A team can report strong productivity while its most important work continues to age.

That sounds contradictory.

But it can happen when employees are allowed to choose which cases they process.

Given a queue containing easy, difficult, new and old work, people may naturally gravitate toward transactions that are:

  • Easier to complete
  • More familiar
  • Less risky
  • Newer
  • Faster to process
  • Less likely to require research or follow-up

This behaviour is often called cherry-picking.

It does not necessarily mean employees are intentionally avoiding work.

In many cases, the operating model itself makes selective work picking possible.

And once that happens, traditional productivity numbers can become misleading.

What Is Cherry-Picking in Operations?

Cherry-picking occurs when employees can select favourable work from a larger queue rather than receiving work through controlled allocation rules.

Consider a queue containing:

Case A
5-minute expected handling time

Case B
35-minute expected handling time

Case C
Requires research and follow-up

Case D
Simple data update

If employees are free to select their next transaction, Cases A and D may naturally be processed first.

Cases B and C may remain behind.

Now multiply that behaviour across hundreds or thousands of transactions.

The operation may start developing an unusual pattern:

Strong completion volume

but

Increasing aged backlog

That is one of the clearest warning signs that work allocation deserves attention.

Why Employees May Cherry-Pick

It is easy to assume cherry-picking is simply an employee-performance issue.

That is not always fair or accurate.

Employees may choose easier work because of how performance is measured.

Suppose an organization evaluates employees heavily on:

Cases Per Hour — CPH

An employee may realize that processing six 10-minute cases produces a better CPH result than spending an hour resolving one complicated case.

The employee is responding logically to the incentive structure.

This means cherry-picking can be created by:

  • Poor allocation controls
  • Productivity targets
  • Inconsistent complexity
  • Lack of skill routing
  • Pressure to meet daily volumes
  • Poor backlog visibility
  • Inadequate performance measures

The solution therefore needs to address the operating model, not only individual behaviour.

How Cherry-Picking Distorts Productivity

Imagine two employees.

Employee A

Processes 48 simple cases in 8 productive hours.

CPH:

48 ÷ 8 = 6 CPH

Employee B

Processes 24 complex cases in 8 productive hours.

CPH:

24 ÷ 8 = 3 CPH

At first glance, Employee A appears twice as productive.

But suppose the expected handling time is:

Simple cases: 10 minutes

Complex cases: 20 minutes

Both employees may actually be performing exactly at the expected standard.

Raw completed volume hides the difference.

This is why productivity analysis should consider the type and complexity of work being processed.

Cherry-Picking Can Create an Aging Problem

One of the biggest consequences of selective work picking is backlog aging.

Suppose employees regularly choose new, straightforward cases.

Incoming volume continues to be processed.

Daily productivity looks healthy.

But difficult cases from previous days remain untouched.

The operation can therefore report:

1,500 cases received

1,500 cases completed

and still have a growing aged backlog.

The total backlog may even appear stable.

The problem is hidden inside the aging distribution.

That is why operations teams should analyze both:

Backlog volume

and

Backlog age

For a deeper discussion, see:

How to Manage Backlog, Aging and SLA in Case-Based Operations

https://www.praevexa.com/insights/manage-backlog-aging-sla-case-operations

Older Work Often Becomes Harder

There is another operational consequence.

Cases that sit in backlog can become harder to resolve.

Information may become outdated.

Customer expectations may increase.

Additional follow-ups may be required.

Escalations may occur.

Documents may need to be requested again.

SLA may already be breached.

So avoiding a complicated case today can make it even more complicated tomorrow.

This creates a cycle:

Difficult case avoided

↓

Case ages

↓

Complexity increases

↓

Case becomes even less attractive

↓

Further delay

Controlled allocation helps break that cycle.

SLA Can Be Damaged Even When Productivity Looks Good

Suppose a team completes 1,000 cases today.

That sounds positive.

But if most of those cases were recently received while 300 old cases are approaching SLA breach, high completion volume may not translate into good service performance.

This is why managers should not ask only:

How many cases did we complete?

They should also ask:

Which cases did we complete?

and:

Which cases did we leave behind?

Those questions provide a much more accurate picture of operational health.

The Simplest Control: FIFO

FIFO means:

First In, First Out

The oldest eligible case is worked first.

Instead of employees selecting any case from the queue, the workflow determines the next transaction based on received date.

This immediately reduces the ability to choose only newer work.

FIFO is especially useful when:

  • Work has similar priority
  • Cases have similar complexity
  • Aging control is important
  • Service commitments are date-based

But FIFO alone does not solve every problem.

Priority Must Sometimes Override FIFO

Imagine two cases.

Case A

Age: 6 days
Priority: Standard

Case B

Age: 1 day
Priority: Critical

Pure FIFO would select Case A.

The business may require Case B to be handled first.

This means operations may need a hierarchy such as:

Critical Priority

↓

High Priority

↓

Standard Priority

and then FIFO within each group.

That maintains aging discipline without ignoring genuine business urgency.

Skills Should Also Control Eligibility

Cherry-picking and work allocation become more complicated when employees have different skills.

A processor trained only for Worktype A should not receive Worktype B simply because it is the oldest case.

A stronger workflow first determines:

Which cases can this employee process?

Then applies allocation rules to the eligible work.

For example:

Skill Eligibility

↓

Priority

↓

SLA Risk

↓

FIFO

This provides much stronger control than allowing employees to browse the entire queue.

For more detail:

FIFO vs Priority vs Skill-Based Work Allocation: Which Is Better?

https://www.praevexa.com/insights/fifo-priority-skill-based-work-allocation

Consider SLA Risk, Not Just Received Date

Two cases can have different SLA requirements.

For example:

Case A

Age: 7 days
SLA: 30 days

Case B

Age: 5 days
SLA: 7 days

FIFO considers Case A older.

But Case B is only two days away from SLA breach.

A more sophisticated workflow can use:

Remaining SLA Time

as part of case selection.

A practical routing hierarchy might therefore be:

Skill Eligibility

↓

Critical Priority

↓

Cases Closest to SLA

↓

FIFO

This directs capacity toward the work carrying the greatest operational risk.

Prevent Employees from Browsing the Entire Queue

One of the simplest design changes is also one of the most effective.

Instead of showing every available case and asking employees to select one, give them a controlled action such as:

Get Next Case

The system then evaluates the routing rules and assigns the appropriate transaction.

This creates several benefits:

  • Less cherry-picking
  • Clear ownership
  • More consistent allocation
  • Reduced duplicate work
  • Better workload distribution
  • More reliable productivity measurement

Employees focus on processing work rather than deciding which work to process.

Exclusive Ownership Is Important

Once a case has been allocated, the system should establish clear ownership.

Otherwise another employee may open the same case.

A controlled workflow should answer:

Who owns this case right now?

The owner remains responsible until the case is:

  • Completed
  • Reassigned
  • Pended according to workflow
  • Returned to queue
  • Cancelled

This creates accountability and helps prevent duplicate processing.

But Controlled Allocation Should Not Become Inflexible

There is a risk of going too far.

An operations manager may occasionally need to override the normal routing process.

For example:

  • A customer escalation
  • Specialist investigation
  • Training case
  • High-value transaction
  • Employee absence
  • Work redistribution
  • Urgent client request

Therefore, supervisors should generally retain controlled manual-assignment capability.

The distinction is important:

Manual assignment should handle exceptions.

It should not necessarily be the default method for distributing thousands of routine cases.

Compare Work Mix Before Comparing Employees

If productivity is used for performance management, managers should look at the work mix behind the number.

For example:

EmployeeCasesProductive HoursCPH
Employee A5086.25
Employee B3284.00

At first glance, Employee A appears much stronger.

But now add case type:

Employee A processed primarily simple transactions.

Employee B processed complex transactions.

The comparison changes immediately.

Useful dimensions may include:

  • Work type
  • Complexity
  • Expected AHT
  • Priority
  • Skill
  • Case outcome
  • Rework

Productivity should be interpreted within the context of the work performed.

Weighted Productivity Can Help

Some operations use weighted transactions to account for complexity.

For example:

Simple case = 1 point

Medium case = 2 points

Complex case = 4 points

An employee completing:

20 simple cases
10 medium cases
5 complex cases

would generate:

20 × 1 = 20

10 × 2 = 20

5 × 4 = 20

Total weighted output:

60 points

This can sometimes provide a fairer productivity view than raw case count.

Another approach is to use standard handling times or expected AHT.

The appropriate methodology depends on the operation.

Monitor Work Distribution

Managers should also examine whether certain employees consistently receive particular types of work.

Useful questions include:

  • Who receives the most complex cases?
  • Who receives the easiest cases?
  • Are older cases distributed fairly?
  • Are particular employees repeatedly working one work type?
  • Are high-priority cases concentrated with too few employees?
  • Are some skills overloaded?

Work-distribution analysis can reveal problems that productivity reports alone cannot show.

Monitor the Oldest Cases

One useful management control is simply monitoring the oldest open transactions.

For example:

Top 20 Oldest Cases

For each case, management might review:

  • Received date
  • Age
  • Work type
  • Owner
  • Status
  • Priority
  • Follow-up date
  • SLA position

If the same cases remain on the oldest-case list repeatedly, management can investigate why.

The cause may be:

  • Missing skill
  • Process complexity
  • External dependency
  • Incorrect routing
  • Employee avoidance
  • Policy issue
  • System limitation

This turns aging into a diagnostic tool.

Look for the Productivity-Aging Paradox

One of the most useful warning signals is:

Productivity improving while aged backlog gets worse.

For example:

Month 1:

CPH = 5.2
Cases aged 10+ days = 500

Month 2:

CPH = 5.8
Cases aged 10+ days = 850

Month 3:

CPH = 6.1
Cases aged 10+ days = 1,200

Productivity appears to be improving.

Operational risk is clearly increasing.

Possible explanations include:

  • Cherry-picking
  • Changing case complexity
  • Incorrect skill distribution
  • Priority imbalance
  • Capacity shortage in one work type
  • Difficult cases repeatedly deferred

This is why CPH should never be reviewed in isolation.

Quality Must Also Be Considered

Employees under heavy productivity pressure may avoid complex cases.

They may also process work too quickly.

So controlled allocation should be monitored alongside quality.

A balanced operating view might include:

Productivity

Quality

SLA

Backlog Aging

AHT

Rework

Utilization

A team performing well across these measures is much more likely to be operating sustainably.

Supervisor Behaviour Matters Too

Cherry-picking is not always caused by employees.

Supervisors can unintentionally create similar behaviour.

For example, a supervisor under pressure to improve daily completion numbers may allocate easier work because it produces immediate output.

The daily dashboard improves.

The difficult backlog remains.

Therefore, allocation rules should be aligned with broader operational goals rather than short-term volume alone.

Good Work Allocation Improves Fairness

Controlled work allocation is not only about efficiency.

It can also improve fairness.

Without structured routing:

One employee may continuously receive difficult work.

Another may regularly process straightforward transactions.

Their productivity is then compared using the same target.

That creates understandable frustration.

Structured allocation and work-type visibility help management make more credible performance comparisons.

How to Know Whether Cherry-Picking Is Happening

Possible warning signs include:

  • New cases completed while old cases remain untouched
  • Rising aged backlog despite strong productivity
  • Significant differences in case complexity between employees
  • Certain work types consistently accumulating
  • Employees repeatedly processing the same easy categories
  • High CPH combined with poor SLA performance
  • Cases repeatedly reassigned
  • Difficult work left until supervisors intervene

No single indicator proves cherry-picking.

But several appearing together deserve investigation.

A Practical Anti-Cherry-Picking Framework

A useful operational approach can be:

Step 1 — Define Worktypes

Separate processes with different rules and complexity.

Step 2 — Define Skills

Determine who can process each type of work.

Step 3 — Define Priority

Establish objective critical, high and standard rules.

Step 4 — Define SLA Risk

Identify cases approaching service-level breach.

Step 5 — Apply FIFO

Process the oldest case among otherwise equal eligible work.

Step 6 — Assign Exclusive Ownership

Give the case to one employee.

Step 7 — Measure Work Mix

Compare productivity with case complexity and work type.

Step 8 — Monitor Aging

Watch which cases remain behind.

This creates an operating model that is difficult to reproduce reliably through employee self-selection alone.

From Case Picking to Controlled Work Allocation

The transition often looks like this:

Employee Searches Queue

↓

Employee Selects Case

↓

Supervisor Allocates Work

↓

System Determines Eligibility

↓

Priority and SLA Rules Applied

↓

Oldest Appropriate Case Selected

↓

Exclusive Ownership Assigned

The goal is not to remove judgment from the operation.

The goal is to use judgment when it adds value rather than requiring it for every routine case.

How Praevexa CaseFlow Can Help

Praevexa CaseFlow is designed for case-based and back-office operations that need structured work allocation and clearer operational control.

CaseFlow supports capabilities including:

  • Configurable Departments, Queues and Worktypes
  • Employee skill eligibility
  • Priority-based routing
  • FIFO/LIFO allocation
  • Controlled case assignment
  • Exclusive case ownership
  • Manual supervisor assignment
  • Pend and hold workflows
  • Follow-ups
  • Rework and reassignment
  • TAT and SLA monitoring
  • AHT and CPH
  • Productivity and utilization
  • Backlog and aging visibility
  • Role-based Operations Intelligence

Instead of requiring employees to search a large tracker and choose what to process, the workflow can help determine the appropriate next case.

The objective is simple:

Put the right work with the right person at the right time — while giving management visibility into what is being left behind.

Learn more about Praevexa CaseFlow:

https://www.praevexa.com/CaseFlow.aspx

Related reading:

FIFO vs Priority vs Skill-Based Work Allocation: Which Is Better?

https://www.praevexa.com/insights/fifo-priority-skill-based-work-allocation

How to Manage Backlog, Aging and SLA in Case-Based Operations

https://www.praevexa.com/insights/manage-backlog-aging-sla-case-operations

What Is Case Management Software for Back-Office Operations?

https://www.praevexa.com/insights/case-management-software-back-office-operations