Strategic Intelligence and Knowledge Management as drivers of Decision-Making in Mining Industry: An analysis of the literature

Author(s):  
A. Faz-Mendoza ◽  
N. K. Gamboa-Rosales ◽  
A. Castorena-Robles ◽  
M. J. Cobo ◽  
R. Castaneda-Miranda ◽  
...  
2021 ◽  
Vol 169 ◽  
pp. 120803
Author(s):  
Douglas K.R. Robinson ◽  
Antoine Schoen ◽  
Philippe Larédo ◽  
Jordi Molas Gallart ◽  
Philine Warnke ◽  
...  

2012 ◽  
Vol 01 (11) ◽  
pp. 22-30
Author(s):  
Kamran Nazari ◽  
Mostafa Emami

Knowledge management is a process that helps organizations to find important information, select, organize and publish them; and it’s a proficiency that will be necessary for actions like solving problems, dynamic learning, decision making. Knowledge management can improve a wide range of organization performance properties by enabling company to more intelligent performance, but it’s not enough alone; because knowledge management to be useful needs undertaking staff to organization and their job, that accept the knowledge management process with spirit and heart and perform it (Wiig, 1999:14).Knowledge management is the leveraging of collective wisdom to increase responsiveness and innovation. It is important that you discern from this definition three critical points. This definition implies that three criteria must be met before information can be considered knowledge. » Knowledge is connected. It exists in a collection (collective wisdom) of multiple experiences and perspectives Knowledge management is a catalyst. It is an action – leveraging. Knowledge is always relevant to environmental conditions, and stimulates action in response to these conditions. Information that does not precipitate action of some kind is not knowledge. In the words of Peter Drucker, ‘‘Knowledge for the most part exists only in application.’’ » Knowledge is applicable in un-encountered environments. Information becomes knowledge when it is used to address novel situations for which no direct precedent exists. Information that is merely ‘‘plugged in’’ to a previously encountered model is not knowledge and lacks innovation.


2021 ◽  
Author(s):  
Ney Kassiano Ramos ◽  
Cristina Keiko Yamaguchi

In this book, the authors propose that information from different animal health laboratories (here known as interlaboratory data), can be examined using the Knowledge Management discipline and Data Science technology, generating knowledge assets, information that can be useful in animal diagnosis, scientific studies and in the laboratories’ decision making process.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sami Wasef Abuezhayeh ◽  
Les Ruddock ◽  
Issa Shehabat

Purpose The purpose of this paper is to investigate and explain how organizations in the construction sector can enhance their decision-making process (DMP) by practising knowledge management (KM) and business process management (BPM) activities. A conceptual framework is developed that recognises the elements that impact DMP in terms of KM and BPM. The development of this framework goes beyond current empirical work on KM in addition to BPM as it investigates a wider variety of variables that impact DMP. Design/methodology/approach A case study is undertaken in the context of the construction industry in Jordan. A theoretical framework is developed and assessment of the proposed framework was undertaken through a questionnaire survey of decision-makers in the construction sector and expert interviews. Findings The outcomes of this research provide several contributions to aid decision-makers in construction organizations. Growth in the usage of KM and BPM, in addition to the integration between them, can provide employees with task-related knowledge in the organization’s operative business processes, improve process performance, promote core competence and maximise and optimise business performance. Originality/value Through the production of a framework, this study provides a tool to enable improved decision-making. The framework generates a strong operational as well as theoretical approach to the organizational utilization of knowledge and business processes.


2016 ◽  
Vol 14 (1) ◽  
pp. 176-182 ◽  
Author(s):  
Dinko Herman Boikanyo ◽  
Ronnie Lotriet ◽  
Pieter W. Buys

The main objective of this research study is to investigate the extent to which knowledge management is used within the mining industry. Knowledge management includes the identification and examination of available and required knowledge and the subsequent planning and control of actions to develop knowledge assets to accomplish organizational objectives. A structured questionnaire is used for the study. A total of 300 mines were randomly selected from a research population of mining organizations in South Africa, Africa and globally. The respondents were all part of senior management. A response rate of 64% was achieved. A significant number of respondents indicates that there is no transfer of knowledge about the best practices within their organizations. Some of the participants indicate that their organizations do not have the required technical infrastructure to enable knowledge sharing whilst some agree that the culture in their organizations is not conducive to the sharing of knowledge. A statistically and practically significant positive relationship with a large effect is found between the construct of knowledge management and perceived business performance. The mining organizations in Africa are ranked the lowest in terms of applications of knowledge management principles


2021 ◽  
Vol 8 (1) ◽  
pp. 15
Author(s):  
Eko Nur Hermansyah ◽  
Danny Manongga ◽  
Ade Iriani

<p align="center"><strong>Abstrak</strong></p><p>Intansi Kearsipan memiliki berbagai pengetahuan yang digunakan untuk pengelolaan arsip yang dimilikinya, <em>knowledge management</em> digunakan untuk mengumpulkan, mengelola, dan menyebarluaskan pengetahuan yang dimiliki, sehingga pengetahuan yang dimiliki oleh instansi kearsipan dapat digunakan untuk kemajuan intansi dan tidak hilang. Penelitian ini dilakukan di Dinas Perpustakaan dan Kearsipan Kota Salatiga. Pengumpulan data dilakukan dengan wawancara petugas kearsipan untuk mengumpulkan data tentang pengetahuan yang dimiliki dan cara penyimpanan serta penyebarluasan yang diterapkan di intansi kearsipan. Analisis data dilakukan dengan mengelompokkan pengetahuan yang dimiliki oleh intansi kearsipan sesuai dengan model <em>Choo-Sense Making</em>, untuk kemudian diterapkan di <em>Confluence</em> sesuai dengan hasil dari pengolahan data dengan model <em>Choo-Sense Making</em>. Hasil dari penelitian ini untuk model <em>Choo-Sense Making</em> pengetahuan di intansi kearsipan dibagi atas 3 tahap yaitu <em>Sense Making</em> yang berisi tentang pengetahuan yang berasal dari luar intansi dibuatkan wadah sebagai media diskusi, <em>chatting,</em> <em>Knowledge Creating</em> berisi tentang pengetahuan-pengetahuan yang dimiliki intansi kearsipan yang telah di dokumentasikan diubah dalam betuk <em>softfile</em> kemudian diunggah kedalam <em>space</em> untuk memudahkan penyimpanan serta penyebarluasan pengetahuan yang dimiliki, dan <em>Decision Making</em> yang berisi tentang jadwal-jadwal intansi dan evaluasi yang dilakukan intansi kearsipan. Hasil dari model <em>Choo-Sense Making</em> dimasukan ke <em>Confluence</em>, memperoleh hasil <em>space</em> yang dapat memudahkan menyimpan pengetahuan yang dimiliki berupa file aplikasi, <em>softfile</em>, serta memudahkan dalam pencarian kembali dan penyerluasan pengetahuan yang dimiliki. Penerapan <em>Choo-Sense Making</em> selain untuk mempermudah penyimpanan dan penyerbaluasan serta komunikasi, dapat mengurangi resiko kehilangan pengetahuan yang dimiliki oleh intansi kearsipan.<strong> </strong></p><p><strong>Kata kunci<em>: </em></strong><em>Knowledge Management, Model Choo-Sense Making, Confluence</em>, Perpustakaan dan Arsip</p><p align="center"><em>Abstract</em></p><p><em>Archival Agency has several knowledge that are used to manage the owned archive, knowledge management is used to collect, manage and disseminate the owned knowledge so that the knowledge that the archival agency has can be used for the agency progress and it will not missing. The research is conducted in Dinas Perpustakaan dan Kearsipan Kota Salatiga. Data collecting is conducted by interviewing the archival officer to gather data related to its knowledge, the storage system and dissemination applied in this archival agency. Data analysis is conducted by categorizing the agency knowledge according to Choo-Sense Making model and then it is applied in Confluence in accordance with the result of the data analysis from the Choo-Sense Making model. The result of this research, for Choo-Sense Making model, the knowledge in the archival agency is divided into 3 steps; Sense Making, Knowledge Creating and Decision Making. Sense Making contains knowledge coming from the outside of the agency that has forum as discussion media, chatting. Knowledge Creating contains knowledge that owned by the archival agency that has been documented and changed in the form of softfile then uploaded into space to ease the storage and the knowledge dissemination. Decision Making is about agency schedules and evaluation toward the activity in this archival agency. The result of Choo-Sense Making Model is input into Confluence, get space result that ease to save the knowledge in the form of application file, softfile, and ease to search and disseminate the owned knowledge. The application of Choo-Sense Making eases the storage system, dissemination, and communication. It also reduces the risk of losing knowledge owned by the archival agency.</em></p><p><em> </em></p><p><strong>Keywords</strong>: <em>Knowledge Management, Model Choo-Sense Making, Confluence, Library and Archive</em></p>


2018 ◽  
Vol 5 (2) ◽  
pp. 1-30
Author(s):  
Andi Wijaya Putra ◽  
Mulyanto Mulyanto ◽  
Risnal Diansyah

Perusahaan yang sukses untuk mencapai tujuannya secara optimal adalah perusahaan yang mampu merumuskan strategi, dan mengimplementasikan strategi secara efektif dan efisien. Hal ini dapat diterapkan dengan knowledge management model menggunakan metode Fuzzy Screening System untuk menentukan kuadran kondisi perusahaan, Fuzzy Screening System adalah salah satu metode multicriteria decision making (MCDM) yang menyatukan informasi yang diberikan oleh berbagai ahli dari menejemen tingkat atas dan menengah, dengan studi kasus PT. Jakarta Teknologi Utama aplikasi yang dibuat ini diharapkan dapat mengetahui sampai mana pencapaian kinerja perusahaan. Aplikasi dibangun berbasis web dengan menggunakan bahasa pemrogram PHP dan database my SQL Server, pengguna dari aplikasi ini adalah admin yang berperan mengelola data utama, pimpinan yang berperan melihat proses akhir dan laporan dan karyawan yang berperan mengisi quisioner. Dari hasil pengujian dapat disimpulkan bahwa metode Fuzzy Screening System dapat memberikan hasil berupa kuadran kondisi perusahaan dalam bentuk mapping.


2021 ◽  
Author(s):  
◽  
Edward Johnson

<p><b>The gold mining industry in Ghana is characterised by complexity in terms of its extended/sequential operations, its system-wide reach, its multiple stakeholders, and the variety of formal and informal organisations that constitute the industry. Perceptions of the industry differ considerably amongst stakeholders, depending on their stakes and interests, knowledge, understanding, involvement and agency within or without the sector. Studies of the industry to date have overlooked these diverse viewpoints and used limited-scope, single-frame analyses. However, they have highlighted wide-ranging industry issues that impact the diversity of stakeholders, which could benefit from a fuller and more comprehensive analysis.</b></p> <p>This study addresses this need by adopting a multi-framing systems-based approach. Data was examined and analysed through a variety of systems-based lenses and frames, including a stakeholder analysis (SA) frame, a causal loop modelling (CLM) frame, supply chain analysis (SCA) frame and the Theory of Constraints (TOC) Thinking Processes analytical frames lenses. First the Current Reality Tree (CRT) tool of the Theory of Constraints (TOC) was used to synthesise information from the literature examined, providing an initial provisional CRT model. Interview data was collected by sharing and seeking feedback to the CRT model at multiple levels of the industry, giving voice to stakeholders throughout the sector. Subsequent analysis used all the modelling frameworks mentioned above in a multi-framing analysis.</p> <p>In particular, the evaporating cloud (EC) tool from TOC was used to structure and develop potential solutions to conflict highlighted by the literature review, the SA, SCA and CLM. Building on this, a final CRT was developed, and a goal tree (GT) used to design the desired future whilst employing the future reality tree (FRT) to test the plausibility of solutions from the EC to deliver the desired future. The prerequisite tree (PRT) was then used to identify obstacles and intermediate objectives that must be overcome for successful transition to the desired future.</p> <p>Insights from the research shows a desire by multi-national large scale-gold mining companies and government alike to minimise adverse impacts and maximise the sector’s outcomes for key stakeholders, including those at the community level. However, the research has documented many instances of actions taken to address issues and improve outcomes that have instead resulted in unresolved dilemmas and paradoxes, failing to achieve desired outcomes.</p> <p>A number of factors have been identified as being responsible for these situations. Key amongst them is a limited understanding to deliver desired outcome for stakeholders without compromises, a focus on short-term goals, no collective effort, and arms-length/win-lose relationships amongst the Ghanaian stakeholders of the industry.</p> <p>The study’s concluding findings and results allow decision makers to benefit significantly from the study through its recommendations and showcasing of tools that may allow them to make sound decisions and address endogenous and exogenous cause-effect relationships limiting desirable outcomes from actions taken.</p> <p>Theoretical and knowledge-based contributions are made by conceptualising and offering evidence for three key factors or dimensions that can explain a significant number of issues limiting desirable outcomes for stakeholders of the gold mining industry. These include difficulty to transition from theory (espoused aims) to practice, a relative focus on local optima (silo thinking), poor monitoring (lack of evaluation), and a control culture. Methodological contributions are made by demonstrating the application of a multi-framing approach in a more organic and iterative manner as opposed to its use in a designed sequence, working down through layers of various systemic levels of an industry (in this case, the gold mining industry in Ghana). By so doing, the study builds on and extends the practicality of the multi-framing approach and stimulates further research in the field.</p> <p>In terms of its contribution to practice, the study provides Government, political and mining sector policy decision makers, and other interested actors, with a platform for understanding the sector in order to support their decision making about the industry to ultimately improve outcomes for key stakeholders. In particular, the study allows mining sector policy decision makers and other stakeholders to recognise complexity, uncertainty and conflicts that are embedded in the mining system and in their everyday decision-making activities about the industry. It also allows these stakeholders to become more aware that such issues can be addressed and improved by identifying and focusing on one or few underlying causes.</p> <p>This thesis draws on systems-based frameworks drawn both from functional management, for example, the supply chain and value chain frameworks of operations management and the stakeholder framework of strategic management, and from the broad domain of systems thinking (ST) and systems-based methodologies; and then focuses on the intersection of these frameworks in relation to the gold mining sector in Ghana. Due to the wide range of techniques applied, none are over-explored, creating potential for further research. On the other hand, with regard to explanations, depending on background, practitioners, and researchers familiar with some techniques may consider those sections over-explained. The researcher has sought a balance for the purpose of this study. Whilst limiting the scope of this work has been necessary in the context of doctoral study, topics ripe for future research are set out in the conclusion.</p>


Author(s):  
Constantin Bratianu

Abstract The purpose of this paper is to analyze the limitations induced in Knowledge Management by the processes of linearization and discretization, which happen frequently in decision-making. Linearization is a result of applying linear thinking models in decision-making, regardless of the complexity of knowledge management phenomena. Knowledge and all the other intangible resources are nonlinear entities and they should be evaluated with nonlinear metrics. However, in many situations managers use simple solutions based on linear thinking models and get large errors in their decision-making, with significant negative consequences in management. Also, linear thinking model is dominant in legislation, which may lead to significant errors in managerial decision-making. Discretization is a process in which an entity with a continuous representation, like a knowledge field, is transformed into a piecewise entity to be handled more easily. Also, social media uses discretized systems for different evaluations which should be interpreted accordingly. For instance, counting the number of “like” on Facebook for a certain message or image may lead to the conclusion that friendship is proportional with the number of “friends”, which might not be in concordance with reality. Knowledge management is a complex activity dealing with knowledge, which means nonlinear entities. Using linear thinking models and discretization methods in evaluations and decision-making may lead to significant errors and negative consequences.


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