Sami Tayara BI Presentation ATT Jan07B

Examining Best Practices And Potential Pitfalls
In The Use Of BI Dashboards
Sami Tayara, Independent Consultant
Based on extensive experience of BI and BSS related initiatives
across a number of leading Middle East operators including Iridium,
Djezzy, Syriatel, MTC Touch, and Spacetel Yemen Sami Tayara
will share key insights into utilizing dashboards to successfully
communicate key metrics to all stakeholders in your organization.
• Outlining current interest in the use of performance dashboards
and the potential pitfalls that arise during implementation
• Understanding design challenges and developing effective
solutions that will aid the success of data warehouse and dashboard
initiatives
• Reviewing best practice as applied at #1 wireless operator in USA:
Tactical dashboard for monitoring and analysis of product lifecycle information.
Metrics in dashboard enable management to quickly adjust the product offering
or adjust quality and performance characteristics, leading to increased
subscribers satisfaction and an optimized portfolio
Presentation Summary
Sami Tayara | Bicentric | 227 Bellevue Way NE #157 | Bellevue, WA 98004 | USA | email: sami@tayara.net

• Investing in BI became a must with the large increases in available business data
and the increasing importance of having the right information at the right time
• The proliferation of enterprise applications in all departments as well as services
delivered through external partners resulted in a “data jungle” and raised the need
for standardization and consolidation, and for “one version of the truth”
• Managers at all levels realized the EIS of the 1980s is not cutting it anymore!
• Rising competitive pressures plus legal compliance requirements put more weight
and urgency on developing a new BI strategy, which gave dashboards prominence
as the most visible component at the top of the BI pyramid
Embracing BI and Dashboards within Management Strategy
A 2005 Gartner research 4 emphasized this persistent misconception that dashboards are a
“quick way to present strategic KPIs in a portal to top management”. It warns that the failure of
a poorly conceived dashboard project can harm the prospects of future better planned BI
initiative, and urges BI consultants to be prepared to stand up and explain to managers why it is
not enough to “only want a dashboard”.

• Business Performance Management (BPM) is an emerging framework that moves us
from measuring performance to managing performance
• “A Performance Dashboard is a multilayered application built on a business intelligence
and data integration infrastructure that enables organizations to measure, monitor, and
manage business performance more effectively“ 6
• Operational Dashboards monitor key operational processes and are used by
employees closer to the customer such as in Call Centers
• Tactical Dashboards are used at the department or project level and emphasize
analysis and monitoring against targets
• Strategic Dashboards mostly use a Balanced Scorecard approach to monitor
progress of strategic objectives, and provide the critical link between KPIs and company-
wide strategic goals
Without a business context, dashboards are of little benefit, and in many cases can be
counterproductive. This pitfall is documented since the 1990s in the works of experts such as
Kaplan and Norton, Harvard Business School 1, and widely adopted by today’s leading BI tools
providers.
Not Just Dashboards: Performance Dashboards and Scorecards

1. Alignment of Tactics and Strategy by using a “strategy map”1 and
the sharing of metrics and communication of goals throughout the
organization
2. Focusing Employees on Priorities by enabling managers to focus
on performance in those areas aligned with strategy, and not get
distracted with unrelated opportunities
3. Promoting Accountability and Ownership by assigning employees
responsibility over specific metrics, and avoiding cases where a
problem remains unattended for lack of clear ownership
• Avoid metrics that single out particular individuals and produce undue pressures in the
workplace, as these have shown to backfire
• Metrics used to influence behavior or evaluate future strategies will affect employees’
actions and decisions, and behavioral dynamics will push the company to inadvertently
“become what it measures” 2, despite the executives best intentions
Careful KPI Selection To Achieve Three Specific Business Gains

Current organizational structures tend to promote information silos which obstruct information
sharing and increase the cost and implementation time of BI projects, even leading to total
project failures. Above mentioned policies can be a cure to the silos phenomenon.
• Executive sponsorship of BI initiatives is critical, but a more practical and
effective approach is the introduction and enforcement of company-wide metadata
and BI policies and standards, as well a the setup of BI competency centers
• Metadata for all company data-holdings should be centrally developed and
managed as soon as possible, within the context of company-wide data integration
• BI standards cover many areas, but they should all serve the ultimate goal of
enabling the sharing of data by BI applications to guarantee one version of the truth.
Another key goal is to balance and align short-term tactical BI initiatives with the
long term goal of integrated BI systems company-wide
• Implement strict controls on the integrity of data assets using QA processes, data
lineage, and audit trails. Restrict the “Excel culture” which was proven to be an
impediment to BI in the best cases and a vehicle of fraud in many cases
Company-Wide Metadata and BI Policies

Meet Both Current and Future Requirements
A successful dashboard is one that will get high user adoption, and that will
consequently grow and be subjected to new user requirements. Scope
expansion needs to be foreseen in the original design, and should have a clear
roadmap from the start.
A dashboard is primarily a tool to visualize data in an underlying data
warehouse. The data warehouse architecture is key to meeting the scope
expansion challenge. In particular, the right metadata architecture within the data
warehouse, and building metadata-driven ETL processes, will both greatly
contribute to a flexible and scalable solution.
Metadata-Centric Data Warehouse Architecture

Data Quality Assurance
Gartner article 5 predicts that in 2007, half the BI projects in the USA will have
limited acceptance, or fail outright, due to lack of user trust in the completeness
and accuracy of the data in the warehouse.
• The first line of defense against bad data is the ETL code used to import it into
the data warehouse. Your ETL design should enable customizable quality
checks for each input data stream, and clear flagging of detected bad data
• The second line of defense is the inclusion in the data warehouse architecture
of complete end-to-end audit trails and data lineage, which are required enablers
for automated (as well as people driven) Quality Assurance systems
Enable QA with End-to-End Audit Trails and Data Lineage

Data Integration
• The flow of data into your warehouse is preceded by several pre-requisites, one of
them being source data “profiling”, a discovery process that precedes the setup of
ETL processes to bring the right data into the warehouse
• Data profiling is greatly simplified when a company has implemented a form of
data/metadata integration. Data profiling can get complex, time-consuming,
inefficient, and unreliable when no data integration exists
• As a result, many BI and dashboard initiatives have faced bottlenecks at this
critical step at the very beginning of the data pipeline, and project costs and/or
success rates have suffered
• There is no immediate quick fix to this problem! There are many Data Integration
standards currently gaining acceptance (such as SOA for BI, JSR 168, etc), but they
haven’t matured yet
• BI projects time and cost can be gradually lowered when companies introduce BI
policies that mandate all IT transactional systems and other data sources be “BI-
friendly”, as per emerging Data Integration standards
Include Data Integration Standards in Company-Wide BI Policies

Operations and Maintenance (O&M) for Long Term Success
Once your new BI system passes acceptance testing, continued operations and
management (O&M) often prove more significant than originally expected. This
is mainly due to IT limited familiarity with this most recent addition to its portfolio.
The below table from a 2002 DMReview article 3 provides an estimate of human resource
commitments for O&M, excluding any change requests and new features
Plan and Budget O&M Resources Early in BI Project

Dashboard Implementation Example
from USA #1 Wireless Operator
• Tactical Dashboard for monitoring and analysis of product lifecycle
information. It includes 100s of metrics from many internal and external
(partner) data sources and allows drill-downs for root-cause analysis
• Allows quick analysis on a product by product basis thus enabling as-needed
adjustments to the product offering or to the quality and performance
characteristics, leading to increased subscribers satisfaction and an optimized
portfolio
• Dashboard usage is integrated within a complete business process that
involves periodic requirements and quality review sessions with product
managers, and is supported by a department dedicated to service quality
measurement

Example of Best Practices in BI Systems Design
• Support for End-to-End Data Quality Assurance
• Metadata-Driven ETL for Scalability and Lower Operational Costs
• Most efficient ETL when data sources are standardized, but acknowledging
shortcomings in data integration, the design allows for import of unstructured data
• Pre-calculated metrics enable delivering new dashboards while ETL team is still
integrating the detailed data sources, leading to faster response to new requirements

• With competition so intense,
dashboard enables executives,
managers, and other
stakeholders to easily remain
on top of their numbers
• As a result of the metrics
alignment with strategy,
information in the dashboard
provides the right insight
management is looking for
• Below is one possible
dashboard concept that
implements this best practice
Best Practices in Dashboard Design : Alignment of Metrics and Strategy
NOVEMBER 7, 2005 INFORMATION TECHNOLOGY/Online Extra
Getting Cingular Up to Speed
CEO Stanley Sigman talks about the challenges of the AT&T Wireless merger and how he plans
to catch up with Verizon Wireless
How are you doing in key metrics like churn and profitability?
We call the key metrics in this company the Four Rs -- rate of penetration, revenue intensity,
return on operations, and reputation. On rate of penetration, we're certainly behind Verizon. We
outsell them in gross sales by 20%, but their churn is better than ours, so their net addition of customers
is better. In average revenue per user, we were about a dollar better than them -- about $50 vs. $49. On
return on operations, they're the best in class and we're the lowest in class on our margins. And on
reputation, they're best in class and we're toward the bottom of the pack.
What's the strategy for improving your service and reputation?
I don't think it's time for us to go out touting on a national basis that we have the best network until we do
have the best network. I know where our network stacks up. There's absolutely no reason why we can't
have as good a network as Verizon has. If we don't, we failed to execute.
What's your data strategy?
We have more data customers than anyone else in the market today. We have the most prolific 2.5G
data network [which runs at 60 to130 kilobits per second] in the country. We have nearly 47,000 sites.
What services do you offer that have given you the No. 1 spot in data?
[The biggest segment] of the data services is e-mail messaging. We're the leader in BlackBerry (RIMM ).

1) Kaplan, Robert and Norton, David (1996) “The Balanced Scorecard:
Translating Strategy Into Action” Harvard Business School Press
2) Hauser, John and Katz, Gerald (1998) “Metrics: You Are What You
Measure!”
3) Gallo, James (2002) “Operations and Maintenance in a Data Warehouse
Environment” Published in DMReview in December 2002
4) Buytendijk, Frank and Gassman, Bill (2005) “Management update: Just
Give Me a CPM Dashboard” Gartner Inc.
5) Hostmann, Bill and Buytendijk, Frank and Friedman, Ted (2005) “Avoid
the Fatal Flaws of Business Intelligence and Corporate Performance
Management” Gartner Inc.
6) Eckerson, Wayne (2005) “Performance Dashboards: Measuring,
Monitoring, and Managing Your Business” Publisher: Wiley
References:

Thank you for attending!
For additional information
contact Sami Tayara
at the address below

Sami Tayara BI Presentation ATT Jan07B

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