Business Intelligence

Michael Lamont, ’12

lamont@post.harvard.edu

Decisions

Stra

teg

ic

Tactic

al

Decisions

Decisions

Decisions

Possible to make a good decision

without data technology

Looking at the right data can help you

make better decisions

Decisions aren’t judged on a binary

“good” or “bad” scale.

Decisions

Decision quality is measured on a

gradient scale

Disastrous Excellent

Decisions

Decisions drive companies

Better decisions lead to:

More efficient operation

Higher profitability

Greater customer satisfaction

Companies that make better

decisions are more successful

Business Intelligence

Business Intelligence (BI): Using data

about yesterday and today to make

better decisions about tomorrow

BI makes companies smarter:

The right criteria to judge success

Locating and transforming the right data

Arranging information

Lets management see things more

clearly, and glimpse the future

Limited Resources, Unlimited Decisions

Every organization has to make do with

only what they have, all the time

You can’t hire only the brightest minds

and spend unlimited money on

efficiency

Time is the most precious resource your

company has – it has to move quickly,

not just correctly

Limited Resources, Unlimited Decisions

BI is a powerful ally when a decision is

required

Flexible resource that can be used by

any level of the organization

Limited Resources, Unlimited Decisions

Examples of simultaneous BI tasks:

VP of Sales deciding which markets &

accounts to target to meet sales targets

Product developers deciding which

fragrances to use in future products

Gulf Coast marketing team deciding on

holiday weekend promotions

BI Defined

Lots of very different definitions of

business intelligence exist

BI used to be a marketing buzzword that

got tied to not strictly related

technologies

Every vendor invents a definition that

skews toward their products

Researchers, authors, & consultants all

have their own pet definitions

BI Defined

Business Intelligence is timely, accurate,

high-value, and actionable business

insights, and the work processes and

technologies used to obtain them.

There’s no “magic list” of processes or

software that constitute BI

BI is high tech, and thus always evolving

Every company’s situation is different

Insights

Insights should flow

out of successful BI

projects

An insight is:

A new way to look at

things

A moment of clarity

A path forward

Something that you

didn’t already know

about your company

Business Intelligence

Accurate Valuable Timely Actionable

Accurate Answers

Decisions should be:

Informed by data

Made by subject matter experts

Based on hard information

For BI to be valuable, it has to:

Reflect objective reality

Adhere to strict standards of correctness

Accuracy is a core attribute of BI

insights

Accurate Answers

BI is subject to “Garbage In, Garbage

Out” (GIGO) rule

Business Intelligence Process

Inaccuracy Example

Sales exec sees a region lagging behind

Senior executives adjust sales process

(and personnel) in that region

What if the insight was wrong?

Some sales offices were incorrectly

allocated to neighboring region

Sales volume wasn’t correctly allocated

Actions taken were less than helpful –

may have made things worse

Accurate Answers

Accuracy is also important from a

political perspective

BI can’t have a real impact unless

people trust it

BI insights can be

Surprising

Counterintuitive

Threatening to some groups/managers

Accurate Answers

Any error, no matter how small, is going

to be used to call into doubt every

conclusion pulled from the data

BI has to be as accurate as possible to

protect its reputation from skeptics

Inaccurate BI insights are worse than

useless – they’re damaging

One bad BI experience will keep it from

ever being trusted again

Valuable Insights

Not all insights are created equal

Reporting that people who buy peanut

butter also buy jelly isn’t much of an

insight

BI should produce information that can

have a real impact on a business

Valuable Insights

Impact of valuable BI insights can be:

Reduced costs

Increased sales

Operational efficiency

Other positive factors

High-value insights aren’t usually

deducible

Insights aren’t always obvious, but can

have huge impact

Valuable Insight Example

Walmart analysis of most popular

products after severe hurricane damage

Valuable Insight Example

Timely Information

Die Geist der Treppe – the “Spirit of the

Staircase”

Delivering facts late in a debate keeps

them from mattering

Information delays in business can have

the same level of impact

Timely Information

Information delays come in many forms:

Workflow (not refreshing data frequently

enough)

Technology (lack of computational power

and efficiency)

Unexpected logistics issues

The time taken for each step in a BI

process, added together, has to be short

enough to make results useful

Timely Information

Timeliness is a required part of useful

insights

High quality BI processes need current

information

Analysis products need to be provided

to decision makers in time for them to

consider all courses of action

Actionable Conclusions

Insights are worthless if they can’t be

acted upon

Non-actionable insights:

Major competitors should instantly cease

operating

Factories should be 20 years newer

Decision support tools will happily find

non-actionable insights if you let them

Actionable Conclusions

An insight is actionable if there’s a

reasonable way to take advantage of the

situation

Conclusion Action Result

The Value of BI

Links information with action

What’s the real value returned from an

investment in BI tools and processes?

Promoting and supporting better

decision making habits

The BI Cycle

Raw Operational

Data

Business Insights

Take Action

Measure Results

The BI Cycle

Companies that follow the cycle have a

rational decision making process

Business Intelligence supports the cycle

Obtain insights from operational data

Good insights can be applied to decision

making process

Decisions lead to actions, and improved

operational results

Cycle repeats and decisions are refined

Trends

BI continues to increase in importance

to both large enterprises and SMBs

BI is flexible, and responsive to

technological advances

Trends

BI projects are originating outside IT

departments

IT used to be the only group that knew what

data and analyses were available

Executives and other decision makers have

gotten comfortable with BI

Trends

Delivery of analytics to desktop (and

mobile devices)

Premier vendors can round-trip data to

standard Office applications

Excel includes advanced analytical tools

Trends

Data access is becoming more dynamic

and approaching near-real-time

BI systems of the future will be able to

directly pull data from operational systems

Computational efficiency of BI systems is

constantly increasing

Conclusions

Business Intelligence isn’t just about

computing

Requires a corporate culture that

supports data-driven decision making

Business managers must promote data-

based decision making

IT has to support the tech behind BI at

all levels of the company

Conclusions

BI gives you new tools and perspectives

Lets you ponder what-if questions

Decision makers have to know how to

ask the right questions

No set rules for determining the “right”

reports and analytics for a particular

company

Conclusions

The right people have to be in the right

positions for BI to work

BI is a commitment to rational decision

making processes

Must be supported at all levels of the

company, by both managers and IT

Michael Lamont, ’12

lamont@post.harvard.edu