To improve the competitiveness in the
modern world, forecasting and modeling of company activity results in Business
Intelligence (BI) is used. Managing customer experience and building long-term
relationships with clients is an important aspect of the successful functioning
of high-tech companies, especially in the field of telecommunication, which is
one of the most promising and fast-growing sectors of the economy. It should be
noted that the analysis of customer experience should be transformed into
convenient information and telecommunication services. This article is discusses
the development of business graphics models for analyzing and improving the
activity of a cellular communication operator using a system of key performance
indicators. Information processing of informational arrays about the client database
and the provided services allow to create powerful tools for making weighted
and informed managerial decisions to improve services and build a client
information storage based on the system of analytical models.
In recent years, performance management
technology based on key performance indicators (KPI - Key Performance
Indicators) has become increasingly popular in the design and development of
organizational business models, as well as at the stage of making strategic and
tactical decisions for the development of selected business areas.
This article represents a visual approach
to solving decision-making problems by the example of a Russian high-tech
company in telecommunications. Attention is paid to the development and
application of visual methods based on the use of business intelligence tools.
Using a business analytics tool Tableau, a set of interrelated visual models
was built. This set is based on key performance indicators and forms a
systematic picture of the operation and development of a Russian high-tech
telecommunications company.
Currently, Business Intelligence systems
remain one of the most promising solutions in the field of business
intelligence, despite the general economic stagnation and the global economic
crisis. In 2017, the volume of the global market for business intelligence
platforms (Business Intelligence) and analytical applications reached $ 16.9
billion, increasing by 5.2% in comparison to 2016 [16]. According to the
forecasts published by a number of analytical agencies, until 2020 the market
for BI systems and analytical platforms will remain one of the most fast-growing
segments of the global IT market. Figure 1 shows the distribution of the
leading BI-systems in 2017 in the whole world. As can be seen from Figure 1,
the leader in the number of implementations is the Tableau system, its share
reaches 30%. Thus, the software complex of the Tableau Company was chosen in
this article as the instrumental tool to form a system of key performance
indicators. The Tableau system implements functions for mixing or combining
data from different sources, allowing users to simultaneously operate with an
array of information in real time. Visual models are implemented in the system
based on a word cloud, bubble and tree-visible (hierarchical) diagrams, which
allow to acquire a higher level of business analysis context.
Fig.
1. Distribution of BI-systems by the number of projects-implementations in the
telecommunications industry in the world (in 2017).
The analytic hierarchy method (T. Saati)
was used to choose the Business Intelligence software product. The main goal is
located at the top of the hierarchical tree and it is used to represent the
problem. The second layer is occupied by lower criteria, the lowest level – by alternatives.
The obtained hierarchical model is shown in Figure 2. Systems were evaluated
according to eight criteria, among them are: price policy, implementation
period, integration with data storage, availability of support services, mobile
platforms support, possibility of quick modifications, integration with
Microsoft Office and user-friendly interface.
Fig.
2. Visualization of a hierarchical model for choosing the business intelligence
system.
It should be noted that the key factors for
Business Intelligence systems are the quality and convenience of integration
with external data storages. The result of the applying of analytic hierarchy method
is represented in Figure 3. MY Priority software was used for the calculations.
The sizes of the sectors of the diagram are determined by the priorities of the
alternatives, which were calculated using pairwise comparisons of the
alternatives.
From the figure 3 it is possible to conclude
that the Tableau software product with a priority weight of 0.4302 is the most
preferable. The Tableau system is implemented in large telecommunication
companies, e.g. Rostelecom PJSC, and taking into consideration industry specificity,
it is 1) the most cost-efficient solution, 2) implements a fairly simple
possibility of integration with the storage systems, as well as with Microsoft
Office packages, 3) has a multi-level Russified support and reduced implementation
duration.
Fig.3.
Results of the quantitative comparison of alternatives according to the
selected criteria based on the analytic hierarchy method.
The architecture of the proposed BI
solution is presented in Figure 4 and displays sources, table storages and
showcases which containe data about the calls, money transactions, telecommunication
equipment, points of sales and client tariffs. The structure of the proposed BI
solution requires the involvement of IT specialists from the big data analysis
divisions in order to customize and integrate the information platform with the
software systems used in the enterprise.
Fig.4.
Visual structural model of the BI-system architecture.
The process of data marts adjustment and
adapting the application to the necessities of the enterprise is presented in
Figure 5. A number of IT specialists, including system analysts and data
management engineers (BI specialists), is involved into the process of implementation
of a Business Intelligence information system. The process includes the
development of data marts and reports (Dash Boards) and their integration into
the corporate enterprise information storage (DWH - Data Warehouse), taking
into consideration business process reengineering. The process also includes
setting up corporate data marts, reports, drawing up a calculation methodology
and visualizing a system of indicators, checking data quality, and launching
the calculation of key performance indicators. On average, the implementation
process takes about eight months, taking into account the involvement of a team
of experienced developers: a BI specialist, system analysts responsible for
collecting business user requirements for graphical visualization, developing a
system of strategic performance indicators, setting up reports in accordance
with the business performance indicators model.
Fig.5.
Process of business intelligence application adjustment.
The first step in adjustment and adapting of
a software product is to collect functional and business requirements for the
designed system. It is performed by an analyst and business users of the
application. The analyst develops the methodology for creating a system of
visual models of enterprise performance indicators according to established
calculation methods. Corporate data which contains the planned and actual
values of performance indicators is used to create visual models.
Information from external systems, i.e. ERP, CRM and MES [17] is also
incorporated. A Business Intelligence system, therefore, builds and streamlines
the corporate data warehouse structure, providing access for external business
users to the system of visual models of company’s performance indicators. Thus,
the company, according to the developed business process, gets an effective
tool for creating corporate reporting system, which will contain all the
strategic KPIs, their dynamics in various details. The result is a complex
system, by analyzing which you can construct an enterprise development strategy
based on the created model of key performance indicators, by creating a visual
library of indicators for making weighted and approved strategic decisions.
The process of implementation of Business
Intelligence information systems depends substantially on the size of the
corporate data warehouse, the experience of the project team, including
developers and analysts. The economic effect of this class of systems implementation
for the medium-sized businesses is reasonably assessed on the basis of integral
financial indicators (NPV - Net Present Value, IRR - Internal Rate of Return,
DPB - Discounted Payback Period) used in the practice of evaluating efficiency
project and investment activities analysis. Figure 6 shows a visual model of a project
schedule for implementation of the Tableau information system (describing the
application installation and development process), prepared using the Project
Expert analytical system. A set of activities displays the stages of formation
of the enterprise business model.
Fig.
6. Project schedule in the form of a Gantt
line chart [2,3] of the project for the implementation of the Business Intelligence
information system.
Figure 7 shows the payback period for the implementation
project of a Business Intelligence information system.
Fig.
7. Schedule of recoupment (dependence of the net present value in rubles during
the implementation time) of the project.
The financial model of the implementation
project assumes a return on investment over a period of approximately two years
at a set discount rate of 15% per annum and an average inflation rate of 7% per
annum. By the end of the three-year project implementation period, the value of
the net present value (NPV) reaches 8 million rubles. According with
implementation of information systems, a deferred effect is usually associated
with the necessity of users training, the generation of operational
documentation, and the commissioning of the system. At the same time,
additional costs at the stage of implementation of software product are related
to the necessity of attraction of qualified IT specialists in the field of data
mining. The positive effect from implementation of Business Intelligence
technology based on key performance indicators is associated with increase in
sales, quality of the provided services and management.
In up-to-date conditions of high-tech
business, creating a successful business-model of enterprise management gives a
competitive advantage on the market, which is especially important in developing
companies. According to Russian and Western analytical agencies [10,12,15], the
technology of key performance indicators for performance evaluation [11] is the
most developed and adopted for the conditions of a changing and growing
business. In figure 8 presented a visual model of the influence of the system
of key performance indicators (KPI) characteristics on creation of a business
model of a successful company [13, 14].
Fig.
8. KPI system and factors for improving business processes in an organization.
In case of a high-tech growing business,
application of visual models of key performance indicators using Business
Intelligence (BI) tools based on storage, integration, analysis and visual
presentation of data [6] is one of the most widely used tools for making managerial
decisions [7 ].
The most frequently used techniques of data
visualization in modern BI solutions are information panels [6], in which the analyzed
indicators are displayed in the form of scales and scores, which allow to
monitor the currently achieved values, compare them with threshold values
and, thus, identify potential risks which allows to adjust managerial
decisions.
Control panels based on the analysis of key
performance indicators [8,9] are designed to compare the current values
of the indicators with those established at the preliminary
planning stage and display the dynamics of their change over time [1,3].
The visual model [1] of the organization’s
balanced scorecard indicators system in the telecommunications industry,
developed during the implementation of the Business Intelligence Table
information system, in case of a mobile operator is presented in Figure 9.
Fig. 9. Visual model of key performance indicators
system aimed at creation of company’s business model in telecommunication
industry.
Using the visual
model presented in Figure 9, a control panel is created, and a business model
is built, aimed at optimizing the business processes of an enterprise in the
high-tech business [14, 15].
Data visualization technology enables to
use special Data Warehouses, reflecting the current, real and complete
information for visual business analysis. Information in the repository,
including historical data, is collected from various operational
(transactional) systems and is structured in a specific way for more efficient
analysis and processing of requests, in the same time to solve narrower,
specific tasks, sub-sets of data could be separated from the general repository
in the so-called data marts. The scheme of visualization of enterprise efficiency
key indicators based on the business intelligence tools, reflecting the
processes of adjustment and adapting instrumental software systems, setting up
and aggregating data as shown in Figure 10.
The dynamics of changes in the selected
performance indicators can be carried out both in retrospect and taking into consideration
future forecasted values [3, 14], herewith the step or interval of information
displaying may be adjusted by the user.
According to the proposed model and the
specificity of high-tech business, in this paper, the dynamics of key
performance indicators (KPI) changes [7] taking into consideration an
established step (one calendar week) are considered.
Fig.
10. Visual model of the process of strategic performance efficiency indicators forming
[9, 11] based on Business Intelligence tools.
Based on the constructed visual model of
key performance indicators, let us perform their visualization using Business
Intelligence visual analytics tools.
The KPIA strategic revenue
indicator reflects the weekly revenue changes in detail, both for individual
macro-regions or regions, and for the whole Russia. Figure 11 presents a visual
model reflecting the dynamics of changes in this indicator. The visual model is
presented in the format of the heat map diagram of the Russian Federation,
which reflects the intensity of revenue receipt with gradations of color, from yellow,
corresponding to a decrease in the amount of funds received from the previous
period of time to dark green, which is an indicator of increase in the revenue
level. The colors on the heat map reflect changes in performance indicators in
comparison with a previous period of time, for example, a week.
Fig.
11. Visual model of the dynamic changes in the “revenue” (a combined heat map
model and a “bar graph”).
Combining various types of diagrams, it is
possible to perform representative visualization of large information arrays with
reference to the selected region, analyzing and monitoring changes in the
selected performance indicator. In the lower bar charts of figure 11 dynamics
of changes in the whole Russia are shown.
Figure 12 presentes an example of a visual
model of the indicator “revenue” in the format of a heat map for a selected
region - Yekaterinburg. As it could be inspected from Figure 12, for this
geographical region, in the weekly presentation, the revenue indicator fell by
5.9%. Manipulating information using the implemented visual model can be done according
with various sectional drawings, combining the search for the necessary
information with the process of making managerial decisions.
Fig.
12. Visual model of changes in revenue in the selected region of localization
in the form of the heat map.
A visual model of the strategic KPIB
performance indicator - the formation of the client base - is presented in
Figure 13.
Fig.
13. The visual model of changes in the indicator of the client base formation in
the regional representation.
In figure 13 the structure of sales of the
main price plans is also shown [13, 14], directly reflecting the structure of
the product line. Names of price plans have typical names according with the
confidentiality agreement. In figure 13, the following designations were
adopted to describe indicators affecting the managerial decision-making process
to achieve the required level of a strategic indicator: Gross intake - the
number of new subscribers connected over a set period without adjustment to
subscribers who refused the service, Net intake - the number of new subscribers
connected during the set period, adjusted for subscriber churn, Churn - the
number of subscribers who refused the service, Average conversion per salon -
the number of customers who connected at the point of sale, Average traffic to
the salon - the number of customers who came into the communication salon,
Disconnect - the number of customers disconnected from communication services,
or with a blocked account status, Reconnect - the number of customers who
renewed use of communication services and a positive balance on the account.
As it is shown in figure 13, directly next
to the corresponding numerical value of the indicator, a colored geometric
figure, circle, is located, as a result of comparison with the corresponding
value, which was obtained in an earlier period of time, the circle is indicated
by an appropriate color. The chromaticity gradations are set from dark green,
light green, lime green, yellow, light yellow, orange and bright red, indicating,
respectively, positive, neutral and negative results of comparison with the
previous period of time. At the same time, the more intense the color of the
corresponding geometric figure, the more significant will be the managerial
decisions that in necessity must be taken based on the results of monitoring
this indicator.
Figure 14 represents visual model of the price
plans dynamics of sales in absolute terms (by selected categories), reflecting
the number of contracts concluded in a selected period of time.
The visual model reflects the structure of
sales of price plans, which allows to make a conclusion about the seasonality
of the indicator, because due to the pricing policy, sales segmentation and
customer acquisition, for example in New Year period, for the last week of 2017
the maximum number of contracts was concluded.
Fig.
14. Visual model of sales dynamics by price plans categories.
A visual model of a strategic KPIC
- customer baseline quality indicator - is presented in Figure 15. At the same
time on this figure 15 presented a heat map by the region and a bar graph for
detailed analytics by time periods (weeks) with the indicator as the line which
is drawn over for comparison with the previous period (in the year scale) indicator
value during the time interval which was the predecessor for chosen one.
The set of quality indicators of the customer
base includes:
•
Flash Base - current subscriber base,
•
3G / 4G Enabled - the share of devices with
support for 3G / 4G standards,
•
ADU (Active Data Users) - the proportion of
users with active consumption of data traffic,
•
3G / 4G ADU - share of active data traffic users
using 3G / 4G standard as a connection source,
•
not USIM c 4G - the share of subscribers whose
first SIM card is not operator’s, but supports standard 4G connections,
•
Auto Pay share - the share of users with the
service of automatic payment,
•
Subs Fee share - the share of users with the
promised payment service,
•
Talking subs share - the share of
"talking" subscribers who make at least one voice call once within 9
days.
Fig. 15. Visual model of quality indicators of the customer base.
Data presented in Figure 15, as well as the
comparison with the previous period - year (indicated as a percentage in the
upper left of the chart), shows to business users the general growth trend of
the subscriber base and enables to make strategic decisions, implementing a
customer segmentation system based on the category of subscribers B2B or B2C.
Visual model of a group of indicators
responsible for analyzing devices and the proportion of primary purchased SIM
cards by subscribers enables to make decisions about future trends in data
traffic usage and sales promotion taking into consideration traffic packets for
users of mobile devices with multiple SIM cards. A visual representation of the
indicator of “talking” subscribers enables to assess general trends in the
consumption of voice traffic and timely identify problems of base stations and
coverage areas affecting on the quality of communication.
Visual model of the strategic indicator
KPID - customer satisfaction with the functioning of mobile operator
for the various types of service provision - is presented in Figure 16.
One of the generally accepted indicators
of customer satisfaction with the services provided is the NPS (net promoter
score) index of consumer loyalty, which enables to determine adherence to a
product or company by means of surveys of subscribers. As it could be seen from
figure 16, the consumer loyalty index is at a high level, which is marked with
a green color indicator in the circle shape.
Data presented in Figure 16 reflects the
dynamics of points of contact with service users, which enable to take into consideration
the degree of customer satisfaction with selected quality criteria, such as
corporate customer confidence, voice and SMS activity analysis, mobile Internet
use, call center operation, and the operator’s retail network.
Fig.
16. Visual model of customer satisfaction indicators for a mobile operator.
Visual analysis of customer service
indicators enables to make decisions about operating with contact appeals of
subscribers, with indicator of subscriber engagement and with shares of
solutions to problems of subscribers for the first calls to the call center.
The bottom graph in figure 16 represents
the overall dynamics of the quality assessment of services provided to
operators according to weekly data. The decrease in the NPS indicator of the plan
fulfillment dynamics is due to the lack of subscriber polling during certain
periods of low activity.
Visual model of the strategic indicator KPIE
- an assessment of the sales of branded equipment (mobile phones) of the
operator - is presented in Figure 17, data on real model names are replaced by
patterns due to the confidentiality agreement.
Visual analysis of equipment sales enables
to predict the success factors of a particular equipment model on the market
and estimate the share in the overall sales structure, since the most
non-functional phone models are used only to activate SIM cards (model 6 in Figure
17) or initialize specialized equipment.
Visual model of indicator make possible to
display not only a share in the volume of sales, but also a share in the
revenue of a particular phone model.
Visual analysis of sales revenue in Figure
17 allow to make decisions regarding the implementation of a marketing policy
aimed at identifying and maintaining a stable level of sales of the most
promising mobile phone models. For the market of budget telephones, model 4 is
the most promising from the point of sales support view, and for the market of
a higher price range, model 2 is the most promising.
Fig.
17. Visual model of sales rate of mobile operator branded equipment
(mobile phones).
Visual models of key performance indicators
of a high-tech telecommunication enterprise, presented in the article, make it
possible to structure the organization activities, taking into account the
factors of increasing competitiveness, operating stability, setting up a
business model, optimizing operational and strategic business processes.
Visual models of key performance indicators
of a high-tech telecommunication enterprise, presented in the article, make it
possible to structure the organization activities taking into consideration the
factors of increased competitiveness, operating stability, business model
adjustments, optimizing operational and strategic business processes.
A set of visual models developed by the
authors make it possible to use visual analytics tools for making managerial
decisions in the sphere of strategic and operational planning and also for the
management of marketing activities of the company's based on monitoring and
display of the dynamics of changes in a selected set of indicators during a
specified period of time. The proposed approach to visualization is illustrated
by examples from the operation activity of a high-tech mobile operator company
in telecommunication industry.
Creation of visual models of key
performance indicators of company efficiency assessment is implemented using
Business Intelligence tools based on the storages and data marts formation by
collecting large information arrays. The formation and implementation of the
Business Intelligence system enables to use functional information tools and
create powerful techniques for visual analytics of heterogeneous information,
taking into consideration performance management technology.
The approach proposed by the authors for
the purposes of enterprise business model creation utilizes the methods of
visual analytics in order to make approved decisions both at the stage of
business planning and also at the stage of operational planning and management
of the organization's activities in the field of high technologies in a
competitive environment and integrated business processes.
By implementing BI technology for creation
of corporate reporting it is possible to get benefits in the form of a
comprehensive solution that will provide access to financial statements for
multiple business users. Developed BI system improves the effectiveness of
managerial decisions in accordance with the developed key performance
indicators strategic model of the organization.
The proposed system of visual models could
be adapted to almost any research domain. Portability of the formulated
solutions is to make it possible to develop models of key indicators related to
the necessity of the enterprise, adjust mechanisms for visualizing performance
indicators, data integration in the corporate storage of the organization and
flexible application settings, and a comprehensive system of reports formation.
By the author's opinion, the main task in the construction of hybrid data
visualization systems based on Business Intelligence systems is to develop a detailed
and approved methodology for developing a system of performance indicators
based on the retrospective of the organization’s functioning, operational and
financial experience of the company. The effect associated with implementation
of the visual models system is associated with a reduction in decision-making
time to promote the company's products or services to the market in modern economy
conditions, which is in turn allows the company to increase its
competitiveness, by improving product quality and shortening the marketing life
cycle of a product.
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