Five Good And Really Bad Ideas For Bi Iniatives

ITA BI Roundtable
The Top 5 Good and Very Bad Ideas
in Implementing your BI Initiative

Jeff Block
Capstone Consulting

Tuesday, January 13, 2009
© Copyright 2008 Capstone Consulting, Inc.
Capstone Consulting, Inc

What are we talking about?

Today’s Agenda
 Why are we here?
 Who’s in the room?
 Presentation – Five Good and Very Bad Ideas
 Discussion / Networking

© Copyright 2008 Capstone Consulting, Inc. 2 Capstone Consulting, Inc


Today’s Agenda


Where’s “here”? Why are we here?

Welcome
to the first meeting of the

ITA
Business Intelligence
Roundtable


Who am I? Why are we here?

Jeff Block, Capstone Consulting
BI Roundtable Chairman


Logistics Why are we here?

• 2nd Tuesday of every month; 8-10 AM
– Here at the ITA TechNexus unless there’s a good
reason to change venues
• Sometimes a presentation
– My ideas, your ideas, case studies, best practices, new
developments, etc
• Sometimes an outside speaker
– Love to have some of you step up to the plate
– Don’t want to hear myself talk to much
• Always discussion
– Collaboration is the whole point of this group
• Always networking
– Meet people who will be valuable connections


Topics and Target Audience Why are we here?

• Business and technology leaders
– Not going to spend much time deep in the
technical weeds
• Those who want to
– Learn from each other
– Collaborate on solutions
– Network
in the BI space
• ITA members and their friends and their
friends and …


In Scope Why are we here?

• Business Intelligence
– Vision and strategy
– Planning and implementing BI initiatives
– High-level architecture
– Best practices / Anti-patterns
– Case studies
– Etc
• What about data warehousing?
– It’s in! (part of BI, in my world)


What is Business Intelligence? Why are we here?

BI is not about delivering access to a massive
repository of data, often unconstrained and
overwhelming. BI is about delivering highly relevant,
highly valuable applications, reports, and dashboards,
designed to maximize the user’s ability to gain specific,
actionable knowledge from corporate data.
Of course – and this can’t be overstated – this requires
a culturally-relevant, well-supported governance
model and a highly-specialized, flexible data
architecture, both optimized for this purpose.


Classic BI Architecture Why are we here?

Our focus is the stuff in this picture and the practices
and processes that get it there effectively.
BI Presentation Components

Data Data Data Data
Mart Mart Mart Mart

OLAP Services

Source Source
Systems ETL Data Warehouse ETL Systems


Out of Scope Why are we here?

• Other stuff
– How’s Aunt Ruth’s cat?
• Building the tech together
• Arguing over low-level tech details
• If we talk about
– Project management / SDLC
– Architecture and design
– Business processes
– Etc
then it will be in the context of BI / DW


Some Quick Feedback Why are we here?

How does this line up with
your expectations?



Today’s Agenda


Brief Introductions Who’s in the room?

Please share with us…

• Name
• Company
• Role
• What you want to get
out of this group?



Today’s Agenda


Five

Best Practices


Five Best Practices

1. Build a solid value statement


Solid Value Statement Best Practices #1

Axiom: Every complex, expensive
initiative requires a strong business case
describing cost and benefits


Solid Value Statement Best Practices #1

• Make an air-tight case
– For the right solution
– To real needs
– And measurable pain
– Which key people are feeling
– And passionate about fixing
• Be straightforward about cost
– Be able to justify that cost with projected ROI
– They’ll likely be qualitative, but quantitative is better
• Speak in the language of the business
• Think out objections and know how to handle
them before you start


Five Best Practices

2. Make sure the right person sponsors the
initiative


Initiative Sponsored
Best Practices #2
by the Right Person

Axiom: Strength of character,
leadership, political influence, and
personality are required


Initiative Sponsored
Best Practices #2
by the Right Person

• One person has to be responsible
– Advocacy: The initiative’s top champion
– Authority: The influence to make it happen
– Accountability: Where the buck stops
• Typically the CIO
– Or someone he trusts and appoints himself
• Must first be a business person
– Sponsor has to know the business
– Cannot be (even perceived as) an IT initiative
• Must have cross-functional clout
– Cannot be (even perceived as) about a single business unit
• Must be a diplomat
– Will have to broker countless peace agreements


Five Best Practices

initiative
3. Warehouse no more or less data than you
need right now


No More or Less Data
Best Practices #3
Than you Need

Myth: Everything has to be in
the data warehouse


Best Practices #3
Than you Need

• Understand strategy and organization’s KPIs
• Gather and prioritize requirements from key
data stakeholders
• Build EXACTLY what they need
– No more
• If you can’t “justify” why a piece of data is in the data
warehouse, then it shouldn’t be there
• “Justify” means relating back to the business case /
strategy / top-level KPI’s
• Everything you do should have that traceability


Best Practices #3
Than you Need

• Build EXACTLY what they need
– No less
• Make sure you get everything you need to delivery value
• Don’t worry about “complete” requirements
– There’s no such thing
• Don’t fudge, clean up, assume or create data in your ETL
• Data quality issues are fixed in the source system
• Mature iteratively
– Release new versions (with concrete value) frequently
• Presentation layer – every 30 days
• Data marts – every 60 days
• Data warehouse / ETL – every 90 days


Five Best Practices

initiative
need right now
4. Identify and build on bedrock data


Bedrock Data Best Practices #4

Axiom: Drive a stake in the
“bedrock data” in your organization,
and only graft onto it when expanding


Bedrock Data Best Practices #4

• Bedrock data is
– Data you have (typically)
– Data structures that won’t change easily or any time
soon
• Don’t build on shifting sand
– Data most important people in the organization can
agree on (conformed dimensions)
– Likely related to your business’ most important
processes
• Which makes it simultaneously very important and very
difficult to lock down
• Work hard to avoid silos in your BI/DW solution
– Hard to work with silos in transactional systems
– Nearly impossible to consolidate silo’d DWs


Five Best Practices

initiative
need right now
5. Rely on dimensional modeling to structure
your data


Dimensional Data Modeling Best Practices #5

Axiom: Transactional systems
and BI systems require completely
different data models



• Operational systems
– Where we put data in
– Users make the wheels of the organization turn
– Users affect one row at a time
• Data model optimized for the current transaction; writing a
single new record
• No need to know history (so shouldn’t)
– Users perform the same tasks over and over



• BI systems / Data warehouse
– Where we get data out
– Users watch the wheels of the organization turning
– Users read and perform domain aggregate
functions on many, many rows at a time
• Almost never deal with one row at a time
• Optimized for reading and comparing many rows,
aggregating and disaggregating data, drilling
up/down/through, etc
• Ideal for consistent historical and comparative trending
– Users continuously change the kinds of questions
they ask



Dimensions Dimensions
• Two core elements: Facts
Customers Clerks
“facts” and “dimensions”
– Facts Customer
• Core data of a Items Purchased Dates
business event Item
• The “verb” in the
sentence describing Store Times
the event
– Dimensions
• Context in which the event occurred
• The “nouns” in the sentence
• Sometimes called “cubes”
– Because comparisons are made by pivoting on dimension
tables joined by fact tables
• Sometimes called a “star schema”
– Because of the star-like shape of a fact table surrounded by
dimension tables


Five Best Practices: Questions?

initiative
need right now
5. Rely on dimensional modeling to structure
your data


Five

Worst Practices


Five Worst Practices

1. Pick the technology first


Pick the Technology First Worst Practices #1

Myth: The technology is the hard part



• Many see BI / DW as a technology problem
– So, they purchase tools in an attempt to “buy BI”
• Tech is actually the (comparatively) easy part
• Much harder
– Securing executive commitment (including funding)
– Building consensus / conforming dimensions
– Establishing governance
– Controlling scope and growth
– Accurately defining requirements
– Supporting the system
– Etc, etc, etc



A quick, rough order of priority…

1. Plan
2. People
3. Process
4. P… Technology



2. We’re agile; we should just start building


Just Start Building Worst Practices #2

Myth: We can figure that out later
(whatever “that” is)


Just Start Building Worst Practices #2

• News flash: The reason you’re putting it off is
because it’s hard
• Hard stuff has to get done first, not last
• Always flesh out your risk as soon as possible
• Agile / iterative is good, even essential
– Applies to iterative construction of tools, delivering on
requirements
– Implies phased rollout, short sprints, frequent releases
of value, etc
– Does NOT imply that we jump over or scream by the
vision and strategy stages



3. Ignore the political landscape


Ignore the Political Landscape Worst Practices #3

Myth: Good planning, smart people,
and hard work can overcome anything


Ignore the Political Landscape Worst Practices #3

• Do invest too heavily in your BI initiative until you
have…
– Plentiful executive support
• Demonstrated, not just verbal
– Some skeptics won over
– Staff bribed in key positions all over the organization
– Excellent business case
– Well-conceived objection handling plan
– Outside help on speed-dial for areas which aren’t your
strengths
• Much of this implies quick wins up front



4. Leave out critical support functions


Critical Support Functions Worst Practices #4

Myth: Build it and they will come



• You need governance
– How do we decide how to decide?
– People, policies, processes, permissions, etc
– Key policy needed: Limit Jeff’s alliteration of “P”
• You need marketing
– It’s not true that “if we just have this awesome data
warehouse, then everyone will fall over
themselves to use it”
– Build a communication plan
– Expect most people to be skeptics, especially
most of those who helped you get your funding



• You need user training
– Fact: Business users won’t know how to use BI unless
the presentation is mind-numbingly simple
• If you need paragraphs of explanation, rethink your design
– Spend time in the classroom, not generating help files
• You need IT support
– The DW won’t take care of itself
– Needs more care and feeding than other apps, not less
– Consider external managed support



5. Don’t address the question of data
ownership


Data Ownership Worst Practices #5

Myth: IT owns the data


Data Ownership Worst Practices #5

• IT should NOT own the data
– They own the machinery that holds the data
– Difference between “water” and “plumbing”
• No one business unit should own the data
either
– The more you can make it the whole
organization’s data, the better off you’ll be
– After all, the goal is cross-functional analysis
• Governance council is the representative
government of the data warehouse / BI


Five Worst Practices: Questions?

5. Don’t address the question of data
ownership


Capstone BI Preparedness Index

• Six key dimensions of readiness
– Passion – Knowledge
– Need – Vision
– Influence – Credibility
• Capstone meets with key personnel
– In the context of a BI assessment
– Organization has to collectively score well enough on
all these dimensions to justify firing the start gun
• Offer simple quantitative indicator of readiness
– Offer gap analysis if not ready
– Recent example:


Q&A Group Discussion


w w w. c a p s t o n e c . c o m


Five Good And Really Bad Ideas For Bi Iniatives

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