Introduction To Predictive Analytics Part I

Introduction to Predictive Analytics – Part I

Jay RoyChief Strategy Officer

May 2011 | Dallas, TX

© 2011 Predictive Dashboards LLC

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Table of Contents …

Definition of Analytics and Predictive Analytics

How Analytics and Predictive Analytics Compare

Defining Business Intelligence “BI” and its Relationship to Predictive Analytics

Business Intelligence’s Evolution & its Organizational Impact

The Importance of Communication Skills & Predictive Analytics

The Business Case for Predictive Analytics

Conclusion and Key Takeaways

Definition of Analytics & Predictive Analytics


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What is Analytics?

Using analytics is like driving your car but watching traffic through the rear-view mirror, not seeing what’s ahead and thereby in danger of crashing

“… the application of computer technology, operations research and statistics to solve

problems in business and industry. Analytics is carried out within an information system.”

“… the application of computer technology, operations research and statistics to solve

problems in business and industry. Analytics is carried out within an information system.”

Tom Davenportnoted author


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What is Predictive Analytics?

Using predictive analytics is like driving your car and watching traffic through the front windshield, anticipating traffic, making course corrections to avoid

traffic jams and getting there faster and safer

“predictive models exploit patterns found in historical and transactional data to identify risks and

opportunities. Models capture relationships among many factors to allow assessment of risk or potential

associated with a particular set of conditions, guiding decision making for candidate transactions.”

“Any solution that supports the identification of meaningful patterns and correlations among

variables in complex, structured and unstructured, historical, and potential future data sets for the

purposes of predicting future events and assessing the attractiveness of various courses of action.”

How Analytics & Predictive Analytics Compare


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Predictive Analytics are more sophisticated analytics that “forward thinking” in nature

Analytics is the understanding of existing (retrospective) data with the goal of understanding trends via comparison

Developing analytics is the first step towards deriving predictive analytics

They used for gaining insights from mathematical and/or financial modeling by enhancing understanding, interpretation and judgment for the purpose of good decision making


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Attribute Analytics Predictive Analytics

Purpose:

Understand the Past

Observe Trends

Catalyst for Discussion

Gain Insights

Make Decisions

Take Action

View: Historical and Current Future Oriented

Metrics Type: Lagging Indicators Leading Indicators

Data Used: Raw & Compiled Information

Data Type: Structured Structured and Unstructured

Users: Middle & Senior Mgt

Analysts, End Users

C-Level & Senior Mgt

Strategists, Analysts, Mgrs

Benefits: Gaining an understanding of data

Productivity Improvements

Gaining Information & Insights

Process Improvements


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Benefits of Analytics and Predictive Analytics

Benefits of analytics: productivity gains through improved data-gathering processes results in less time required for producing reports and metrics

Takeaway: Both types of gains are beneficial but improvements in analytics are NOT as scalable as to the benefits in predictive analytics which are repeatable, virtuous and scalable

Benefits of predictive analytics: process improvement gains through improve revenue generation & cost structures leading to enhanced decision making

Defining Business Intelligence “BI” & its Relationship to Predictive Analytics


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Defining Business Intelligence & its Relationship to Predictive Analytics

Unfortunately, the human & business strategy elements are often overlooked and forgotten but are key ingredients to the

success of BI

“… computer-based techniques used in identifying, extracting and analyzing business

data … aims to support better business decision-making … BI technologies provide historical,

current and predictive views of business operations.”

BI is typically thought of in terms of technology inclusive of data management practices, data warehouses, ETL processes, etc.

Predictive Analytics are a sub-set of Analytics and a branch of BI which is the least understood and underestimated


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Analytics serves as the “glue” in aligning the key elements of business

Analytics provide the feedback to business people signaling success or failure of their strategy and business model

Business Intelligence = Business + Intelligence

Business = The Strategy + Business Model + Infrastructure + Technology

+ + +

http://www.clker.com/clipart-70079.html


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People create information for the organization in order to gain understanding of its customers, competitors and ecosystem

Business Intelligence is a process of generating insights and or knowledge (predictive analytics) through people and technologies in order to execute their strategy

This process needs to be leveraged into a core competency, a unique and virtuous process to differentiate the business in a world of “me-too” organizations & strategies

Intelligence = People + Processes + Analytics

+ +=

Business Intelligence’s Evolution & its Organizational Impact


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BI’s Evolution and its Organizational Impact

The most important part of BI is the human element and achieving people’s business and personal goals

Most businesses organize their BI activities and professionals under the IT function under the Enterprise 1.0 model

With advances in technology and social media, the Enterprise 1.0 model, is not the most efficient, scalable, and collaborative way to execute your business strategy especially from a human resourcing perspective

With globalization, advances in internet technologies and social media, we have advanced to the era of Enterprise 2.5

As a result of Enterprise 2.5, changes in business require evolution in BI


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BI’s Evolution & its Organizational (Design) Impacts

In the era of Enterprise 2.5, BI is readily becoming a distinctive capability & asset for organizations

If BI is deemed strategic, this function should be realigned to fall under the direction of the CEO or Office of Strategy Management (OSM)

Implementing a new organizational structure will encounter language and communication challenges between business and BI professionals

CEO

CIO

Business Intelligence Group

CEO

COO

CIO

Office of Strategy Management & Business Intelligence Group

Old Model – “Enterprise 1.0”

New Model – “Enterprise 2.5”



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The purpose of predictive analytics is to help organizations see relationships between business elements so senior management may craft targeted business strategies and exploit opportunities on a timely basis with a focus on the future

In order to benefit from predictive analytics, people across the organization must communicate and understand with one another but language often becomes a barrier

BI professionals often think language is SQL (Structured Query Language) and business people often think language is reports, metrics and meetings

IT & BI professionals need to understand the language of strategy, business models and performance while solving business not technology problems

SQL vs

http://www.clker.com/clipart-70079.html


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Need market segmentation report,

now!

OK, what are the parameters and

how do you want it rendered?

CEO/Business People BI People

Conversations @ Work


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Huh? What is he asking me?

Just need my report!

CEO/Business People

Huh? What is he asking me?

Market Segmentation?

BI People

Conversations @ Work


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Takeaway: Business professionals need to appreciate the role of technology as an enabler and they need to lead and determine where & how IT/BI infrastructure should be deployed to improve decision making

Takeaway: It is not enough to have state of the art in BI technologies, without having a common understanding and a common language between the business people and BI professionals, otherwise BI efforts will fall short of desired results

Takeaway: IT & BI professionals need to understand the language of strategy, business models and performance while solving business NOT technology problems

The Business Case for Predictive Analytics


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The Business Case for Predictive Analytics – Macro level

On a macro level, organizations need predictive analytics for:

Strategic Planning

Financial Planning

Focusing on Priorities

Competitive Analyses

Achieving Profit and Revenue Targets

Developing Competitive Advantages and Differentiation

Predictive analytics can provide timely feedback to executives on their strategic initiatives – without feedback course corrections may be too late

Predictive analytics provide leading indicators and insight to assist in planning for answering the big question: What should we do next? – next quarter, next year etc.


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The Business Case for Predictive Analytics – Micro level

On a micro level, organizations need predictive analytics for:

Improving business processes

Doing more with less budget (working smarter not harder!)

Allocating resources appropriately

Understanding correlations and sensitivities with customer segments

To ensure long term financial resources are available to run the business

Developing Competitive Advantages and Differentiation

Q: Why do most organizations struggle with Analytics and especially Predictive Analytics?

A: Organizations fail to recognize and misunderstand the necessary and intangible elements of people, skills, and corporate culture and tying these elements back to their analytics, business model and strategies – Caution: this is a long-term fix

Conclusion & Key Takeaways


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Takeaway: Predictive Analytics is the analytical ability to see relationships between business drivers and performance and the ability to model these relationships performed by people to improve organizational visibility

Conclusion: Business Intelligence begins with your organization’s strategy and business model and only then should performance metrics and analytics be appropriately conceived and deployed

Takeaway: It is not enough to have state of the art in BI technologies, without having a common understanding and a common language between the business people and BI professionals, otherwise BI efforts will fall short of desired results


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Takeaway: IT & BI professionals need to understand the language of strategy, business models and performance while solving business not technology problems

Takeaway: IT & BI professionals need to understand the language of strategy, business models and performance while solving business not technology problems

Takeaway: Business professionals need to appreciate the role of technology as an enabler and they need to lead and determine where & how IT/BI infrastructure should be deployed to improve decision making


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Sources, References, and Trade Marks

www.wikipedia.org

Competing on Analytics, 2007, Thomas H. Davenport

www.forrester.com

The Lego Minifigure is a trade mark of The Lego Group

Clipart provided by OCAL and www.clker.com

Introduction to Predictive Analytics – Part I

Jay Roy, Chief Strategy Officer

www.predictivedashboards.com

[email protected]

T:214-621-7612

Documents

Introduction To Predictive Analytics Part I