Wilkerson- Business Intelligence.pptx

From Data to Insight:
The Value of Business
Intelligence at ORNL
Ramie Wilkerson
Institutional Planning and Performance Management
Business Planning and Process Improvement
November 2012
A strong assurance system…
–  demonstrates responsible and
accountable leadership
–  sets clear expectations
–  promotes the right behaviors
–  focuses on outcomes
–  manages risk appropriately
–  executes reliable operations
–  pursues continual improvement
–  communicates openly with
transparency
–  strengthens “ Shared Learning”
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Business Analytics:
Understanding performance data is critical
What will happen next?
What should we do?
Improving performance
INTELLIGENCE
Why did it happen?
INSIGHT
What does it mean?
INFORMATION
What happened?
DATA
Value Extracted from Information
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Business Intelligence …
Communicating performance information
thru analysis and visualization
•  Enables analysis
and decision making
•  Facilitates understanding and
communication of performance
•  Fosters a culture of
transparency, learning and
continuous improvement
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What makes up Business Intelligence?
Data
Reports:
how data is
communicated Data
Warehouse:
how data
is stored Criteria •  Zero Learning Curve
–  Simple, intuitive structure
Data Cubes:
how data
is organized User
Interface:
how data
is accessed •  Select critical key performance
indicators thoughtfully
–  What indicators best measure
the health of the lab?
Critical
Components
Data
Analytics:
how data
is analyzed –  Easy to Navigate
Data
Visualization:
how data
is displayed •  Data Integrity
–  Is the data complete? validated?
data owner identified?
•  Standard layouts to best display data
patterns, trends, outliers, etc
•  User training to use tools efficiently for
data analysis
•  Gather feedback from user community
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What are we trying to achieve?
•  Create an asset of value
§  Assists R&D and Support staff in getting their job done
§  Assists leadership in “managing” the laboratory
•  Offer capability to view, monitor and interact with performance data
§ 
§ 
§ 
§ 
Central portal to access information
“Standard” way to view data
Central data warehouse
Way to view data from iPad to the Desktop to the Big Screen
•  Provide tools to functional owners to enhance data analysis
§  Capability to interact with data
§  “Standard” way to extract data from various data sources
§  User training
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Overview
2010: Chose Microsoft BI tool
• 
• 
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2011: OIP BI Project
Lab-­‐wide interest in BI •  Develop requirements for capability; 9 Directorates SNS User Facility Dashboard Market Analysis of •  Developed prototype in industry leaders in Business Intelligence QA –  SAP; Microso@; •  Lessons Learned: Oracle –  Management support Microso@ selected –  IdenBfy how these tool –  BI suite opBmal for can/will be used by the ORNL environment InsBtuBon –  Excel is the –  Partnership between foundaBon for user project team and data interacBon with the owners/business data analysts –  Training on tool and technical processes needed Managed by UT-Battelle
for the U.S. Department of Energy
Presentation_name
2012: Project endorsed
• 
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FY12 operaBonal focus: Enhancing funcBonal support for R&D – enabling informaBon systems Challenge: Reproduce current KPIs using BI tool Proof of concept presented to OperaBons Council Endorsement to begin project Learning begins… Benchmarking…continuing to learn
•  National laboratories
•  Universities
•  Private Industry
•  Users Groups
Business Intelligence Users Group (Local) 8
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NaBonal Laboratory InformaBon Technology Getting started…
Resources Technical: 1.5 FTEs FuncBonal: 1 FTEs Cost of Entry: Hardware Ini/al challenges…a few • 
• 
• 
• 
• 
• 
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Establishing technical and funcBonal processes Learning Curve of tools for project team and user community Buy-­‐in from organizaBons – Value Thoughbul selecBon of key performance indicators Data Sources varied – “MeeBng data owners where they are” Speed of delivery SharePoint 2010 MigraBon – troubleshooBng MulBple phase project Managed by UT-Battelle
for the U.S. Department of Energy
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Phased approach – statistics to date…
FY10
FY11
FY12
FY13
FY14
Institutional Interest
BI OIP Project
Project Phase 1
Project Phase 2
Master Data Warehouse
•  Procedures to extract data: 110
•  Data staging tables: 338
•  Fact tables (Measures): 199
•  Dimension tables (Ways to view
measures): 314
•  Cubes (computer mechanisms to
interact with MDW): 21
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Dashboards
•  S&T Performance Areas: 5
•  Operations Performance Areas: 14
•  Data Sources: 49
•  Metrics visualized: 152
•  Functional Owners: 17
•  Business Analysts: 29
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Technology
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Process
Data
sources
Collect
data
Data
staging
Data
warehouse
Deliver
data
Data
analysis
Data
reports
Extract Transfer Load Internal External Desktop 12
Security Managed by UT-Battelle
for the U.S. Department of Energy
Normalize and consolidate data Central repository Presentation_name
Charts Drilldown Graphs Comparisons Scorecards Slice and CombinaBon dice of data Dashboards Reports Scorecards Workbooks Structure
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Demonstration
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Planned improvements
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User Interface
new design; better functions
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Planned improvements
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Visualization and Data Interaction
right tools; user training
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Excel
Power Pivot
Power View
IT Advisory Council AIM Project:
[Business Intelligence - CMPS]
Project Status Definitions
Green = No significant issues jeopardize the project
Yellow = Significant risk to schedule and budget
Red = Clear roadblocks prevent successful completion
Objectives!
Date: 11/29/2012
State the primary technical objectives of the project."
  Establish a master data warehouse"
Project Status: Green
 
Build data cubes of functional areas"
 
Delivery of Information"
User/Data Interaction"
 
Stakeholders
"
Project Sponsor: Jeff Smith"
Functional Project Manager: Ramie Wilkerson"
IT Technical Lead: Rick Short"
MSO Advisor: Shaun Gleason/Mike Baker
"
"
"
""
Phase 2: 10/1/12 – 3/15/13
Milestone
!
1.  User Facilities
2.  Information Security"
3.  Publications"
4.  High Hazard"
"
5.  Worker Safety"
6.  Environmental Stewardship
"
7.  Human Resources"
"
!Orig.!
Timeline
Completion!
Rev.
Actual
!!
"10/1/12"
10/2/12 "
10/31/12
11/26/12
"
12/21/12
"1/4/13
"
1/11/13
"
On Track At Risk Off Track 11/29/12"
12/3/12 ""
12/24/12"
"1/23/13
2/8/13""
2/21/13
Planned Duration
Progress
3/15/13
1Q13!
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Not Started On Hold Completed 2Q12!
2Q13!
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3Q13!
4Q13!
IT Advisory Council AIM Project:
[Business Intelligence - CMPS]
Accomplishments to Date"
Issues/Risks"
Changes"
List major tasks/accomplishments that have been
completed and/or milestones achieved since the last
status was prepared..!
List key issues and/or risks that may affect the project
budget, schedule or general objectives. !
Describe any changes to the project objectives, schedule,
budget or any other aspects that have significantly
impacted the project over the past month. Also documents
major baseline changes.!
 
"
 
Established processes: technical and functional"
Stats to date: see below "
 
CMPS – In production but not deployed"
 
 
Institutional support and buy-in "
 
Learning curve of tools"
Selection of KPIs"
 
User/Data interaction – training needed"
 
 
 
"
"
Master Data Warehouse!
• 
Procedures to extract data: 110 "
• 
Data staging tables: 338 "
• 
Fact tables (Measures): 199 "
• 
Dimension tables (Ways to view
measures): 314 "
• 
Cubes (computer mechanisms to
interact with MDW): 21"
Dashboards!
• 
S&T Performance Areas: 5"
• 
Operations Performance Areas: 14"
• 
Data Sources: 49"
• 
Metrics visualized: 152"
• 
Functional Owners: 17"
• 
Business Analysts: 29"
Cost!
"
Budget:
"
Spent:
"
%Budget Spent:
"%Project Period Complete:
"
"
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"$175K"
"$37K"
"21%"
"30%"