Business intelligence viewpoint on managerial decision-making : Ill-structured problems and decision support systems

Vaikka liiketoimintatiedon hallintaa sekä johdon päätöksentekoa on tutkittu laajasti, näiden kahden käsitteen yhteisvaikutuksesta on olemassa hyvin rajallinen määrä tutkimustietoa. Tulevaisuudessa aiheen tärkeys korostuu, sillä olemassa olevan datan määrä kasvaa jatkuvasti. Yritykset tarvitsevat jatkossa yhä enemmän kyvykkyyksiä sekä resursseja, jotta sekä strukturoitua että strukturoimatonta tietoa voidaan hyödyntää lähteestä riippumatta. Nykyiset Business Intelligence -ratkaisut mahdollistavat tehokkaan liiketoimintatiedon hallinnan osana johdon päätöksentekoa. Aiemman kirjallisuuden pohjalta, tutkimuksen empiirinen osuus tunnistaa liiketoimintatiedon hyödyntämiseen liittyviä tekijöitä, jotka joko tukevat tai rajoittavat johdon päätöksentekoprosessia. Tutkimuksen teoreettinen osuus johdattaa lukijan tutkimusaiheeseen kirjallisuuskatsauksen avulla. Keskeisimmät tutkimukseen liittyvät käsitteet, kuten Business Intelligence ja johdon päätöksenteko, esitetään relevantin kirjallisuuden avulla – tämän lisäksi myös dataan liittyvät käsitteet analysoidaan tarkasti. Tutkimuksen empiirinen osuus rakentuu tutkimusteorian pohjalta. Tutkimuksen empiirisessä osuudessa paneudutaan tutkimusteemoihin käytännön esimerkein: kolmen tapaustutkimuksen avulla tutkitaan sekä kuvataan toisistaan irrallisia tapauksia. Jokainen tapaus kuvataan sekä analysoidaan teoriaan perustuvien väitteiden avulla – nämä väitteet ovat perusedellytyksiä menestyksekkäälle liiketoimintatiedon hyödyntämiseen perustuvalle päätöksenteolle. Tapaustutkimusten avulla alkuperäistä tutkimusongelmaa voidaan analysoida tarkasti huomioiden jo olemassa oleva tutkimustieto. Analyysin tulosten avulla myös yksittäisiä rajoitteita sekä mahdollistavia tekijöitä voidaan analysoida. Tulokset osoittavat, että rajoitteilla on vahvasti negatiivinen vaikutus päätöksentekoprosessin onnistumiseen. Toisaalta yritysjohto on tietoinen liiketoimintatiedon hallintaan liittyvistä positiivisista seurauksista, vaikka kaikkia mahdollisuuksia ei olisikaan hyödynnetty. Tutkimuksen merkittävin tulos esittelee viitekehyksen, jonka puitteissa johdon päätöksentekoprosesseja voidaan arvioida sekä analysoida. Despite the fact that the literature on Business Intelligence and managerial decision-making is extensive, relatively little effort has been made to research the relationship between them. This particular field of study has become important since the amount of data in the world is growing every second. Companies require capabilities and resources in order to utilize structured data and unstructured data from internal and external data sources. However, the present Business Intelligence technologies enable managers to utilize data effectively in decision-making. Based on the prior literature, the empirical part of the thesis identifies the enablers and constraints in computer-aided managerial decision-making process. In this thesis, the theoretical part provides a preliminary understanding about the research area through a literature review. The key concepts such as Business Intelligence and managerial decision-making are explored by reviewing the relevant literature. Additionally, different data sources as well as data forms are analyzed in further detail. All key concepts are taken into account when the empirical part is carried out. The empirical part obtains an understanding of the real world situation when it comes to the themes that were covered in the theoretical part. Three selected case companies are analyzed through those statements, which are considered as critical prerequisites for successful computer-aided managerial decision-making. The case study analysis, which is a part of the empirical part, enables the researcher to examine the relationship between Business Intelligence and managerial decision-making. Based on the findings of the case study analysis, the researcher identifies the enablers and constraints through the case study interviews. The findings indicate that the constraints have a highly negative influence on the decision-making process. In addition, the managers are aware of the positive implications that Business Intelligence has for decision-making, but all possibilities are not yet utilized. As a main result of this study, a data-driven framework for managerial decision-making is introduced. This framework can be used when the managerial decision-making processes are evaluated and analyzed.

A decision support system for selective cleaning

[Abstract]

Ensuring the efficient utilization of Business Intelligence

In recent years, chief information officers (CIOs) around the world have identified Business Intelligence (BI) as their top priority and as the best way to enhance their enterprises competitiveness. Yet, many enterprises are struggling to realize the business value that BI promises. This discrepancy causes important questions, for example: what are the critical success factors of Business Intelligence and, more importantly, how it can be ensured that a Business Intelligence program enhances enterprises competitiveness. The main objective of the study is to find out how it can be ensured that a BI program meets its goals in providing competitive advantage to an enterprise. The objective is approached with a literature review and a qualitative case study. For the literature review the main objective populates three research questions (RQs); RQ1: What is Business Intelligence and why is it important for modern enterprises? RQ2: What are the critical success factors of Business Intelligence programs? RQ3: How it can be ensured that CSFs are met? The qualitative case study covers the BI program of a Finnish global manufacturer company. The research questions for the case study are as follows; RQ4: What is the current state of the case company’s BI program and what are the key areas for improvement? RQ5: In what ways the case company’s Business Intelligence program could be improved? The case company’s BI program is researched using the following methods; action research, semi-structured interviews, maturity assessment and benchmarking. The literature review shows that Business Intelligence is a technology-based information process that contains a series of systematic activities, which are driven by the specific information needs of decision-makers. The objective of BI is to provide accurate, timely, fact-based information, which enables taking actions that lead to achieving competitive advantage. There are many reasons for the importance of Business Intelligence, two of the most important being; 1) It helps to bridge the gap between an enterprise’s current and its desired performance, and 2) It helps enterprises to be in alignment with key performance indicators meaning it helps an enterprise to align towards its key objectives. The literature review also shows that there are known critical success factors (CSFs) for Business Intelligence programs which have to be met if the above mentioned value is wanted to be achieved, for example; committed management support and sponsorship, business-driven development approach and sustainable data quality. The literature review shows that the most common challenges are related to these CSFs and, more importantly, that overcoming these challenges requires a more comprehensive form of BI, called Enterprise Performance Management (EPM). EPM links measurement to strategy by focusing on what is measured and why. The case study shows that many of the challenges faced in the case company’s BI program are related to the above-mentioned CSFs. The main challenges are; lack of support and sponsorship from business, lack of visibility to overall business performance, lack of rigid BI development process, lack of clear purpose for the BI program and poor data quality. To overcome these challenges the case company should define and design an enterprise metrics framework, make sure that BI development requirements are gathered and prioritized by business, focus on data quality and ownership, and finally define clear goals for the BI program and then support and sponsor these goals.

Business intelligence and management control

The purpose of this study is to explore the possibilities of utilizing business intelligence (BI)systems in management control (MC). The topic of this study is explored trough four researchquestions. Firstly, what kind of management control systems (MCS) use or could use the data and information enabled by the BI system? Secondly, how the BI system is or could be utilized? Thirdly, has BI system enabled new forms of control or changed old ones? The fourth and final research question is whether the BI system supports some forms of control that the literature has not thought of, or is the BI system not used for some forms of control the literature suggests it should be used? The study is conducted as an extensive case study. Three different organizations were interviewed for the study. For the theoretical basis of the study, central theories in the field of management control are introduced. The term business intelligence is discussed in detail and the mechanisms for governance of business intelligence are presented. A literature analysis of the uses of BI for management control is introduced. The theoretical part of the study ends in the construction of a framework for business intelligence in management control. In the empirical part of the study the case organizations, their BI systems, and the ways they utilize these systems for management control are presented. The main findings of the study are that BI systems can be utilized in the fields suggested in the literature, namely in planning, cybernetic, reward, boundary, and interactive control. The systems are used both as the data or information feeders and directly as the tools. Using BI systems has also enabled entirely new forms of control in the studied organizations, most significantly in the area of interactive control. They have also changed the old control systems by making the information more readily available to the whole organization. No evidence of the BI systems being used for forms of control that the literature had not suggested was found. The systems were mostly used for cybernetic control and interactive control, whereas the support for other types of control was not as prevalent. The main contribution of the study to the existing literature is the insight provided into how BI systems, both theoretically and empirically, are used for management control. The framework for business intelligence in management control presented in the study can also be utilized in further studies about the subject.

On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

Business Intelligence: Microsoft Power BI

Työn tavoitteena on tutkia Business Intelligencen ja BI-työkalujen vaatimusten kehittymistä viime vuosien aikana ja tutkia miten Microsoft Power BI -ohjelmisto vastaa modernin päätöksenteon tarpeisiin. Työ on toteutettu suurimmalta osin kirjallisuuskatsauksena, minkä lisäksi Microsoft Power BI:n toiminnallisuutta on tutkittu käytännössä käyttäen ohjelmiston ilmaisversiota. Tutkimuksessa on havaittu, että tiedon lähteiden määrän ja datan monimuotoisuuden kasvaessa on syntynyt tarve uusille, tehokkaille BI-järjestelmäratkaisuille, jotka hyödyntävät uudenlaisia menetelmiä. Modernissa BI 2.0 -mallissa korostuvat kehittyneemmän verkkoinfrastruktuurin ja ohjelmistotekniikan täysi hyödyntäminen, käytön helppous, tiedon tuottaminen ja jakaminen massoille, tiedon rikastamisen mahdollistaminen ja visualisoinnin ja interaktiivisuuden keskeinen asema tiedon tulkinnassa. Tutkimuksen perusteella Microsoft Power BI vaikuttaisi täyttävän keskeneräisyydestään ja muutamista tiedonhallinnallisista puutteistaan huolimatta lähes kaikki toimivan BI 2.0 -järjestelmän määritelmistä. Ohjelmisto tarjoaa riittävät analyyttiset ja esitystekniset työkalut useimpien tyypillisten käyttäjien tarpeisiin, minkä lisäksi paranneltu Location Intelligence -ratkaisu sekä uudet Q&A ja nopea oivallus -toiminnot luovat mielenkiintoisen tavan selata dataa. Jää nähtäväksi, miten ratkaisu kehittyy vielä tulevaisuudessa.

Business Intelligence -järjestelmä päätöksentekijöiden tukena asiantuntijayrityksessä

Työn tarkoituksena oli kartoittaa ja tehdä esiselvitys Business Intelligencen(BI) mahdollisuuksista tiedon hallinnassa. Tavoitteena oli selvittää, kuinka yritys voi tietotekniikan avulla paremmin hyödyntää operatiivisten järjestelmien tuottamia tietoja päätöksenteon tukena. Työssä sovellettiin konstruktiivista tutkimusotetta. Business Intelligence -teknologiaan tutustuttiin aluksi kirjallisuuden avulla. Ongelmaa lähestyttiin selvittämällä kohdeyrityksen tiedonhallinnan nykytila ja siihen liittyvät ongelmat. Käyttäjävaatimukset selvitettiin strukturoidulla kyselytutkimuksella. Lisäksi työn empiriaosuudessa tutustuttiin kahteen Business Intelligence -toteutukseen ja arvioitiin teknologian kypsyyttä suhteessa asiakasvaatimuksiin. Tiedonhallinnalta toivottiin joustavuutta ja helppokäyttöisyyttä.Erityisesti tutkimuksessa esiin nousi se, että tiedon jakeluun tarvitaan monipuolisempia vaihtoehtoja. Käyttäjät olivat valmiita hyödyntämään uusia BI-ominaisuuksia varsin laajalti. Haastavinta tutkimuksessa oli liiketoiminnan ymmärtäminen. Suurimmat BI-teknologian puutteet havaittiin loppukäyttäjän sovelluksissa. Tietovarastointiprosessiin liittyvä teknologia todettiin toimivaksi.

Technology selection and group decision support systems: Case studies on supporting strategic technology selection processes

The objective of the dissertation is to increase understanding and knowledge in the field where group decision support system (GDSS) and technology selection research overlap in the strategic sense. The purpose is to develop pragmatic, unique and competent management practices and processes for strategic technology assessment and selection from the whole company's point of view. The combination of the GDSS and technology selection is approached from the points of view of the core competence concept, the lead user -method, and different technology types. In this research the aim is to find out how the GDSS contributes to the technology selection process, what aspects should be considered when selecting technologies to be developed or acquired, and what advantages and restrictions the GDSS has in the selection processes. These research objectives are discussed on the basis of experiences and findings in real life selection meetings. The research has been mainly carried outwith constructive, case study research methods. The study contributes novel ideas to the present knowledge and prior literature on the GDSS and technology selection arena. Academic and pragmatic research has been conducted in four areas: 1) the potential benefits of the group support system with the lead user -method,where the need assessment process is positioned as information gathering for the selection of wireless technology development projects; 2) integrated technology selection and core competencies management processes both in theory and in practice; 3) potential benefits of the group decision support system in the technology selection processes of different technology types; and 4) linkages between technology selection and R&D project selection in innovative product development networks. New type of knowledge and understanding has been created on the practical utilization of the GDSS in technology selection decisions. The study demonstrates that technology selection requires close cooperation between differentdepartments, functions, and strategic business units in order to gather the best knowledge for the decision making. The GDSS is proved to be an effective way to promote communication and co-operation between the selectors. The constructs developed in this study have been tested in many industry fields, for example in information and communication, forest, telecommunication, metal, software, and miscellaneous industries, as well as in non-profit organizations. The pragmatic results in these organizations are some of the most relevant proofs that confirm the scientific contribution of the study, according to the principles of the constructive research approach.

Business Intelligence -ohjelmistot päätöksenteon tukena

Työn tavoitteena on tutkia Business Intelligence -ohjelmistojen käyttöä päätöksenteon tukena. Lisäksi tutkitaan näiden ohjelmistojen merkitystä yrityksille. Työssä tarkastellaan myös mahdollisia tulevaisuuden näkymiä. Työ on kirjallisuustyö, joka pohjautuu lähdeaineistoon. Työn tuloksena on huomattu, kuinka tärkeitä Business Intelligence -ohjelmistot ovat yritysten päätöksenteossa. Suuren tietomäärän vuoksi on tärkeää, että yrityksellä on työkalu, jonka avulla kaikki merkityksellinen tieto saadaan välitettyä päätöksentekijöille. Business Intelligence -ohjelmistot tuottavat monenlaisia analyyseja, joiden avulla voidaan tehdä onnistuneita päätöksiä. Mitä tarkempia analyyseja tehdään, sitä enemmän voidaan myös saavuttaa kilpailuetua. Business Intelligence -ohjelmistojen avulla yrityksillä on mahdollisuus saavuttaa monia erilaisia hyötyjä. Hyötyjen mittaaminen on kuitenkin haastavaa, koska osa hyödyistä on aineettomia. Hyötyjen ja liikearvon mittaamiseen on kehitetty mittareita, joiden avulla on tarkoitus pystyä perustelemaan Business Intelligence -ohjelmistoihin investointia. Tulevaisuudessa Business Intelligence -ohjelmistojen merkitys yrityksille kasvaa. Yritysten muuttuvia tarpeita varten kehitetään uudenlaisia Business Intelligence -sovelluksia. Teknologia ja ohjelmistojen innovatiivinen käyttö muokkaavat BI-ohjelmistoja tehokkaammiksi. Jatkuva uusien sovellusten kehittäminen luo myös haasteita ennen niiden laajempaa käyttöönottoa.

Business intelligence – enabling self-service: A case study in a global manufacturing company

Business intelligence (BI) is an information process that includes the activities and applications used to transform business data into valuable business information. Today’s enterprises are collecting detailed data which has increased the available business data drastically. In order to meet changing customer needs and gain competitive advantage businesses try to leverage this information. However, IT departments are struggling to meet the increased amount of reporting needs. Therefore, recent shift in the BI market has been towards empowering business users with self-service BI capabilities. The purpose of this study was to understand how self-service BI could help businesses to meet increased reporting demands. The research problem was approached with an empirical single case study. Qualitative data was gathered with a semi-structured, theme-based interview. The study found out that case company’s BI system was mostly used for group performance reporting. Ad-hoc and business user-driven information needs were mostly fulfilled with self-made tools and manual work. It was felt that necessary business information was not easily available. The concept of self-service BI was perceived to be helpful to meet such reporting needs. However, it was found out that the available data is often too complex for an average user to fully understand. The respondents felt that in order to self-service BI to work, the data has to be simplified and described in a way that it can be understood by the average business user. The results of the study suggest that BI programs struggle in meeting all the information needs of today’s businesses. The concept of self-service BI tries to resolve this problem by allowing users easy self-service access to necessary business information. However, business data is often complex and hard to understand. Self-serviced BI has to overcome this challenge before it can reach its potential benefits.

Business intelligence – enabling self-service: A case study in a global manufacturing company

Business intelligence (BI) is an information process that includes the activities and applications used to transform business data into valuable business information. Today’s enterprises are collecting detailed data which has increased the available business data drastically. In order to meet changing customer needs and gain competitive advantage businesses try to leverage this information. However, IT departments are struggling to meet the increased amount of reporting needs. Therefore, recent shift in the BI market has been towards empowering business users with self-service BI capabilities. The purpose of this study was to understand how self-service BI could help businesses to meet increased reporting demands. The research problem was approached with an empirical single case study. Qualitative data was gathered with a semi-structured, theme-based interview. The study found out that case company’s BI system was mostly used for group performance reporting. Ad-hoc and business user-driven information needs were mostly fulfilled with self-made tools and manual work. It was felt that necessary business information was not easily available. The concept of self-service BI was perceived to be helpful to meet such reporting needs. However, it was found out that the available data is often too complex for an average user to fully understand. The respondents felt that in order to self-service BI to work, the data has to be simplified and described in a way that it can be understood by the average business user. The results of the study suggest that BI programs struggle in meeting all the information needs of today’s businesses. The concept of self-service BI tries to resolve this problem by allowing users easy self-service access to necessary business information. However, business data is often complex and hard to understand. Self-serviced BI has to overcome this challenge before it can reach its potential benefits.

Business Intelligence Competency Centerin perustaminen: Case LähiTapiola

Tässä diplomityössä selvitetään case-tutkimuksena parhaita käytäntöjä Business Intelligence Competency Centerin (BICC) eli liiketoimintatiedonhallinnan osaamiskeskuksen perustamiseen. Työ tehdään LähiTapiolalle, jossa on haasteita BI-alueen hallinnoinnissa kehittämisen hajaantuessa eri yksiköihin ja yhtiöihin. Myös järjestelmäympäristö on moninainen. BICC:llä tavoitellaan parempaa näkyvyyttä liiketoiminnan tarpeisiin ja toisaalta halutaan tehostaa tiedon hyödyntämistä johtamisessa sekä operatiivisen tason työskentelyssä. Tavoitteena on lisäksi saada kustannuksia pienemmäksi yhtenäistämällä järjestelmäympäristöjä ja BI-työkaluja kuten myös toimintamalleja. Työssä tehdään kirjallisuuskatsaus ja haastatellaan asiantuntijoita kolmessa yrityksessä. Tutkimuksen perusteella voidaan todeta, että liiketoiminnan BI-tarpeita kannattaa mahdollistaa eri tasoilla perusraportoinnista Ad-hoc –raportointiin ja edistyneeseen analytiikkaan huomioimalla nämä toimintamalleissa ja järjestelmäarkkitehtuurissa. BICC:n perustamisessa liiketoimintatarpeisiin vastaaminen on etusijalla.

Are Evaluation of ICTs Investment Using Decision Support Systems:Case Applications from Distributor's and End User's Perspective Group Decision

The evaluation of investments in advanced technology is one of the most important decision making tasks. The importance is even more pronounced considering the huge budget concerning the strategic, economic and analytic justification in order to shorten design and development time. Choosing the most appropriate technology requires an accurate and reliable system that can lead the decision makers to obtain such a complicated task. Currently, several Information and Communication Technologies (ICTs) manufacturers that design global products are seeking local firms to act as their sales and services representatives (called distributors) to the end user. At the same time, the end user or customer is also searching for the best possible deal for their investment in ICT's projects. Therefore, the objective of this research is to present a holistic decision support system to assist the decision maker in Small and Medium Enterprises (SMEs) - working either as individual decision makers or in a group - in the evaluation of the investment to become an ICT's distributor or an ICT's end user. The model is composed of the Delphi/MAH (Maximising Agreement Heuristic) Analysis, a well-known quantitative method in Group Support System (GSS), which is applied to gather the average ranking data from amongst Decision Makers (DMs). After that the Analytic Network Process (ANP) analysis is brought in to analyse holistically: it performs quantitative and qualitative analysis simultaneously. The illustrative data are obtained from industrial entrepreneurs by using the Group Support System (GSS) laboratory facilities at Lappeenranta University of Technology, Finland and in Thailand. The result of the research, which is currently implemented in Thailand, can provide benefits to the industry in the evaluation of becoming an ICT's distributor or an ICT's end user, particularly in the assessment of the Enterprise Resource Planning (ERP) programme. After the model is put to test with an in-depth collaboration with industrial entrepreneurs in Finland and Thailand, the sensitivity analysis is also performed to validate the robustness of the model. The contribution of this research is in developing a new approach and the Delphi/MAH software to obtain an analysis of the value of becoming an ERP distributor or end user that is flexible and applicable to entrepreneurs, who are looking for the most appropriate investment to become an ERP distributor or end user. The main advantage of this research over others is that the model can deliver the value of becoming an ERP distributor or end user in a single number which makes it easier for DMs to choose the most appropriate ERP vendor. The associated advantage is that the model can include qualitative data as well as quantitative data, as the results from using quantitative data alone can be misleading and inadequate. There is a need to utilise quantitative and qualitative analysis together, as can be seen from the case studies.

Development of tender information process by business intelligence in a global company unit

The purpose of this Thesis was to study what is the present situation of Business Intelligence of the company unit. This means how efficiently unit uses possibilities of modern information management systems. The aim was to resolve how operative informa-tion management of unit’s tender process could be improved by modern information technology applications. This makes it possible that tender processes could be faster and more efficiency. At the beginning it was essential to acquaint oneself with written literature of Business Intelligence. Based on Business Intelligence theory is was relatively easy but challenging to search and discern how tender business could be improved by methods of Busi-ness Intelligence. The empirical phase of this study was executed as qualitative research method. This phase includes theme and natural interviews on the company. Problems and challenges of tender process were clarified in a part an empirical phase. Group of challenges were founded when studying information management of company unit. Based on theory and interviews, group of improvements were listed which company could possible do in the future when developing its operative processes.