Operations Research in Govt & Commercial Sectorsscsr.jp/document/20130725-SCSR_Sim.pdf ·...

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Operations Research in Govt & Commercial Sectors SCSR Presentation 25 July 2013

Transcript of Operations Research in Govt & Commercial Sectorsscsr.jp/document/20130725-SCSR_Sim.pdf ·...

Page 1: Operations Research in Govt & Commercial Sectorsscsr.jp/document/20130725-SCSR_Sim.pdf · 2014-01-24 · Operations Research Core Competency Definition Discipline of applying advanced

Operations Research in Govt & Commercial Sectors

SCSR Presentation

25 July 2013

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Agenda

Brief Intro to IDSC Public & Private Sector Track Record Potential Areas of Collaboration Discussion

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IDSC Pte Ltd

An Introduction

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Operations Research Core Competency

Definition Discipline of applying advanced analytical methods to

rich data to help make better decisions Distinctive Nature

Goes beyond informing to advising • Can find the best among many choices, in reasonable time • Can consider & balance multiple objectives • Can help measure, control & reduce risk

Scientific & verifiable

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IDSC Partial Client List

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Areas of Consultancy Logistics

Supply chain design, maint optimisation Fleet routing, warehouse optimisation

Manpower Modeling & designing MP policies &

organisational structures Optimising ROAs & posting plans Rostering & ranking software

Others Telecommunications policy (TAS) SPF BPR - Logs, Traffic & Licensing Corporate modeling & technical audit

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Public Sector Operations Research

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Singapore Ammunition Logistics

Singapore is a tiny country of 710 sq km

Where ammunition is stored, people cannot live or work nearby

Quite a large military for its size – how to store the ammunition?

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Procurement & Turnover Planning

Time (year) 3 6 9

3

6

9

12 15

12

18

21

15

24

27

30

33

36

39

0 18

Life-cycle perspective of buying & turning over perishable items

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Containerised Load Planning With Routing & Storage Considerations

Lot Synchronisation

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If every pallet can be put away such that they can be retrieved without any blockage, why do we need racks?

Entrance

Main Aisle

Narrow Aisle

Narrow Aisle Narrow Aisle

Narrow Aisle

7 7 7 7

2 2

2 3

1 2

6 6 6

4 3

3 3

2 2

1 1

4

1 2 3 4 5 6 7

1 1 1

3 4 5

5 6 7

7

1 2 3 4 5 6 7

5 5 5 5 2 1

7 5 3 1

7 4 2 1

6 3 2 1

5 3 1 1

7 6 6 5

7 6 5 4

7 6 5 4

7 6 5 4

2 2 2

4 6 6

Floor Planner (Palletized Warehouse)

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Dynamic Cross Docking

Total Safety Stock (Approx) De-centralised ≈ σ n √ (L + 1 ) Centralised ≈ σ √ n (L + 1 ) Cross Dock ≈ σ n √ (L1/n + L2 + 1 )

n identical warehouses, each with demand std dev σ, L is lead time

L1 L2

Crossdock

L Factory Factory Warehouses

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Dynamic Cross Docking & Ports Why should ports only seek to process containers as

quickly as possible? What if one can dynamically cross-dock once customs is

cleared? Warehouse-on-wheels ??

Ports with cross docks

Cross docks in hinterland

Wholesale or Retail Pts

Cross docks in hinterland

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Knowledge Content Distribution Hub Svcs Proven Supply Chain & Life Cycle Mgt Technologies

Implicit Mental Models

Explicit Formal Models

Organizational Learning

Commerce & Industry

Library

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NLB Collection Planning POC Model

Model

Initial Collection

Loan-to-Collection

Ratios

Tiers

Books per Tier

Books to Buy

Projected Loans

Planned Budget

Planned Tiers

Planned Final

Collection

Planned Weeding

Book Cost

Constraints: Total Budget

Space Constraint Min/Max Size of Each

Category Limits on Change

Objective: Maximize loans!

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Stock Mix Optimization Product Mix Optimization

For given budget & space allocated to each category in each store Determine product mix in

terms of new & existing products & their inventory which will maximize sales

Space constraint caters for step-wise increases in frontage of each product within the knapsack shelves

Shelf Frontage

A B C

Existing Products New Products

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Library Selection

Top 1000

HRFIS & LCM

Auto pre- selection

Electronic recommendations

Selector’s choice

Demand Analysis

Gifts & donations

Unsolicited donations

Other suppliers

Traditional paper catalogues

Database Of Candidate

Titles

Residual Budget & Likely LCC

Estimated Demand & Lead Times

OCLC Connexion Holdings in Partner Libraries Rareness Out of Print Likelihood

POD Availability

Selected Titles

Acquisition Sys

VISTA Availability & performance in NLB’s Collection

NLB Portal

Patrons & Br recommendations

Reference Websites

Suppliers including Global Sourcing panelists

Feedback & Decision Support

Br Mgrs

Selectors

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Integrated HRM (i-HRM) Suite Strategic Planning

Demand Forecasting Steady State MP Planning Transition MP Planning

Tactical Planning Vocational Career Planning

Operational Planning Succession Planning Posting Planning Ranking & Performance Mgt

Employee Post

Pool of new employees

Vaca

nt P

osts

Can

did

ates

’ Po

sts

Managers

Dir

Senior Executives

Executives

Attrition Flow

Recruitment Flow

PromotionFlow

SustainableEstablishment

20

200

80

300

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Steady State MP Planning

Managers

Dir

Senior Executives

Executives

Attrition Flow

Recruitment Flow

Promotion Flow

Sustainable Establishment

20

200

80

300

An Equilibrium System Inflows = Outflows

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Gr 1 CEPGr 2 CEPGr 3 CEPGr 4 CEP

Grade 1

Grade 2

EntryGrade 4

Grade 3

Years of Svc

Organisational Grade Progression

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Screen Shots of SSMP FLOW DIAGRAM

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Transitional Analysis Transitional Analysis AttainabilityAttainability

CurrentCurrentProfileProfile

Year 10Year 10

Year 8Year 8

Year 4Year 4

Year 1Year 1

TargetTargetProfileProfileKey Annual IndicatorsKey Annual Indicators

* LOS Distribution* LOS Distribution* CEP Distribution* CEP Distribution* Career Progression Diagram* Career Progression Diagram

Transitional Planning

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DESO 3/4

DESO 2

DESO 1

SS

400

300

50

150

EstablishmentsEstablishmentsfor DTG Engineersfor DTG Engineers

AttritionAttritionFlowsFlows

PromotionPromotionFlowsFlows

Estabs for sayEstabs for sayElectronics EngineersElectronics Engineers Recruitment FlowsRecruitment Flows

Vocational/Career Planning

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Succession & Posting Planning

Employee Post

Pool of new employees

Vaca

nt P

osts

C

andi

date

s’ Po

sts

Determines posting chains which maximises person-to-job fit within the whole organisation – postings does not create new vacancies to be filled the next time

Considers succession plans, career development plans & personal preferences

Handles both incumbents & new employees

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Screen Shots of Posting Planning

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Changi Airport Pre-Board Screening

Passenger Arrival @ Gate

28

No Delay

Minor Delay

Serious Delay

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OR in Healthcare

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Surgical Operating Theatres

Loss of capacity found to be mostly due to poor forecasts

Why do hospitals rely on surgeons’ duration estimates when it is clear that they don’t really know how long they take?

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Predictors like disease code, education, occupation, doctor rank & new/repeat visit were identified – dramatic improve-ment of appointment system is possible

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Appointment Optimisation System Based on Yield Management

Sessions are dynamically optimised as date approaches Optimal overbooking based on profile of patients booked for given

session & historical patterns & trends to maximise probability of a full session finished on time

Optimal allocation of time inventory to urgency classes based on anticipated future bookings before session date to maximise chance of patients getting appointments within their urgency horizons

Appointments are booked with Accurate prediction of consultation/surgery duration with

uncertainty in duration considered in appt schedule Systematic urgency assessment of self-referral cases Optimal allocation of doctor where appropriate

Page 33: Operations Research in Govt & Commercial Sectorsscsr.jp/document/20130725-SCSR_Sim.pdf · 2014-01-24 · Operations Research Core Competency Definition Discipline of applying advanced

Raising Productivity

Each company wants to know how competitors perform but are reluctant to share “sensitive” info about itself Secure benchmarking can overcome such a

problem preventing industries from knowing key performance data crucial to raising productivity of individual companies & industries over time

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Secure Benchmarking Client Excel-spreadsheet

Server Application

Data Encryption

Data Validation

summary & a few samples

Client Data Regression

Global Regression

Analysis Reports

Further Investigation

raw transportation data

Statistical Analysis

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Backend Aggregation & Analysis

Aggregation can be across companies, across lanes (corridor or region), or across time

Consolidated Summary 8083.62, 904.95, 293.44, 78670.62, 8142.881, 2738.37, 918.36, 297.23, 100

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Aggregated Regression Equation Returned to Clients

Trucking Cost =

-0.1836 + 0.9371 Weight (tons) + 0.01215 Distance (km)

Example of comparisons for client A Y = - 0.187 + 0.938 Weight + 0.0123 Distance Weight rate is higher but distance rate is lower than “global” norm

Solution to get Asian businesses to truthfully benchmark their performance & costs?

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Private Sector Logistics / Supply Chain

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Distribution enterprise

Distribution enterprise

Distribution enterprise

Supplier

Supplier

Inventory

Transportation

Manufacturing enterprise

Manufacturing enterprise

Manufacturing enterprise

Retail enterprise

Retail enterprise

Retail enterprise

Customer Customer Customer Customer Customer Customer Customer Customer Customer

Response time? Service level?

Mode?

Where? How much?

How big?

Source from?

What price?

What to make?

Strategic Supply Chain Design

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URUMQI M

TIANJIN M TIANJIN E SHENYANG M

QINDAO M ZHENGZHOU M XI’AN M

CHENGDU M WUHAN M TIACANG M

NINGBO E

DONGGUAN M

HONG KONG M

DALIAN M

CHANGCHUN M

WUHAN E

GUANGZHOU E

CHENGDU E

SHANGHAI E

Exxon-Mobil (As-Is)

Page 40: Operations Research in Govt & Commercial Sectorsscsr.jp/document/20130725-SCSR_Sim.pdf · 2014-01-24 · Operations Research Core Competency Definition Discipline of applying advanced

URUMQI

TIANJIN SHENYANG

QINDAO ZHENGZHOU XI’AN

CHENGDU WUHAN TIACANG AND/OR NINGBO SHANGHAI

DONGGUAN

HONG KONG

Exxon-Mobil (Optimised)

Page 41: Operations Research in Govt & Commercial Sectorsscsr.jp/document/20130725-SCSR_Sim.pdf · 2014-01-24 · Operations Research Core Competency Definition Discipline of applying advanced

Key Benefits of Mobil Study Models enable Mobil to 1. Bring products at best cost, response time &

service level to the regions in China 2. Assess impact of duties, production capacity/cost,

use of grey channel & various pricing policies 3. Design better matched sales & logistics territories 4. Strategise how to roll out RDCs & to organise

mfg, mktg & logistics to stay ahead of competition

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Supply Chain Simulation

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Warehouse Simulation

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Industrial Real Estate

Traditional Business Model

Selling/leasing space to individual tenants & leaving them to manage each space themselves Static spaces not able to

deal with seasonalities Overlapping transporta-

tion needs ignored

Properties marketed individually & not as a valuable network in the context of tenants’ supply chains

45

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Collaboration Amongst Tenants Why do tenants in all

warehouses currently all handle their logistics independent of each other?

Why not share common spaces & transportation services?

Need the following: Trust regime to ensure

that competing tenants know their business info is protected

Equitable scheme to share costs & savings

Proper framework to understand & manage collaboration

46

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Fleet Routing & Scheduling

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Bank ATM Inventory Routing Minimization of Total Cost

DC

Customer #1

Customer #2

Customer #3

Supplier decides when to order, how much

Optimized Inventory & Transportation!

l demand rate l storage capacity l product value

Demand forecasting Stowage capacity Network topology Traffic & routes

Page 49: Operations Research in Govt & Commercial Sectorsscsr.jp/document/20130725-SCSR_Sim.pdf · 2014-01-24 · Operations Research Core Competency Definition Discipline of applying advanced

Service Logistics Optimisation

0 50 100 150 200Inventory Investment

0.5

0.6

0.7

0.8

0.9

1

1.1

Syst

ems

Avai

labi

lity

OptimalCurrent

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Enable manufacturers to gain control of supply chain by helping downstream players – distributors, wholesalers, retailers – optimize their stock mix

Moves relationship with these players from “customer” to “partner” by helping them achieve higher sales yield per space given to the brand

Will lead to these players giving more space & holding more inventory for the brand while achieving a higher performance supply chain overall

“Optimal Stock Mix” Strategy

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Demand Sensing Demand sensing & visibility

used to be difficult as distributors, wholesalers & retailers do not have any incentive to share their sales & stock data

Forecast Error as Multiple of Actual

“Optimal Stock Mix” persuades the players in the supply chain to collaborate with the manufacturer or brand owner enabling accurate demand sensing in the whole supply chain

Page 52: Operations Research in Govt & Commercial Sectorsscsr.jp/document/20130725-SCSR_Sim.pdf · 2014-01-24 · Operations Research Core Competency Definition Discipline of applying advanced

“Optimal Stock Mix” Benefits Expectations of 5-20% savings compared with manual

forecasting & stock management With timely end-customer demand updates &

forecasting, supply chain turbulence & costs are reduced Sales teams become more organized to systematically

Collect market intelligence Build solid partnerships with distributors, wholesalers & retailers Develop more effective marketing campaigns Provide better guidance on how they should market & merchandise products in the

light of own & rivals’ campaigns

Leaner & higher performance supply chain

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Collaboration Opportunities?

Partnership for Innovation

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7/11/2013 54

Strategy (What do we do?)

Tactical Planning

(How do we do it?)

Operational Planning (Do it!)

Evaluation (How did we do?)

Integrated Decision Systems Strategy to Operations

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To help clients: a. harness the power of information & decision technologies b. distill corporate wisdom into explicit models in order to: i. promote better communications ii. make decisions coherently & consistently iii. learn & build knowledge capital over time so as to gain & maintain the competitive edge

IDSC’s Mission

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Collaboration

Relationships are important but may not lead to best results as humans are complex & cannot handle complex systems well without technological assistance IDSC seeks to work with partners to use OR

to help Japanese govt & companies do better

Page 57: Operations Research in Govt & Commercial Sectorsscsr.jp/document/20130725-SCSR_Sim.pdf · 2014-01-24 · Operations Research Core Competency Definition Discipline of applying advanced

IDSC’s Branding Proven capability to develop unique solutions to

address challenges of scarce resources – same HR & space issues as experienced in major cities such as in Japan – innovation which can provide sustainable advantage

Experience in harnessing technology to lead in fostering public sector excellence – know-how to help organisations shift paradigms to institute progressive mind-sets (relationships + systems)

Page 58: Operations Research in Govt & Commercial Sectorsscsr.jp/document/20130725-SCSR_Sim.pdf · 2014-01-24 · Operations Research Core Competency Definition Discipline of applying advanced

IDSC’s Business Strategy/Model

Training

Products & Internet Svcs

Report

Consultancy

Trg leads to product sales

Trg opens doors & develops long-term relationships

Synergy

Implementation involves trg to make changes permanent & successful

Consultancy to create unique customised solutions to provide competitive edge to industry leaders

Consultancy experience produces quality trainers

Generic products for non-core functions as well as industry-specific products

Page 59: Operations Research in Govt & Commercial Sectorsscsr.jp/document/20130725-SCSR_Sim.pdf · 2014-01-24 · Operations Research Core Competency Definition Discipline of applying advanced

Summary of Possibilities Collaborate to help Japanese public sector raise

productivity – military, police, hospitals, libraries, HR, etc

Private sector opportunities Stock Mix Optimization Dynamic Cross Docking Secure Benchmarking – logistics, salary, productivity,

etc

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Discussion

Comments? Questions? What’s next?