OPSM 301 Operations Management

Class 2:

Business process flows:

Measurement

Koç University

Zeynep Aksinzaksin@ku.edu.tr

Announcements

Wrap-up: King Sooper’s video New module: business process flows From notes and handouts Study questions Also: cases at the end

– Kristen’s Cookie– Benihana

Performance Measurement

External performance strongly depends on output, input, and resource markets, and transformation effectiveness of the process

Internal performance measures: processing cost, flow time, variety, service availability...

The Dynamics of a Process

We examine processes from the perspective of flow To study process flows, we first answer three important

questions:– On average, how many flow units pass through the process

per unit time?

– On average, how much time does a typical flow unit spend within process boundaries?

– On average, how many flow units are within process boundaries at any point in time?

Operational Measures

On average, how many flow units pass through the process per unit time?

THROUGHPUT RATE (TH)

Operational Measures

On average, how much time does a typical flow unit spend within process boundaries?

FLOW TIME (FT)

Operational Measures

On average, how many flow units are within process boundaries at any point in time?

INVENTORY (I)

LITTLE’S LAW

Relating throughput rate, flow time, and inventory

Throughput RateInventoryFlow Time

Inventory I[units]

Throughput Rate[units/hr]

... ...... ......

Flow Time T [hrs]

...Inventory I

[units]

Throughput Rate[units/hr]

... ...... ...

Flow Time T [hrs]

Time=0

...Inventory I

[units]

Throughput Rate[units/hr]

... ...... ...

Flow Time T [hrs]

Time=t

...Inventory I

[units]

Throughput Rate[units/hr]

... ...... ...

Flow Time T [hrs]

Time=FT

Understanding Little’s Law: Consider a first come first served Queue

An Intuitive Argument for Little's Law

Consider a process with the FCFS queue discipline

An order departs the process: At this moment there are I (Inventory) orders within the process

The orders that are in the process now are the ones that came after our departing order had arrived, in other words, they arrived during the waiting period of the departing order

Since order arrival rate is equal to the throughput rate, we have the following relationship:

Inventory = Throughput Rate x Flow Time

Once again...

Throughput RateInventoryFlow Time

Inventory = Throughput x Flow Time

Flow TimeInventory

Throughput Rate

Little’s Law basics

Little’s Law is for a system in steady state: input rate = output rate

Applies to most systems, even those with variability

Uses AVERAGE values

Example: flow unit is material

Fast food restaurant processes an average of 5000kgs, of hamburgers per week. Typical inventory of raw meat in cold storage is 2500kg.

Throughput R=5000kg/week Average Inventory I=2500 kg. Average flow time T=I/R=2500/5000=0.5 weeks

Example: flow unit is customers

A café in Beyoglu serves on average 60 customers per night. A typical night is about 10 hours. At any point there are on average 18 customers in the café.

Throughput R=60 customers/night; 6 customers/hour

Average Inventory I=18 customers Average flow time T= I/R= 3 hours

Example: flow unit is cash

A steel company processes $400 million of iron ore per year. The cost of processing is $200 million per year. The average inventory is $100 million. How long does a typical dollar spend in the process?

R=$600 million/year I=$100 million T=I/R=1/6 year or 2 months

Example

Koç University

3000 studentsenrolled

600 new students admitted on average

Example: MBPF Finance Inc.adapted from Managing Business Flows, by Anunpindi et al.

MBPF Finance Inc. provides loans to qualified customers. The company receives about 1000 loan applications per 30-day working month and makes accept/reject decisions based on an extensive review of each application

MBPF Finance Inc.

Currently, MBPF Finance Inc. processes each application individually. On average, 20% of all applications received approval. An internal audit showed that, on average, MBPF Finance Inc. had about 500 applications in process at various stages of the approval procedure, but on which no decisions had yet been made.

In response to customer complaints about the time taken to process each application, MBPF Finance Inc. called in OPSM Consulting Inc.

Example: cont’d

OPSM Consulting found out that although most applications could be processed rather quickly, some took a disproportionate amount of time because of insufficient and/or unclear documentation. They suggested the following Process II:

Because, the percentage of approved applications is fairly low, and Initial Review Team should be set up to pre-process all applications according to strict but fairly mechanical guidelines.

MBPF Finance Inc.

Each application would fall into one of three categories: type A (looks excellent), type B (needs more detailed evaluation), and type C (reject summarily). Type A and B applications would be forwarded to different specialist subgroups

Each subgroup would then evaluate the applications in its domain and make accept/reject decisions

Example: (cont’d)

Process II was implemented on an experimental basis. The company found out that, on average, 25% of all applications were of type A, 25% were of B, and 50% were of C. Typically, about 70% of type A and 10% of B were approved on review.

Example (cont’d)

Internal audit checks showed that, on average, 200 applications were with the Initial Review Team undergoing preprocessing. Only 25 were with the Subgroup A Team undergoing the next stage of processing and approximately 150 were with the Subgroup B Team

MBPF Finance Inc. would like to determine if the implemented changes have improved service performance.

FlowLoan Inc.(Initial Process)(Initial Process)

AcceptReview

200/month

500 Reject 800/month

20%

80%

1000/month

FlowLoan Inc.(Modified Process)(Modified Process)

30%

90%

InitialReview

200

Subgroup AReview

Subgroup BReview

Accept

Reject

200/month

800/month

25%

25%

70%

10%

25

150

1000/month

50%