Workforce Management & BPM Integration

Welcome Robert M. Shapiro

Senior Vice President: ResearchGlobal 360

SessionTitle:Workforce Management & BPM integration

April 21-23, 2008

Renaissance Washington, DC

Overview

• Business Process Management Suite• Analytics Architecture• Simulator• Workforce Management Scheduler• Case Study: ROI in Wholesale Lock Box

application• Typical Pattern of Use• Conclusions

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BPMS Overview

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Part

icip

an

ts,

UD

Fs, X

PD

LAnalytics Architecture

Staging and Event

Queue Tables

Staging and Event

Queue Tables

Fact and Dimension

Tables

Fact and Dimension

TablesPublish

AE Relational Database

Events OLAP andDataMining Databases

OLAP andDataMining Databases

Process

Analysis Engine

ProcessEngine

ProcessEngine

Administration

Con

trols

An

aly

sis

En

gin

e

Exp

ose

sU

DFs

Tri

gg

ers

Cu

be P

roce

ssin

g

Mon

itors

DB

s

Queries

Web Service

Con

text

Data

Client

Business Operations

April 21-23, 2008


OVERVIEW OF SIMULATION

• The typical simulator for making predictions in a BPMS environment is a discrete event simulator. Preparation of a simulation run is commonly referred to as a scenario. The scenario consists of:– Set of processes to be simulated– Incoming work (arrivals)– Resources, Roles and Shifts– Activity Details– Simulation Options

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Incoming Work

• Actual– Arrival rates for work items, based on

historical data. Includes key attribute values.

• Forecast– Projected arrival rates, including key

attribute values.

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Resources, Roles and Shifts

• Human Resource Data– Roles

• Defines the process activities (Tasks) the person can perform.

– Availability• Scheduled work hours. Includes breaks, holiday and vacation

information.

– Proficiency• Skill rating for each job position.

– Salary (Hourly Rate).

• Equipment Data• Equipment could be, for instance, Check Sorter in Check Clearing operation.

– Type– Role– Quantity

– Throughput

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Activity Details

• Activity Durations– How long each activity (Task) takes. May be

characterized by a distribution.• Decision distributions

– For each decision, the probability of each outcome.

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Simulator Outputs

• Staff requirements by role and time period– for each time period, how many people are required

for each role.• Staff utilization by period• Equipment utilization by period• Cycle time deadline and holdover reports

– Percent satisfying SLA for end-to-end cycle time.• Unprocessed volume by period

– Work in Progress Report by period• Work arrival profile report

– Arrival volume by period• Activity summary report

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Output Example: To-Be Staff Utilization

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all staff /Utilization all staff /Excess Capacity

9/00

9/03

9/06

9/09

9/12

9/15

9/18

9/21

10/0

010

/03

10/0

6

10/0

910

/12

10/1

510

/18

10/2

1

11/0

011

/03

11/0

6

11/0

911

/12

11/1

5

11/1

811

/21

12/0

0

12/0

312

/06

12/0

9

12/1

212

/15

12/1

8

12/2

1

160

150

140

130

120

110

100

90

80

70

60

50

40

30

20

10

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Scheduler

• A Workforce Management Scheduler assigns detailed schedules to the staff of an organization. It uses two input sets:– Work load drivers that define how much work

has to be done in each time period and what skills are required to perform the work.

– Resource characteristics that define staffing availability, preferred work hours, work rules, salaries and so forth.

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Output Example: To-Be Work In Progress

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A2165_Set_Work_Unit_S A2211_Distribute_Extract A2212_Open_Out_Extra A22131_Extract_Opened

9/00

9/03

9/06

9/09

9/12

9/15

9/18

9/21

10/0

0

10/0

3

10/0

6

10/0

9

10/1

2

10/1

5

10/1

8

10/2

1

11/0

0

11/0

3

11/0

6

11/0

9

11/1

2

11/1

5

11/1

8

11/2

1

12/0

0

12/0

3

12/0

6

12/0

9

12/1

2

12/1

5

12/1

8

12/2

1

180,000

160,000

140,000

120,000

100,000

80,000

60,000

40,000

20,000

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Scheduling Algorithm

• The scheduling algorithm creates a schedule for each resource, trying to precisely match the work load.

• The result is generally not perfect. In some time periods there is more staff than is needed; in other time periods there is less.

• The algorithm has to contend with holiday and vacation schedules, minimum and maximum shift lengths, hours per week, skill sets and so forth.

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Fit of a Schedule

• Understaffing in a time period implies that some work will not be completed. Schedulers usually do not propagate the incomplete work. It is treated like a dropped call in a Call Center.

• Overstaffing represents excess resource availability in a time period and offers the opportunity for cost savings by better scheduling.

• A scheduling program usually provides some measure of the ‘fit’ of a schedule based on the understaffing and overstaffing.

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Scheduler Inputs

• Staff requirements by role and time period– Workload demand. Historical Data or Projections.

• Roles– For each person, what positions (roles) they can fill.

• Availability– Preferred work hours, possible work hours.

• Proficiency– Performance measure for each role.

• Minimum and maximum work hours– per day, week and month.

• Break rules and Holiday schedules.

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Availability

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Employee Data, Roles and Work Hour Requirements

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Match Resource Supply to Workload Demand

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Generate A Schedule

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Wholesale Lock Box Case Study

• BPMN Process Model• Process Hierarchy• Current Productivity• Model FTE Requirements• First Wave Opportunity• Second Wave Opportunity• Summary of Opportunity

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Overview of Process Hierarchy• Process Enterprise Payments• Proof Items Remotely• Item Processing

– Proof Work• Receive Proof Work

– Register Inbound Transportation– Receive and Scan Bag– Open Bag and Scan Bundles– Distribute Work for Encoding

• Encode Work and Correct Operator Difference• Deposit Error Correction• Tray or Box Work and Deliver to Capture

– Item Processing Operations• Receive and Prep Checks for Capture

– Receive Items– Open Package– Prep and Tray Work for Capture– Receive Encoded Proof or Lockbox Items– Receive Branch Captured or Other Items for Power Decode– Open Branch/Unencoded Bags– Prep and Tray Branch/Unencoded Work for Power Encode

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Process Hierarchy (continued)

• Capture and Sort– Conventional Prime Capture– Transit Repass– Cycle and Exception Sorts– Image Capture– Power Encode

• Reject Repair– Repair Prime Pass Rejects– Process Repass/CP Hard Rejects– Document Repair

• Reconcilement– Reconcile Prime Entries– Balance Image Presentment– Reconcile and Repass Entries– Endorse Entry and Post ICRE

• Cash Letter Prep and Dispatch• Image Balancing

– Balance Teller Errors, ICR errors and Key Errors– Balance Entries– Endorse and Post Items

• IRD Processing• Image Exchange• Retail Lockbox

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Current Productivity• Productivity is reflected as total items per total paid hours• Wholesale Lock Box Operation for one region of major bank:

• The current productivity of 41 WLB items per hour is equivalent to median benchmark productivity

• Based on the current productivity profile the model computed a labor utilization rate of 70% including paid time off

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Model FTE Requirements

• Model FTE compared to current FTE

• The model FTE target is a long-term end state goal

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First Wave Opportunity

• Based on experience working with similar customers, it is more realistic to implement the scheduling opportunity in two waves

• The first wave productivity target is slightly better than the benchmarking 66th percentile

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Second Wave Opportunity

• The longer term goal should be the end-state Model FTE target

• The second wave productivity target is slightly less than the benchmarking 85th percentile

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Summary of Opportunity

• Summary of paid hour benefit

Annualized Paid Hour BenefitAnnual Fully

Loaded SalarySaving

Opportunity

32.9 FTE 29,276$ 963,186$

Annualized OT Benefit Annual Salary Total CostSaving

Opportunity

38.7 FTE @ Straight Time 22,872$ 885,146$

38.7 FTE @ Time and a Half 34,308$ 1,327,720$ 442,573$

• Summary of overtime reduction benefit

• Total combined benefit – $1,405,759

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Typical pattern of Use

• The BPM system has been in operation for a while. The analytics component has collected statistics about work arrival patterns, resource utilization, work-in-progress and activity loads.

• The appropriate data, staff requirements by role and time period (Workload demand), is extracted from the analytics and fed to the scheduler.

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Schedule

• The scheduler has other inputs that characterize the staff resources. These include for each person their roles, availability, proficiency, minimum and maximum work hours. Also included are ‘break rules’ and holiday schedules.

• The scheduler generates a best-fit schedule that matches the Workload demand to the staff, minimizing the understaffing/overstaffing according to adjustable criteria. The algorithm may be based on neural nets or some other constraint-based optimization technique.

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Simulate

• The new resource schedule is passed back to the simulation component of the BPM system. A scenario is created based on the set of business processes being studied, work arrivals (derived from the analytics), the new resource schedule and activity details (also determined from the analytics).

• The simulation run generates a new set of data which includes an updated version of Workload demand, along with other information about the effect of the new staff assignment. This data includes:– Staff utilization– Equipment utilization– Cycle time SLA report– Unprocessed volume– Activity summary report

• The optimization loops back to the scheduler until no further improvement is possible.

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Conclusion

• This approach appears to be most suited to situations where the business process being executed is well structured (rather than ad hoc), the work item arrivals can be characterized as repeatable patterns and the total resource pool to be scheduled is large. Under these circumstances it is not unusual to achieve a 10 to 20% reduction in staff costs.

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Thank You!Robert M. ShapiroSenior Vice President: ResearchGlobal 360

Contact Information:[email protected]

Technology

Workforce Management & BPM Integration