© 2016 Chevron

SASBU Data Management Data Quality Journey /

MetricsJoao Cardoso/Osorio Costa

DQ Analyst/Data Architect

Luanda, Jun 6th 2018

2© 2018 Chevron

Topics Key Messages

• Audience obtain a clear understanding of the SASBU Data Foundation Program.

Desired Outcome

• Data Quality are the processes and technologies involved in ensuring the conformance of data values to

business requirements and acceptance criteria

• Data Foundation (DF) is a systematic approach to drive operational discipline in how we manage high

priority data. The DF framework consists of 5 components (Data, Governance, Organization Capability,

Standards, and Managed Integration System) to enable Chevron’s IM strategy.

• Data Governance must be in place to enable and sustain data quality efforts/initiative.

• Managing data quality requires a long term perspective and effort due to the dynamic nature of our

business, new data types, new consumers and consumer needs, process changes, etc. Data Quality is a

program, not a project

Data Quality is implemented using a methodology that consists of 4 phases:

”Define-Assess-Remediate-Monitor”

• Leadership alignment and endorsement is key for a sustainable Data Quality Program and to improve

organization capability in the management of information as a high priority business asset.

Executive Summary

• Data Foundation Framework

• Data Quality Framework

Data Quality Management

• Data Quality Tool - DQ

Checker & DQ Methodology

• Show Case

3© 2018 Chevron

SASBU Data Foundation

▪ Data is an asset and treated

as such.

▪ Through the lens of core

business workflows, high

value data is identified and

governed, standardized,

supported and integrated as

intended

Org

CapabilityStandardsGovernanceData

▪ There is strong leadership in

both the business and IT for a

high quality data foundation.

▪ Right resources and the

required training is in place to

ensure the ongoing

improvement and

sustainability of the Data

Foundation

▪ Standards needed to

maintain a high quality data

foundation are in place.

▪ Data is stored and

maintained in standard

SoR’s.

▪ SoR’s meet characteristics

of a high quality SoR.

▪ The processes, policies,

governing bodies and roles

needed to maintain data to

the required quality are in

place.

▪ Continuous monitoring is

ongoing.

▪ Plans for integration are in

place

▪ Design approach and

technologies are defined,

including managing

master data and

unstructured content

Managed

Integration

Data Foundation is a Chevron Global Upstream initiative and management system driven by the Business Units aimed at

improving the quality of high value data in daily operations.

4© 2018 Chevron

Data

5© 2018 Chevron

Goal of Data QualityGood Data. Great Decisions.

Why Data Quality?

▪ High Quality data is trusted by the business

▪ Improve decision making as a result of good quality data

▪ Increase productivity – e.g. less time spent validating data

▪ Easy implementation of new solutions / technologies

▪ Meet legal and audit requirements

▪ Alignment with Data Foundation initiatives and efforts

The goal of Data Quality : from data capture to retrieval, from improved decision making to employee

productivity, people will be able to trust and rely on the data they use.

The state of data should be complete, correct, currency, consistent and conform that make it fit

for its intended uses in operations, decision making and planning

6© 2018 Chevron

What is the Data Quality Management (DQM)* Framework?

Enablement

Delivery

Support

Data G

ove

rnan

ce

Leadership

Organizational Capability

Governance

Data Quality Management

Knowledge Sharing

Standards

Measurement and Metrics

Define Assess Remediate Monitor

• Endorsement

• Alignment

• Strategy/Policies

•Roles and Responsibilities •On-Boarding/Training•Instilling Data Quality Values

• Portfolio Management/Prioritization

• Data Ownership

• Decision Enablement

•Data Readiness

•Apply rules to data

•Ticket Management

•Root Cause Analysis

•New Data Loading

•Process Library

•Resource Registry

•Rule Repository•Data Catalog

•Dashboard

•Reporting

•Team Readiness

Assessment

•Logical Data Dictionary

•Data Lifecycle

•Business & Data Rules

•SORs

•Determine assessment

tool

•Embed rules in tool

•Apply Rules to Data

•Report Out

•Training Data Creators

•Develop remediation

process

•Develop remediation

tools

•Report Progress

Governance• Portfolio Management/Prioritization

• Data Ownership

• Decision Enablement

DQM consists of three sections: Enablement, Delivery & Support

* Also referred to as Information

Quality Management

7© 2018 Chevron

SASBU Data Quality Program

Governance (Strategic / Tactical / Operational) 4 functions with data being monitored

Reservoir

ManagementHuman Resources Finance SCM

In Progress…data being monitored

2014-2015• Obtain Leadership support for Data Foundation

• SASBU IM Governance body established

• DQ Awareness for key stakeholders

• IM Data Quality Team established

2015-2016• Prioritized DQ assessments and remediation (UWT)• Functional SMEs for UWT Engaged

• DQ Competency Development Progressed

• PDQ tool for DQ deployed

2017-2018• New DQ Tool (DQ Checker) deployed

• 3 Non-Petrotech functions engaged

• DQ process refined and documented

• Started monitoring additional data (Finance, HR, SCM)

SASBU DQ Journey5 Data Quality Program Deliverables

Data Quality Team

Governance Body

DQ Competency Development

DQ Tools and Processes

DQ Dashboard

• Central facilitation of SASBU data Quality Program

• SASBU’s Data Quality maturity

• Visible functional leadership support, provision of resources, and ownership of department DQ processes

• Roles, responsibilities and performance objectives

• Fit for purpose DQM training to priority functions

• Function specific training for various data categories/ types

• Periodic Data Quality Integrity Checks

• Business Rules Inventory

• Data Quality dashboard (metrics and scores)

• Functional Leadership reviews

▪ Visible Leadership Support

▪ Provide strategic direction

▪ Provide resources

▪ Implement IQM (Define, Assess, Remediate

and Monitor) and Governance Processes

▪ Publish standards

▪ Progress DQ Competency Program

▪ Implement and support DQ Tool

▪ Develop Business Rules

▪ Monitor & Maintain DQ Process

83 Business Rules:

• Asset Development Plan

• Geophysics

• Reservoir forecast

• Reservoir model

• Well Design

9 Business Rules:

• Employee

• Organization

10 Business Rules:

• Business Hierarchy

• Joint Venture

Reporting

• Payment

5 Business Rules:

• Materials and

Warehousing

• Procurement

operations

• Suppliers

Data Quality Teams – The core DQ team

resides in the IT function and consists of a DQ

Champion (DQ Supvr) and 4 DQ Analysts

2019+• Engage remaining functions• DQ a key component in

SASBU Functions

This DQ team drives the DQ program and works with selected knowledgeable individuals from each business

function to deliver DQ to the business function

8© 2018 Chevron

Governance

9© 2018 Chevron

Hierarchy of Information Governance Roles

Operational Level

Tactical Level

Strategic

Level

Executive Level

Executive Sponsor- Provides strategic direction and business alignment

- Provides resources and funding

- Ensures information governance activities are aligned with key

business priorities

IM/DF Oversight Committee (IM Steering Committee & IM/DF Governance

Board)• Steering group for governance policies and activities

• Accountable for monitoring and improving information management &

governance capabilities

• An ultimate decision body for issues/exceptions

Information Steward (Gold Key Holder)• Responsible for the data content

• Ensures compliance with processes, quality rules

• Provides input about issues, values, etc

Information/Data Architect• Leads or supports development of data models, info standards

• Publishes standards and maintains alignment

Data Quality Champion• Responsible for processes and monitoring the quality of the information

• Direct DQ analysts

• Responsible for IM governance implementation and compliance

Information Custodian• Ultimate authority on definitions and quality thresholds

• Works with stewards, Quality Managers and Quality Analysts

Information Quality Analyst• Applies data definitions, business rules and quality thresholds for a set of

information

• Produces quality reports, investigates issues

• Recommends and assists on data clean up activities

Information Consumer • Provides requirements for and feedback on the information

10© 2018 Chevron

Data Governance

SASBU IM/DF OC - Steering Committee

Steering Committee

(Business function Representative)

Business Function Name

Asset Development

Base Business

Drilling & Completions

Facility Engineering

Finance

Human Resources

HES

MCP

Operations

Supply Chain

Management

Information Technology

SASBU

IM/DQ

Governance

Project 1,2…

Prj 3

Prj 2Prj 1

BU IM Project Portfolio

• Steering group for governance policies and activities

• Acts as information stewards (accountable for data

content)

• Provide guidance on IM project portfolio & prioritization

• Provides input about issues, values, etc.

11© 2018 Chevron

SASBU IM/DF OC – Governance Board

Governance Board

(Business function Representative)

SASBU

IM/DQ

Steering

Committee

Project 1,2…

Prj 3

Prj 2Prj 1

BU IM Project Portfolio

Business Function Name

Asset Development

Base Business

Drilling & Completions

Facility Engineering

Finance

Human Resources

HES

MCP

Operations

SCM

Information Technology

• Ensures compliance with process,

quality rules

• Responsible for data quality and

management capabilities

• An ultimate decision body for

issues/exceptions

12© 2018 Chevron

Data Governance Model (SASBU Standard)

Steering Committee Function

LT + IT Representative)

Sub-

Committee

Ensure the Function data review process is conducted

and enforced - Quarterly reviews (minimum)

- Workflows & analysis use approved values

- Team representation is respected

Sub-

Committee

Sub-

Committee

• Data Governance sub-

committees:

➢ Implement and conduct Function

data quality and integrity review

process

➢ Empower relevant others

beneath to ensure the work is

done

➢ Led by the Gold Key Holder with

representatives from impacted

Teams and SMEs of relevant

disciplines

➢ The Gold Key Holder will report

out at every Function LT Meeting

➢ Cross-Disciplinary point of view

XXXX Data Type

XXXX Data Type

XXXX Data Type

Gold Key

Holder

Gold Key

Holder

Gold Key

Holder

13© 2018 Chevron

Standards

14© 2018 Chevron

Standards

Systems of Record (SOR's) in

place

Aligned identified SoR’s and all identified information objects with Chevron SoR Standards.

Standard Chevron SOR by Data Element

Information Standards in place

Information standards for key information objects are identified and used consistently within identified SoR’s aligned with enterprise

standards and drive to improve data quality within the SOR's

Technology Standards in place

Technology standards for key workflows, systems, or data are identified and are used consistently.

Technology standards in use are aligned with enterprise standards.

15© 2018 Chevron

Organizational Capability

16© 2018 Chevron

Organization Capability (OC)

Goal & Audience Duration Due Date Link

1. LMS - Introducing to Data Quality

or

2. F2F training – Introduction to DQ

(e.g. DQ Overview)

Required audience: All Team Members

1. LMS ~1 hour or

2. F2F training: 1.5 hour - Conducted by DQ Lead

Upon kick off Meeting

Date:

Business Acumen

Scope: Function Overview – focus on

Business Processes impacted by Data

Elements/Data types in scope.

Required audience: All Team Members

1 hour

Conducted by Function SME “GKH” (prepare or use

an existing formal deck – save under SP)

Upon kick off Meeting

Date:

Data Quality Execution Phases – Quick

Overview (used separately or included in

the F2F Training – line 1)

Required audience: All Team Members

30 min

Conducted by DQ Initiative Lead

Upon kick off Meeting

Date:

DQ Dashboard Training

Required audience: All Team Members

1 hour

Conducted by DQ Initiative Lead

Assess Phase

Date:

IQM Training (Delivery Phase Specific)

Required audience: All Team Members

1. Overview on IQM Define Phase – 30 min

2. Overview on IQM Assess Phase – 30 min

3. Overview on IQM Remediate Phase – 30 min

4. Overview on IQM Monitor Phases – 30 min

Conducted by DQ Initiative Lead

Each IQM Phase @

Beginning of each Phase

Use this

deck

IM Academy

Busines

s

Acumen

Add link

here

F2F Training

Training is critical to ensure all stakeholders understand and speak the same

language relating to Data Quality. Training covers various aspects of Data quality

and is available in various forms for various roles.

17© 2018 Chevron

Managed Integration

18© 2018 Chevron

Managed Integration

19© 2018 Chevron

Data Quality Showcase

20© 2018 Chevron

DQ Checker for Human Resources

What

• DQ Checker is the data quality tool used in SASBU to

monitor the state of the data thought the use of applied

controls (business rules)

• It allows us to almost instantly know what is wrong with

our data, correct it at source and get updated reports

• Enables good decision making based on data status

• Promotes trust in data used for daily operations

Who

• DQ Checker should be used by all function members on a

need to know basis upon filling the access request form

• The Steering Committee will use it to monitor the status

of function’s data and recommend cleanup actions to

GKH

• The GKH will use it to monitor and control data cleanup

efforts

• Subcommittee members to know when and where to go

and clean the data

DQChecker

21© 2018 Chevron

SASBU Subsurface Data Quality MetricsThis is a template with trial data

Data Quality Metrics – Q1 2018

DQChecker

Data Element being trackedTarget

Score

Apr 2018

Avg Score

May 2018

Avg Score

Wellbore 100% 93% 96%

Direction Survey 100% 98% 95%

Well Header 99% 92% 98%

Below TargetOn Target Last update: Q1 2018 (Mar)

2018 DQ dashboard

target

Q1 DQ

Average Score

99% 76%

Key Challenges

▪ Multiple SOR having the same data

22© 2018 Chevron

Questions/Feedback