Project Charter

Project Title : Improvement of Data Collection for GHG Inventory Monitoring and Control

Champion : Chatiya Nantham

Team Leader : Hendy Widjaja

Members : Edzen Jogie B. Garcia Ma.Gina Soriano/OAIS -TR Leo Modesto Reyes /OIST

Gloria Tria / OAIS-LMCarina L. Soriano/OAIS-LMBenedicto A. Santoyo/OAIS-LMOlivia Anne V. Sebastian/OAIS-LMEleazer C. Bernabe/OAIS-LM

Julito Baldisimo/OAFA-FM Annabelle Balbastro / OAFA-FM (Contractor)

Project Charter

Business Case

As part of Asian Development Bank (ADB) initiative in promoting environmentally sustainable economic development, ADB has consider climate change issue seriously. One of the primary concerns that ADB is addressing is the need to reduce the level of emission of greenhouse gases (GHG) which has been attributed as the primary cause of global warming.

The first Greenhouse Gas (GHG) Inventory Mapping Study was initiated in October 2007. The inventory covers direct and indirect emissions from the operations of ADB HQ for the calendar years 2005 and 2006. The study was able to accomplish a complete inventory of the direct emissions for the covered years. The inventory for indirect sources was not completed due to data gathering constraints. The study suggested the completion of inventory for 2005 and 2006 indirect emission sources and implementation of 2007 GHG inventory to establish GHG emission reduction target for 2008 and 2009 .

However, the GHG Inventory Team has limited time and resources to complete the emission data. This project aims to improve data collection system that allows ADB to complete its GHG inventory in less time, in less cost and with less errors resulting to a simple process that gives out high quality information.

DEFINE

Problem Statement:

The GHG activity data was not readily available and significant time was needed to extract the required for GHG emission calculation.

Activity data needed to calculate emissions from business travel, postage and freight of ADB documents and shipment of goods for ADB Staff was incomplete. The original tracking scheme requires additional resources to estimate distances between ports and air travel , a tedious and time-consuming process.

Project Goals:1. To complete GHG Inventory from 2005 to 2008 first quarter by May 2008.2. To improve data collection system by streamlining data gathering process and build a computer application with a custom designed database to minimize errors and obtain high quality information.

Revised CTQRevised CTQANALYZEANALYZE

Output Characteristic

(Big Y)

C T Q

95% data accuracy and completenessTarget

Defect < 95% data accuracy and completeness

Operations Definition Distances (Origin to Destination) and Weights from Various Activities: Business Travels, Shipment of goods for ADB staff,Postage and Freight of ADB Documents,Transport of Recyclable Paper,Hazardous Waste,Non-Recyclable Waste, STP Sludge and Biodegradable Waste. Consumption of Refrigerant Fuel Consumption Consumption of LPG for cooking and water heating element and diesel for Power Generators

Distance ( km), Weight (kg), Refrigerant (kg), Electricity (kwh), LPG(kg), Diesel (L)

Project Y (Little y) Measure

Specification Limits

USL- 100% data accuracy and completeness LSL- 90% data accuracy and completeness

High Level Need Improvement on Data Collection

ADB HQ GHG Inventory Report 2006, 2007 and 2008 First Quarter

Output Unit

Raw data, complete and accurate for CO2 Emission Calculation

CASE STUDY:2006 TRAVEL DATA


This should be 5,001.56 (3% higher)

ANALYZEANALYZE



• The 3% difference is within CTQ, however the following discrepancies in detail data submissions did not meet the CTQ

For the sample, distance between Philippine and Hong Kong are not consistent: 1. It ranges from 216km to 13,687km;2. There are 3 blank fields for distances;3. In comparison with the actual distances of 1,116km, the total variances for 112 PHI HKG trips is 222,260km or on average is 1,984km more per trip.

ANALYZEANALYZE



• Quick look of other variances:

Actual distance of PHI - VIE is 1,751km

Actual distance of PHI - CAM is 1,776km

ANALYZEANALYZE




Actual distance of PHI - VIE is 1,751km

ANALYZEANALYZE




Actual distance of THA - LAO is 525km

ANALYZEANALYZE



• There are 3,465 or 49.94% that do not meet the CTQ target of 95% data accuracy.

• Detailed analysis:– The original CO2 calculation by GHG consultant based on the

data provided by the users unit is 4,857ton CO2, the corrected CO2 calculation indicates 5,001ton CO2 or 3% higher – meet the CTQ;

– Based on the master distance table developed independently: • 2,587 of 6,938 travel data or 37.29% has ZERO variance, this

means the distance data was correctly recorded then the CO2 emission was also correctly calculated - meet the CTQ,

• 886 records (12.77%) differ between -5 to 5% of the actual distances listed in the master table - meet the CTQ,

• however 3,465 records or 49.94% have variances greater than 5%, ranging from -100 to 8,221% of the actual distances (39 records without distances) – did not meet the CTQ.

ANALYZEANALYZE

DATA COLLECTION

ISSUES

ERRORS IN DATA ENTRY

PEOPLE

LACK OF MANPOWER

NO PROPER TRAINING

NO SYSTEM COMPATIBLE WITH GHG AWARENESS

UNAVAILABILITY OF DATA

SOURCE DOCUMENTS

MEASUREMENT

MACHINE

METHODS

N/A

NO QA/QC

WRONG DATA ENTRY

DATA NOT NEEDED IN OPERATION

LACK OF AWARENESS

OF GHG IMPACT

N/A

ENVIRONMENT

INCOMPLETE INFORMATION



Variances may result from the causes listed below

ANALYZEANALYZE

U:\Documents and Settings\J9T\My Documents\PP SPC\aug 30\PEOPLE.xls







6,949 Point to Point Destination

Sample distances: GHG calculation for Manila – New Delhi - Manila

An estimated total of 20 staff-days to complete the calculation, based on approximately 350 records per day.



Further, the GHG data collection consumed many staff/consultants hours

ANALYZEANALYZE

Inventory Limitations and Improvements Needed (Based on Consultant’s GHG Inventory Report)

Air Travel

2005 and 2006 Inventory

Improvements Needed

Airport names and cities of countries and origin and destination were difficult to extract because they are not electronically accessible yet. To estimate air travel distances, pre-selected cities/airports of countries of origin and destination were used which can cause variation.

- It is recommended that ADB expand its business travel documentation procedures (electronically) for GHG Inventory.

- Eliminate the cause of variation.


CASE STUDY:2006 TRAVEL DATAANALYZEANALYZE

ISSUES/CONCERNS PROPOSED SOLUTIONS TIME FRAME Status SECTION RESPONSIBLE

Unavailability of Data /Completion of GHG Inventory / Lack of Manpower

Manual Extraction of Data from the Mainframe/ Manual input of Data

Incomplete Information

Set a meeting with concerned Business Unit to discussed the completion of 2005-2006 inventory report and baseline inventory for 2007

Set a meeting with OIST representative to discussed the extraction of Travel Data from the mainframe.

Provide standard report of Air Travel download from the mainframe

Set a meeting with Service Providers (Couriers Company) to report origin and destination on per “City to City” basis rather than “Zone to Zone”

Feb 2008

Feb. 2008

Mar. 2008

Apr. 2007

Done

Done

Done

Done

OAFA-FM

OAIS-TROIST

OAIS-TROIST

OAIS-LM

Completed Actions to improve Data Collection

Completed Actions to improve Data CollectionIMPROVEIMPROVE

Green House Gas (GHG) EmissionOAIS-TR Air Travel Data Flow Diagram (DFD)

Procedure Process Parameter

Determine File Naming Convention:

UNIT FOCUS DATE, i.e. OAISTR AIRTRAVEL 200801

Requesting direct data download from OIST through the responsible unit – CSV file

format

Preparing table for Air Travel Distance (in 2007, there are

about 1800 point-to-point distances) – MS Excel file

format

Calculating the CO2 Emission and generate an “exception” report to identify “missing”

distances – IDEA processing

Running Data Analysis Software (we are using IDEA

Software)

Updating table for Air Travel Distance (there will only be few

“missing” additional point-to-point distances) – MS Excel file

format

Based on the updated Air Travel Distance Table, re-

calculate the CO2 Emission – IDEA processing

Grouping the CO2 Emission data based on the traveling

staff – IDEA processing

Generate “Missing”

distances table in MS Excel file

format

Generating the CO2 Emission report in MS Excel file format based on the traveling staff

• Data download: once the procedure is in place, OIST can directly provide the data to us. However, data owner needs to approve the process and endorse the data validity

• Data processing: The tool (IDEA data analysis) will automatically analyze the data and generate the reports, i.e. table for missing air travel distance to be completed by GHG staff, periodic report on CO2 emission per traveling staff

• Result dissemination: Based on the discussion with others, report will be distributed for monitoring or reducing CO2 emissions.



Data collection process is re-engineered, to achieve CTQ target of 95% accuracy and

completeness

IMPROVEIMPROVE

Master Table for Distance Travel that will require only minor update when we process subsequent year

data, out of 1744 distances in 2007, 2008 may only have about 300 new unique distances

AIR TRAVEL 2007 DATA EXTRACTED FROM MAINFRAME

Manual input of Distance for 18,367 Point to point

Destination

1744 Unique Point to point

Destination

IMPROVEIMPROVE CASE STUDY:2007 TRAVEL DATA


IDEA generates Script that can be customized – this script import the data to IDEA, analyze them and generate report



(CTQ: 95% data accuracy and completeness)

50% meet CTQ



(CTQ: 95% data accuracy and completeness)

100% meet CTQThe Master Distance Table developed by the GHG team went through rigorous checking procedures. Distances

obtained from various websites are compared to improve consistency. The table was imported to IDEA

to automate CO2 emission calculation.

ACHIEVING CTQ TARGET


Sample distances: GHG calculation for Manila – New Delhi - Manila

An estimated total of 19 staff-days require to develop the distance table (17.5 days for completing 1744 segment-to-segment destinations) and 1.5 days to complete the automatic calculation.




NO. OF REQUIRED STAFF DAYS TO

FINISHED THE TASK

Using old process, the calculation requires approximately 34 more days or 178.95 % more time than using new process



IMPROVE PROCESS = CUT COST

Rate : 350 Distances / day


FINISHED THE TASK

X

X

$ 177.00

$ 177.00

RATE PER DAY

= $ 9381.00

= $ 3363.00

$ 6,018.00



In addition to achieving CTQ (95% data accuracy and completeness), saving was obtained in the current process to calculate CO2 emission for 2007 data

$177 cost per day refers to the charge rate of the first GHG consultant engaged to calculate CO2 emission. With the intensity of many activities during the manual

data collection, many staff require external resources to assist.

REPLICATION OF IMPROVED PROCESS TO POSTAGE AND FREIGHT


FINISHED THE TASKPOSTAGE AND FREIGHT DATA



2,393 Unique Point to Point

Destination


12 Staff Days 1.5 Staff Days

Using old process, the calculation requires approximately 19.5 more days or 244 % more time than using new process

+

IMPROVEIMPROVE 2007 POSTAGE AND FREIGHT DATA

2007 POSTAGE AND FREIGHT DATA

REPLICATION OF IMPROVED PROCESS TO SHIPMENT OF GOODS (Inbound and Outbound)


FINISHED THE TASKSHIPMENT OF GOODS (Inbound and Outbound)



181 Unique Point to Point

Destination

2.5 Staff Days 1.5 Staff Days

Using old process, the calculation requires approximately 11 more days or 375 % more time than using new process


+

IMPROVEIMPROVE 2007 SHIPMENTS OF GOODS DATA

2007 SHIPMENTS OF GOODS DATA

Air Travel Data

Postage and Freight

Shipment of Goods

Required No. of Days

Old Process 53 33 15

New Process 19 13.5 4

Resource reduction in days 34 19.5 11

Estimated Cost Savings, based on @ $177.00 rate/day $6,018.00 $3,451.50 $1,947.00

Total Savings $11,416.50

IMPROVEIMPROVE CURRENT SAVINGSCURRENT SAVINGS

Less Savings obtained for the first year as master table are set for the

first time for 2007 Data.

Air Travel Data

Postage and Freight

Shipment of Goods

Required No. of Days

Old Process 53 33 15

New Process 4.5 3 2

Resource reduction in days 48.5 30 13

Annual Cost Savings, based on @ $177.00

rate/day $8,584.50 $5,,310.00 $2,301.00

3 Years Cost Savings $25,753.50 $15,930.00 $6,903.00

Total Savings for 3 years $48,586.50

IMPROVEIMPROVE FUTURE SAVINGS to process 2008, 2009, 2010

Data

FUTURE SAVINGS to process 2008, 2009, 2010

Data

Savings Projection for Three Years

(the project may continue after, by that time there may be a better solution to calculate GHG Inventory)

Assumption for updating Master Table data: Additional 300 unique destination / year (Air Travel and Postage and Freight)Additional 40 unique destination / year (Shipment of Goods)

Net Savings

Savings for 2007 Data Processing

$ 11,416.50

Savings for 3 subsequent years $ 48,586.50

$ 60,030.00

Less : Cost of IDEA Software $ 3,000.00

$ 48,003.00

Less : Cost of IDEA annual helpdesk support ($3000 per year)

$ 9,000.00

IMPROVEIMPROVE NET SAVINGS to Calculate 2007, 2008, 2009 & 2010

Data

NET SAVINGS to Calculate 2007, 2008, 2009 & 2010

Data

Gross Savings

CONTROLCONTROL NEXT STEPSNEXT STEPS

• Procure the software• Train the GHG team• Replicate the effort done by Six Sigma for

calculating 2008 data for Q2, Q3 and Q4• Monitor the implementation for continuous

improvement until end of 2008 – end of six sigma project

• Institutionalize the procedure for processing future data: 2009 onward

• Review this process again in 2011 – future six sigma project ?