Dengelenmiş performansın Bayes ağları ile modellenmesi: Finans sektöründe bir uygulama
Modeling of the balanced scorecard with the Bayesiannetwork approach: A case study in finance sector
Yazar: MERVE AGARAK
Danışman: PROF. DR. SEÇKİN POLAT
İstanbul Teknik Üniversitesi / Fen Bilimleri Enstitüsü / Endüstri Mühendisliği Ana Bilim Dalı / Mühendislik Yönetimi Bilim Dalı
Derece: Yüksek Lisans, 2019
Konu: Endüstri ve Endüstri Mühendisliği = Industrial and Industrial Engineering

Özet:
1992 yılında Robert Kaplan ve David Norton tarafından ortaya koyulan Dengelenmiş
Performans, organizasyonların gelecek odaklı performanslarını ölçmeye yarayan bir
yöntem olarak karşımıza çıkmaktadır. Performansın ölçülmesine yeni bir bakış açısı
getirilerek yalnızca finansal verilerden yararlanmak yerinde, finansal olmayan
boyutlarda araştırılmış ve bunların performansa olan etkileri ortaya koyulmuştur.
Ayrıca uzun ve kısa dönemde planlama yapılabilmesine yarayan bu yöntem, daha
sonraları geliştirilerek organizasyonların strateji haritalarını belirlemek için büyük
ölçüde kullanılmaya başlanmıştır.
Yalnızca finans odaklı olan strateji haritaları ve performans göstergeleriyle, şirketler
rekabetin yüksek olduğu günümüz dünyasında üstünlük elde edemeyeceklerini
görmüşlerdir. Böylelikle Dengelenmiş Performansın kullanımı önemli ölçüde artış
göstermiştir.
Literatür incelendiğinde Dengelenmiş Performansın farklı sektörlerde, farklı
yöntemlerle pek çok araştırmada farklı konuda yer edindiği görülmüştür. Araştırma
yöntemi olarak çoğunlukla vaka analizi çalışmaları yapılmış olup, deneysel
yöntemlerin yanı sıra anket kullanımları ve analitik metotların kullanıldığı
görülmüştür. Bunların yanı sıra niteliksel ve nicel araştırmalarla birlikte kullanıldığı
da olmuştur. Ancak Dengelenmiş Performansın bir karar verme yöntemi olarak Bayes
Ağları ile kullanıldığı bir çalışmaya rastlanılmamıştır. Bu kapsamda uzmanlardan
faydalanılarak elde edilen mevcut verilerin gerçekleşme olasılığına dayalı gelecek
durum tahminlerinde önemli seviyede yer edinen Bayes Ağları, Dengelenmiş
Performansın modellenmesinde kullanılabilir mi sorusundan yola çıkılarak bu tez
çalışması hazırlanmıştır. Dengelenmiş Performansın amaçları doğrultusunda, ana
performans göstergeleri belirlenmiş ve bunlar arasında ilişkiler kurulmuştur.
Oluşturulan model üzerinden belirlenen ilişkilere yönelik uzman görüşleri ile
modeldeki olasılık dağılımları belirlenerek geleceğe yönelik tahminlerde
bulunabilmek için Bayes Ağları, bu çalışma kapsamında Dengelenmiş Performansın
modellenmesinde kullanılmıştır.
Yapılan bu tez çalışmasının amacı; Türkiye'de finans sektöründe faaliyet gösteren bir
bankanın İş Süreçleri Departmanında, Dengelenmiş Performans faktörleri ve bunlar
arasındaki ilişkilerin tespiti sonucunda geleceğe yönelik strateji senaryolarının
oluşturulmasıdır. Bu doğrultuda ilgili banka, performansının Dengelenmiş Performans
boyutları dahilinde çeşitli senaryolarda nasıl iyileştirmeler yapılması gerektiği
konusunda fikir sahibi olabilecektir. İyileştirmelerin yanısıra, banka da
gerçekleşebilecek belli kötü senaryolar doğrultusunda sonuçların ne olabileceği
hakkında da bilgi sahibi olunabilecek ve bu durumlar gerçekleşmeden çeşitli önlemler
alınabilecektir.

xviii

Bu tez kapsamında öncelikle literatür araştırması yapılarak Dengelenmiş Performansın
dört ana perspektifinde bulunan göstergelerin finans sektöründe nasıl kullanıldığı
incelenmiştir. Sonrasında bunlar arasından modelde kullanılacak olan alt faktörler
belirlenmiştir. Belirlenen bu alt faktörler arasındaki ilişkilerin oluştrulabilmesi için
Dengelenmiş Performans boyutları arasındaki genel hiyerarşi doğrultusunda, uzman
görüşlerine başvurulmuştur. Aynı şekilde ilişkiler kurulduktan sonra, koşullu
olasılıkların belirlenebilmesi için uzmanlardan destek alınmıştır.
Bayes Ağları ölçümlemesinde literatürde en çok karşılaşılan Netica adlı yazılım
programı, modelin derlenmesi ve analizlerinin yapılmasında kullanılmıştır.
Oluşturulan model kapsamında yedi farklı senaryo geliştirilmiştir. Bunlar
Dengelenmiş Performansın finansal olmayan üç ana boyutundaki en iyi ve en kötü
durum analizleriyle birlikte finansal boyutun en iyi durumunu içermektedir.
Geliştirilen senaryolar ardından üç farklı duyarlılık analizi yapılarak modelin
geçerliliği ölçülmüştür.
Sonuç olarak literatürden faydalanılarak oluşturulmuş kavramsal modelde,
Dengelenmiş Performansın boyutları arasındaki hiyerarşi, model kapsamında
oluşturulan senaryolarda da varlığını korumuştur. Bu hiyerarşiye paralel olacak
şekilde elde edilen sonuçlarda çelişkiler ya da tutarsızlıklar meydana gelmemiştir.
Beklenenin aksi yönde gelişen bir durum ile karşılaşılmamıştır.
Son olarak, elde edilen sonuçlara ve modelin geliştirilmesi adına ileride üzerinde
durulabilecek noktalara, sonuçlar ve öneriler bölümünde yer verilmiştir.

Abstract:
In 1992 Robert Kaplan and David Norton was introduced the Balanced Scorecard
(BSC) as a method for measuring the future-oriented performance of organizations.
Their study's purpose was to put forward intangible assests roles in the overall
performance. It was the new perspective for the performance measurement. Because,
not only the financial but also the non-financial assets were evaluated to find the effects
of the overall performance. Since its presentation in the mid 1990s, it has evolved from
the performance measurement system to the strategic management tool. In addition,
this methodology can be used for long-term and short-term planning, and also can help
the organizations to determine their strategy maps.
The infrastructure for the strategic management decisions or activities can be created
by the Balanced Scorecard. BSC can help the managers to understand various
interrelationships and also cause-and-effect relationship.
The BSC has a sequence of four perspectives. These can reflect the organizations value
creation activities. The sequence is as follows: learning and growth perspective,
internal or business process perspective, customer perspective, and financial
perspective. Core outcome or overall performance measures within each perspective
are adopted as leading indicators of the core outcome measures in the next perspective.
The four perspectives of the BSC can be describe like below:
• Learning and growth perspective: In order to adapt to changing world and
administrate the business, it deals with the organizational compliance,
employee skills and information systems. The success of the process depends
on the right and timely knowledge as well as the talented and motivated
employee.
• Internal or business process perspective: This perspective accepts the employee
capacity as an important factor in the development of the internal process. It
focuses on the intangible assets of an organization, especially on the internal
skills and capabilities that are required to support the value-creating internal
processes.
• Customer perspective: In order to satisfy customers, this perspectives defines
the value creation that organization can apply. Thus it can generate more sales
to the most desired customer groups. The value proposition is important in this
perspective and it can be centered on one of the three: operational excellence,
customer intimacy.
• Financial perspective: This perspective can be costs, cash flow, revenue
growth, profit margins, net operating income, etc. Therefore it examines if the
company's implementation and execution of its strategy are contributing to the bottom-line improvement of the company. It represents the long-term strategic
objectives of the organization and thus it incorporates the tangible outcomes of
the strategy in traditional financial terms.
When considiring the benefits of Balanced Scorecard, it is found that it has been
widely used and adopted easily almost every industries around the world. Since the
rising popularity, it is also getting take a place in the academic research more and more.
While reviewing the literature, it's seen that the Balanced Scrorecard has used with
different research methods in different sectors. Besides the experimental methods such
as AHP, SEM; mostly case studies have been conducted with survey and analytical
methods. Because of the fact that various BSC research topics for articles have been
published. Also it has been used in conjunction with qualitative and quantitative
research. However, there is no study discovered in which Balanced Scorecard is used
with the Bayesian Networks as a decision making method.
Therefore this thesis study was prepared based on the question of whether Bayesian
Networks which depends on experts probabilistic ideas to forecast future situation,
could be used in modeling of Balanced Scorecard. For the purposes of Balanced
Scorecard, key performance indicators were identified and relations were established
among them. Bayesian Networks were used in the modeling of Balanced Scorecard in
order to be able to make predictions for the future by determining the probability
distributions with expert opinions about the relationships of key performance
indicators over the model.
A Bayesian network is a representation of a joint probability distribution of a set of
random variables with a possible mutual causal relationship. The network consists of
nodes representing the random variables, edges between pairs of nodes representing
the causal relationship of these nodes, and a conditional probability distribution in each
of the nodes. The fundamental goal of the technique is to demonstrate the back
contingent likelihood conveyance of result (frequently causal) variable(s) subsequent
to watching new proof. Bayesian systems perhaps developed either physically with
learning of the hidden area, or consequently from a huge dataset by suitable software
program.
The purpose of the study is; defining the Balanced Scorecard key performance
indicators and their cause-effect relationships and than at the Bussiness Solutions
Department of a bank in Turkey. After defining these relationship, estimating the
several future oriented strategy scenarios. In this respect, the related bank will be able
to have ideas on how to improve their performance with the Balances Scorecard four
perspectives. In addition to the improvements, the bank will be able to forecast the
results of certain bad scenarios and than it will be able to take precautions before these
situations occur.
First of all, conceptual model has developed according to the literature. Within the
scope of this conceptual model, literature is reviewed again in order to find the usage
of Balanced Scorecard key performance indicators in finance sector. Also Bayesian
Network structure have researched. Its usage areas and advantages have identified in
details. Then application steps of Bayesian Network have emphasised.
The usage of Balanced Scorecard four main perspectives key performance indicators
are defined in finance sector. Firstly, customer satisfaction, customer turnover rate,
training and development program are specified as a learning and growth perspective
sub-factors. Secondly, service and product innovation, investment of technology, regulations and supervisions, after-sales and operational services are specified as a
business process perspective sub-factors. Thirdly, customer acquisition, customer
retention and attention rate, and market share rate are specified as a customer
perspective sub-factors. Last but not least, sales, incomes and growth are specified as
a finance perspective sub-factors. Therefore, the sub-factors (main perspective's key
performans indicators) are determined around the overall finance key performance
indicators.
After that, survey has conducted to the experts in order to establish the relationships
between these sub-factors in the direction of Balanced Scorecard main perspective
allignment. Norton and Kaplan (2005) was reported in their article the relations of
these four perspectives as one-way in measuring the strategy map of organizations.
After the relations and their directions are established, the final model has developed.
Than the expert opinions have collected once again in order to determine conditional
probabilities of sub-factors of each perspective.
Netica software program, which is the most commonly encountered in the literature,
have been used to compile and analyze the model. Netica is a complete, easy-to-use,
and powerful program for working with belief networks and influence diagrams. It is
very suitable for easy exploring, and for teaching belief network and influence diagram
concepts.
Under the scope of the network diagram that designed from Netica, seven different
scenarios have been developed. These scenarios include the best and worst-case
analysis of the three non-financial perspectives of the Balanced Scorecard. In addition
the best case of the financial perspective has been developed.
After the scenario analysis have run in the model, three different sensitivity analysis
have conducted. Also the model validity has measured by doing sensitivity analysis.
As a result, in the conceptual model which is formed by using the literature, it is found
that the hierarchy between the dimensions of the Balanced Scorecard has also existed
in the scenarios created within the scope of the model. No contradictions or
inconsistencies have occurred. Moreover the results have obtained in parallel with the
literature. It is seen that there is no situation was encountered in the opposite direction.
Modeling of the Balanced Scorecard with Bayesian Networks is a new point of view
for literature, so that there is no specific source about it. Also there is lack of
information how to model overall performance with these methods together. For this
reason, various difficulties have been encountered. In order to prevent all of those
difficulties, some limitations and restrictions have been imposed. One of them is
choosing the Bussiness Solutions Departmant of the bank for the performance
measurement and limited the experts only this departmant.
Finally, the obtained results and the points that can be discussed in the future in terms
of developing the model, have given in the section of results and recommendations.
For instance, in the relevant department of the bank, it is deduced that if the worst
performance case in the customer perspective occurs, the sales rates and revenues will
be lower by 78%, and the growth in the sector will be be lower by 83%. Based on this,
it can be said that sales rates and revenues will fall by 45%. At the same time, it is
observed that the performance of the growth in the sector could be reduced by 35%.
In order to optimize the Bank's financial performance, it is necessary to gain 20% more
of the new customer acquisition. Also, it is observed that the importance given to
customer retention policies should be 15% higher. It has been observed that the financial performance of Balanced Scorecard in the relevant department of the Bank
is maximized when the new customer acquisition is 90% higher and customer retention
rates are 83% higher in customer perspective. Likewise, being market or product leader
should be high at 75% to maximize the financial performance.
Furthermore according to the results of those analysis, implications and contributions
aspects of this study for that domain were indicated.