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DOI: https://doi.org/10.48009/4_iis_2021_168-179
Competency evaluation for careers in business intelligence analysis
Mark Fox, Indiana University South Bend,
mfox1@iusb.edu
Jennifer L. Breese,
Penn State University,
jzb545@psu.edu
Ganesh Vaidyanathan, Roosevelt University,
gvaidya[email protected]
Abstract
We use the US Occupational Resource Network (O*NET) to derive competencies required of those
pursuing careers as Business Intelligence Analysts (BIA). Specifically, we look at the knowledge, skills,
abilities, and work styles required of BIA occupations. We then group those competencies into more
meaningful, but related, competency categories that we call: personal effectiveness competencies;
communication competencies; cognitive competencies; management & interpersonal skills; systems
competencies; and mathematics, statistics, and applications. We contrast the competencies we found with
those mentioned in previous studies and conclude by making some observations about the implications of
our research.
Key
words: business data, business intelligence analyst, business data analyst, competencies, careers
Introduction
The
Bureau of Labor Statistics categorizes occupations by Standard Occupational Classifications (SOCs).
The SOC that most closely correlates to big data analytics is 15-2050 Data Scientists. That occupational
category is defined as involving those who:
“Develop and implement a set of techniques or analytics applications to transform raw data
into meaningful information using data-oriented programming languages and visualization
software. Apply data mining, data modeling, natural language processing, and machine
learning to extract and analyze information from large structured and unstructured datasets.
Visualize, interpret, and report data findings. May create dynamic data reports.” (National
Center for O*NET Development, 2021a)
The SOC Data Scientists category incorporates two subcategories, namely Business Intelligence Analysts
(15-2051.01) and Clinical Data Managers (15-2051.02). Our focus is on Business Intelligence Analysts.
Business Intelligence Analysts (BIA) include jobs with titles such as: Business Intelligence Analyst,
Competitive Intelligence Analyst, Data Analyst, Intelligence Analyst, Market Intelligence Analyst, Market
Intelligence Consultant, Strategic Business and Technology Intelligence Consultant, Strategist (National
Center for O*NET Development, 2021b). In 2019, the Bureau of Labor Statistics estimated there were
33,200 jobs for data scientists and mathematical science occupations (including BIA jobs), and from 2019
to 2029 an additional 10,300 new jobs in these areas were predicted (a growth of 31%, which is much faster
than average) (Bureau of Labor Statistics, 2021).
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We use O*NET in this study as other researchers have used it in the past (e.g., Burrus et al., 2013; Cifuentes
et al., 2010; Hadden et al., 2004; Zimmerman et al., 2004). O*NET is particularly useful as it creates
standardized occupation-specific descriptors and it is based on surveys of job incumbents.
The purpose of our research is to identify the most important competencies needed by Business Intelligence
Analysts so as to help educators with curriculum design in this fast-changing field. Our research is also
useful for students and human resource professionals, who may be evaluating the relevance of different
programs to their needs. In the next section we identify the competencies needed by business intelligence
analysts. We then compare those competencies with those competencies that have been identified by other
researchers. The final section includes the conclusion and the implications of our research.
Competency areas for business intelligence analyst jobs
O*NET provides importance rankings that “indicates the degree of importance a particular descriptor is to
the occupation” (National Center for O*NET Development, 2021c). We look at these importance rankings
for each of competencies areas that are the focus of this paper (namely knowledge, skills, abilities, and
work styles). Importance rankings are provided by O*NET on a scale of 0 to 100, where zero is not
important and 100 is the highest possible score. O*NET defaults to listing rankings that have numerical
scores of at least 50 and we do the same (50 is the mid-range for something to be considered “important”).
We now turn our attention to the each of the competency areas for BIA jobs, namely, knowledge, skills,
abilities and work styles. These four areas form the basis for the competencies needed for BIA jobs. We
focus on these areas as they were deemed to be important by Burrus et al. (2013), who focused on those
areas after examining previous research. From O*NET we identified the following items with importance
scores of 50 or higher:
● Four knowledge competencies, each of which comprises “Organized sets of principles and facts
applying in general domains” (National Center for O*NET Development, 2021d);
● Sixteen skill areas, where skills are “Developed capacities that facilitate learning or the more rapid
acquisition of knowledge” (National Center for O*NET Development, 2021d);
● Seventeen ability areas, where abilities are “Enduring attributes of the individual that influence
performance” (National Center for O*NET Development, 2021d); and
● Fifteen work style areas, i.e., “Personal characteristics that can affect how well someone performs
a job” (National Center for O*NET Development, 2021d). As with abilities, these can be developed
through education and experience.
Specifically, we generated knowledge, skill, ability, and work style competencies using the custom report
feature in O*NET (National Center for O*NET Development, 2021a). The knowledge areas with
importance rankings over 50 (out of 100) appear in Table 1, and the skills, abilities and work styles with
ratings over 50 (out of 100) are in Tables 2 and 3. Most of the abilities required are cognitive abilities and
a few are sensory abilities.
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Table 1: Knowledge Requirements for Business Intelligence Analysts
Knowledge
Knowledge description
Importance
English Language
Knowledge of the structure and content of the English language
including the meaning and spelling of words, rules of
composition, and grammar.
76
Mathematics
Knowledge of arithmetic, algebra, geometry, calculus, statistics,
and their applications.
58
Administration
and Management
Knowledge of business and management principles involved in
strategic planning, resource allocation, human resources
modeling, leadership technique, production methods, and
coordination of people and resources.
51
Computers and
Electronics
Knowledge of circuit boards, processors, chips, electronic
equipment, and computer hardware and software, including
applications and programming.
51
Table 2: Skills and Abilities for Business Intelligence Analysts
Skills
Importance
Importance
Reading Comprehension:
Understanding written sentences and
paragraphs in work related documents.
75
ability to read and understand
information and ideas presented in
writing.
78
Critical Thinking: Using logic and
reasoning to identify the strengths and
weaknesses of alternative solutions,
conclusions or approaches to problems.
75
to communicate information and
ideas in writing so others will
understand.
78
Active Listening: Giving full attention
to what other people are saying, taking
time to understand the points being
made, asking questions as appropriate,
and not interrupting at inappropriate
times.
72
ability to listen to and understand
information and ideas presented
through spoken words and
sentences.
75
Speaking: Talking to others to convey
information effectively.
72
communicate information and
ideas in speaking so others will
75
Writing: Communicating effectively in
writing as appropriate for the needs of
the audience.
69
to combine pieces of information
to form general rules or
conclusions (includes finding a
relationship among seemingly
unrelated events).
75
Active Learning: Understanding the
implications of new information for
both current and future problem-solving
and decision-making.
69
to apply general rules to specific
problems to produce answers that
make sense.
72
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Judgment and Decision Making:
Considering the relative costs and
benefits of potential actions to choose
the most appropriate one.
66
to generate or use different sets of
rules for combining or grouping
things in different ways.
69
Skills
Importance
Importance
Complex Problem Solving: Identifying
complex problems and reviewing
related information to develop and
evaluate options and implement
solutions.
63
ability to arrange things or actions
in a certain order or pattern
according to a specific rule or set
of rules (e.g., patterns of numbers,
letters, words, pictures,
mathematical operations).
66
Mathematics: Using mathematics to
solve problems.
60
speak clearly so others can
66
Systems Analysis: Determining how a
system should work and how changes in
conditions, operations, and the
environment will affect outcomes.
60
to identify and understand the
speech of another person.
63
Systems Evaluation: Identifying
measures or indicators of system
performance and the actions needed to
improve or correct performance,
relative to the goals of the system.
56
come up with a number of ideas
about a topic (the number of ideas
is important, not their quality,
correctness, or creativity).
60
Time Management: Managing one's
own time and the time of others.
56
to tell when something is wrong or
is likely to go wrong. It does not
involve solving the problem, only
recognizing there is a problem.
60
Monitoring: Monitoring/Assessing
performance of yourself, other
individuals, or organizations to make
improvements or take corrective action.
53
ability to choose the right
mathematical methods or formulas
to solve a problem.
60
Learning Strategies: Selecting and
using training/instructional methods and
procedures appropriate for the situation
when learning or teaching new things.
50
to identify or detect a known
pattern (a figure, object, word, or
sound) that is hidden in other
distracting material.
56
Coordination: Adjusting actions in
relation to others' actions.
50
up with unusual or clever ideas
about a given topic or situation, or
to develop creative ways to solve
53
Persuasion: Persuading others to
change their minds or behavior.
50
add, subtract, multiply, or divide
quickly and correctly.
53
details at close range (within a few
feet of the observer).
53
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Table 3: Work Styles for Business Intelligence Analysts
Work style
Importance
Analytical Thinking: Job requires analyzing information and using logic to
address work-related issues and problems.
95
Attention to Detail: Job requires being careful about detail and thorough in
completing work tasks.
93
Dependability: Job requires being reliable, responsible, and dependable, and
fulfilling obligations.
85
Initiative: Job requires a willingness to take on responsibilities and challenges.
82
Integrity: Job requires being honest and ethical.
82
Persistence: Job requires persistence in the face of obstacles.
81
Cooperation: Job requires being pleasant with others on the job and displaying
a good-natured, cooperative attitude.
76
Achievement/Effort: Job requires establishing and maintaining personally
challenging achievement goals and exerting effort toward mastering tasks.
74
Adaptability/Flexibility: Job requires being open to change (positive or
negative) and to considerable variety in the workplace.
74
Independence: Job requires developing one's own ways of doing things,
guiding oneself with little or no supervision, and depending on oneself to get
things done.
73
Stress Tolerance: Job requires accepting criticism and dealing calmly and
effectively with high stress situations.
63
Innovation: Job requires creativity and alternative thinking to develop new
ideas for and answers to work-related problems.
62
Leadership: Job requires a willingness to lead, take charge, and offer opinions
and direction.
58
Self Control: Job requires maintaining composure, keeping emotions in check,
controlling anger, and avoiding aggressive behavior, even in very difficult
situations.
54
Concern for Others: Job requires being sensitive to others' needs and feelings
and being understanding and helpful on the job.
51
General listings of competencies such as those in Tables 1 through 3 have some value, but they are not as
useful as grouping related competencies together into more meaningful, and related, categories. We did just
this. In creating these overall competency categories we attempted to reach a balance between relevance
and focus. Where there were multiple related items we tended to group these together, but not to bundle
them into categories that were too small. Each of the three authors independently categorized the general
competencies from Tables 1 to 3 into overall competency categories that we believe would be more helpful
for teachers, practitioners, and students. The area where we had some difference of opinion was where to
place persuasion skills, namely whether or not this constitutes a communication competency or is a
management and interpersonal skills competency. We ultimately decided to limit the communication
competencies to more basic communication skills (reading, speaking, writing). We also believed that,
although persuasion is a communication skill, it is a more advanced skill that belongs more to the
management and interpersonal skills competency category—which is ultimately where we placed it.
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Below, we present the overall competencies that we developed, i.e., the most important competency areas
of BIA professionals. We order these from what can be seen as more foundational to more complex
competencies, i.e., as we progress, the competencies (generally speaking) build upon one another. (As an
aside, the only item that did not fit was a physical competency, namely “near vision”). The definitions for
these competencies already appeared in Tables 1 to 3, above.
Personal effectiveness competencies are competencies that drive individuals to be engaged and motivated
in the BIA field. These can be viewed as foundational competencies. Without these competencies
individuals are unlikely to be motivated and able to succeed in the BIA field. The specific competencies
that are related to personal effectiveness are as follows:
● Achievement/effort, attention to detail, dependability, independence, initiative, integrity,
persistence, self-control, and stress tolerance.
Communication competencies involve being able to communicate effectively. These competencies are
useful for BIA professionals as the job involves understanding the needs of others and then, once complex
data is analyzed, communicating findings to others within their organizations (White, 2019).
● English language knowledge.
● Reading comprehension, speaking, active listening, and writing.
● Written comprehension and expression; oral comprehension and expression; speech clarity and
recognition.
Cognitive competencies involve how we think about and solve problems. These competencies are needed
as BIA professionals need to “distinguish relevant from irrelevant data, draw the right assumptions, and
translate information into insights” (Sato & Huang, 2015, p. 210). The cognitive competencies that we
grouped into this category are as follows:
● Active learning, critical thinking, judgment and decision-making, and complex problem solving.
● Category flexibility, deductive and inductive reasoning, fluency of ideas, flexibility of closure,
information ordering, originality, and problem sensitivity.
● Analytical thinking, adaptability/flexibility, and innovation.
Management and interpersonal skills: We grouped these competencies together as interpersonal skills
are essential to effective management and management also involves the management of non-human
resources, such as time.
● Knowledge of administration and management.
● Monitoring, coordination, learning strategies, persuasion, and time management.
● Cooperation, leadership, and concern for others.
Systems competencies: We grouped systems analysis and evaluation together as a distinct competency
category as this is a distinct domain with information systems (although it may also involve the use of
applications such as ERP systems; see, for example, Irani & Love, 2001). Understanding systems is
important for BIA professionals as one of their key roles is to make use of data in ways that create business
value. That potential value can often be identified by evaluating current systems needs in light of emerging
customer and competitor trends (White, 2019).
Statistics, mathematics and applications: We viewed this as the most complex of the competency groups
as it involves not only statistical expertise, but also the ability to use various software tools. As one expert
notes, “Through use of data analytics, data visualization and data modeling techniques and technologies,
BI [Business Intelligence] analysts can identify trends that can help other departments, managers and
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executives make business decisions to modernize and improve processes in the organization” (White,
2019). The specific competencies that we grouped into this area are:
● Knowledge of computers and electronics
● Knowledge and skills in mathematics;
● Mathematical reasoning and number facility.
With regard to software applications, O*NET provides examples of technology skills for BIA jobs (see
Table 4). What is striking about these is the wide range of software expertise required and the large number
of these technologies that are categorized by O*NET as being “hot”, i.e., that are mentioned frequently in
job postings. O*NET identifies the “hot” technology skills by using a fire icon.
Table 4: Examples of Technology Skills for Business Intelligence Analysts
Source: Screenshot from National Center for O*NET Development (2021b). We used the default settings for 10
technologies, with up to four examples being given per category. Interested readers could vary these settings.
When discussing data scientists in general, Mikalef et al. (2018) noted that, “there is limited research on
the discrepancies between the skills that are needed in the market and what graduates possess” (p. 1). Their
finding is still largely true today. This is particularly true when we consider our area of interest, namely the
subset of data scientists that are business intelligence analysts. Next, we look at key research previously
undertaken in this area and contrast it with our own findings.
Comparing our O*NET findings with other studies
A study by Debortoli et al. (2014) used text mining on job advertisements to compare BIA skills found that
BIA skills could largely be categorizes as either business skills or IT skills. Descriptive terms such as
“developer,” “SQL server,” “data warehouse,” “ETL (extraction, transformation, and Loading),” and “BI
developer” and associated titles of job ads such as “BI Developer SQL Server,” “ETL Developer,” and
“SQL Server DBA” were assigned for BIA jobs. Terms like “sales,” “business development,” “marketing,”
“account,” and “new business” described a second group of jobs with associated job titles such as “Business
Development Manager BI,” “Sales Executive BI,” and “New Business Sales Executive.” The first few high-
loading extracted factors were found to be job titles that include “Business Analyst” and “Business
Development Manager”. Of the job titles 6% included titles such as “Business Analyst,” “Business Analyst
SAP APO Excel Expert,” “Data Analyst,” “Reporting Data Analyst,” “BI Report Analyst,” and “Technical
Business Analyst”. The factor loadings reported specific domains such as healthcare and digital marketing,
specific managerial competencies such as project management, and specific IT competencies related to
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vendor-specific products (e.g., Microsoft, SAP, SAS) and those related to general concepts and methods
(e.g., database administration, BI architecture) as the most dominating demands. SAP BusinessObjects,
SAP Business Warehouse, SAP High Performance Analytical Appliance (HANA), SAS BI Platform, IBM
BI Platform were found to be leading factors of technology competencies (Debortoli et al., 2014). The
findings support the technology skillsets we found in O*NET.
De Mauro et al., (2018) also examined online job postings. For business analyst roles they found that
database management, project management, systems management, analytics and business impact skills
were the most mentioned in job postings. This is pretty much consistent with our findings, although the
project management skills would have been somewhat subsumed into our management and interpersonal
competencies category and the analytics and business impact skills would largely be within our statistics,
mathematics and applications category.
Dubey and Gunasekaran (2015) interviewed the heads of business analytics for ten companies based in
India. Based on these interviews and an examination of previous research the authors developed a
framework of BDBA (Big Data and Business Analytics) that comprised hard skills (Statistics,
Forecasting, Optimization, Quantitative finance, Financial accounting, Multivariate statistics,
Multiple criteria decision making, Marketing, Research methods, Finance) and soft skills (Leadership
ability, Team skills, Listening skills, Learning, Positive attitude, Communication skills, Interpersonal skills,
Patience, Passion). What is interesting here is the prominence of finance skills among the hard skills and
the inclusion of skills such as leadership ability, learning, passion and patience among the soft skills. This
may be accounted for by the senior positions of those being interviewed.
Persaud (2020) examined job postings, programs BDA (business data analytics) programs offered by
colleges and universities, and interviews with executives whose firms utilize BDA. The author developed
a concept map of themes and data based on big data jobs. These themes were: data, computer science,
information, source; business; customers; skills, and people. Also, text mining analysis yielded four broad
categories of knowledge, skills, and abilities that employers are seeking for big data professions, namely:
data analytics, computing, business, and soft skills. This is in line with the competencies presented in
O*NET.
Business skills used to analyze and make decisions based on the analytical reports are important to both
business analysts and data scientists. The most important and desirable skills for an entry role for a BIA
include data analytics, modeling, and business strategy in the hard skills category; analytical, problem
solving and written communication in the soft skills category; and SQL, Python and Java in the software
skills category (Ozturk & Hartzel, 2020).
In general, we see significant overlaps between the competencies we generated from O*NET for BIA jobs.
Where there are differences this is likely a function of focus: we focused specifically on BIA jobs and on
the framework used by O*NET, whereas many earlier studies were broader (focusing on big data or data
analytics, rather than BIA specifically) or narrower (focusing just on, say, job advertisements).
Implications and conclusions
Business Intelligence Analysis has been predicted as an area that would lead to numerous jobs (Chen et al.,
2012). There is clearly a need for individuals with knowledge in descriptive, predictive, and prescriptive
analytics and in making good decisions using such analysis. Business intelligence analysis is usually
covered in academic disciplines such as Information Systems, Computer Science, Statistics, and Business.
Each discipline offers a niche in educating and graduating students to become BIA.
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Information systems programs offered in business schools and can provide a unique set of skills and
knowledge to their students. To obtain such knowledge and skills, students must gather a holistic knowledge
emphasizing in data management, business-oriented statistical analysis, management science techniques,
and obtaining general business domain knowledge such as marketing, accounting, finance, and economics.
Courses need to offer content focusing on data mining, text mining, opinion mining, social media/network
analytics, web mining, and predictive analytics. The education for a BIA demands an interdisciplinary
business and domain knowledge with a focus on statistical analysis of both structured data and unstructured
text (Chen et al., 2012). Clayton and Clopton (2018) further elaborate that a team consisting of multi-
disciplinary faculty, advisory board members, and key alumni who work with data analytics must be
involved to develop a BIA curriculum. Dubey and Gunasekaran (2015) recommended training as a
complementary aspect for offering skills and knowledge to students. They argued a need to revamp the
education system by analyzing a proper fit between education and training in order to improve the
effectiveness of student learning outcomes.
The purpose of our research was to determine the most important competencies needed by Business
Intelligence Analysts. The O*NET database was useful to transform mountains of data from job incumbents
into precise, focused occupational intelligence that can be understood easily and efficiently by educators,
employers, and students alike. Our findings can be readily applied for program design and assessment.
Further, they are useful for identifying textbooks, instructional resources or gaps in such resources. While
preconceptions by students and instructors exist in any field, this data could provide foundational elements
from which to reconstruct those opinions. Our findings are also useful for human resource management
(HRM) systems. HRM is a corporate function that is increasingly using competency systems as a basis for
selection, training and development (Lucia & Lepsinger, 1999). The competencies we identified, along with
organization-specific needs, can form a useful basis for evaluating candidates and also identifying what the
training and development needs of current employees.
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