Premium Service Plan Proposal

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© 2012 GLOCO


Confidential and Proprietary







Premium Service Plan Proposal

Suresh Akana, Sheraz Choudhary, Craig Davis, Dave Fobert, Susan Korgen

12/15/2012


Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al and Propri etary


Page |

i

Table of Contents


Executive Summary
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...
1

Part I. Business Requirements

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.........
2

Business Context

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2

Use Case 1: Call To Service the Device (As
-
Is)

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.....................

2

Use Case 1: Call To Service the Device (To
-
Be)

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...................

2

Use Case 2: Producing Device Status Reports (As
-
I
s)

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................................
........

3

Use Case 2: Producing Device Status Reports (To
-
Be)

................................
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................................
......

4

Use Case
3: Preventative Maintenance (As
-
Is)

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....................

4

Use Case 3: Preventative Maintenance (To
-
Be)

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..................

4

Required Functionality

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...............................

5

Business Benefit Justification

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6

Solution Costs

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7

Solution Benefits
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7

Success Metrics
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7

Part II. Technical Specification and Prototype

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....
8

Architectural Approach
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8

Software Components

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10

Software Solutions

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12

Cloud Solution Provider Selection: Amazon Web Services (AWS)
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12

Dashboard Vendor Selection: Tableau
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................................
.

14

Integration with Existing Enterprise
Systems

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................

14

Data Design and Management

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16

Solution Demonstration
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17

Part III. Implementation Plan

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21

Project Development and Deployment

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21

Project Development Timeline

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21

Project Milestones

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.....

23

Operational Governance
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24

Resources

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24

GLOCO MedListener™ and OmniDash™ Project Team

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24

Beta Partner Health Care Provider Project Team
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26

GLOCO Stakeholders
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.

26

Communicating Using a Project Dashboard

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29

Communicating Agile Progress Against Milestones

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30

Dependencies and Health Check

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30

Risk Management

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31


Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al and Propri etary


Page |
i
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User Enablement and Training

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32

Transition


Beta Period
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..........................

32

Training
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........................

32

OmniDash
TM

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33

Success Metrics
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33

Appendix A: Breakdown of Development Costs

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35

Appendix B. Solution Benefits
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........
36

Service Plan Sales

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.......

36

Reduced Repair Costs

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36

Increase in Help Desk Productivity

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.....

37

Appendix C. Database Design and Management
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..............................
38

Device, Device Log, and Device Log Detail Tables

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.........

38

Device, Device Log, and Device Log Detail Record Diagrams

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....................

39

One
-
to
-
Many Relationships

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40

SQL for Creating Tables

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40

Data Flow Examples
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...

42

Java Code

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42

Sample Output

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44


Figures

Figure 1: As
-
Is Flow Diagram (Use Case 1)

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...............................

2

Figure 2: To
-
Be Flow Diagram (Use Case 1)
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..............................

3

Figure 3: As
-
Is Flow Diagram (Use Case 2)

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...............................

3

Figure 4: To
-
Be Flow Diagram (Use Case 2)
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..............................

4

Figure 5: To
-
Be Flow Diagram (Use

Case 3)
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..............................

5

Figure 6: High Level Architectural Overview Featuring MedListener™

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............

8

Figure 7: High Level Architectural Overview Featuring OmniDash™
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9

Figure 8: Detailed Technical Architecture

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...............................

10

Figure 9: Cloud Solution Pl atform Types

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.

13

Figure 10: Integration Model

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15

Figure 11: Data Flow

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17

Figure 12: Two Vi ews of a Preventative Maintenance Dashboard
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18

Figure 13: GLOCO’s Service Dashboard
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....

19

Figure 14: GLOCO’s Existing Trouble Ticketi ng System
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.......

19

Figure 15: Health Care Provider’s Dashboard

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20

Figure 16: Project Development Timeline

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22

Figure 17: Project Milestones
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23

Figure 18: GLOCO Project Team

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25

Figure 19: Beta Partner Health Care Provider Project Team
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26

Figur
e 20: GLOCO Project Organization and Stakeholders

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................................
.

28

Figure 21: Project Dashboard

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29

Figure 22: One
-
to
-
Many Rel ationshi ps

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40



Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

Page |

1


Executive Summary

Client Company

GLOCO, a large multi
-
national medical equipment manufacturer, employs 29,000 people and generates
$5.1
billion in medical equipment sales and $1.9 billion in service revenue
.

GLOCO’s vision to lead the world market
for high
-
quality medical equipment drives it to deliver innovative digital solutions to address pressing business
issues through new Information Technology and Communications (ICT)
projects.

IT Supplier

TeamOne So
lutions is an internal group within GLOCO that is piloting a new project to provide premium
equipment service plans with near real
-
time monitoring and analysis initially for ultrasound
machines.

TeamOne has developed two new products that will be used in
coordination with GLOCO’s existing
enterprise infrastructure as follows:



MedListener™

is a turnkey solution to integrate equipment capable of sending diagnostic information
for analysis and alerts in real
-
time for service calls.



OmniDash™

is a suite of web
-
based management dashboards. Each dashboard visualizes data to deliver
monitoring and alerting to support service and sales functions at the Health Care Providers (HCPs) and
GLOCO.

Business Goal

GLOCO

will offer a new level of premium support to hospitals, clinics, and labs that use GLOCO ultrasound
equipment.

MedListener™ and OmniDash™ can grow GLOCO’s
service
revenue by at least 4% in 2015 by:



Offering a higher priced premium level of support to the

existing customer base.



Capturing a larger market share by offering services not provided by competitors.

Implementation

The implementation will include a six
-
month pilot program at selected Health Care Provider(s) using GLOCO
ultrasound machines and then

will be available for purchase to all customers using GLOCO ultrasound machines
.
TeamOne will coordinate with pilot site IT personnel to enable outbound transmission of machine data to
Amazon Web Services (AWS) to support MedListener™.

TeamOne will then
train pilot site and GLOCO
superusers on how to use OmniDash™ for monitoring and analysis.

Measuring Success

GLOCO
will

measure the success of MedListener™ and OmniDash™ as follows:



Financial:

Grow GLOCO’s revenue by at least 4% in

2015.



Observable:

Increa
se customer satisfaction measured by surveys and focus groups of stakeholders.


Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

Page |

2


Part I. Business Requirements

This part of the proposal describes the business requirements for the solution:



Business context:

How the solution will improve business processes at the customer and GLOCO
.



Required functionality:

A specification of technical capabilities for the solution
.



Business benefit justification:

A summary of costs and benefits to be expected from the solutio
n
.



Success metrics:

How the success of the solution will be measured and verified
.

Business Context



Use Case 1:

Handling an unexpected call to service a device
.



Use Case 2:

Producing device status reports upon request
.



Use Case 3:

Scheduling routine mainte
nance for a device
.

Use Case 1: Call To Service the Device (As
-
Is)

The following diagram shows the current business process when a need for repairs to the devi
ce is observed at
the HCP
, GLOCO is alerted to this need by
HCP
, and GLOCO services this need.

F
igure
1
: As
-
Is Flow Diagram (Use Case 1)


Use Case 1: Call To Service the Device (To
-
Be)

The following diagram shows the future business process when a need for repairs to the device is occurs

at the
HCP
, GLOCO is
automatically

alerted to this need
in real
-
time
, and GL
OCO services this need.




Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

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3


Figure
2
:
To
-
Be Flow Diagram
(Use Case 1)


Summary of Benefit:

Reduction in steps,
faster
turn
-
around time

due to
real
-
time issue creation
, faster repairs

due to

relevant diagnostic information
, and
less
human involvement.

Use Case 2: Producing Device Status Reports (As
-
Is)

The following diagram shows the current business process when there is a need to collect device data for
analysis and report results.

Figure
3
: As
-
Is Flow Diagram

(
Use Case 2
)



Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

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4


Use Case 2: Producing Device Status Reports (To
-
Be)

The following diagram shows the future automated

business process when there is a need to collect device data
for analysis and report results.


Figure
4
: To
-
Be Flow Diagram (Use Case 2)


Summary of Benefit:

Reduction in steps, turn
-
around time, and human involvement. The larger the number of
ultrasound machines at an HCP the greater the benefits the HCP derives.

GLOCO
receives reports on units in the
field.

Use Case 3: Preventative Maintenance (As
-
Is)

Pr
eventative maintenance is currently not provided for ultrasound devices.

Use Case 3: Preventative Maintenance (To
-
Be)

The following diagram shows the future business
process in which the solution allows preventive maintenance
to be performed on the devices.




Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

Page |

5


Figure
5
: To
-
Be Flow Diagram

(Use Case 3)


Summary of Benefit:

Reduction in steps, turn
-
around time, and human involvement. Automatic re
porting allows us
to schedule maintenance when the machine needs it, not too late, and not too soon using a calculated Preventative
Maintenance Index (PMI)
.

Diagnostics also allow repair parts to be identified before technician arrives
.

Required
Functionality

The following points outline the IT functionality to be provided under this proposal:

1.

Each ultrasound device’s network settings
shall

be updated to permit communication with the hospital
network and the cloud.

2.

All device data
shall

be stored
in a central database in the cloud.

3.

The device
shall

transmit diagnostic information every 1 hour to the central database.

4.

The device
shall

transmit errors and warnings immediately to the central database. These transmissions
shall be called alerts.

5.

At the

same time an alert is sent, the device
shall

also access information from GLOCO’s CRM database to
send a message to the appropriate person at the HCP.

6.

In case of a complete device failure (system goes down), after reboot, the device
shall

send system
dump
s to the central database.

7.

In case of a normal maintenance or shutdown event, the device
shall not

send alerts to the HCP but shall
send data to the central database.

8.

All device data
shall

be made available to the HCP via a dashboard accessible through the

customer’s
existing customer service portal at GLOCO in a presentable way. This shall be called the HCP Manager
dashboard.

9.

The HCP Manager dashboard
shall

have the ability to generate presentable reports regarding multiple
devices.

10.

The HCP Manager dashboard
shall

have the ability to display repair and maintenance history for
individual devices.

11.

The HCP Manager dashboard
shall

have the ability to forecast future preventative maintenance needs
based on current usage levels.

12.

The HCP Man
ager dashboard
shall

show alerts and track the progress of the alerts.


Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

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6


13.

GLOCO
shall

have the ability to create multiple dashboards for its divisions.

14.

The GLOCO dashboard system
shall

show basic HCP customer information in addition to visualizations.

15.

The GLO
CO dashboard system
shall

be able to tie the equipment data to HCP orders, contracts, and
equipment inventory in
GLOCO
’s CRM system.

16.

GLOCO’s dashboard view
shall

show data across multiple HCPs at once allowing for the development of
business intelligence tools.

Busine
ss
Benefit Justification

Premium Service Package

will provide the following business benefits to GLOCO:



Increased revenue compared to as
-
is service s
upport plan:

o

Premium support will have higher margins than as
-
is support plan due to higher price and lower
costs
(benefit of automation and increased efficiency).

o

Increase in percentage of HCPs signed up with GLOCO for service packages. Presently, a port
ion of
HCPs use third
-
party ultrasound service
companies that

offer packages comparable to GLOCO’s
Standard Service Package. Third
-
party service companies will not be able to offer a plan comparable
to Premium Service Package leading to a competitive advan
tage.



Shorter amount of time and less money spent by support service staff per incident:

o

Decreased time spent on initial call from customer.

o

Automated trouble ticket population
in
GLOCO
’s Seibel CRM
.
Real
-
time monitoring results in
immediate notification

a
nd appropriate assignment

of incident
s.

o

Faster resolution of incidents.
Service support has customer information and incident details from
the machine diagnostics.

o

Anticipate maintenance

and staff
ing needs

based on
equipment
usage and incident history.

o

Create m
ore efficient service support workforce

with the use of a dashboard as a business
intelligence tool
.



Analyze world
-
wide equipment data on a variety of dimensions:

o

Find common faults and analyze any statistically significant factors related to incid
ents and usage
.

o

Better service support staff training to resolve incidents based similar past incidents.

o

Accurate data on probabilities of incidents


predictive models to accurately price service packages
to make determined profit margin
.

o

Ability to predi
ct equipment usage and end
-
of
-
life to develop a competitive sales edge
.


Premium Service Package

will provide the following advantages to the HCP:




Increase level of service support increases uptime and decreases risk:

o

Regular proactive maintenance decreas
es probability of malfunction
.

o

Immediate alert and more informed support staff


faster repair


reduction in costly downtime.

o

Coverage decreases risks associated with unexpected expenses.



Automatic monitoring of ultrasound machine, and daily and scheduled

maintenance:

o

Less staff time required
in
performing and logging

daily checks on equipment.

o

Less staff time to track and schedule regular maintenance.


Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

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7


o

Automatic tracking of daily usage of each ultrasound machin
e. This will enable the HCP
to
increase
effic
iency by distributing
use
across multiple ultrasound machines evenly.

o

Fault warnings and alerts for all equipment are automatically sent to GLOCO CRM system.



Premium support plane fulfills ac
creditation of equipment require
ment:
http://www.acr.org/Quality
-
Safety/Accreditation/Ultrasound
.


Solution Costs

The following table shows the premium service solution costs in financial terms.

Component

Initial Cost

Annual Cost

Software
Licenses

$200,000

$17,000

Development Costs
(See Appendix A)

$
316,941

$0

Maintenance Costs

$0

$60,500

Cloud Platform


Amazon 坥b Services

$5,000

$150,000

Employee Training

$50,000

$5,000

Total
s

$
554,565

$232,500

Solution Benefits

The following table shows the premium service solution benefits in financial terms. See Appendix
B

for
supporting calculations.

Component

Estimated Annual Benefit

Increase in Service Plan Sales

$8,580,000

Reduction in Repair Costs

$706,200

Increase in
Help Desk Productivity

$2,700,000

Ongoing
Solutions Costs

-
$
316,941

Total
s

$11,
669,259

Success Metrics

This proposal offers the following metrics for measuring the success of the project:

Metric

Goal

Increase Revenue

Increase GLOCO’s Service Revenue by

4%
.

Ultrasound Machine Downtime

Reduce downtime due to repairs by 60%
.


Reduction in Repair Costs

Reduce
time to repair machines by

20% by providing
diagnostic reports prior to site visits.

Increase in Help Desk Productivity

Reduce
average call times

20% by
automating trouble ticket
population.

Customer Satisfaction

Increase customer satisfaction by 20% based on survey data
.



Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

Page |

8


Part II. Technical Specification and Prototype

This part of the proposal describes the technical specification for the
solution:



Architectural approach:

a broad overview of the solution and its components.



Software
components
:

a detailed description of software components and their interactions.



Software solution
s
:

a discussion of specific software packages.



Integration wi
th existing enterprise systems:

interfaces between new and existing components.



Data design and management:

architecture and flow of data between components.



Solution demonstration:

a guided tour of user interfaces for the solution.

Architectural Approach

The following figure provides a high level overview of the architectural approach. This figure can be best
understood by tracing how data flows through the architecture in support of a breakdown at a Health Care
Provider site:

1.

A cooling fan breaks down and ultrasound machine sends an alert to the
MedListener™

application.

2.

The
MedListener™

application uses the device identifier from the alert to find information about the
customer and appropriate service representative in databas
es at GLOCO.

3.

MedListener™

files a trouble ticket in the customer resource management (CRM) system at GLOCO.
Processing of the trouble ticket proceeds as usual, as discussed in Part 1 of this document.

4.

MedListener™

acquires the ticket identifier and other i
ncident information from the CRM system.

5.

MedListener™

stores information about the alert and incident in its database.


Figure
6
: High Level Architectural Overview Featuring MedListener™



Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

Page |

9



The next figure continues a high level
overview of the architectural approach by tracing how data flows through
the architecture in support of a GLOCO user who wants to gain insight into ultrasound machine sales:

1.

Every night, GLOCO pushes information about ultrasound sales and service to the da
shboard database.

2.

A GLOCO user requests an OmniDash™ dashboard view of Health Care Providers and ultrasound machines.

3.

OmniDash™ pulls incident data from the MedListener™ database.

4.

OmniDash™ pulls customer and service representative data from the CRM and ot
her GLOCO databases.


Figure
7
: High Level Architectural Overview Featuring OmniDash™



Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

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10


Figure
8
: Detailed Technical Architecture


Software Components

The software solution is primarily a “green field”
installation of new software, but it will interact with and
require extensions to existing software. The software solution consists of the following components:



There will be
scripts

running on each ultrasound machine
that

send the following data to Amazon Web
Services via an encrypted connection
:

o

Hourly:

“normal” machine data such as battery levels, filter levels, fan speeds, etc
.

o

Immediately:

Alerts

when certain conditions are detected

such as a failed cooling fan.

o

After
a shutdown or network connection loss:

a

system dump upon reconnection.



MedListener™ will provide

a
listener application

in the cloud that:

o

Accepts machine data from the
ultrasound machines.

o

Stores machine data in the database.

o

Accepts alerts from the
ultr
asound machines

that include an error code and time of failure.

o

Responds to any received alert by entering a defect ticket into the CRM system at GLOCO.

o

Receives as a response from the CRM system an incident ID and service representative ID.

o

Stores inciden
t data in the database.


Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

Page |

11




MedListener™ will provide

a
proprietary database

in the cloud that:

o

Contains machine and incident data.

o

Accepts machine and incident data updates from the listener application.

o

Provides basic machine and incident data to the
Health
Care Provider

dashboard application.

o

Responds to queries from the GLOCO dashboard application.



There will be
an
existing CRM system
and

other databases

on the internal GLOCO network that:

o

Work

as before; for example,
allowing manual entry of defect tickets into the
CRM
system.

o

For the new solution:



Will receive electronically submitted defect tickets from the listener application.



Will provide a service that matches customers to service representatives.



Will respond to

a defect ticket with an incident ID and service representative ID.



Will respond to queries from the GLOCO and
Health Care Providers

dashboard applications.



There will be a
managed file transfer

FTP module at GLOCO that:

o

Pushes data from
GLOCO
databases to
dashboard caching databases in
the cloud.

o

Supports the GLOCO and
Health Care Provider

dashboard applications.



There will be an
existing self
-
service portal

for the
Health Care Provider

that works as before:

o

Pulling data from the Siebel datab
ases
.

o

Permitting access to support tickets and related information.



OmniDash™ will provide

an
Health Care Provider

dashboard application

in the cloud that:

o

Interacts with the database to display basic machine and incident data to Health Care Provider and
GLOCO
.

o

Supports reports on machine performance and status.

o

Supports reports on machine repair and maintenance history.

o

Allows tracking the progress of alerts and defect tickets.

o

Forecasts future preventative maintenance needs based on current usage levels.



OmniDash™ will provide

a
GLOCO dashboard application

in the cloud that:

o

Aggregates data from the database to display actionable analytics to GLOCO.

o

Supports analysis of equipment reliability statistics
.

o

Identifies aging or decommissioned devices that need

replacement
.




Premium Service Plan Proposal


© 2012 GLOCO


Confi denti al
and Propri etary

Page |

12


Software Solutions

TeamOne Solutions implementation of Premium Service Plans will use the following software solutions:

Extensive use of cloud services allows for faster implementation, scalability, on
-
demand use, and reliability.




Firmware upgrade on Ultrasound Machines performed by service technician
(
enable
cron job
1

schedule,
log file creation,
and secure

file transfer
)
.


Note:

Firmware will use existing wired and wireless connection capabilities present in the ultrasound
machi
ne
.



Amazon Web Services:

o

S3
(storage of all log files)
.

o

Route 53
(connection to AWS infrastructure: EC2, S3, Elastic Load Balancer)
.

o

EC2 Instances
(App Server to parse data for database; Windows Tableau Server for dashboard)
.

o

RDS
(database of log file dat
a)
.

o

SWS
(integration with GLOCO enterprise systems using a Tibco enterprise bus)
.

o

EMR
(MapReduce data)
.



Siebel
:

(existing solution
s

implemented at GLOCO)

o

Self
-
service portal
.

o

Sales and merchandising module
.

o

CRM system
.



Tableau Desktop

on GLOCO workstation to develop dashboards.



Tableau Server

on Amazon EC2 Windows instances to host dashboards.


Cloud Solution Provider Selection: Amazon Web Services (AWS)

GLOCO will use a cloud solution for the new infrastructure rather than use a trad
itional hosted solution within
GLOCO’s enterprise system. GLOCO can dynamically increase capacity as service plans are sold or decrease
capacity if accounts are lost. GLOCO will not need to invest in physical infrastructure, additional staff,
maintenance
, or software licenses. The incremental costs of the cloud solution will be incorporated into the
Premium Service Plan pricing.




1

A cron job is a simple software program that executes at specific time(s) of day. Cron is derived from “Chronology.”


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Figure
9
: Cloud Solution Platform Types


Amazon Web Services (AWS) and Microsoft Azure (Azure) are the two largest cloud solution providers. Both
these providers offer extensive services, competitive pricing, reliability, scalability, flexibility and reputation.
Azure is a Platform As A Service

(PAAS) while AWS is an Infrastructure As A Service (IAAS). Though, Azure’s
PAAS provides the benefit of easier setup
its

lock
-
in to Microsoft
-
based technologies was a major detriment as
detailed below.

The main factor of differentiation that lead to A
WS being selected for GLOCO Premium Service Plans is that AWS
is largely software agnostic while Azure is extensively integrated with Microsoft .NET technologies. GLOCO’s
existing infrastructure includes Siebel and Oracle ERP
systems, which

cannot easily
integrate with Azure without
extensive customization. AWS does not lock GLOCO into a particular software platform and provides equivalent
services and pricing to Azure.

Note:

For .NET
-
based technologies Azure provides easier integration than AWS and wou
ld be the preferred
selection.


AWS offers 99.95% uptime per their Service Level Agreement (SLA). TeamOne Solutions considered AWS highly
available
services that

offer 100% uptime
. We

determined that the additional uptime was not worth the extra
cost;

duplication of the architecture would essentially double the cost. AWS basic
-
level of service meets the
needs of the project
, as

each ultrasound machine will cache the diagnostic data in the event of a failed connection.


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Dashboard Vendor Selection: Table
au

Tableau Server was selected for its ability to create web
-
based dashboards and ability to easily integrate with
multiple data sources and formats.

For example, Tableau Server can integrate with Hadoop allowing for the
MapReduce

data generated by Amazon EMR to be used as a data source for dashboards.

This flexibility will
allow GLOCO to create dashboards on any of its existing data warehouses.

The dashboard is web
-
based and
requires no special software and has extensive securit
y access capabilities decreasing implementation
complexity and cost.

The dashboards can be integrated into existing web portals at GLOCO.

Tableau Server can be set up in a distributed environment with worker servers supporting the primary
server.

This wi
ll allow GLOCO to increase or decrease capacity as more support plans are sold.

Tableau primary
and worker servers will be hosted on Windows Amazon EC2 instances allowing GLOCO to scale without buying
hardware in advance to meet future demands.

The team i
nvestigated several Dashboard and Business Intelligence vendors including Domo, InetSoft, and
Dundas. Our research found that Tableau had the best value proposition in terms of balancing scalability, ease of
use, per user cost, and level of vendor support
. It can quickly be deployed “off the shelf” with no modifications.

Integration with
E
xisting
E
nterprise
S
ystems

The following figure illustrates the integration model for the solution. Segments of the drawing trace a variety of
interfaces from the ultras
ound machine to the dashboard visualization.




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Figure
10
: Integration Model





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Data
D
esign and
M
anagement

The purpose
of

the proprietary database
for the solution
is to collect
basic
information about the device


OEM,
n
ame,
m
odel, serial
n
umber and installation date



as well as
log information and start

and

end dates.

The
proprietary database

also
get
s

information from
the Siebel CRM system, such as the

c
lient
n
ame and all service
progress information
. The solution references

the

Seibel CRM Ticket ID

for this data
.

This way, all the needed
information about the ticket can be pulled into the dashboard for reporting.

The following diagram shows the data flow from the ultrasound machine to the dashboard.

The ultrasound device sends information


data logs, geographical location, IP address, error codes, warning
codes, and error or warning flags, if any


every hour to the cloud based solution. The flow of data from the
source starts with a data file collec
ted from the device and uploaded to a local file server. A Java program on an
application server in the cloud gets the file from the file server and uploads it to an Amazon S3 bucket in cloud.
In the cloud, an application server gets the file from the Ama
zon S3 bucket and parses the data to insert it into
database to support the reporting tool.

The data flow from the Health Care Provider to the cloud works as follows. For deta
ils of each step, see
Appendix

B
:

1.

Device connected either with
Wi
-
Fi

or Ethernet
.

2.

Ultrasound operating system to collect Machine information.

3.

File Creation job, output <DeviceName>+Datetime.txt.

4.

Cron job to run at schedule time.

5.

Secure transfer of data to Amazon over encrypted connection via on site App Server at Health Care
Provider
Location
.

6.

Java Program on Sever to Upload files from file system to S3 bucket.

7.

In Amazon access S3 from EC2 APP server via Java Program.


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Figure
11
: Data Flow



Solution
D
emonstration

The following figure shows two views of a
sample preventative maintenance dashboard. The dashboard pulls
together customer data from GLOCO as well as machine information in the cloud to calculate each ultrasound’s
Preventative Maintenance Index (PMI). Hours of use, fan speed, diagnostics, and so
forth all get calculated into a
PMI number that allows us to see which machines need maintenance. Any PMI value between 0 and 1 means no
maintenance is needed, any value greater than 1 means we need maintenance.

The dashboard shows all machines in their ge
ographic locations and has several filtering options. You can view
customers by their Zone, look at only certain Healthcare Providers, and change the PMI range that is displayed.
The map and bar charts update automatically.


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Figure
12
: Two Views of a Preventative Maintenance Dashboard




The following figure shows GLOCO’s Service Dashboard. Unlike the Preventative Maintenance Dashboard this
dashboard shows ultrasound machines that have errors and associated trouble tickets. Her
e we can see a similar
geographic view of Health Care Providers as well as a table describing the issues. We can also filter by date
range, zone, error code, and assigned technician.


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Figure
13
: GLOCO’s Service Dashboard


When
the user clicks on one of the cases, either in the table or map, they are brought directly to GLOCO’s existing
trouble ticketing system as seen below. The ticket is listed as “Machine Reported” as GLOCO was automatically
notified of the failure. A ticket

and a technician were assigned to the case without any human interaction.

Figure
14
: GLOCO’s Existing Trouble Ticketing System

2





2

Image courtesy of
http://www.mroshaw.co.uk/OllerenshawIT/index.php/2012/11/enabling
-
siebel
-
helpdesk/

and modified to fit our case.


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The following figure is an example of the Health Care Provider’s dashboard
, which will be integrate
d into their
existing customer service portal at GLOCO
. Unlike the previous GLOCO examples, this is a detailed view of the
customer’s data that they can track and look for trends. In the example below Emergency Medicine, OBGYN, and
Surgery all have multi
ple ultrasound machines. Each department also has a machine that is used twice as often
or more than another machine located in another room. An administrator may want to consider rotating the
machines for more equal use.


Figure
15
: Health Care Provider’s Dashboard



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Part I
I
I
.
Implementation Plan

This part of the proposal describes the
implementation plan

for the solution
:



Project development and deployment

describes the approach, timeline, and milestones.



Operational

governance

identifies the project team,

describes how stakeholders will stay involved,
and
describes plans for handling risk, communication, and change during the project.



User enablement and training

describes how to make people use the system.



Success metrics

expl
ains
how the promised results will be measured and reported
.

Project Development
and

Deployment

The project is
divided

into phases rather than the traditional project
life cycles
. Each phase represents
a
full
iteration through inception, elaboration, cons
truction
,

and transition. Using an agile and iterative approach, we
believe the project will succeed despite our aggressive timeline.

Business stakeholders will be informed of
project progress by a weekly status report. Milestones hit, missed and upcomi
ng will be reported.


The development iterations will be completed within one year of product launch in January 2014. At this time,
our first beta site will launch with the new system. Our beta test will run with one user for 6 months from
January 2014


June 2014.

Project Development Timeline

This
timeline
deals specifically with tasks requiring development and configuration of software systems.

These
tasks will be the responsibility of members of the project team identified in the “Resources” section be
low.

As the project progresses, the Project Manager will keep the stakeholders updated with regular status reports.
There will also be a monthly status meeting where an interactive dialog and questions can be asked.

The project will be done iteratively.

In other words, inception, elaboration, construction and transition will occur
repeatedly within each of the three phases of the project. In each phase, different final deliverables will be
produced, but some activity within each discipline will occur.

Training of support personnel and management will start in November. During this period, training will be with
real
-
world scenarios. Using the model of “tell, show and involve,” we will first teach users how the new
processes will work. Next we will sho
w them how it works. Next, we will run through real
-
world incidences
with the users. The project team business analysts will continue to provide hands
-
on training after beta go
-
live
by being physically relocated and sitting with the support staff for the

first 3 weeks after go
-
live. They will be
available until April for any questions or concerns.



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Figure
16
:

Project Development Timeline



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Project Milestones

Figure
17
:

Project Milestones



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Operational
Governance

This section describes operational governance for the project. The section:



Identifies needed resources
.



Describes how
stakeholders will stay involved.



Describes plans for handling change, communication, and risk

during the project.

R
esources

Th
e primary resource required for this project is staffing

required to complete the project. It includes staff from
GLOCO
, consultants, and

staff from the Beta Partner health care provider.

GLOCO
MedListener


and OmniDash


Project Team

The following table an
d diagram illustrate the GLOCO staff to complete the project, and show the reporting
structure within the project team. GLOCO’s team will be assembled from several sources, including:



Temporary resources
that

will be onboard as needed or for the project’s
duration.



Consultants who will complete specific deliverables.



New hires to fit a new job classification.



Permanent GLOCO personnel who will have added responsibilities as a result of the project.

Role

Status

Responsibility

Stakeholders

Temporary

Serves
on advisory board, works to assure cooperation
between departments and clears away roadblocks.

Project Manager (1)

Temporary

Works with Stakeholders and Product development
team in understanding business needs and transforming
into technical details with
better project timelines.

Project Lead (1)

Temporary

Works on MedListener™ application.

Software Engineer ⠱)

Consultant

Works on MedListener™ application and File transfer
process application in HCP.

Amazon Architect ⠱)

Consultant

Designs architecture

and advises team of best practices
for Amazon cloud computing.

Clinical Software Engineer

⠱)

Permanent

Develops firmware upgrade to allow ultrasound
machines to communicate with
MedListener™
.

Application Business Analyst ⠱)

Permanent

Develops business

and functional requirements.

Dashboard Developer ⠱)

New Hire

Develops dashboards in Tableau for G䱏CO and Health
Care Providers.

Quality Assurance Analyst ⠱)

Permanent

Develops quality of service requirements.

G䱏CO CRM Architect ⠱)

Temporary

Designs architecture and advises team of best practices
for G䱏CO CRM application.

G䱏CO CRM Software Engineer ⠱)

Temporary

Develops software to interface with G䱏CO CRM
application


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Role

Status

Responsibility

GLOCO IT Support (1)

Permanent

Installs and

maintains MedListener™ and OmniDash™

G䱏CO Help Desk Personnel

Permanent

Provides end user support and dispatches tickets to
service technicians.

G䱏CO Service Technician⡳)

Permanent

Services equipment at the customer site.

Document 坲iter

Permanent

Develops documentation on OmniDash™, Premium
package.

Trainer

Permanent

Provides end user training Sales, Customer Support on
applications.


Figure
18
:

GLOCO Project Team





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Beta Partner Health Care Provide
r

Project Team

The following
table

and
diagram

illustrate the staff required at the Beta Partner health care provider to complete
the project

during its beta testing phase
.

Role

Responsibility

Clinical Operations Manager (1)

Views status of trouble equipment on Web sit
e, manages IT support
person workload.

IT Support

Deploys equipment and installs firmware upgrades.

Ultrasound Technician(s)

Uses the ultrasound machine for patient care.



Figure
19
:

Beta Partner Health Care Provider Project Team



GLOCO Stakeholders

The following table and diagram illustrate the stakeholders in the premium service package project at GLOCO
and show
s

how they fit into the overall corporate structure at GLOCO. These illustrations identify four levels of
stakeholder and provide examples of individuals at each level.

As you can see from the table and diagram, when considering the different levels of stak
eholder, while traveling
up the chain of command, the level of involvement in daily project activities decreases while the level of
responsibility and accountability for project success increases. The immediate members of the project team
know much more ab
out project progress than those at higher levels, but those at higher levels have more
responsibility for the outcome. This means that all stakeholders need a means for two
-
way communication


input and feedback


as the project progresses. For example, un
der the GLOCO COO there are four VPs of
Operations, one for each major international region. Under each of these VPs
are

the Directors of Sales and
Service for the region. Each of these Directors will want to know what is happening with the premium service

plan project in the ICT organization
. Eventually

the ultrasound machines for which they are responsible will be
eligible for the premium service plan
. B
eyond this initial offering the concept of the premium service plan may
be extended to other equipmen
t as well.

All of this requires a communication plan and change management plan. The following sections describe them.


Manager

IT Support

Technician


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Key

Level

Type of Project Involvement

Stakeholders


Participant



Designs and delivers solution



Attends project meetings



Participates in

discussions



Generates project documents



Creates software for solution



Acquires hardware for solution



Follows communication plan



Follows risk management plan



Monitors health of project



Reports to supervisory stakeholders



ICT Budget Office Member



MedListener™ and OmniDash™
Project Manager



MedListener™ and OmniDash™
Project Team Members



Change Authorization Board
Member



Director of Sales and Service,
North American Region (this is
the target of the pilot program)



Product Development Team
responsible

for the launch of
MedListener™
-
compatible
ultrasound machines


Advisory



Holds no direct responsibility for project
success but is held accountable for success



Department impacted by the solution



Receives reports from participants



Provides input to the
design process



Provides feedback regarding the solution



TeamOne Consulting



VP, Operations and Technology



VP, Corporate Systems



VP, Information Security



VP, Corporate Budget Office



Director, Marketing



Director of Sales and Service:



APAC Region



LATAM Region



EMEA Region


Supervising



Holds implicit responsibility for project
success and is held accountable for success



Provides, acquires resources to support
project



Receives reports from participants



Provides input to the design process



Provides feedback
regarding the solution



Advises regarding change and risk



Suggests course corrections as needed



ICT Project Management Office
Manager



VP, Enterprise Architecture



VP, Application Delivery



VP of Operations:



APAC Region



LATAM Region



EMEA Region



NA Region


Executive



Holds explicit responsibility for project
success and is held accountable for success



Acts toward supervising and advisory levels
as those levels act toward the participant
level: provides resources, reporting, input,
advice, and so forth.



CIO, M
ichelle Matus



CFO



COO



CEO



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Figure
20
:

GLOCO Project Organization and Stakeholders



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Communicating Using a Project Dashboard

There is one communication tool that everyone involved in the project must be familiar with, so as to quickly
come up to speed with new developments as the project progresses: This is the project dashboard.

Figure
21
:

Project Dash
board



Figure source:

Peter R. Orszag, Memorandum M
-
10
-
26 for Heads of Executive Departments and Agencies,

Executive Office of the President, Office of Management and Budget, June 28, 2010.

“Responsible Party” column added by the authors of this paper


As shown in the figure, the project dashboard is a one
-
page, high
-
level, graphically oriented overview of project.
The project dashboard will be generated weekly by the MedListener™
-
OmniDash™ Project Manager based on
input by other participant stakeholders
. It will be distributed to stakeholders farther up in the chain of
responsibility, including advisory, supervising, and executive stakeholders.

It is a goal of the project to avoid unnecessary meetings, and to channel necessary meetings into a structure
and
schedule that serves the agile methodology of the project. The project dashboard supports this goal by providing
all interested parties with the same weekly “quick look” at what is going on. It is assumed that most upper level
stakeholders merely need
to remain informed and will not react with feedback unless the dashboard indicates a
serious problem in an area of direct concern to them.


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Communicating Agile Progress Against Milestones

The immediate project team, working under the MedListener™
-
OmniDash™
Project Manager, will be using an
agile development methodology that incorporates change as part of the process. The full methodology is outside
the scope of this document. Basically, it involves a cyclical approach to moving forward. A subset of the plan
is
agreed upon and frozen for a short period of time, such as two to three weeks, during which the team fulfills that
part of the plan only. At the end of the cycle, progress toward the project’s original business goal is reevaluated
against the project mi
lestone and timeline. Plans are revised, and a new cycle is begun, in which the team
implements another segment of the plan.

Outside the immediate project team there are many stakeholders who need to be informed of progress toward
project milestones. This

is a particularly important concern for agile methodology, whose immediate focus is on
time intervals rather than the larger
milestones that

interest higher level stakeholders. It is important for the
project team, as part of wrapping up each agile cycle,

to publish a mapping from the recent agile achievement to
the milestone that is its eventual goal. Stakeholders may use this mapping or the project dashboard as a basis for
submitting change requests.

Dependencies and Health Check

The following are the te
chnical dependencies of the MedListener™ and OmniDash™ systems. Testing that these
items are in place will comprise a basic health check for the system:

At Hospital



There is an IT Person with device knowledge.



We are able to upgrade the firmware to set the

cron job.



We can configure the cron job to send files to the local server.



The local server can be configured to communicate with Amazon Servers.

In Amazon



MedListener™ application is able to process the file.



Files are dropping into the S3 bucket
.



We are

able to send information to CRM to generating a service ticket.

At GLOCO



CRM application must be able to accept information to generate a Service Ticket.


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Risk Management

The following table explains risks inherent in the project, their impact and probabi
lity, and the project’s strategy
for mitigating each risk.

Risk

Impact

Probability

Mitigation Strategy

Schedule Overruns

High

High



Formation of an advisory board made up of
department heads and senior leadership to help
clear bottlenecks.



Development team

will meet with advisory
board monthly and will provide weekly status
updates.



Pay for performance: A bonus pool for
completing the work on schedule.

User Adoption /
Rejection

High

High



Formation of a steering committee made up of
GLOCO personnel the
project will impact.



Development team will meet with steering
committee monthly to go over progress and
elicit feedback.

Loss of network
connectivity

Low

Medium



Ultrasound machines cache logs in event of a
network outage and sends again when
connectivity
is restored.



Logs and diagnostic information can be
manually obtained from the physical machine.



Customer has the ability to call GLOCO directly
in event of an unreported problem.

Data is lost due to
routing or equipment
failures.

High

Low



GLOCO conducts
regular “drills” to simulate
equipment failures, stress and load tests.



GLOCO maintains images and backups of all key
components.



GLOCO monitors health of all servers and
equipment



GLOCO maintains a change committee for all
production code and servers.

Fluctuation of pricing
from third party
vendors

High

Medium



GLOCO enters in Service Level Agreements with
guaranteed pricing.



GLOCO audits data and reports being stored to
minimize bandwidth, processing, and data costs.



GLOCO uses non
-
proprietary formats w
henever
possible to allow smoother transitions to other
service providers.


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User Enablement and Training

The GLOCO Premium Ser
vice Plan includes optional new software
OmniDash™

that will enhance
, automate

and
simplify the
users’ tasks
.

The automatic creation of defects when an ultrasound fault occurs and faster resolution
of defect require no additional software and/or change at the HCP. One of the main advantages of the Premium
Service Plan is that some of its major benefits are real
ized without any major changes at the HCP
.

OmniDash™
will further benefit the HCP by automating manual processes related to maintaining, certifying and
replacing ultrasound machines. To facilitate user adoption of the Premium Service Plan and
OmniDash™

Te
amOne Solutions will:



Conduct

user surveys
.



Model

UI on existing paper forms
.



Provide

training.



Include

paper and embedded documentation
.



Allow

for

user
customizations.



Deploy

automation where
ver

possible
.

Transition


Beta Period

To minimize risks and improve the offering TeamOne Solutions is prototyping the Premium Service Plans and
OmniDash™ at a small number of HCPs for a period of
six

months. These HCPs will be selected by GLOCO and
will not be charged extra for the Premium Se
rvice Plan during the beta period. Initially, the existing Standard
Service Plan will continue to be used in conjunction with the Premium Service Plan at the selected HCPs. The
beta period will allow TeamOne Solutions to:



Conduct user surveys
.



Improve do
cumentation/traini ng materials
.



Align functionality to meet HCP
requirements.



Perform real
-
life user and load testing
.



Fix defects prior to sale
.



Train GLOCO
-
internal staff
.


Training

The Marketing, Sales, Training, Service and Customer Support teams are all critical to the successful deployment
of the Premium Service Plan. Though, the documentation and training will be iteratively enhanced throughout
the life cycle of this project som
e target dates for the initial training and documentation are detailed below:



08/13/2013: Complete documentation
.



10/13/2013: Customer Support team training
.



11/13/2013: Service team
“Day in the Life”
training
.

During the Beta phase documentation and
training for the HCP will be developed in conjunction with the selected
beta HCPs. This partnership with the HCP will allow for documentation and training that takes into
consideration the needs of the HCP.


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OmniDash
TM

The

HCPs
now
manually log and maintai
n ultrasound machines to meet accreditation requirements.
OmniDash


is designed to decrease user interaction through automation. HCP staff will not need to directly interact with the
software unless there is an issue with an ultrasound machine(s) or they

need to generate a report showing
ultrasound machine usage and maintenance status. Each HCP will be able to access a customized
dashboard for
all their ultrasound machines by logging into
their customer service portal

using their
existing
username and
lo
gin.

Success M
etrics

The following table shows the metrics this project will use to measure success. It also explains the actions that
will be taken if any goal in this table is not realized.

Metric

Plan for Execution

Increase Revenue

Increase GLOCO’s
Service Revenue by 4%

GLOCO generates $1.9 billion of revenue in services. GLOCO sells 26,000 ultrasound
machines annually worldwide. The sales team will sell premium service plans for at
least. 7,800 of those units (30%) for new and existing clients at a
n average rate of
$9,800 per machine per year. This will generate at least $77 million in revenue and
meet the goal.

Service plan adoption is tracked in Siebel CRM and we will be adding a new SKU for
premium service plans in addition to our basic plans.

Sales people will have access to
reports on their performance compared to the average of their peers and will earn
higher commission on premium service plans over basic plans.

Sales people who fall below their quota will meet with their manager for
analysis and
review. Divisions that fall below their quota will meet with the vice president of sales
for analysis and review.

Ultrasound
Machine
Downtime

Reduce downtime due to repairs by 60%

GLOCO’s Siebel CRM system has historical data on downtime col
lected via the trouble
ticketing system. 坥 expect a 60% reduction in downtime compared to previous
quarters with standard service plans. If this number is not met we will escalate the
client to Quality Assurance to resolve the discrepancies.

Reduction

in
Repair Costs

Reduce time to repair machines by 20% by providing diagnostic reports prior to
site visits.

We expect a total reduction in repair time by at least 20% by providing service
technicians the logs and diagnostic information before arrival at the customer site.

GLOCO’s Siebel CRM system has historical via the trouble ticketing system and reports
on a
verage resolution time will be available to the service team. If this number is not
met we will escalate the client to Quality Assurance to resolve the discrepancies.


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Metric

Plan for Execution

Increase in Help
Desk Productivity

Reduce average call times 20% by automating trouble

ticket population.

We expect a total reduction in average call length to decrease from 15 minutes to 12
minutes based on the automated reporting by the ultrasound machine to GLOCO’s
Siebel CRM System.

Call centers regularly log and report average call
length. If the average call length is
not decreased the Help Desk manager will investigate and report to Quality Assurance
to determine a root cause and formulate a plan for improvement.

Customer
Satisfaction

Increase customer satisfaction by 20% based o
n survey data

GLOCO customer retention team dispatches annual surveys to customers as well as
after repairs. Account managers will track the survey data for improvement and will
work with customers to improve relationships for those unsatisfied with GLOCO

service.




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35


Appendix
A
: Breakdown of Development Costs


Role

Project
Hours

Cost
per

Hour

Total

Responsibility

Project Manager (1)

750

$
80.58

$
60,435

Works with Stakeholders and Product
development team in understanding business
needs and transforming
into technical details
with better project timelines.

Project Lead (1)

750

$
76.92

$
57,690

Works on MedListener™ application.

Software Engineer (1)

200

$110.42

$
22,084

Works on MedListener™ application.

Amazon Architect (1)

200

$
110.42

$
22,084

Designs
architecture and advises team of
best practices for Amazon cloud computing.

Clinical Software

Engineer

(1)

3
00

$
72.46

$
4,362

Develops firmware upgrade to allow
ultrasound machines to communicate with
MedListener™
.

Application Business

Analyst (1)

750

$
55.47

$
41,603

Develops business and functional
requirements.

Dashboard Developer (1)

300

$
69.30

$
20,790

Develops dashboards in Tableau for GLOCO
and Health Care Providers.

Documentation Person

(1)

120

$
43.08

$
5,170

Writes documentation.

Trainer

(1)

120

$
48.76

$
5,851

Trains support and users.

Quality Assurance

Analyst (1)

120

$
52.46

$
6,295

Develops quality of service requirements.

GLOCO CRM Architect (1)

200

$
1
10.49

$
22,098

Designs architecture and advises team of
best practices for GLOCO CRM
application.

GLOCO CRM Software
Engineer (1)

200

$
82.82

$
16,564

Develops software to interface with GLOCO
CRM application.

GLOCO IT Support (1)

120

$
46.88

$
5,626

Installs and maintains MedListener™ and
OmniDash™.

GLOCO Help Desk
Personnel

120

$
34.62

$
4,154

Provides end user support and dispatches
tickets to service technicians.

GLOCO Service
Technician(s)

120

$
39.66

$
4,759

Services equipment at the customer site.

Totals

4
,
3
70



$
316,941




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Appendix B. Solution Benefits

Service Plan Sales

Ultrasound
machines sold worldwide per year

26,000

Target of service plans sold, 30% of all new machines

7,800

Average revenue per service plan

$9,800

Average cost per service plan

$8,700

Projected annual profit

$8,580,000


Reduced Repair Costs

Productivity per
Service Technician

Description

Current Help
Desk Cost

20% Reduction in
Time per Repair

Average salary per technician

$55,000.00

$55,000.00

Average taxes and benefits

$27,500.00

$27,500.00

Work hours per year

2080
.00

2080
.00

Total average support
cost per hour

$39.66

$39.66

Total average support cost per minute

$0.66

$0.66

Average repair time in minutes


240.00


192.00

Total support call cost

$158.65

$126.92

Annual trouble tickets

428

428

Total Annual Support Cost

$67,903.85

$54,323.08

Total Savings


$13,580.77


Productivity across Service Offices Worldwide

Description

Current Help
Desk Cost

20% Reduction in
Time Per Repair

Number of service offices

26

26

Average headcount per call center

2

2

Total Annual Support Cost

$3,531,000.00

$2,824,800.00

Total Savings


$706,200.00


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Increase in

Help Desk
Productivity

Productivity per Help Desk Technician

Description

Current Help
Desk Cost

20% Reduction in
Time per Call

Average salary per technician

$48,000.00

$48,000.00

Average taxes and benefits

$24,000.00

$24,000.00

Work hours per year

2080
.00

2080
.00

Total average support cost per hour

$34.62

$34.62

Total average support cost per
minute

$0.58

$0.58

Average call resolution time in
minutes


15.00


12.00

Total support call cost

$8.65

$6.92

Annual trouble tickets

8000

8000

Total Annual Support Cost

$69,230.77

$55,384.62

Total Savings


$13,846.15


Productivity across Service Desks Worldwide

Description

Current Help
Desk Cost

20% Reduction in
Time per
Call

Number of call centers

6

6

Average headcount per call center

32.5
0

32.5
0

Total Annual Support Cost

$13,500,000.00

$10,800,000.00

Total Savings


$2,700,000.00



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Appendix
C
. Database Design and Management

Device, Device Log, and Device Log Detail
Tables


Relationship

Relation Table

Comments

tbl_Device







Device_ID

pk

bigint

Internal ID

Client_ID



varchar(50)

Same ID from Seibel CRM

Device_OEM



varchar(50)

OEM
(
O
rigi
nal
E
quipment
M
anufacturer)

Device_Name



varchar(50)

Device Name
(
e.g.

UltraSound)

Device_Installation_Date



Datetime

Date of Installation

Modified_By



varchar(50)

Modified/Added by User

Modified_On



Datetime

Modified/Added on Date










Relationship

Relation Table

Comments

tbl_DeviceLog







DeviceLog_ID

pk



Internal ID

Device_ID

fk

tbl_Device

Reference Device ID of tbl_Device

Device_Log_StartDateTime



Datetime

Log Start DateTime

Device_Log_EndDateTime



Datetime

Log End DateTime

Device_Location_IP



varchar(25)

Transmitting IP Address

Device_Lat



varchar(50)

Geo Location Latitude

Device_Long



varchar(50)

Geo Location Longitude

Modified_By



varchar(50)

Modified/Added by User

Modified_On



Datetime

Modified/Added on Date










Relationship

Relation Table

Comments

tbl_DeviceLogDetails







DeviceLogDetails_ID

pk



Internal ID

DeviceLog_ID

fk

tbl_DeviceLog

Reference Device ID of tbl_Device

Device_DataElementName


varchar(50)

Data Element Name
(e
.
g. CoolingFan)

Device_DataElementValue


varchar(50)

Data Element Value
(e
.
g. Working/
Failed
)

Device_Error_Code_Flag



char(1)

For Quick
Notification


Device_Error_Code



varchar(50)

varchar(50)

Device_Warning_Code_Flag



char(1)

For Quick
Notification


Device_Warning_Code



varchar(50)

For Refe
re
nce Warning Code

SiebelCRM_Ticket



varchar
(50)

Siebel CRM Service Ticket

(Response from CRM System)

Modified_By



varchar(50)

Modified/Added by User

Modified_On



Datetime

Modified/Added on Date


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Device, Device Log, and Device Log Detail Record Diagrams










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One
-
to
-
Many Relationships

Figure
22
:
One
-
to
-
Many Relationships



SQL for Creating Tables

USE [OmniDash]

GO

/****** Object: Table [dbo].[tbl_Device] Script Date: 11/12/2012 23:29:46 ******/

SET ANSI_NULLS ON

GO

SET QUOTED_IDENTIFIER ON

GO

SET ANSI_PADDI
NG ON

GO

CREATE TABLE [dbo].[tbl_Device](


[Device_ID] [bigint] IDENTITY(1,1) NOT NULL,


[Client_ID] [varchar](50) NULL,


[Device_OEM] [varchar](50) NULL,


[Device_Name] [varchar](50) NULL,


[Device_Installation_Date] [datetime] NULL,


[Modified_By] [
varchar](50) NULL,


[Modified_On] [datetime] NULL CONSTRAINT [DF_tbl_Device_Modified_On] DEFAULT (getdate()),


CONSTRAINT [PK__tbl_Device__7C8480AE] PRIMARY KEY CLUSTERED

(


[Device_ID] ASC


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)WITH (PAD_INDEX = OFF, IGNORE_DUP_KEY = OFF) ON [PRIMARY]

) ON

[PRIMARY]


GO

SET ANSI_PADDING OFF

GO

/****** Object: Table [dbo].[tbl_DeviceLog] Script Date: 11/12/2012 23:29:46 ******/

SET ANSI_NULLS ON

GO

SET QUOTED_IDENTIFIER ON

GO

SET ANSI_PADDING ON

GO

CREATE TABLE [dbo].[tbl_DeviceLog](


[DeviceLog_ID] [big
int] IDENTITY(1,1) NOT NULL,


[Device_ID] [bigint] NOT NULL,


[Device_Log_StartDateTime] [datetime] NULL,


[Device_Log_EndDateTime] [datetime] NULL,


[Device_Location_IP] [varchar](25) NULL,


[Device_Lat] [varchar](50) NULL,


[Device_Long] [varchar](50) NU
LL,


[Modified_By] [varchar](50) NULL,


[Modified_On]
[datetime] NULL CONSTRAINT [DF_tbl_DeviceLog_Modified_On] DEFAULT (getdate()),

PRIMARY KEY CLUSTERED

(


[DeviceLog_ID] ASC

)WITH (PAD_INDEX = OFF, IGNORE_DUP_KEY = OFF) ON [PRIMARY]

) ON [PRIMARY]


GO

SET ANSI_PADDING OFF

GO

/****** Object: Table [dbo].[tbl_DeviceLogDetails] Script Date: 11/12/2012 23:29:46 ******/

SET ANSI_NULLS ON

GO

SET QUOTED_IDENTIFIER ON

GO

SET ANSI_PADDING ON

GO

CREATE TABLE [dbo].[tbl_DeviceLogDetails](


[DeviceLogDetails
_ID] [bigint] IDENTITY(1,1) NOT NULL,


[DeviceLog_ID] [bigint] NOT NULL,


[Device_DataElementName] [varchar](50) NULL,


[Device_DataElementValue] [varchar](50) NULL,


[Device_Error_Code_Flag] [char](1) NULL,


[Device_Error_Code] [varchar](50) NULL,


[Devic
e_Warning_Code_Flag] [char](1) NULL,


[Device_Warning_Code] [varchar](50) NULL,


[SiebelCRM_Ticket] [varchar](50) NULL,


[Modified_By] [varchar](50) NULL,


[Modified_On]
[datetime] NULL CONSTRAINT [DF_tbl_DeviceLogDetails_Modified_On] DEFAULT (getdate()),


CONSTRAINT [PK_tbl_DeviceLogDetails] PRIMARY KEY CLUSTERED

(


[DeviceLogDetails_ID] ASC

)WITH (PAD_INDEX = OFF, IGNORE_DUP_KEY = OFF) ON [PRIMARY]

) ON [PRIMARY]


GO

SET ANSI_PADDING OFF

GO

ALTER TABLE [dbo].[tbl_DeviceLog] WITH CHECK ADD CONSTRAINT
[FK__tbl_Devic__Devic__7F60ED59]
FOREIGN KEY([Device_ID])

REFERENCES [dbo].[tbl_Device] ([Device_ID])

ON DELETE CASCADE

GO

ALTER TABLE [dbo].[tbl_DeviceLog] CHECK CONSTRAINT [FK__tbl_Devic__Devic__7F60ED59]

GO

ALTER TABLE [dbo].[tbl_DeviceLogDetails] WITH

CHECK ADD CONSTRAINT
[FK__tbl_DevLogDet__DevicLog__999] FOREIGN KEY([DeviceLog_ID])

REFERENCES [dbo].[tbl_DeviceLog] ([DeviceLog_ID])

ON DELETE CASCADE

GO

ALTER TABLE [dbo].[tbl_DeviceLogDetails] CHECK CONSTRAINT [FK__tbl_DevLogDet__DevicLog__999]



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Data

Flow Examples

1.

Create Job

Name:

get_device_log

Steps in Create code residing on Mini Linux OS in Devices



Creating a file by capturing information on devices.



Output file name : <DeviceName> _ MMDDYYYYHHMM.txt



Time in filename is on 24hrs.

2.

Cron Job

Steps in Create code residing on Mini Linux OS in Devices:



Creating a file by capturing information on devices.



Schedule a Background Cron Job for Every 60 Minutes



Syntax of Job



*/60 * * * * /home/suresh/get_device_log



Dropping file into File Ser
ver.

3.

Copy file to File Server in Hospital.

Cron Job pushes file to File Server internally in Hospital.

4.

Upload files to Amazon S3 from App Server on Hospital Network.

Working Java code
(next topic)

5.

From S3 to Database through App Server in Cloud

Steps in Ja
va code residing on App Server in Cloud:



Checking file in S3 bucket



If No file exists the process keeps checking the folder.



If exists the file content is parsed to upload to Database.



Data is parsed into 2 tables (tbl_Device, tbl_DeviceLogs).

Java

Code

import

java
.
io
.
File
;

import

java
.
io
.
IOException
;

import

java
.
util
.
UUID
;


import

com
.
amazonaws
.
AmazonClientException
;

import

com
.
amazonaws
.
AmazonServiceException
;

import

com
.
amazonaws
.
auth
.
PropertiesCredentials
;

import

com
.
amazonaws
.
services
.
s3
.
AmazonS3
;

import

com
.
amazonaws
.
services
.
s3
.
AmazonS3Client
;

import

com
.
amazonaws
.
services
.
s3
.
model
.
PutObjectRequest
;


public

class

S3Sample

{



public

static

void

main
(
String
[]

args
)

throws

IOException

{


/*


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* Important: Be sure to fill in your AWS access credentials in the


* AwsCredentials.properties file before you try to run this sample.


* http://aws.amazon.com/security
-
credentials


*/


AmazonS3

s3

=

new

AmazonS3Client
(


new

PropertiesCredentials
(
S3Sample
.
class


.
getResourceAsStream
(
"AwsCredentials.properties"
)));


/*


* Setting a Standard Bucket Configuration file,



* Here we are setting a standard Bucket Name.


*/


String

bucketName

=

"gloco_client_data_files";


try

{


System
.
out
.
println
(
"==========================================="
);


System
.
out
.
println
(
"Locating Files
in Hospital File Server"
);


System
.
out


.
println
(
"C:
\
\
Hospital_Files_to_Gloco"
);

System
.
out
.
println
(
"==========================================="
);


// Getting directory


File

directory

=

new

File
(
"C:
\
\
Hospital_Files_to_Gloco "
);

System
.
out
.
println
(
"
\
n==========================================="
);


System
.
out
.
println
(
"Directory Name : "


+

directory
.
getName
().
toString
());

System
.
out
.
println
(
"=================================
==========
\
n"
);



String

key

=

directory
.
getName
().
toString
();


// Getting files list


File
[]

files

=

directory
.
listFiles
();


// Iterating through the files.


for

(
int

index

=

0
;

index

<

files
.
length
;

index
++)

{


// Print out the name of files in the directory


System
.
out
.
println
(
files
[
index
].
toString
());


}


System
.
out
.
println
(
"
\
n==========================================="
);


System
.
out
.
println
(
"Getting Started with Amazon S3"
);


System
.
out
.
println
(
"===========================================
\
n"
);



// Uploading files into S3 bucket


for

(
int

index

=

0
;

index

<

files
.
length
;

index
++)

{


File

file

=

new

File
(
files
[
index
].
getName
().
toString
());


// Print out the name of files in the directory


String

photoKey

=

key

+

"/"

+

file
.
getName
();


System
.
out
.
println
(
"Uploading a file "

+

file
.
getName
()



+

" to S3."
);


s3
.
putObject
(
new

PutObjectRequest
(
bucketName
,

photoKey
,


new

File
(
files
[
index
].
toString
())));


}



System
.
out
.
println
(
"==========================================="
);


System
.
out
.
println
(
"Files copied to folder
-

"

+

key
);


System
.
out
.
println
();



}

catch

(
AmazonServiceException

ase
)

{


System
.
out


.
println
(
"
Caught an AmazonServiceException, which means your request made it"


+

"
to Amazon S3, but was rejected with an error response for some reason.
"
);


System
.
out
.
println
(
"Error Message: "

+

ase
.
getMessage
());


Sys
tem
.
out
.
println
(
"HTTP Status Code: "

+

ase
.
getStatusCode
());


System
.
out
.
println
(
"AWS Error Code: "

+

ase
.
getErrorCode
());


System
.
out
.
println
(
"Error Type: "

+

ase
.
getErrorType
());


System
.
out
.
println
(
"Request ID:

"

+

ase
.
getRequestId
());


}

catch

(
AmazonClientException

ace
)

{


System
.
out


.
println
(
"
Caught an AmazonClientException, which means the client encountered
"


+

"
a serious internal problem

while trying to communicate with S3,
"


+

"
such as not being able to access the network.
"
);


System
.
out
.
println
(
"Error Message: "

+

ace
.
getMessage
());


}


}

}


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Sample Output

==================================
=========

Locating Files in Folder
-

Hospital_Files_to_Gloco

===========================================


===========================================

Directory Name :
Hospital_Files_to_Gloco

===========================================


C:
\
Hospital_Files_to
_Gloco
\
U600
-
4556
-
8989_103020121420.txt


===========================================

Getting Started with Amazon S3

===========================================


Uploading a file U600
-
4556
-
8989_103020121420.txt to S3 Bucket.