CHAPTER 2_ Analysis Techniques and Process.pdf

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1. ANALYSISANALYSIS
TECHNIQUES &TECHNIQUES &
PROCESSPROCESS
CHAPTER 2
reported by: Del Mundo, Inocencio & Reyes
SUBJECT: STRATEGIC BUSINESS ANALYSIS (SBA)

2. Recognize different techniques in strategic
business analysis.
1.
Use analysis in constructing strategy and
decision making.
2.
Use performance measurement as tool for
analyzing productivity.
3.
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3. 1
WAYS OF ASSESSING STRATEGICWAYS OF ASSESSING STRATEGIC
ANALYSIS TECHNIQUES AND PROCESSANALYSIS TECHNIQUES AND PROCESS
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Internal Factors
it begins within the company or business itself.
EXAMPLES:
Current Resource
Policies
Process
Performance
Capabilities

4. 2
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External Factors
encompasses everything that is outside of the control
of a business.
EXAMPLES:
Environmental condition
Political or government system
Sociological norms and trends
Technology and innovation
Economics
Legal or laws
WAYS OF ASSESSING STRATEGICWAYS OF ASSESSING STRATEGIC
ANALYSIS TECHNIQUES AND PROCESSANALYSIS TECHNIQUES AND PROCESS

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3 Review of Performance
these are set goals and aligned to the set
measurements.
4 Dynamic Concept
is analyzing the correlation, significance, and
effect of one variable to others. It is so called
“domino effect”
WAYS OF ASSESSING STRATEGICWAYS OF ASSESSING STRATEGIC
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6. SMART Objective as Analysis PlatformSMART Objective as Analysis Platform
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SMART Objective was developed by George Doran,
Arthur Miller, and James Cunningham in 1981.
The SMART acronym stands for Specific, Measurable,
Attainable, Realistic, and Time Bound.

7. SMART Objective as Analysis PlatformSMART Objective as Analysis Platform
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It is about providing a clear
picture as a focus.
Oriented and detailed in form.
Pointing or naming the
variable (person, things,
event, etc.).
pecific
It is usually quantifiable in form.
Usually measured by numbers,
rate, fraction, amount, ratio,
period, and the like.
It could be also expressed in
character and attributes
easurable

8. SMART Objective as Analysis PlatformSMART Objective as Analysis Platform
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The objectives and results are
bound into reality.
Attainment of goals are
challenging but feasible to attain.
The indicators are set to be
calculated in reasonable values.
ealistic
It is achievable in form.
Being feasible is intended
because goals shall be met.
ttainable

9. SMART Objective as Analysis PlatformSMART Objective as Analysis Platform
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Time is the essence.
Timely structure is organized in setting goals.
The authenticity of period is relevant in the process of analysis.
ime Bound

10. 3
Reach goals in a straightforward and specific direction.1.
Set goals and ways in strategic and competitive manner.2.
Increase productivity.3.
Reduce or avoid idle time.4.
Foster teamwork and well-coordinated employee
ambiance.
5.
Reduce or avoid wastages and unnecessary costs.6.
Encourage decision-makers to have creative and
analytic solutions.
7.
Incorporating SMART Objective in business analysis has
advantages such as:
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11. WAYS OF PRESENTATION AND ANALYSISWAYS OF PRESENTATION AND ANALYSIS
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Presentation is reporting of both written and oral
activity for demonstration of results and exhibit,
dissemination of information, and arrangement of
proposed action plans, putting in together for
analysis and problem-solving task.
Using statistics will help the presenter and the
audience understand issues better.

12. PRESENTATIONS ARE CATEGORIZED INTO THREE, NAMELY:
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1.
Through immediate superior of boss
Person to person meeting.
The presenter discusses the findings, observations
and proposal through his boss.
TYPES OF REPORTS
Charts
Pictures
Findings
Summary of Analysis
Action plan

13. PRESENTATIONS ARE CATEGORIZED INTO THREE, NAMELY:
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2.
Departmental or Division
Group meeting.
The presenter discusses the findings observations and
proposal in the group.
This is subject for verification, brainstorming,
enhancement, polishing, approval and rejection (if
needed).
Charts
Pictures
Findings
TYPES OF REPORTS
Summary of Analysis
Action plan

14. PRESENTATIONS ARE CATEGORIZED INTO THREE, NAMELY:
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3.
Top Management Level
Group meeting or board meeting.
The presenter discusses the findings observations and
proposal in the group.
This is subject for verification, brainstorming,
enhancement, polishing, approval and rejection (if
needed).
Charts
Pictures
Findings
TYPES OF REPORTS
Summary of Analysis
Action plan

15. WAYS OF PRESENTATION AND ANALYSISWAYS OF PRESENTATION AND ANALYSIS
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During presentation of reports, analyses of
performance with its effect and corresponding
budget are important factor in determining to
approve or reject the action proposals.
Topics are delivered into demonstration, discussion,
collaborative learning, review of data, case study or
discussion method, using multimedia such as
audio video report, brainstorming, portfolio, and
video conferencing.

16. SIX CATEGORICAL ANALYSIS TECHNIQUES:
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1.
Critical Analysis
It focuses on the subjective
findings of the analyzer by
commenting on the relationship,
connection, and effects of variables
in the data evidence.
The analyzer may also comment about projections
through basis during the research.
The facts are studied in breaking facts and analyzing the
numbers.

17. SIX CATEGORICAL ANALYSIS TECHNIQUES:
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2.
Creative Analysis
It encourage invention, innovation,
enhancement, of unique and
existing ideas. It promotes finding
the strategies while delivering into
inventive manner.
Creative analysis amplifies formation of tactics in
fabricating of products, combating competition, designing
of products, creating organization structure and job
description, securing property and assets, and the like.
Creative analysis is also an art of finding solution with
ideas, possibilities, opportunities, and alternatives.

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3.
Description Analysis
Somewhat is describing the status
of facts or data.
Foretold narrative or summary of
the result finding is the form of the
analysis.
Description analysis assures summarizing significant
remarks such as causes, effects, status of performance,
statistics, and other detailed descriptions that bear impact
to the performance result.
Description analysis is getting the basis of decision from
the circumstance of evidence.

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4.
Diagnosis Analysis
Studies the previous performance
to identify and examine the events
which answer the what and why.
It uses techniques pertaining to drill
down, discovering data, correlations,
and storing of data.
The analysis itself considers the root causes of events and
factors contributing to the performance outcome. The
statistician may use likelihoods, outcome distribution of
analysis and probabilities.

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5.
Prediction Analysis
It is a type of analysis of predicting
or forecasting the future results
(both quantitative and qualitative).
The prediction of outcome and
output is the primary tasks of this
analysis.
The decision makers may have educated guess using
statistical model and learning mechanisms. It foretells the
future basing the past performance and current research.

21. SIX CATEGORICAL ANALYSIS TECHNIQUES:
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6.
Prescription Analysis
It is an analysis of combining one course
of action to another. Fabricating solution
to situational problem is the style of
prescription analysis.
The decision makers could interpolate
each course of action to another action to
produce conducive and timely solution.
Incorporating a strategy in addressing the needs and demands of
customers, with the help of prescription analysis, lessens the burden
and satisfies the clients.
A good example of it is online booking of service or products such as
using apps like Grab, Lalamove, Transportify, and the likes.

22. QUALIQUALITATIVE ANALYSISTATIVE ANALYSIS
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It describes the attributes of appearance, events, and
outcome in subjective judgment.
The analysis of it is used in making management
assumptions, customer insights and behaviors, process,
procedures, and so on.
It is helpful in the research process because it supplies
ideas generation and description of observation findings.
It is used in focus group discussion (FGD), open-ended
survey and interview.

23. QUALITATIVE ANALYSIS IS CLASSIFIED INTO DATA ANALYSIS METHODS:
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1.
Content Analysis
It is used to analyze information in form of words,
media, and physical items. The content is
connected to the structure assumption and
findings.
EXAMPLE:
An irate customer complained about the service of a restaurant.
The duty manager will pacify the customer by listening to his
experience and direct opinion. The manager will analyze and
interpret the content of customer's need at the moment. After
listening to the side of customer, the manager will come up with a
solution in order to satisfy the client.

24. QUALITATIVE ANALYSIS IS CLASSIFIED INTO DATA ANALYSIS METHODS:
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2.
Narrative Analysis
It focuses on understanding of experiences and
stories of people for answering questions during
interview, survey, and observation.
EXAMPLE:
On budget deliberation meeting, the budget proponent or the one
who proposed of his department plan such as a manager will
narrate the activities and programs. The panel during the meeting
will ask questions while the manager describes the possible returns
to the company and justifies the amount needed.

25. QUALITATIVE ANALYSIS IS CLASSIFIED INTO DATA ANALYSIS METHODS:
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3.
Discourse Analysis
It is used in analyzing the interaction of people pertaining to
social context. The researcher asks several questions to the
respondents about certain topics that are connected to the issue.
Noting some contributable basis coming from daily activities from
the environment will add information in processing analysis.
EXAMPLE:
There is a problematic employee who commits several tardiness and
absences from his work. The employees will be interviewed by his
immediate superior about the reasons for his attendance problem. The
supervisor throws questions to the employee pertaining to finding
options or ways that the employee could do despite the issue. Through
that, the supervisor can find out the truth and recommend possible and
practical solutions to the problem.

26. QUALITATIVE ANALYSIS IS CLASSIFIED INTO DATA ANALYSIS METHODS:
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4.
Grounded Theory
It is an analysis of certain phenomenon or events that happened.
Some prior studied could be driven as basis of the activity. Similar
cases in the past might influence the present activity using causal
approach. Decision makers could change or create explanation in
studying the events.
EXAMPLE:
The grand opening day of a newly-opened retail branch vastly generate
more customer visits or traffic count on the first day. High sales are expected
during the grand opening day. Customers will buy products because of
curiosity. However, the competitor's business will be affected because of new
the entrant. The question is: How will the competitor outdo competition
during the newcomer's grand opening of contrary? What building sales
activation and other marketing activities will they implement?

27. Guidelines in Conducting Qualitative Analysis
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1. Get familiar with the facts, evidence, and information.
The researcher obtains inputs coming from respondents, literature, and
observation. Highlighting significant facts, problems, solutions and
results gathered from the source will lessen information overload.
2.Set objectives.
The decision makers and/or researchers must set research objectives
and list matters to be discussed during the research period. Prioritizing
the most needed guarantees a smart way of doing research.
3.Draft the framework of the research.
Structuring the research finding such as using concept, patterns, flow,
phrases, ideas, and behaviors is done in developing a framework. The
decision makers and/or researchers settle problems by writing a
paradigm.

28. Guidelines in Conducting Qualitative Analysis
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4.Correlate variables.
The managers and the business analyst connect vital information to the
real scenario and make feasible decisions. The patterns derived,
respondent's answers, and significant observations are correlated in
structuring the connection until solutions are formed.
5.Provide educated birds eye view of the future.
The decision makers and/or researchers see the future outcome.
Summing up all the efforts and the time taken during the research
period will attain modest outcome in the future. The view contributes to
formation of strategy and tactics of activities of a business organization.

29. QUANTIQUANTITATIVE ANALYSISTATIVE ANALYSIS
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These are necessary in deriving accuracy and
completeness of action formation.
Mathematics, statistics, measurements, and research are
important components in supporting decisions.
It is a technique used in performance evaluation,
measurement, valuation, and forecast of event.
The analysis is basically applied in business
management and economics, and results in numerical
value.

30. 1. Validate the Data
The business analyst will validate if
the gathered data do not contain
biases and were done in preset
standards. During validation of data,
the authenticity of the interview will be
checked to find out if the respondents
were really interviewed or not to avoid
any fraud. The respondents are also
accordingly screened based on the
set criteria. The data collection
procedure must be followed and the
completeness of questions asked to
the respondents must be ensured.
Steps in Preparing Data for Quantitative Analysis
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31. Steps in Preparing Data for Quantitative Analysis
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2.Edit the Data
The goal is to avoid errors in the data
by thoroughly checking the outliers and
raw data. By doing these, it will limit the
errors in the results leading to reality of
the situation.
3.Code the Data
It is simply the preparation of the data
by way of data grouping and assigning
values. Creating bracket of the data like
age, income, hobbies, and etc. are
some samples of coding activities.

32. MOST COMMONLY METHODS IN QUANTITATIVE ANALYSIS USED IN BUSINESS
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1.
Descriptive Analysis
According to Will Kenton (2019), descriptive analysis is the
brief descriptive coefficients that summarize a given
data set which can be either a representation of the entire
or a sample of a population. It describes data using a
graph or chart.

33. MOST COMMONLY METHODS IN QUANTITATIVE ANALYSIS USED IN BUSINESS
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a. Percentage - functions as rate, proportion, or share. Some practical
applications are market share, percentage of sales target met,
performance evaluation, components in budget allocation, product fill
in rate, customer traffic conversion, and etc.
b. Range - the upper and lower limit of data scale. Some practical
applications are demographic profile of the target market (customer)
like age and income. The range is also used in pipelining of
distribution channel, sales forecast using probable highest and lowest
amount, merchandising visual design, and etc.
c. Frequency - the quantity or number of variables found in the data.
Some practical applications are used in studying consumer behavior
such as of frequency of visit and purchase. Other business application
is frequency of manpower violation pertaining to attendance problem
like tardiness and absences. The frequency is also used in digital
marketing performance indicator such as recognizing citizen as top
fan, subscriber, viewer, and liker.

34. MOST COMMONLY METHODS IN QUANTITATIVE ANALYSIS USED IN BUSINESS
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d. Mean - is the average of numerical set of values.
For example: number of 1, 2, 3,3, 5; the mean is 2.8. Mean is used in setting mark up,
benchmarking, average of sales or basket sales in retail management, inclusion in
amortization and equity formula, deciding for locating branch, offsite, factory or
offshore assigned place, sales and economic growth and etc.
e. Median - is the middle value/s of the data.
For example: 1,2,3,4,5: the median is 3. Another example is 5,6,7,8,9,10; the median is
7.5. The formula is 7+8 then divide it by 2. Some practical applications are used in
brainstorming by combining ideas transforming into action plan, product
designing, logo making, sales negotiation, and salary negotiation. These can also
be applied in productivity report and operational deadlines.
f. Mode - is the number that is repeated most often.
For example: 11,12,12,13,14,15. The mode is 12. Some practical applications used in
business setting are getting the product request order of customers, suggestions
and complaint feedback by employees and customers, supplies / materials /
tools / equipment preferred, knowing the most requested item in group volume
purchase, identifying the channels and customers' most frequent mode of
transactions, most frequent problems in the workplace, and etc.

35. MOST COMMONLY METHODS IN QUANTITATIVE ANALYSIS USED IN BUSINESS
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2.
Inferential Analysis
It is the predictions from the data. Samples are obtained
for analysis and concluded for generalizations on
population set up.
The two main areas of inferential statistics are estimation
and hypothesis test. The estimation is taking statistic from
data like sample mean and applying it as population
mean. Hypothesis is using sample data in answering
questions from the research.
Some of situational examples are the effectiveness of new
products prior to the launching up to the commercial
phase, effectuality of promotion sales during sale, success
of market penetration strategy, and the likes.

36. Some of Inferential Statistics Used in Business
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a. Binomial Theorem - makes probabilities or results like head
or tail option possible to figure out. In business analysis, it is
applicable in investing and budget programs in sales
promotion, acquisition of new technology, hiring new
employees, branch expansion and etc. The choice is either of
the results as probability with the number of times decided
and happened.
b. Hypothesis Testing - is an educated guess, a product of
observation experiment. Some of workplace examples are
new variation of product that will be produced, promotion of
employee, creation of projects, integration of social media as
platforms in converting sales, employee skeletal schedule
during lockdown and etc. The acceptance and rejection of
null analysis will come out during the computation.

37. Some of Inferential Statistics Used in Business
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c. Normal Distributions - is the bell curve of distribution in several situations. It is also
used when there are more samples. These statistics could be used in the analysis of
applicant and employee's testing scores, salaries distribution, performance
distribution result, branch and product performance, performance evaluation of
product category, offtake of products, manpower performance evaluation, budget
allocation offtake, and the likes. By applying this, the managers may know the
primary contributor/top performer or strength, middle, and lowest contributor or
weakness depending on the variables.

38. Some of Inferential Statistics Used in Business
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d. T-Distributions - is the family distribution of normal distribution. The curve is
thicker and shorter compared with the normal distribution. It is also used in small
samples like 30 and below. This analysis is applicable in accepting or rejecting null
hypothesis. The rejection area might be located on the most right and left part of the
bell while the non- rejection or acceptance is located in the middle part. This analysis
is applicable during the proposal of new projects, programs, and strategies of the
organization. The result will provide safe judgment, whether to invest or not to take
risk.

39. Some of Inferential Statistics Used in Business
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e. Central Limit Theorem - is the analysis of getting sample distribution from sample
means. While the sample size is getting larger, the sample mean is transforming into
normal distribution. This is applicable in identifying the company's target market
whose geographic coverage is broader and wider, consumer's product acceptance,
multinational companies with so many branches and employees whose
performance and support to new policy and system must be analyzed, effect of
competitor's new strategy vis-a-vis company, and etc.

40. Some of Inferential Statistics Used in Business
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f. Confidence Intervals and Confidence Level
Confidence Level is the percentage of confidence.
Confidence Interval is the percentage or number of uncertainty and written as
margin of error.
This is used in decision making on the level of confidence in the program and
projects prior to the approval on a particular investment of property, equipment,
machines, and other asset. The 'approach may also have the same result when
adjustment of number will be encountered. Other set up may apply on
consumer's purchasing behavior.

41. Regression Analysis / Linear Regression - is an analysis of
relationship between one dependent variable and one or
more independent variables. In business setting, there are
factors that affect decisions and performances. Some
applications of regression analysis are when deciding to
locate a branch, an outlet, or a factory which might be
affected by proximity, consumer profile and buying habit, laws,
competitors, route, parking area, competitors, and other
dependent variables. Another situational example when
deciding on good leadership through a leader's sufficient
knowledge, skill, and attitude; determining the impact of
budget to department/division activities and performance;
and establishing customer focused approach and system of
accounting personnel to employee; and etc. Regression
analysis also applies in supply chain, logistics, information
technology, security management, financial management,
and more.
Some of Inferential Statistics Used in Business
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g.

42. Comparison of Means - is comparing two or more samples/population. Using the
normal distribution, the comparison of means may use t-test (independent sample,
one sample, and paired sample), and ANOVA (One Way Analysis of Variance).
Independent sample t-test is used when comparing of two independent data sets)
and ANOVA (One way analysis of variance). Independent t-Test is used when
comparing two independent data sets with each other. One sample t-test is for one
set of data and specified set of data. Paired sample t-test is when one tested group
is paired in two different period of time. On the other hand, ANOVA is the comparison
of means by incorporating two levels of independent variable.
The comparison of means is useful in business when studying the comparison of
competition, benchmarking, product benefits, merchandising display, insurance,
consumer behavior, logistics, and etc. The comparison of means strives to find out
which is the better way or approach until the best answer is chosen.
Some of Inferential Statistics Used in Business
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h.

43. COMBINATION OF QUALITATIVE ANDCOMBINATION OF QUALITATIVE AND
QUANTITATIVE ANALYSISQUANTITATIVE ANALYSIS
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The qualitative speaks for the
describable characteristics of
the variable/s while the
quantitative demonstrates
the numerical result of the
study.
Realism of analysis is found
to be the balance in terms of
combination analysis.

44. ADVANTAGES OF USING THE COMBINATION ANALYSIS:
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1. | The alignment of the result of the qualitative analysis must
be supported by the quantitative analysis.
This results in making sound judgment decisions that
equate figures to achieve goals.
An example is when forecasting to have good sales in
retail store. The management conducts traffic count of
customers and observes the customers' behaviors. After
the data gathering, figures will be computed and
consumer behavior will be corelated. The combination
analysis shows joint findings of objective and subjective
type of results.

45. ADVANTAGES OF USING THE COMBINATION ANALYSIS:
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2. | The combination analysis keeps track of the current
issues, trends, and challenges.
Being updated on the latest situation of business makes
the strategy fuller and bolder.
The analysis will discuss actual scenario and obtain data
from the sources.
An example is benchmarking of practices and strategy
of competitors in the same line of business.

46. ADVANTAGES OF USING THE COMBINATION ANALYSIS:
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3. | The combination analysis concludes summary of results.
The analysis itself supplies the most salient needed
information in order to make agreeable and conducive
decision for the leaders or managers, like discussing the
result of research for possible foreign direct investment
(FDI) in other regions of the world. Since investing during
the pandemic crisis is challenging, the analysis serves as
basis in decision making because of the summary of
results.

47. ADVANTAGES OF USING THE COMBINATION ANALYSIS:
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4. | The combination analysis is tool for answering business
challenges.
Although the combination analysis declares either
feasible judgement or not feasible result, it also answers
the approval, status quo and rejection of programs,
proposal and projects. It also formulates or improve
process, policies, and procedures. Mostly, the analysis
determines strategies for the company to have
meaningful growth and development of the organization
vis-a-vis performance evaluation.

48. 3
Key Performance Indicators (KPI) or
Key Performance Measurement (KPM)
Measurement of performance.
It is expressed in figures such as number, percentage,
ratio, fraction, amount, and attributes.
Some advantages of KPIs are continuous
improvement (KAIZEN), innovation, legal compliance,
industry benchmarking, prestige, and customer
satisfaction.
KEY PERFORMANCE INDICATOR,KEY PERFORMANCE INDICATOR,
METRICS, DASHBOARD, AND REPORTSMETRICS, DASHBOARD, AND REPORTS
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52. 3
Be familiar with the company’s goal.1.
Align job description and role vis a vis company’s goal.2.
Align job description and role vis a vis setting of KPI.3.
The human resource department should collaborate with management
and employees on how to align KPI to the job description.
4.
KPI should integrate the SMART objective concept.5.
KPI should incorporate the human resource manual and company’s
standard operating procedure (SOP).
6.
KPI should be periodically reviewed if still applicable on the current
situation otherwise it maybe subject for enhancement when needed.
7.
KPI’s mantra is to improve the company and employee’s performance
rather than terminating employees.
8.
KPI is the alignment process from vision to mission to employee’s job
role until productivity output and outcome.
9.
GUIDELINES IN SETTING KEY PERFORMANCE INDICATOR (KPI)
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53. 3
Metrics
It is the mathematical computation of results. It is
done through analysis and assessment used for
tracking performance as well as comparison.
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54. BUSINESS METRICS ARE CLASSIFIED INTO SOME CATEGORIES:
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1. Marketing Metrics
web traffic, incremental sales, social sentiment, end-action sale, SEO
Keyword ranking, customer lifetime value, and etc.
2.Sales Metrics
sales growth, average profit margin, average purchase value, product
performance, monthly recurring revenue, sale by region, and etc.
4.Social Media
social followers, Facebook page statistics, Twitter followers’ metrics, and
key social metrics.
3.Financial Metrics
quick ratio or acid-test, debt to equity ratio, current ratio, working capital,
gross profit margin, net profit, debt asset ratio, total revenue, and etc.

55. BUSINESS METRICS ARE CLASSIFIED INTO SOME CATEGORIES:
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5.Operational Metrics
project completion rate, manpower productivity, SOP compliance, lead
to opportunity ratio, lead conversion rate, revenues per employee, and
etc.
6.Human Resource Metrics
absenteeism rate, overtime hours, employee efficiency, quality of work,
adherence to value, time to hire, cost per hire, and etc.
8.Information Technology
total tickets vs open tickets, average handling time, budget variance,
capability rate, change request cycle time, change success rate,
customer satisfaction rate, and etc.
7.Logistics
delivery time, order status, transportation cost, on time shipping,
warehouse capacity, accurate order fulfillment, and etc.

56. 3
Dashboards and Reports
It is the summary combination of selected KPI and
metrics done in periodic monitoring. It is mostly
used as business intelligence, and information
management.
CHAPTER 2: ANALYSIS TECHNIQUES & PROCESS
56
POS
CONSOLIDATED
REPORT OF
STORE POS
HEAD OFFICE
DASHBOARD
COMPUTER
MANAGEMENT
ANALYSIS AND
DESCISION
MAKING
Figure. POS dashboard information process flow