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Defining BI Success

Defining BI Success

Defining BI Success is Challenging

For BI practitioners, understanding project critical success factors is crucial

Ask

“How will I know my project is a success?”

“What measures should we track to confirm improved {enter project deliverable here, e.g. data access, cycle time improvements, increased sales} that we can directly attribute to {enter the project name here}”

This session is about defining value and success to secure active support

2

BI Success and Business Impact

Vendors present this situation as worse than it is

That said, the degree of very successful BI deployments is low (note the mistake

in 2012, the second “slightly successful” should be “very successful”)

3

Source: Howson

BI’s Contribution to Company Performance

It would be interesting to see what respondents meant by “somewhat” and slightly”

Note: Neither “somewhat” nor “significant” “cracked” 50%

4

Source: Howson

Successful BI’s Contribution to Performance

At 34% the percentage of initiatives significantly contributing to company performance is 10% higher than those who describe their solution as very successfully deployed

So… A BI initiative can be perceived as being less successful but positively contributing to business performance. This might result from poor execution with good content

5

Source: Howson

BI Success and Business Impact Are Not Synonymous

Success Perceptions

IT = Technical implementation

Business = How the data is used

The gap between vision and reality often disappoints

It may be difficult to comprehend specific actions taken directly resulting from BI

A BI solution with great architecture may not have the intended, positive impact with its business users

6

Source: Howson

Prof’s Notes

Howson’s point about IT’s evolution toward a better business orientation mirrors the concept of “IT as a service”

Since BI is highly client facing this is crucial

Project managers (PMs) can bridge the gap

An effective PM captures success criteria, ensures project success and tracks and shares success stories with all parties

7

Justifying Success – Managers Love Numbers

Most projects calculate Net Present Value (NPV) and Return on Investment (ROI) during the project but

rarely calculate it after transition to operation because its not easy to determine the ongoing returns

Where F = future cash flow and R is the company’s discount, or “hurdle” rate

So…

If an investment of $10 yields $20 one year hence, you should invest

If an investment of $10 yields $8 one year hence, you should not invest

Companies who are risk adverse tend to set higher discount rates than companies with a high appetite for risk

8

– Initial Investment

Source: Howson

Class Exercise: Let’s Calculate NPV Using Excel

9

Download your Excel spreadsheet from Canvas module 4

Note how a difference in initial investment triggered acceptance or rejection for Company A, Project A

Note how a difference in the discount, or hurdle, rate triggered acceptance or rejection for Company B, Project B

BI’s Return on Investment (ROI)

BI should be like a phone or the internet. Unfortunately, its not yet, so we have to invest more effort to justify the investment

Not everyone will agree whether revenue increases are specifically related to BI vs. other factors like training or organizational realignments

Cycle time savings tend to be a logical “play” but be careful: sponsors are never keen on promising staff reductions

Suggestion: Tie anticipated cycle time savings to potential growth increases to maintain status quo (this is cost avoidance)

ROI is a precise number derived from imprecise inputs. Always document and confirm the assumptions that went into your numbers! You will be held to account and assumptions provide a potential “escape valve”

Howson (2014)

10

ROI (Continued)

Average ROI for BI projects: 300 – 400% (some as high as 2,000%!)

For every $1 spent on analytics organizations earned an average of $10.66 (Nucleus Research, 2011)

Forrester (2012): if a composite organization of 1,500 employees with $500 million in sales invests in BI, they should see an ROI of 97%

ROI calculations provide a basis for comparison among BI implementations

11

Source: Howson

ROI (Continued)

“Guesstimating” ROI is better than nothing. Your company will probably require an ROI calculation with its project evaluation

For the revenue component, devise a number (it will be debatable) and obtain support prior to presenting it

? Be ready to justify your numbers under heavy questioning!

12

Source: Howson

The Case of Data Mart A

Cost/Benefit Analysis (CBA) completed in Year 0

CBA was refreshed in Year 2

This was a data mart developed to support the small business insurance line of a major primary insurance company

Prof was the program manager for this initiative and then managed it in full operation for three years

13

Data Mart A: User Success Criteria

Captured during the project initiation phase

14

Data Mart A: From the CBA’s Benefits Summary

When the Data Mart A program was initiated three years ago, management anticipated a loss ratio reduction of .01% resulting in additional profit of $3 million annually from cycle time savings and increased productivity

The subject matter experts have since removed this benefit because they confirmed there is no way of verifying whether additional profit was attributable to Data Mart A

The revised benefits included in this analysis cover only cycle time improvements and infrastructure and technical support savings

15

Data Mart A: The CBA’s Reported Cycle Time Improvements

On Year 2 the subject matter experts confirmed:

Cycle time savings of 10% resulted from Data Mart A’s single version of the truth and simpler reconciliation procedures. This percentage is expected to increase to 25% starting with Data Mart A’s third year of operation

Time savings of 75% were also cited from Data Mart A’s provision of a comprehensive data dictionary. This means if analysis using prior applications took one hour to complete, improved data understanding now speeds the same analysis to finish within fifteen minutes

Therefore, for the application’s first two years of operation, 85% of applied analysts’ time should be saved, with an anticipated increase to 100% starting year three. This means starting with the third year of operation, a request that would have taken one hour to finish in previous applications will now take less than a minute

16

Data Mart A: The CBA’s Reported Cycle Time Improvements (Continued)

Despite this positive feedback, we considered our experience in removing the loss ratio benefit and referred to our original subject matter expert feedback captured during initiation that confirmed before Data Mart A, approximately 40% of applied analysts’ time was spent querying data

For year 1 we derived the cycle time benefit by halving the 40% applied time pre Data Mart A to 20% post Data Mart A and taking the difference

For year 2 onward, we halved the applied time again, to 10% and applied the difference

17

Data Mart A: The CBA’s Reported Usage and Salary Impact

To achieve a number of applied resources, we derived an average monthly distinct user count using Data Mart A specific Cognos self service reporting usage statistics. As of May, year 2, an average of 200 distinct users have accessed Data Mart A monthly over a period of six months. We then took a very conservative 40% of that number and applied it for these benefits estimates

A conservative average annual salary, including benefits, of $75,000 was applied in this analysis for all personnel, regardless of organizational role

18

Data Mart A: The CBA’s Reported Infrastructure Savings

With the implementation of Data Mart A a series of legacy applications were decommissioned, among them the “The Express Database,” its Access based ad hoc query tool, multiple data feeds, a legacy data mart and related storage. While the team was unable to procure a precise dollar amount for these savings, for the purposes of this analysis we have conservatively estimated them to be $5,000 annually

19

Data Mart A: The CBA’s Reported Support Savings

Technical support is no longer required for the decommissioned legacy applications. Again, the team was unable to achieve a precise dollar amount, so a similar calculation was applied to that used to derive cycle time savings: the removal of the need for 25% of two employees’ time per year at an annual salary, including benefits, of $75,000

20

Data Mart A: Benefits Summary

21

Data Mart A: Cash Flow and ROI Analysis

22

Data Mart A: Net Cash Flow Analysis

23

Data Mart A: Cumulative Cash Flow Analysis

24

Data Mart A: Net and Discounted Cash Flow Analysis

25

The Case of the Dashboard Program, Project Proposal

Executive Management has requested an executive level dashboard to consolidate and display aggregated data pertaining to key performance indicators for the small business line.

Please Note:

The main savings from this project are in cycle time savings, which the program sponsors confirm equate to approximately two personnel annually.

This will not result in a workforce reduction (italics and color added), instead personnel will be redirected to more productive tasks upon implementation.

26

The Case of the Dashboard Program, Project Proposal

This CBA focuses on all phases with specific target focused on:

Flow, loss and premium information

An Account Executive Dashboard to provide meaningful and actionable metrics to support the field in their daily operations

An inventory management module which will provide account executives with account and policy level flow detail to support the management and growth of their territory

A prospecting module which will assist the account executive in identifying and flagging new prospects. Data from a variety of sources will be used to identify potential prospects

Cognos reporting functionality will be integrated with the tool. Reports will be for use not only by the account executives but by their respective managers to provide higher level “roll-ups” on multiple sales territories

27

Dashboard Program: Dashboard Program Goals and Benefits

Note: This slide refers to that portion of the dashboard program CBA focused on an executive dashboard

28

Dashboard Program ROI Example

29

Dashboard Program Net Cash Flow Analysis

30

Dashboard Program Cumulative Cash Flow Analysis

31

Dashboard Program Net and Discounted Cash Flow Analysis

32

So What Happened?

Data Mart A was originally the primary data store for the company’s small business lines

An executive dashboard was built leveraging Data Mart A which wasn’t used much because executives did not like hands on access

The account executive dashboard was then built leveraging Data Mart A. Since the CEO mandated its use it was a huge success

Note: Your Prof thought that a CRM system would have better served this need

33

So What Happened (Continued)?

The team’s responsibilities grew!

They had been on their own supporting the small business line

They were given an underused corporate data warehouse to manage

Data Mart A’s goal was revised to become a true data mart, no longer accessing source files directly, it now accessed the corporate data warehouse

As your Prof left they considered leveraging lessons learned to leverage Data Mart A to reinvigorate an existing, little used enterprise data mart

34

Managerial Implications

Emphasize business benefits, not technology

The BI team must have both business and technical knowledge

Procure direct business input for critical success factors

Comfort with financial calculations and budgeting is critical

Project and program management skills are fundamental

ROI is most often described by a combination of the net present value (NPV), internal rate of return (IRR) and payback period

35

Reference List

Howson, C. (2014). Successful business intelligence: Unlock the value of BI and big data. New York. McGraw Hill Education.

ISBN: 9780071809184

36

36

ContactFindings

Business Sponsor

– 25% of 40 people’s time is spent on data reconciliation tasks

– Reasonable goal should be to cut that in half: 12.5%

– If that’s the case, then people should free up enough time for more analysis, resulting in improved pricing and profitability

– Thinks we can lower the loss ratio by .1. Against $3 billion in assets under management, that savings is approximately $3m.

User A

– Chuck currently spends 10% of his time in TED. User B spends approximately 25% of her time.

– Loses cycle time to incorrect data and rework

– Data Mart A could reduce cycle time and support faster decisions to support rate

– Selection will be more accurate

– Thinks an improvement in rate adequacy and a reduction in loss ratio is justifiable

User B

– Doesn’t see the same chasing of reconciliation issues as the others but does see the data quality issues being a problem.

– If a Data Mart A t is provided:

a. Sees increased usage among his five folks

b. Sees faster, better decision making

c. Thinks he can hit the hot spots sooner

User C

– Can’t respond to the question “how does my flow look on the 15th?”

– Every region is doing their own calculations

– Calculation:

a. 60 people on staff, at least 50 spend between 25 – 50% pursuing data.

b. They think that there’s an improvement in the loss ratio of at least .1%.

Projected Annual Cycle Time Savings

Average Annual Salary (incl. benefits)$75,000

* Number of Average Distinct Cognos Users (200 * 40%)$6,000,000

/ 40% (Estimated Analysis Time, Pre Data Mart A, 2009)$2,400,000

* 20% (Estimated Analysis Time, Year 1)$1,200,000$1,200,000Savings, year 1 (Pre Data Mart A % – Post Data Mart A %)

* 10% (Estimated Analysis Time: Year 2+)$600,000$1,800,000Savings, year 2+

Estimated Annual Hardware Savings $5,000(50% applied year 1)

Estimated Annual Support Savings, All Applications

Average Annual Salary (incl. benefits)$75,000

* Number of Support Personnel (estimated at 2)$150,000

* 25% (Conservative estimated time dedication)$37,500

Total Estimated Annual Support Savings$42,500(50% applied year 1)

5 Year Benefits ProjectionYear 0 = 2009Year 1 = 2010Year 2 = 2011Year 3 = 2012Year 4 = 2013Year 5 = 2014Total Over 5 Years

Cycle Time Savings$0$1,200,000$1,800,000$1,800,000$1,800,000$1,800,000$8,400,000

Hardware Savings$0$2,500$5,000$5,000$5,000$5,000$22,500

Support Savings$0$18,750$37,500$37,500$37,500$37,500$168,750

$0$1,221,250$1,842,500$1,842,500$1,842,500$1,842,500$8,591,250

** Note: Phase 1.0 was implemented in June, 2010

Goals: The Dashboard program produces an integrated view of Key Business Metrics in an intuitive dashboard visualization format resulting in a readily available,

consistent and well defined business metrics.

Benefits: The Executive Dashboard provides the following key business benefits: Cycle Time Savings, Integrated view of business drivers, Intuitive Dashboard

Visualization with readily available and actionable business metrics, it is the cycle time savings that are proposed heretic is estimated that two full-time employees spend

their time researching in addition to Agent level metrics and IT research ETL design enhancements to streamline the load process thus making it more manageable to

maintain. The time savings that will result will provide a platform to re-route these personnel to move value added work.

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Chapter4HowtoMeasureBISuccess1.pptx
Home>Reading homework help>Research4
How to Measure BI Success

1

Defining BI Success is Challenging

For BI practitioners, understanding project critical success factors is crucial

Ask

“How will I know my project is a success?”

“What measures should we track to confirm improved {enter project deliverable here, e.g. data access, cycle time improvements, increased sales} that we can directly attribute to {enter the project name here}”

This session is about defining value and success to secure active support

2

BI Success and Business Impact

Vendors present this situation as worse than it is

That said, the degree of very successful BI deployments is low (note the mistake

in 2012, the second “slightly successful” should be “very successful”)

3

Source: Howson

BI’s Contribution to Company Performance

It would be interesting to see what respondents meant by “somewhat” and slightly”

Note: Neither “somewhat” nor “significant” “cracked” 50%

4

Source: Howson

Successful BI’s Contribution to Performance

At 34% the percentage of initiatives significantly contributing to company performance is 10% higher than those who describe their solution as very successfully deployed

So… A BI initiative can be perceived as being less successful but positively contributing to business performance. This might result from poor execution with good content

5

Source: Howson

BI Success and Business Impact Are Not Synonymous

Success Perceptions

IT = Technical implementation

Business = How the data is used

The gap between vision and reality often disappoints

It may be difficult to comprehend specific actions taken directly resulting from BI

A BI solution with great architecture may not have the intended, positive impact with its business users

6

Source: Howson

Prof’s Notes

Howson’s point about IT’s evolution toward a better business orientation mirrors the concept of “IT as a service”

Since BI is highly client facing this is crucial

Project managers (PMs) can bridge the gap

An effective PM captures success criteria, ensures project success and tracks and shares success stories with all parties

7

Justifying Success – Managers Love Numbers

Most projects calculate Net Present Value (NPV) and Return on Investment (ROI) during the project but

rarely calculate it after transition to operation because its not easy to determine the ongoing returns

Where F = future cash flow and R is the company’s discount, or “hurdle” rate

So…

If an investment of $10 yields $20 one year hence, you should invest

If an investment of $10 yields $8 one year hence, you should not invest

Companies who are risk adverse tend to set higher discount rates than companies with a high appetite for risk

8

– Initial Investment

Source: Howson

Class Exercise: Let’s Calculate NPV Using Excel

9

Download your Excel spreadsheet from Canvas module 4

Note how a difference in initial investment triggered acceptance or rejection for Company A, Project A

Note how a difference in the discount, or hurdle, rate triggered acceptance or rejection for Company B, Project B

BI’s Return on Investment (ROI)

BI should be like a phone or the internet. Unfortunately, its not yet, so we have to invest more effort to justify the investment

Not everyone will agree whether revenue increases are specifically related to BI vs. other factors like training or organizational realignments

Cycle time savings tend to be a logical “play” but be careful: sponsors are never keen on promising staff reductions

Suggestion: Tie anticipated cycle time savings to potential growth increases to maintain status quo (this is cost avoidance)

ROI is a precise number derived from imprecise inputs. Always document and confirm the assumptions that went into your numbers! You will be held to account and assumptions provide a potential “escape valve”

Howson (2014)

10

ROI (Continued)

Average ROI for BI projects: 300 – 400% (some as high as 2,000%!)

For every $1 spent on analytics organizations earned an average of $10.66 (Nucleus Research, 2011)

Forrester (2012): if a composite organization of 1,500 employees with $500 million in sales invests in BI, they should see an ROI of 97%

ROI calculations provide a basis for comparison among BI implementations

11

Source: Howson

ROI (Continued)

“Guesstimating” ROI is better than nothing. Your company will probably require an ROI calculation with its project evaluation

For the revenue component, devise a number (it will be debatable) and obtain support prior to presenting it

? Be ready to justify your numbers under heavy questioning!

12

Source: Howson

The Case of Data Mart A

Cost/Benefit Analysis (CBA) completed in Year 0

CBA was refreshed in Year 2

This was a data mart developed to support the small business insurance line of a major primary insurance company

Prof was the program manager for this initiative and then managed it in full operation for three years

13

Data Mart A: User Success Criteria

Captured during the project initiation phase

14

Data Mart A: From the CBA’s Benefits Summary

When the Data Mart A program was initiated three years ago, management anticipated a loss ratio reduction of .01% resulting in additional profit of $3 million annually from cycle time savings and increased productivity

The subject matter experts have since removed this benefit because they confirmed there is no way of verifying whether additional profit was attributable to Data Mart A

The revised benefits included in this analysis cover only cycle time improvements and infrastructure and technical support savings

15

Data Mart A: The CBA’s Reported Cycle Time Improvements

On Year 2 the subject matter experts confirmed:

Cycle time savings of 10% resulted from Data Mart A’s single version of the truth and simpler reconciliation procedures. This percentage is expected to increase to 25% starting with Data Mart A’s third year of operation

Time savings of 75% were also cited from Data Mart A’s provision of a comprehensive data dictionary. This means if analysis using prior applications took one hour to complete, improved data understanding now speeds the same analysis to finish within fifteen minutes

Therefore, for the application’s first two years of operation, 85% of applied analysts’ time should be saved, with an anticipated increase to 100% starting year three. This means starting with the third year of operation, a request that would have taken one hour to finish in previous applications will now take less than a minute

16

Data Mart A: The CBA’s Reported Cycle Time Improvements (Continued)

Despite this positive feedback, we considered our experience in removing the loss ratio benefit and referred to our original subject matter expert feedback captured during initiation that confirmed before Data Mart A, approximately 40% of applied analysts’ time was spent querying data

For year 1 we derived the cycle time benefit by halving the 40% applied time pre Data Mart A to 20% post Data Mart A and taking the difference

For year 2 onward, we halved the applied time again, to 10% and applied the difference

17

Data Mart A: The CBA’s Reported Usage and Salary Impact

To achieve a number of applied resources, we derived an average monthly distinct user count using Data Mart A specific Cognos self service reporting usage statistics. As of May, year 2, an average of 200 distinct users have accessed Data Mart A monthly over a period of six months. We then took a very conservative 40% of that number and applied it for these benefits estimates

A conservative average annual salary, including benefits, of $75,000 was applied in this analysis for all personnel, regardless of organizational role

18

Data Mart A: The CBA’s Reported Infrastructure Savings

With the implementation of Data Mart A a series of legacy applications were decommissioned, among them the “The Express Database,” its Access based ad hoc query tool, multiple data feeds, a legacy data mart and related storage. While the team was unable to procure a precise dollar amount for these savings, for the purposes of this analysis we have conservatively estimated them to be $5,000 annually

19

Data Mart A: The CBA’s Reported Support Savings

Technical support is no longer required for the decommissioned legacy applications. Again, the team was unable to achieve a precise dollar amount, so a similar calculation was applied to that used to derive cycle time savings: the removal of the need for 25% of two employees’ time per year at an annual salary, including benefits, of $75,000

20

Data Mart A: Benefits Summary

21

Data Mart A: Cash Flow and ROI Analysis

22

Data Mart A: Net Cash Flow Analysis

23

Data Mart A: Cumulative Cash Flow Analysis

24

Data Mart A: Net and Discounted Cash Flow Analysis

25

The Case of the Dashboard Program, Project Proposal

Executive Management has requested an executive level dashboard to consolidate and display aggregated data pertaining to key performance indicators for the small business line.

Please Note:

The main savings from this project are in cycle time savings, which the program sponsors confirm equate to approximately two personnel annually.

This will not result in a workforce reduction (italics and color added), instead personnel will be redirected to more productive tasks upon implementation.

26

The Case of the Dashboard Program, Project Proposal

This CBA focuses on all phases with specific target focused on:

Flow, loss and premium information

An Account Executive Dashboard to provide meaningful and actionable metrics to support the field in their daily operations

An inventory management module which will provide account executives with account and policy level flow detail to support the management and growth of their territory

A prospecting module which will assist the account executive in identifying and flagging new prospects. Data from a variety of sources will be used to identify potential prospects

Cognos reporting functionality will be integrated with the tool. Reports will be for use not only by the account executives but by their respective managers to provide higher level “roll-ups” on multiple sales territories

27

Dashboard Program: Dashboard Program Goals and Benefits

Note: This slide refers to that portion of the dashboard program CBA focused on an executive dashboard

28

Dashboard Program ROI Example

29

Dashboard Program Net Cash Flow Analysis

30

Dashboard Program Cumulative Cash Flow Analysis

31

Dashboard Program Net and Discounted Cash Flow Analysis

32

So What Happened?

Data Mart A was originally the primary data store for the company’s small business lines

An executive dashboard was built leveraging Data Mart A which wasn’t used much because executives did not like hands on access

The account executive dashboard was then built leveraging Data Mart A. Since the CEO mandated its use it was a huge success

Note: Your Prof thought that a CRM system would have better served this need

33

So What Happened (Continued)?

The team’s responsibilities grew!

They had been on their own supporting the small business line

They were given an underused corporate data warehouse to manage

Data Mart A’s goal was revised to become a true data mart, no longer accessing source files directly, it now accessed the corporate data warehouse

As your Prof left they considered leveraging lessons learned to leverage Data Mart A to reinvigorate an existing, little used enterprise data mart

34

Managerial Implications

Emphasize business benefits, not technology

The BI team must have both business and technical knowledge

Procure direct business input for critical success factors

Comfort with financial calculations and budgeting is critical

Project and program management skills are fundamental

ROI is most often described by a combination of the net present value (NPV), internal rate of return (IRR) and payback period

35

Reference List

Howson, C. (2014). Successful business intelligence: Unlock the value of BI and big data. New York. McGraw Hill Education.

ISBN: 9780071809184

36

36

ContactFindings

Business Sponsor

– 25% of 40 people’s time is spent on data reconciliation tasks

– Reasonable goal should be to cut that in half: 12.5%

– If that’s the case, then people should free up enough time for more analysis, resulting in improved pricing and profitability

– Thinks we can lower the loss ratio by .1. Against $3 billion in assets under management, that savings is approximately $3m.

User A

– Chuck currently spends 10% of his time in TED. User B spends approximately 25% of her time.

– Loses cycle time to incorrect data and rework

– Data Mart A could reduce cycle time and support faster decisions to support rate

– Selection will be more accurate

– Thinks an improvement in rate adequacy and a reduction in loss ratio is justifiable

User B

– Doesn’t see the same chasing of reconciliation issues as the others but does see the data quality issues being a problem.

– If a Data Mart A t is provided:

a. Sees increased usage among his five folks

b. Sees faster, better decision making

c. Thinks he can hit the hot spots sooner

User C

– Can’t respond to the question “how does my flow look on the 15th?”

– Every region is doing their own calculations

– Calculation:

a. 60 people on staff, at least 50 spend between 25 – 50% pursuing data.

b. They think that there’s an improvement in the loss ratio of at least .1%.

Projected Annual Cycle Time Savings

Average Annual Salary (incl. benefits)$75,000

* Number of Average Distinct Cognos Users (200 * 40%)$6,000,000

/ 40% (Estimated Analysis Time, Pre Data Mart A, 2009)$2,400,000

* 20% (Estimated Analysis Time, Year 1)$1,200,000$1,200,000Savings, year 1 (Pre Data Mart A % – Post Data Mart A %)

* 10% (Estimated Analysis Time: Year 2+)$600,000$1,800,000Savings, year 2+

Estimated Annual Hardware Savings $5,000(50% applied year 1)

Estimated Annual Support Savings, All Applications

Average Annual Salary (incl. benefits)$75,000

* Number of Support Personnel (estimated at 2)$150,000

* 25% (Conservative estimated time dedication)$37,500

Total Estimated Annual Support Savings$42,500(50% applied year 1)

5 Year Benefits ProjectionYear 0 = 2009Year 1 = 2010Year 2 = 2011Year 3 = 2012Year 4 = 2013Year 5 = 2014Total Over 5 Years

Cycle Time Savings$0$1,200,000$1,800,000$1,800,000$1,800,000$1,800,000$8,400,000

Hardware Savings$0$2,500$5,000$5,000$5,000$5,000$22,500

Support Savings$0$18,750$37,500$37,500$37,500$37,500$168,750

$0$1,221,250$1,842,500$1,842,500$1,842,500$1,842,500$8,591,250

** Note: Phase 1.0 was implemented in June, 2010

Goals: The Dashboard program produces an integrated view of Key Business Metrics in an intuitive dashboard visualization format resulting in a readily available,

consistent and well defined business metrics.

Benefits: The Executive Dashboard provides the following key business benefits: Cycle Time Savings, Integrated view of business drivers, Intuitive Dashboard

Visualization with readily available and actionable business metrics, it is the cycle time savings that are proposed heretic is estimated that two full-time employees spend

their time researching in addition to Agent level metrics and IT research ETL design enhancements to streamline the load process thus making it more manageable to

maintain. The time savings that will result will provide a platform to re-route these personnel to move value added work.

Applied Sciences
Architecture and Design
Biology
Business & Finance
Chemistry
Computer Science
Geography
Geology
Education
Engineering
English
Environmental science
Spanish
Government
History
Human Resource Management
Information Systems
Law
Literature
Mathematics
Nursing
Physics
Political Science
Psychology
Reading
Science
Social Science
Home
Homework Answers
Blog
Archive
Tags
Reviews
Contact
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