Research12

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Selecting the Right BI Tools for Enhanced Adoption

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BI Tool Selection and Building Consensus

Source: Howson

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The Importance of the BI Front End Tool

Front end tools facilitate data access, insight and action

Business users should define requirements for the front end tool

Joint business and IT involvement is key

Joint business-IT evaluations should balance

Ease of use and scalability

Flexibility and ensuring consistent results

Visual appeal and security

While users tend to be reasonable and understand the importance of the solution architecture, they care most about the front end tool

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The Case of the Maligned Tool

Situation

A division of a pharmaceuticals company implemented a locally developed BI application with a Business Objects front end and an unreliable back end

Their enterprise focused colleagues implemented Business Objects with a well engineered solution architecture

What do you think happened?

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The Case of the Maligned Tool (Cont’d)

Result

The division’s users blamed Business Objects for their suboptimal solution and resulting BI use was minimal

Enterprise users embraced Business Objects because they could rely on Business Objects’ output.

 Both sets of users referred to their BI solutions, both the suboptimal local implementation and the well engineered enterprise one, as “Business Objects”

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The Case of “We Like This Other Tool Better”

Situation

A reinsurer embarked on a $100 million enterprise resource planning (ERP) effort

Their standard enterprise BI technologies were Oracle, Informatica and Business Objects

The company shifted from an centralized IT model to a shared IT model with local IT “shops”

One business unit accepted the enterprise BI technologies

The other business unit was more comfortable with Microsoft SQL Server so they used that

This business unit also considered replacing Business Objects with Cognos because they had experience with it and “liked it better”

What do you think happened?

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The Case of “We Like This Other Tool Better”

Result

The business unit that did not follow the enterprise standard needed to manage their own back end databases and extracts built with Microsoft SQL Server

Had they gone with Cognos they would have had to manage that as well

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BI Standardization

Varieties of standard BI “tool stacks:”

Business Objects front end, Informatica ETL, Oracle Back End, SAS for Analytics

Cognos front end, Ab Initio ETL, Teradata Back End, SAS JMP For Analytics

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Source: Howson

BI Standardization’s Pros and Cons

Driver: The business requires a return on their software investment

Pros and Cons:

Pros Cons
The company reaps their required return Lower cost of ownership and improved support. The solution architecture tends to be more scalable with less interfaces between modules to maintain A (potentially) seamless user experience Fosters a single version of the truth Potential inflexibility due to lack of a “best of breed” approach The knowledge required to maintain the modules may be specialized. You may be held captive by your vendor. A (potentially) disjointed user experience May wittingly or unwittingly foster multiple versions of the truth

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Source: Howson

Progress Toward the BI Technology Stack

Companies are proactively managing their BI tool portfolios.

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Source: Howson

Beware Custom BI Applications

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Source: Howson

The Case of the BI Application in Search of a Programmer

Situation

One day when your Professor was working for a large insurer he received a call from a business user

This user had a catastrophe mapping application her team built locally that needed a software upgrade. Unfortunately the programmer had left the company

What do you think happened?

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The Case of the BI Application in Search of a Programmer (Cont’d)

Result

Your Prof assessed the situation and attempted help on an ad hoc basis

As usually happens with “ad hoc work” the time requirement became too demanding so they added the remaining work to the BI team’s demand pipeline

This business user left the company soon afterward

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The Benefits of BI Standards

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Source: Howson

Additional Points About BI Standardization

Switching vendors becomes more difficult as the scale of deployment increases

As tool capabilities evolve companies’ BI services also evolve, i.e. from self service and standard reporting to visualization and big data analytics

Custom development should be used on a very limited basis to supplement existing tool capabilities. These days “build” is rare

Ensure your BI environment evolves with the marketplace and keep your BI vendors “on their toes” and alert

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Source: Howson

The Right BI Tool for the Right BI User

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Source: Howson

BI User Segmentation

General User Population

Management of the General User Population

Functional Subject Matter Experts

Senior/Executive Management

Data Subject

Matter

Experts

Widest, Guided

Use

Narrowest,

Most Autonomous Use

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Source: Howson

Fact-Based Decisions

Strategic Decisions

Long term consequences

Broad implications

Less frequent, annual or longer

Tactical Decisions

More frequent, weekly or monthly

BI’s traditional focus

Operational Decisions

Details

Many more operational decisions are taken than strategic decisions

While one operational decision alone does not make a large difference, in the aggregate thousands of these decisions have a huge impact!

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Source: Howson

Decisions, Value and Volume

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Source: Howson

Predictability

Type of decision (strategic, tactical and operational) drives its predictability

Exploratory analytics are later instantiated into reports or dashboards

When information needs are predictable, dashboards, standard reports or custom-build applications are ideal

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Source: Howson

Job Level and BI

Job level drives the breadth and detail of data accessed

Executives

Broad data, less detail

High access, less analysis

Dashboards are prevalent

Mid Level

Broad data, more detail

Add slice-and-dice and what-if analysis to dashboards

Lower Level

Narrow data, highest detail

Standard reports with interactive prompts

Operational information integrated into customer applications

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Source: Howson

Job Function and BI

Job Function

Segment users by

Similar information needs

Required features

Examples

Finance: Spreadsheet integration

Marketing: Predictive analysis or Powerpoint integration for Marketing

Sales: Mobile and tablet applications

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Source: Howson

Job Context and BI

Analytic Content

Some jobs require more data analysis than others

This segment has the highest BI usage rate

Examples:

Financial Analysts, Actuaries, Data Scientists

Senior personnel

Work intensely with BI tools

Understand data sources and nuances

Comfortable creating complex queries

These people may complain loudest but they’re not your only users!

Other roles may only access BI a few minutes weekly or rely on analytic output

Do not expect users to become BI experts!

Empower them vs. assuming data analysis is their primary job

Just because they demand more features all your users do not need advanced capabilities, recognize the differences

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Source: Howson

Data Literacy

Technical literacy and data literacy are two different things

Some users understand the solution architecture but do not understand business statistics

Some users understand data nuances, others do not

Consider what you provide in your BI solutions. Users may emerge with sufficient capability to hurt themselves!

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Source: Howson

Data Meaning and Tailored Training

Users tend to be more familiar with the precise meanings of data elements

Hierarchies within the BI application may be a new concept for users

Tailor BI training and mentoring to the audience

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Source: Howson

Technical Literacy

As technology has become a consumer product people are more aware of it

Some people are less technically proficient than others due to

Age

Education

Socioeconomic Factors

As previously discussed, different roles require different technical literacy

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Source: Howson

User Demographics = Added Complexity

Baby Boomers (Born 1945 – 1965) Millenials (Born 1980 – 2000)
Technology is new Prefer phone calls and face time Tolerant of errors Willing to wait Accept asynchronous communications Grew up with technology Prefer texting Expect perfection Want instant gratification Are avid users of and expect real time response

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(And Generation X (born 1965 – 1980) must be considered too!)

Source: Dalkir

Include BI Tool Orientation in User Adoption

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Source: Howson

Spreadsheets, Friend and Foe

Many think everything should be delivered via spreadsheet

Microsoft Excel is known as “the leading BI tool”

Spreadsheet management is required or chaos will result

Consider spreadsheet based BI interfaces

Friend: Users work with spreadsheets with refreshed data from the BI platform

Foe: Users export data out of BI applications into their spreadsheets

Exports from BI applications to Excel remain common

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Source: Howson

Other Key BI User Needs

Mobile capabilities for travelling workers

Sharing data with external users (suppliers and customers) introduces

Licensing concerns

Different requirements

Authentication via extranets

Volume and scalability challenges

Potential restrictions on content and functionality

Howson (2014)

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BI Module Success in Declining Order of Impact

The “big three” of fixed reports, query and dashboards in top three spots is no surprise

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Source: Howson

Satisfying Frustrated BI Users

“If someone, whether central IT, central BICC or a power user, is doing a better job of creating that fixed report, the business user is satisfied”

Business users want access to data and to tweak that data as needed

 A recurring theme is IT is not responsive or a roadblock

 IT should “join them, they should not try to beat them”

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Source: Howson

Additional Business Impacts

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Source: Howson

Reference List

Dalkir, K. (2011). Knowledge management in theory and practice (2nd

Ed.). Cambridge. MIT Press.

Howson, C. (2014). Successful business intelligence: Unlock the value

of BI and big data. New York. McGraw Hill Education.

ISBN: 9780071809184

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