cheongsam – Etsy PT

Business Intelligence
B u s i n e s s
T h o m a s
Dynamic SME
I n t e l l i g e n c e
F e l i x
K a r r a s c h
Business Intelligence
Agenda:
1. Definition
1
2. Advantages
2
3. Implementation
3
4. Recommendations
6
5. Attachments
8
6. Bibliography
11
Business Intelligence
1. Definition
In today´s business environment, the ability to create new knowledge and understand the market forces has become a crucial factor for the maintenance of
market share and profitability. 1 This requires the ability to permanently retrieve,
store, analyze and communicate data. The amount of data enterprises daily
have to cope with has, however, constantly increased in the last years. Especially the internet has contributed to a never ending flow of data input, that has
made it difficult for the management to capture the information relevant for
proper decision making. As a result enterprises have developed a business intelligence (BI) KMT, which facilitates the retrieval of information out of data. 2
There are many different definitions for BI. While some differentiate between BI
as the management for internal and CI for external data, 3 others define it “as
the ability to extract actionable insight from the internal and external data
available to an organization, for the purpose of supporting decision making
and improving corporate performance.” (see illustration 3) 4 This thesis will follow the second definition and thus refers to BI as the integration of strategies,
processes and techniques to generate actionable intelligence of dispersed and
inhomogeneous data of an enterprise, the market or competitors.5 BI can be
hence understood as a supply chain process for data. It sources data from the
organizational functions of an enterprise and the exterior, i.e. competitor or
market data and converts it into actionable intelligence (see illustration 4). As a
result BI helps to organize oceans of scattered data and extract all the relevant
information needed by the management to take good business decisions.6
With the increasingly turbulent economic environment, that demands enterprises to remain constantly updated on market movements, the role of BI in the
business world has changed over the last years. From a basic subordinated tool
1
Cf. Kudyba, S./ Hoptroff, R. (2001), p. 5.
2
Cf. Hannig, U. (2002), p. 3.
3
Cf. Steyl, J. (2009): URL: see list of references.
4
Canes, M. (2009): URL: see list of references.
5
Cf. Institute for Business Intelligence (w/o Y.), URL: see list of references.
6
Cf. Harper, D. (w/o. Y.), URL: see list of references.
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Business Intelligence
for the analysis of data, BI has emerged as complete new management approach which is imperative in the decision making process.7
2. Advantages
As many SMEs are merely owner-managed, decisions are mostly taken based
on static reports, simple spreadsheets or instinct. While this routine is practicable if an SME is small and easily manageable, the method soon reaches its limit
with quick market changes or intensifying competition, which demand decision
making based on relevant and current information.8
The BI tool facilitating the extraction of information from data and providing
intelligence needed for strategic decision making, serves this need.9 Through
gaining information i.e. of a new product or service of a competitor, it enables
enterprises to track the movements and changing strategies of
the competition. Based on this, an
Illustration 1: Business intelligence leads to the
discovery of new opportunities
enterprise is able to identify gaps
in the market, which it can use to
fill customer needs.10 By gaining
relevant information about the
competitor, BI furthermore allows
an enterprise to determine its
Source: Original scene from the video.
weaknesses and thus provides insight about the competitive position in the
market environment.11 As a result, BI provides an SME with a good overview
7
Cf. Olszak, C.M./ Ziemba, E. (2012), p. 130.
8
Cf. Canes, M. (2009): URL: see list of references.
9
Cf. Guarda, T. et al. (2013), p. 187f.
10
Cf. Frost, S. (w/o Y.), URL: see list of references.
11
Cf. Bose, R. (2007), p. 511f.
2
Business Intelligence
over threats and opportunities in the market, based on which it can derive
measurements for the improvement of its operations (see illustration 1).12
Another advantage of BI is the ability to forecast trends. 13 Analytical techniques
of BI identify relationships or unusual patterns in the obtained data and are
hence able to visualize information that has not been recognized before.14 By
the discovery of these anomalies, an enterprise becomes aware of emerging
trends and is able to adjust its strategy accordingly. The ability to discover patterns and relationships data also holds advantages for the customer service.
Through the analysis of i.e. sales data, BI assesses the demography as well as
habits of the customers and determines correlating products or services. As a
result, BI offers valuable opportunities for up-selling 15 and cross-selling products 16. This allows an enterprise to streamline its marketing efforts, resulting in
an improved customer experience and better use of resources. 17
3. Implementation
Researchers have proposed many different approaches for the design of a BI
process. This thesis will focus on the most commonly applied structure, which
consists of five distinct phases (see illustration 2). 18
The process starts with the planning phase, in which the objectives for the
process are set. 19 At this point it is important that the decision makers, for
whose demand the process is ultimately created, communicate their intelligence needs, as these establish the foundation for the later phases. Based on
12
Cf. Vedder, R.G. et al. (1999), p. 110.
13
Cf. Sangar, A.B./ Iahad, N.B.A. (2013), p. 177.
14
Cf. Guarda, T. et al. (2013), p. 188.
15
up-selling is a sales strategy in which the seller encourages a customer to purchase more expensive items or upgrades for a higher sales profit
16
cross-selling is the encouragement of an existing customer to purchase an additional product
17
Cf. Williams, S./ Williams, N. (2007), p. 162.
18
Cf. McGonagle, J.J. (2007), p. 71.
19
Cf. Morcillo, P. (2003), URL: see list of references.
3
Business Intelligence
these needs, key intelligence topics (KITs) can be created, which point out the
topics of greatest interest for the achievement of the strategic goals of the
company.20
Once the KITs are defined, the process continues with the collection phase, in
which the data has to be sourced and preprocessed. Here it is first of all important to match the available data sources with the KITs formulated in the planning phase. 21 This compliance with the intelligence needs is necessary to ensure that a correct decision can be taken based on the resourced data. Before
collecting the data, the source should thus furthermore always be checked for
Illustration 2: The business intelligence process
Decision
Making
Re-initiation of Process
Internal
Data
Sources
External
Data
Sources
Databases
Planning
Collection
Analysis
Dissemination
Feedback
Define
necessary
data
Collect data,
data preprocessing,
data analysis
Data analysis,
Project results
Data
Distribution
Feedback
Source: Own illustration based on Bose, R. (2007), p. 513; Guarda, T. et al. (w/o Y.), p. 187f.
its suitability.22 For the collection itself, SMEs have a large variety of potential
sources at their disposal. They can i.e. source the data directly from interviews,
focus groups or executives. The most recommendable source, is probably,
however, the internet, as it has made research, i.e. on competitors, easy and
affordable. Here the SME has the option to connect with experts, customers
and suppliers or gather data from webpages, i.e. of competitors. While these
20
Cf. Krizan, L. (1999), URL: see list of references.
21
Cf. Bose, R. (2007), p. 513.
22
Cf. Sangar, A.B./ Iahad, N.B.A. (2013), p. 177.
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Business Intelligence
are all primary resources 23, an SME can furthermore tap secondary resources 24.
For this purpose search engines and online subscription databases have become popular tools to collect data from commercial news organizations or
news filtering services. 25 Lastly the collected data needs to be refined and
structured for further analysis. 26
The next phase, the analysis phase, is the core stage and most critical part of
the BI process. It differs from the collection process in the way, that its purpose
is not to collect a set of data from diverse sources (i.e. internet, internal or external databases), but to illustrate the significance of a predefined data set. 27 To
do so the refined data collected before is systematically examined, analyzed
and validated.28 The main activity consists of mining the data29 to identify patterns and relationships for the extraction of actionable intelligence. 30 SMEs often encounter difficulties performing this task, as they are not able to afford the
complex BI infrastructures of larger companies (see illustration 5). Nowadays,
however, there are many possible alternatives. Open source software for instance is often available online at no cost and thus offers the SMEs an opportunity to start mining data without committing to a large investment.31
Once the intelligence has successfully been extracted, it needs to be disseminated. In this stage the extracted intelligence is reported back to management
through meetings, reports or dashboards, providing insight on the KITs. For this
purpose it is essential that the report is visualized an easy-to-understand format
so possible misunderstandings can be avoided. 32 Provided with the intelligence on the KITs, the decision makers are then able to take action. Besides for
23
Primary sources are first hand sources that provide direct evidence of a topic.
24
Secondary sources interpret or analyze primary sources and are thus one step remote from
the event.
25
Cf. Botha, A.P. (2007), p. 53.
26
Cf. Barnard, S. (w/o Y.), URL: see list of references.
27
Cf. Krizan, L. (1999), URL: see list of references.
28
Cf. Sangar, A.B./ Iahad, N.B.A. (2013), p. 177.
29
data mining is a set of activities to identify hidden relationships in data.
30
Cf. Miller, S.H. (2001), URL: see list of references.
31
Cf. Chen, X. et al. (2007), p. 4.
32
Cf. Miller, S.H. (2001), URL: see list of references.
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Business Intelligence
decision making, the intelligence may also serve for further analyses such as
competitor profiling, scenario planning or scenario analyses.
The process is concluded with the feedback of the executives. It includes an
assessment of the quality and accuracy of the intelligence as well as guidance
for the analyst of how the process can be improved in the future.33 A BI process
thus has to be understood as iterative in the sense that it permanently repeats
upon completion and is always subject to improvement.34
4. Recommendations
As many enterprises are opposed to change or new technology, the support
from top management is a critical factor for the success of BI. A dedicated
management which endorses the BI process ensures financial resources and
effective project management.35 It is thus the responsibility for those involved
in an intelligence program to convince the senior executives of its usefulness.
They should be encouraged to use the system actively instead of contemplating it just as another reactive management resource.36 Besides its endorsement
for BI as a system, it is important that the top management considers the intelligence program an iterative process rather than a one time project.37 This continuity is essential, as strategic planning requires long-term intelligence and a
continuous basis of information.
Closely connected to continuity are also other critical success factors. A culture
of trust and cross-organizational collaboration, i.e. is vital for the effective
knowledge exchange and thus critical to transform knowledge of an individual
into organizational knowledge. Especially in SMEs, that rely mostly on tacit
knowledge, knowledge workers can only be replaced to a certain extent. A col33
Cf. Bose, R. (2007), p. 514.
34
Cf. William, Y./ Koronios, A. (2010), p. 23ff.
35
Cf. William, Y./ Koronios, A. (2010), p. 23ff.
36
Cf. Global Intelligence Alliance (2004), URL: see list of references.
37
Cf. William, Y./ Koronios, A. (2010), p. 23ff.
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Business Intelligence
laborative culture facilitates a healthy flow of information within the organization, which is needed to make the collected and analyzed information about
customers, competition, market conditions, vendors, partners, products and
employees available at all levels. 38 A properly functioning BI process in this
sense also requires the utilization of tools and applications. They not only facilitate the collaboration by providing means to communicate the intelligence
within the organization, but furthermore encourage BI users to produce content themselves. In the end, it should, however, always be clear to an enterprise
that tools merely support the managing knowledge process and that BI can
consequently only be successful, if the knowledge and skills of the people are
used effectively.39
38
Cf. Atre, S. (2003), URL: see list of references.
39
Cf. Global Intelligence Alliance (2004), URL: see list of references.
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Business Intelligence
5. Attachments
Illustration 3: Definition of Business Intelligence
Data Sourcing
Internal
Data
Sources
Data Processing
Data Visualization
External
Data
Sources
Data
Intelligence
Data Integration from
Departments and
External Sources
Intelligent Data
Analysis
Data
Dissemination
Source: Own illustration.
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Business Intelligence
Illustration 4: The business intelligence value chain
Increasing
potential to
support
business
decisions
Action
Insight
Knowledge
Information
Data
Source: Own illustration.
9
Business Intelligence
Illustration 5: The architecture of business intelligence
Internal Data Sources External Data Sources
(ERP Systems)
(Internet)
Standardized
Reporting
ETL-Tools
Extract
Ad-hoc Reporting
Data
Mining
OLAP Tools
Transfer
- Convert
- Filter
- Aggregate
Load
Data Warehouse
Data Mart
Meta-Data Bank
Archive
Source: Own illustration based on Hannig, U. (2002), p. 6.
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Business Intelligence
6.
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http://www.insideinfo.com.au/files/business@20intelligence@[email protected]
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Bose, R. (2007): Competitive intelligence process and tools for intelligence
analysis, in: Industrial Management and Data Systems, Vol. 108, No. 4, p. 510528.
Botha, A.P. (2007): Knowledge - living and working with it, Cape Town, South
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Canes, M. (2009): Business Intelligence for the SME, in:
http://www.bluelinkerp.com/downloads/2009-10-15-Business-Intelligence-for-t
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Chen, X./ Ye, Y./ Williams, G./ Xu, X. (2007): A Survey of Open Source Data
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