
How do we know whether the issue is the workflow or the information around it?
If staff are constantly checking documents, validating details, re-entering information, or searching for what they need before the next step can happen, the problem is usually both. Work cannot scale when the process and supporting information are inconsistent.
Related Pathways
Capture The Start
If work still begins with paper, PDFs, or incoming mail, explore document intake and data capture to lighten the load.
Automate Workflows
If work depends on routing, approvals, or follow-up to keep moving, explore workflow and automation solutions.
Connect Systems
If work stalls between different teams, workflows, or tools, explore integration and orchestration solutions.
Manage Content
If teams lose time searching for documents or supporting information, explore content and ECM solutions.
We roll up our sleeves to solve your greatest challenges.
See where manual work is limiting scale and what to fix first