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.

Managing Customer Issues through a Support Channel Network

The importance of after-sales service or service in general can be seen and experienced by customers every day with industrial as well as other non-industrial services or products. This dissertation, drawing on theory and experience, focuses on practical engineering implications, specifically the management of customer issues in the after-sales phase in the mobile phone arena. The main objective of this doctoral dissertation is to investigate customer after-sales issue management, specifically regarding mobile phones. The case studies focus on issue resolution time and the issue of corrective actions. This dissertation consists of a main body and four peer-reviewed journal articles and one manuscript currently under review by a peer-reviewed journal. The main body of this dissertation examines the elements of customer satisfaction, loyalty, and retention with respect to corrective actions to address customer issues and issue resolution time through literature and empirical studies. The five independent works are case studies supporting the thesis research questions. This study examines four questions: 1) What are the factors affecting corrective actions for customers? 2) How can customer issue resolution time be controlled? 3) What are the factors affecting processes in the service chain? and 4) How can communication be measured in a service chain? In this work, both quantitative and qualitative analysis methods are used. The main body of the thesis reviews the literature regarding the elements that bridge the five case studies. The case studies of the articles and surveys lean more toward the methodology of critical positivism and then apply the interpretive approach in interpreting the results. The case study articles employ various statistical methods to analyze and to interpret the empirical and survey data. The statistical methods were used to create a model that is useful for significantly optimizing issue resolution time. Moreover, it was found that samples for verifying issues provided by the customer neither improve the perceived quality of corrective actions nor the perceived quality of issue resolution time. The term “service” in this work is limited to the technical services that are provided by product manufacturers and after-sales authorized service vendors. On the basis of this research work, it has been observed that corrective actions and issue resolution time are associated with customer satisfaction and hence, according to induction theory, to customer loyalty and retention. This thesis utilizes knowledge of marketing and customer relationships to contribute to the existing body of knowledge concerning information and communication technology for after-sales service recovery of mobile terminals. The established models in the thesis contribute to the existing knowledge of the after-sales process of dealing with customer issues in the field of mobile phones. The findings suggest that process managers could focus more on communication and training provided to the staff as new technology evolves rapidly. The study also suggest the managers formulate strategies for how customers can be kept informed on a regular basis of the status of issues that have been escalated for corrective action. The findings also lay the foundation for the comprehensive objective to control the entire product development process, starting with conceptualization. This implies that robust design should be applied to the new products so that problems affecting customer service quality are not repeated. The objective will be achieved when the entire service chain from product development to the final user can be modeled and this model can be used to support the organization at all levels.