This document summarizes session 3 of a workshop on workforce centric analytics and continuous improvement. It discusses establishing a culture of continuous improvement through strong communication, feedback processes, and empowering workers with metrics. It also explains how real-time metrics like counts, backlogs, bottlenecks, cycle times, and decision frequency matrices can provide insights and be used to identify areas for improvement. Qualitative analysis methods like process observation are also recommended to complement quantitative metrics.

1. Session 3 of 3
Workforce Centric Analytics
What do they teach us?
Real-time Process visibility and workforce
optimization examples

2. Session 3 Objectives
 Establishing a Culture For Continuous Improvement
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Communicate the Vision
● Molding the Message From Management
 Leveraging the Power of Real-Time Metrics
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Counts and Backlogs
 Understanding Throughput
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Bottlenecks
 Identifying the weak points of the process
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Cycle Time
 A Global or Granular View
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Decision Frequency Matrix
 Learning Workforce Behavior
 Qualitative Analysis
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Going Beyond the Metrics
● Process Observation

3. Establishing A Culture
 Establish a method for feedback
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Ensure that everyone has a voice
A structured method for gathering feedback reduces
hallway discussions
Both negative and positive feedback should be
accounted for
Instil a sense of ownership to the end user by
evaluating feedback and providing a response
 Strong communication by leadership
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The message comes from the top
Management has to support the change effort
Request the end users vision to validate alignment
with management
 Empower the end user with metrics
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Provide the end user with personal and team stats to
validate their role in the company’s success
Implement a reward system based on measured
efficiency gains

4. Real-Time Metrics: Counts and Backlog Trends
 Observation:
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Common Throughput Metrics
Show Us
 Work Entering, Work In
Progress, Work Completed
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Monitoring trends allows you
to determine efficiency gains
 Continuous Improvement:
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Identify which timespans are
have the greatest backlogs
These metrics help recognize
outside contributors to
inefficiencies

5. Real-Time Metrics: Bottlenecks
 Observation:
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Quickly reveal the tasks that are
causing delays
Bottlenecks identify weak points in the
process due to:
 Lack of resources
 Low performers
 Difficult tasks
 Continuous Improvement:
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Investigate why bottlenecks are occurring
● Add resources to difficult tasks
● Divide and conquer
 Split complex tasks into multiple sub-tasks
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Replace resources that are not
performing
Brewmaster Approval: 20/1
20 / 1

6. Real-Time Metrics: Cycle Time
 Observation:
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Cycle time reveals segments of the
process that are causing delays
Determine which individual tasks
take the most amount of time
Monitor the average time to
complete the process
 Find fluctuations across timespans
 Continuous Improvement:
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Shift less experienced resources to
easy/transactional tasks
Investigate why certain process
segments are causing delays
Adjust resources during timespans
when average completion times are
increased

7. Real-Time Metrics: Decision Frequency Matrix

Observation:
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Review how often a user makes one
decision over another in the process
● By adding other variables you can
identify how often invoices are denied by
vendor
● Monitor actions over time to locate
trends

Continuous Improvement:
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Metrics should be used to drive
training
● Streamline the process by sourcing
new vendors that are not causing
denials
● The metrics can be used to verify if
denials have been reduced over time

8. Qualitative Analysis
 Going beyond the metrics
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Requires observation
Everyone develops their own system and routine
Develop a procedure to gather feedback
 Avoiding bypass techniques
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Workers will inevitably find ways to work around a process if it makes their
work easier
Instil ownership to overcome the resistance for change
Determine if controls need to be implemented to avoid bypass techniques
 Process inflexibility
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Is the process design too rigid to allow for exceptions?
Re-evaluate if the exception has become the rule

9. Workshop Wrap Up

Case Study: ClosetMaid
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How we eliminated routine decisions to dramatically improve response times
Session 1: Pitfalls of Analysis
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Identified Pitfalls:
 Client Self Diagnosis
 Focusing on Exceptions
 Not Getting all Perspectives
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
Uncovering corrective actions to avoid common pitfalls of analysis
Session 2: Common Design Pitfalls
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Design Pitfalls:
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Over Engineering
Creating Non-Actionable or Vague Queues
Under Validation
Replicating Paper Processes into Software
Deploying design pitfall resolutions
Session 3: Continuous Improvement
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Establishing a culture for continuous improvement
How metrics can provide visibility and insight
Going beyond the metrics

10. Question & Answer
You have a question, we have an answer

11. Thank you!
Feedback form is an entry into the Smart Watch Raffle - Come see us at Booth 33!