1
Running head: BUSINESS ANALYTICS IMPLEMENTATION
PLAN
Business Analytics Implementation Plan
2
Business Analytics Implementation Plan
Table of Contents
· Cover page
1
· Table of contents

2
· Introduction
3
· The business and summery of business analytics
3
· Benefits and disadvantages of business analytics
4
· Organization proactive in addressing any disadvantages
5
· Challenges that the organization may face using business
analytics 5
· Business analytic techniques
6
· Implementation plan
8
· Back up proposal

12
· Conclusion
13
· References
15
BUSINESS ANALYTICS
Introduction
Business analytics involves studying of data by means of
operations and statistical analysis, formation of models which
are predictive, optimization techniques application, and
communicating the outcome to clients, associate executives and
business associates. Companies which are committed in
decision making which is data driven can use business analytics
(Alvin, 2008). The company can use business analytics in order
for it to gain a clear insight which inform decisions in business.
The business analytics can also be applied in business
processes’ automating and optimization. Business analytics can
be viewed as an intersection between business and technology
(Jeanne, 2005).
The business and summery of business analytics that could be
applied to the business in multiple scenarios
The firm deals with a wide range of graphics design, which
involves creation of items to be used in visual communication
and also use of image, type, and space, for problem solving. The
business has a lot of clients, and uses technology for daily
operations but do not perform data analysis which helps in
business decision making. Business analytics will be of great
help because it can help the firm to integrate their data and
consequently make informed business decisions. The databases
which are all independent of each other can be linked as well as
the other systems which are not connected.

Since the firm is dealing with graphics design and has a wide
variety of clients for different designs, it can apply business
analytics in order for it to be able to focus on methods of
quantitative and the task of data which is evidence based, in the
firm’s business decision making and modeling. This can be
used by the executives or professionals in the firm in order to
improve and take the company to a higher level in decision
making through methods of quantitative, realizing and exploring
relationship in economy of the firm by means of data analysis.
The firm can apply decisive analytics, which give support to
human decisions with analytics which are visual, user models
for reflecting reasoning.
The firm can also apply descriptive analytics in order to get
insight from past data with scorecards, reporting, clustering and
others. Also, predictive analytics can be applied. This involves
predictive modeling which uses statistical and techniques in
machine learning. Prescriptive analytics can also be applied by
the firm through recommendation of decisions by use of
simulation, optimization and others. Through the use of these
business analytics, the firm, for example will be able to clearly
determine and make well informed decision on whether adding
another location in another part of the state would be of benefit.
Benefits and disadvantages of business analytics
Applying business analytics in an organization has benefits, as
well as disadvantages that the organization can face. The
benefits of business analytics include:
1. The process of decision making in the organization is
improved. The organization can as a result be able to make
decisions which are quality and relevant.
2. Apart from improving the process of decision making,
business analytics also enables the process of decision making

to be faster. This is a great benefit to the organization since it
avoids delay in making important decisions in the organization
that could slow down some operations or activities that depend
on the outcome of the decision.
3. The organization can be able to respond to the needs of the
user for data availability on time. This facilitates efficiency
especially on service delivery which enables the organization to
be very efficient.
The disadvantages of business analytics include;
1. Business analytics can be time consuming. This is because; a
lot of time can be taken in the collection of data. Also, data
interpretation can take a substantial amount of time.
2. Tools for data analysis might be expensive, and this can be a
limitation to the organization, but it depends on the
organizations’ financial capabilities.
3. Price fixing for the reason that reliable and accurate
information quality may be a disadvantage to consumers.
How the organization can be proactive in addressing any
disadvantages
The organization can apply different methodology in dealing
with issues so that, when there is a disadvantage, there already
is another option or solution which is established. For example,
the organization should come up with a clear guideline on what
to do when faced with disadvantage by discussing the issues.
Challenges that the organization may face using business
analytics
In the course of using the business analytics, the organization

may face some challenges. They include;
1. Challenge in the strategic alignment; although many of the
organizations have placed some form of business analytics,
there may lack alignment, trust, and availability by the top
executives. The company may be proactive in addressing the
challenge by reviewing the goals of the business which supports
the major company strategies, and each main process of
business which underpins the objective, and try to analyze.
2. There may be difficulty in communicating the results to
business users, since analysts usually work independently. The
organization can try and liberate on its analytical capabilities by
focusing on analytics as a skill.
3. Analytics software can be costly although not difficult to
implement. The users may lose interest by not seeing the results
immediately and may lead to executives losing trust ii the
offered solution, and refusal to rely on the results of the
models. The organization should take responsibility in
establishing analytic environment which is productive.
Business analytic techniques
The three business analytic techniques that I propose to the firm
are;
One, data mining; this creates models byrevealing trends which
are unknown and the patterns in large data amounts. For
instance, insurance claims fraud detection, analysis of retail
market basket. Data mining can be achieved through a number
of statistical techniques which include; sequencing and
association models, regression, clustering, and classification.
One advantage of data mining is that it helps companies
involved in marketing to create models that are based on past
data in order to predict response to new market promotions. The

second advantage is that it provides financial institutions with
information about credit and loan reporting. The disadvantages
of data mining are one; private issues where businesses collect
information about customers making them afraid of how the
information will be used. Two, security issues arise because of
owning of information by businesses concerning their customers
and employees which include payroll, birthday, social security
and others. Two, text mining analytic technique involves
discovering and extracting patterns which are meaningful and
also relationships from collections of text. For example;
understanding of customers’ sentiments on social media sites
may be used to make improvement to customer service or
product or it can also be used to comprehend how competitors
are performing. Text mining has some advantages which include
one, assisting greatly in summarizing documents and two, it
helps significantly in extraction of ideas from text. This
technique also has some disadvantages which include; one,
collection of data needs managing of vast amount of text which
is free. Two, mostly the data is not properly organized, and also
not explained in any form. Three, optimization technique; which
involves application of simulation techniques in order to
identify situations that will give out the best results. For
instance optimization of sale price, discovering optimal
inventory so as to achieve highest fulfillment and avoiding
stock outs. This technique has some advantages which include
one; profitable growth that is intelligent which gives
organizations increased opportunities in developing customers,
new market identification, relationship improvement, and
developing new services and products. Two; it enables risk
management that is proactive hence making the organization
less vulnerable and have high certainty in results because of the
improved ability in predicting and identifying risk events plus
the ability to get ready in response to the risks. The
disadvantages of this technique include; one; it is difficult to
apply this technique in complex problems and two; it may also
be time consuming to apply this techniques in complex

situations.
IMPLEMENTATION PLAN
The implementation plan contains activities listing that is
detailed, difficulties expected, schedules, and costs that are
needed in order to achieve objectives of plans that are strategic.
This implementation plan aims to integrate business analytics
into the organization. Since analytics gives a lot of expected
benefits which includes increment of sales, and a deep focus on
the preferences of the customer, it must be properly integrated
into the organization. This process can be challenging and a
proper layout of how it will be carried must be established. The
business implementation will focus on where to start,
identification of prioritization of projects, the structure of the
organization in order to achieve success, the main innovations
in technology that should be included. This will involve a
creation of plan that will enable the organization to spend
required time in creating a roadmap and strategy that is simple
on how data, algorithms, mathematics, people and tools
integrate in order to achieve business value. I propose this plan
to the management of the organization in order to integrate
business analytics in the business to enhance performance.
The plan for integration is in six steps which indicate how every
activity will carried out and what needs to be done. As the
analytic process strategy moves on, some of the steps will be
revisited a number of times. The steps are important as they
outline main aspects to be considered in taking the organization
to decision making which is data driven. The steps are;
1. Comprehend the strategy of business in the organization and
focal areas that are strategic. The analytic strategy must be
entrenched in the organization’s business strategy. Most of the
times the analytics initiatives fail in supporting the companies
top strategic crucial areas. This leads to the analytics not being

given priority. Due to this reason, the process should be started
by spending substantial amount of time with head strategy
officer, or if possible the chief executive officer including the
management team. This is important because it will make it
possible to comprehend one; the goals or objectives that the
organization wants to realize in coming years for example one
to three years. Two, will be able to understand the central
processes of value chain that the plan is targeting to change.
Three, it will be easier to comprehend what main program
changes will take place.
The business strategy must be broken to pieces which are
manageable, which will enable focusing on strategy of analytics
on areas that are most important for the success of the business.
2. Analytics vision development and setting target for levels of
analytics maturity for the main processes. This will
involvechanging of a single or multiple main processes of the
organization. Maturity models will be used to emphasize how
analytics add value to the processes. This will enable the
organization to get it processes and methods assessed depending
on the best practice of the management, against external
benchmarks that are clearly set. Maturity model will focus on
the company’s main processes at reasonably high level. This
will happen through two discussions that will be separate. The
first one will be to establish the current maturity level of the
organization by analyzing the extent that the organization is
utilizing analytics in the current process and if the analytics are
being used in a manner which is consistent. The second
discussion will be to establish the maturity level target of the
organization, the ambition for analytics and data utilization in
the process. The discussion will also establish if the
organization should aim analytics which are real time and
automated, where analytical models which are advanced are
embedded into processes of customer facing and business
decisions, or should the organization aim at maturity which is
lower where it is the task of each person involved in decision

making to utilize analytical models which are own grown.
The first discussions will assist in driving a consensus and
understanding which is common between the organizations’
managers and me, as the business analyst. The second
discussion will include the same individuals and will take into
consideration issues such as best practices in market, guidelines
to strategy, current level of maturity and also establish what the
organization’s peers in the industry, and also the competitors
are engaging in.
3. The third step involves developing of business ideas for the
analytics. This involves creativity in the process of strategy.
This involves forming set of initiatives which are concrete. This
will help in reaching the strategic ambition that is levels of
analytic maturity target. The initiative that are developed or
possibly the project charters must establish the following; one,
the business challenge that is being addressed by the initiative.
Two, the main elements of the solution that is proposed and
three, associated risks and business case. The development of
the organization’s business case will put special consideration
in the following; one, the data required. The organization’s data
will be integrated and assembled. Valuable data may be stored
in system of IT that is majorly used in different areas for
example pricing, customer service, and chains of supply. If
matters are complicated, valuable information is usually stored
in companies that are outside, in forms which are unstructured
for example conversations in social networks. Two, the
analytical models that are required must be identified. This is
because; integration of data alone will not produce value.
Analytic models which are advanced are required in order to
facilitate optimization which is data driven for the organization,
for instance; schedules of employees, or predictions. This plan
will identify where additional value in business will be created
by the models, and establish who is required to put them to use.
Three, the plan establishes how the work process will be

integrated with the analytics. The modeling output may be very
valuable, but this can only be so if the managers of the
organization and mostly the employees who are on the front line
can access, comprehend, and be able to use it. Output which is
very complex can be devastating and can even be mistrusted.
Mostly, what is required are instinctive tools that are used for
integration of data in daily processes and which are used in
translating outputs of models to actions. The organization has a
huge number of probable initiatives. If they will all be
implemented, the organization’s process will go directly to the
maturity level target. The organization may not have resources
to allow implementing all this initiatives at once. Due to this,
there must be prioritization of project and development of the
roadmap.
4. The forth step is developing the roadmap and prioritizing
project. Critical decisions must be highlighted, and the
organization should create and define the initiatives the must be
prioritized. The initiatives that best support the goals of the
organization are selected from the many which will be
identified in step three above. In order to successfully grapple
with the planning of tradeoffs, it needs a strategic dialogue
which is cross cutting, at the higher level of the organization, in
order to be able to establish priorities in investment. This will
make it possible to balance cost, acceptance, speed and also
creating circumstances for engagement in front line. The result
of this step is to establish a roadmap that highlights the
initiatives to be undertaken, in what order and the individuals
who are responsible for making them happen.
5. The fifth step is creating a blueprint of the target architecture
that results. Technology by itself is near irrelevant to business
user but the ability to quickly and instinctively analyzed vast
data amount is what the users care about the most. However,
creating analytical architecture that is robust is the main thing
for business outcomes realization that has been put forth in the

roadmap. The required data changes must be assessed for the
initiatives, tools and applications, and architecture which is
technical. A transition plan that corresponds must be laid down.
To solve issues in IT relating to storage and other data issues
may take long, hence identifying and connecting the most
valuable data quickly for analytics use and performing
operation in clean up in order to merge and synchronize data
which is overlapping and working around information which is
missing is not a good way of getting started.
6. This is the final step which involves deciding on organization
and development capability. The organization should have
people with capabilities in on order to be able to implement this
plan do avoid failure or disappointment. The people charged
with this task must have implementation skills. I propose to the
organization to assist in the planning of organizing and
assembling pool of talent in order to implement architecture
target and execute roadmap. The organization can raise data
scientists, frontline staff, analytic modelers, who will be good
in the forth coming days of decision making which is data
driven. The organization can do so through training. After
planning, data integration, starting pilot programs, creation of
new tools and efforts in training happens in a context which is
clear for enhancing business values in the organization.
BACKUP PROPOSAL
1. People who work and live with the system which is new
should perform the implementation. This is because; they
contain a vested interest which is strong to make sure that
implementation goes right.
2. Will conduct the organization’s survey for every site, meet
the top executives, try to get their support and fully comprehend
working practices that are local. This will assist in making sure
that the process which is new is fitting seamlessly with
processes that that exist and to make sure bad surprises are

early discovered.
3. Event for implementation must be presented by chairperson
to display support from top of organization’s management.
4. Training which is comprehensive in different sessions for all
users.
5. Reflect on special procedures in order to track progress in
implementation.
In conclusion, decision making in an organization may be
efficient and informed through use of business analytics. The
business analytics have different techniques which can be
applied in business in different situations, and each has its own
advantages and disadvantages. The business should establish
which business analytics to apply in their daily business
operations, and come up with a clear implementation plan on
how to integrate the business analytics to the organization.
References
Alvin, L. (2008). Data to Knowledge to Results: Building an
Analytic Capability. California Management Review.
Thomas, H. (2006). Competing on Analytics. Harvard Business
Review.
Jeanne, G. (2005). Automated Decision Making Comes of Age.
MIT Sloan Management Review.
LASA 2—Business Analytics Implementation Plan Part 2
Assignment Components

Unsatisfactory
Emerging
Proficient
Exemplary
Revise the proposal based upon feedback from instructor.
Few, if any corrections/updates are addressed into the existing
proposal.
Most corrections/updates are addressed into the existing
proposal.
All corrections/updates are addressed into the existing proposal.
All corrections/updates are addressed into the existing proposal,
and expanded upon.
Explain the importance of MIS in relation to data-driven
decisions.
Explanation and definition of MIS are inaccurate or incomplete.
There is no attempt to identify the relationship between MIS to
data-driven decision making.
Explanation and definition of MIS are accurate, but may be
vague. The relationship between MIS to data-driven decision
making is attempted, but may be vague.
Explanation and definition of MIS are accurate. A clear, concise
relationship of the importance of MIS to data-driven decision
making is provided.
Explanation and definition of MIS are accurate. A clear, concise

relationship of the importance of MIS to data-driven decision
making is provided. Supporting diagrams and examples are
provided for relationship.
Describe the techniques and tools that can be utilized to manage
the data.
Discussion of at least 1 appropriate technique and 1 appropriate
tool is attempted in relation to how they could assist in
managing the data for the organization.
At least 1 appropriate technique and 2 appropriate tools are
discussed in relation to how they could assist in managing the
data for the organization.
At least 2 effective techniques and 3 effective tools are
discussed in relation to how they could assist in managing the
data for the organization.
At least 2 effective techniques and 3 effective tools are
discussed in relation to how they could assist in managing the
data for the organization. Justification for choosing the specific
techniques and tools is given.
Explain how the techniques and tools can be utilized to present
the data to management.
Explanation does not demonstrate how the techniques or tools
could be utilized to present the data to management.
Explanation demonstrates how the techniques or tools could be
utilized to present the data to management.
Explanation clearly demonstrates at least 3 examples of how the
techniques and tools could be utilized to present the data to
management.
Explanation clearly demonstrates at least 3 examples of how the
techniques and tools could be utilized to present the data to
management. The examples are innovative and follow current
best practices for managing data.
Explain how data can add value to the organization at all levels.

Explanation does not specifically state how data can add value
to the organization.
Explanation demonstrates how data can add value to the overall
organization.
Explanation demonstrates how data can add value to the
organization not only for day-to-day operations, but also how it
can assist the organization with their strategic planning.
Explanation demonstrates how data can add value to the
organization not only for day-to-day operations, but also how it
can assist the organization with their strategic planning.
Examples are provided to further demonstrate how value was
added to an existing organization.
Writing Components
Organization: Introduction, Thesis, Transitions, Conclusion
Introduction is limited or missing entirely. The paper lacks a
thesis statement. Transitions are infrequent, illogical, or
missing entirely. Conclusion is limited or missing entirely.
Introduction is present but incomplete or underdeveloped. The
paper is loosely organized around a thesis that may have to be
inferred. Transitions are sporadic. Conclusion is present, but
incomplete or underdeveloped.
Introduction has a clear opening, provides background
information, and states the topic. The paper is organized around
an arguable, clearly stated thesis statement. Transitions are
appropriate and help the flow of ideas. Conclusion summarizes

main argument and has a clear ending.
Introduction catches the reader’s attention, provides compelling
and appropriate background information, and clearly states the
topic. The paper is well organized around an arguable, focused
thesis. Thoughtful transitions clearly show how ideas relate.
Conclusion leaves the reader with a sense of closure and
provides concluding insights.
Usage and Mechanics: Grammar, Spelling, Sentence structure
Writing contains numerous errors in spelling, grammar, and/or
sentence structure that severely interferes with readability and
comprehension.
Errors in spelling and grammar exist that somewhat interfere
with readability and/or comprehension.
Writing follows conventions of spelling and grammar
throughout. Errors are infrequent and do not interfere with
readability or comprehension.
The paper is basically error free in terms of mechanics.
Grammar and mechanics help establish a clear idea and aid the
reader in following the writer’s logic.
APA Elements: Attribution: Paraphrasing: Quotations
No attempt at APA format. Insufficient sources cited.
APA format is attempted to paraphrase, quote, and cite, but
errors are significant. Minimum sources cited.
Using APA format, accurately paraphrased, quoted, and cited in
many spots throughout when appropriate or called for. Errors
present are minor. Sufficient sources cited.
Using APA format, accurately paraphrased, quoted, and cited
throughout the presentation when appropriate or called for.
Only a few minor errors present. Sources cited are more than
sufficient.

Page 1 of 2
Data Driven Decision-Making
©2014 Argosy University
Page 3 of 3
Data Driven Decision-Making
©2014 Argosy University
Business Analytics Implementation Plan Part 2
You began writing your business analytics implementation plan
in Module 3_Business Analytics Implementation Plan Part 1
(Assignment Attached). In addition, you already have gained
information about the various technological solutions discussed
in the previous modules. In this assignment, you will now
address ways to implement the plan along with any associated
costs, as this will complete the proposal for management to
make their decision.
Description of LASA
In this assignment, you will amend your existing business
analytics implementation plan developed in Module 3. You will
amend the existing proposal to discuss the importance of
managing information systems, describe the techniques and
tools used to manage the data, and explain how utilizing
technology can help the organization.
Scenario
You have been hired as a business analyst for a well-known
design firm. Currently, they utilize technology for their day-to-
day operations but not to analyze data that could help with
making business decisions. Your task is to convince
management that the usage of business analytics would be a
great benefit to the business and it would help the business to
make well-informed decisions and thus action plans that would
align with the business’s strategic planning.
The firm currently has technology in place but does not have

any connected systems. The databases are all independent of
each other but they do utilize a client/server environment. The
firm currently has one location but is looking to add a second
location in another part of the state but is unsure about whether
it would be beneficial to the firm.
**The firm liked your implementation plan but have questions
about how they will manage the data and how data driven
decision making can help the organization versus just being an
additional expense for the organization (cost of new equipment
or resources).
Instructions
Using the online library resources and the Internet, research
business analytics implementation plans, especially methods of
developing a rationale in support of implementation. Select at
least 6 scholarly sources for use in this assignment.
Amend your existing proposal addressing the importance of
Management Information Systems and managing the data for the
organization.
Objectives of proposals:
1. Revise the previous proposal based upon the comments from
your instructor.
2. Explain the importance of MIS in relation to data-driven
decisions.
3. Describe the techniques and tools that can be utilized to
manage the data. Include at least 2 effective techniques and 3
effective tools.
4. Explain how the techniques and tools can be utilized to
present data to management and other organizational decision
makers. Be sure to include at least 3 innovative examples that
follow current best practices for managing data.
5. Explain to management how the data can add value to the
business in day-to-day operations as well as long-term strategic
planning. Use examples to further demonstrate how value is
added to an existing organization.
Write the paper from the perspective that it will be presented to
the firm’s management team as you are trying to persuade them

to utilize business analytics for data-driven decision making.
The paper should contain:
· Cover Page (update date)
· Table of Contents (auto-generated by Microsoft Word and
updated)
· Introduction
· Implementation Plan (5–6 pages of content revised as per
instructor feedback)
· Management Information Systems Section: (5–6 pages of new
content)
· Importance of MIS
· Techniques and Tools Utilized Along with examples
· Added Value to Organization
· Conclusion
· References
Utilize at least 6 scholarly sources in support of your
recommendations.
Make sure you write in a clear, concise, and organized manner;
demonstrate ethical scholarship in appropriate and accurate
representation and attribution of sources; display accurate
spelling, grammar, and punctuation.
Submit a 10-page report in Word format. Apply APA standards
to citation of sources. Use the following file naming
convention: LastnameFirstInitial_M5_A1.doc.
Grading Criteria and Rubric
Assignment Components
Proficient
Max Points
Revise the proposal based upon feedback from instructor.
All corrections or updates are addressed in the existing
proposal.
24
Explain the importance of MIS in relation to data-driven
decisions.
Explanation and definition of Management Information
Systems are accurate. A clear, concise relationship of the

importance of MIS to data-driven decision making is provided.
76
Describe the techniques and tools that can be utilized to manage
the data.
At least 2 effective techniques and 3 effective tools are
discussed in relation to how they could assist in managing the
data for the organization.
52
Explain how the techniques and tools can be utilized to present
the data to management.
Explanation clearly demonstrates at least 3 examples of how the
techniques and tools could be utilized to present the data to
management.
36
Explain how data can add value to the organization at all levels.
Explanation demonstrates how data can add value to the
organization not only for day-to-day operations, but also how it
can assist the organization with their long-term strategic
planning.
48
Presentation Components
Organization (16)
Usage and Mechanics (16)
APA Elements (24)
Style (8)
Wrote in a clear, concise, and organized manner; demonstrated
ethical scholarship in appropriate and accurate representation
and attribution of sources; and displayed accurate spelling,
grammar, and punctuation. APA format was used. Use of
scholarly sources aligns with specified assignment
requirements.
64
Total

300