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How Smart Companies Use Information to Become More Competitive and Profitable

Gerry Cohen & Dr. Rado Kotorov

Now Available on Amazon!

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Why did you write this book?

To provide a larger picture of the value of our software in real-life situations...

…and an understanding of products that are 'deep' enough to do all of the things we do.

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Who is the intended audience?

BI and analytics practitioners and managers – analysts, IT, line of business managers, executives.

Prospects, customers, and our staff - now and in the future.

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Why organizational intelligence? Why not simply BI?

We observed that the most successful uses of our software are best illustrated by the innovative things our customers do beyond traditional BI to increase the performance of the organization.

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Why is it important to know the history of technology and BI?

• Understanding how we got here helps to navigate today’s complex technology landscape, make better choices, avoid problems, and discern value from hype.

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Key Takeaway What is the one key takeaway

from the book?

We wanted to make it a ‘good read’.

And also illustrate that the real benefits of BI and analytics come when you make it pervasive.

Push it to the 78%.

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Why Are the 78% So Important?

"In the study of organizations, the employee must be the focus of attention, for the success of the structure will be judged by his performance within it".

Herbert Simon, Nobel Prize winner for studies in decision-making in 1978

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What Are the Needs of Different BI Users?

Statisticians, Operations Research Specialists, Mathematicians, etc.

Insights analysts SMEs, Go-To analysts,

Implementation analysts

Front-line employees, partners, suppliers, customers

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How Do You Align Technologies With User Skills?

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What Is an InfoApp And Why Do Users Need It?

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Expedia: 1000s of fields/100s of reports/0 training

Why do we use this analogy?

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Allows Users to Have ‘Dialogue’ with Data

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InfoApp: Iteratively Query Data to Find Answers Quickly

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InfoApps solve an important problem: Too many reports too few answers.

Fast and immediate access to the information you need to make decisions.

Custom built to solve your particular problem.

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9 Great Stories: Why Did You Choose Them?

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They are great case studies because they successfully monetize their data.

What do we mean by data monetization?

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nVision: Capturing Incremental Revenues

nVision processes 100 million invoices and manages $5.2 billion in freight liability each year.

The iFocus InfoApp helped their clients be more self sufficient to analyze invoice costs and save on transportation costs.

iFocus saves customers an additional 2% of shipping costs per year.

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The Path to Data Monetization: Technology Enablement

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What do you expect the readers to learn from these stories?

The use cases are very straightforward

Give people new ideas Offer some practical advice

on how to upsell their ideas and implement them

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Q&A Thank you!