Monitoring And Evaluation Of Knowledge Management ElbEwen Le Borgne
Presentation from the IKM-Emergent group presenting work on M&E of knowledge management. Presentation given during the KMIC webinar organised by USAID.
This document provides an overview of business research methods. It discusses what business research is, common business research methods like questionnaires, interviews and analyzing public data. It also outlines the business research process from defining the problem to analyzing and reporting results. Specific sampling techniques are explained like simple random sampling and stratified sampling. Multivariate analysis methods and correlation are described. Different statistical tests are introduced, like t-tests, ANOVA tests and regression analysis.
The document introduces data mining and knowledge discovery in databases. It discusses why data mining is needed due to large datasets that cannot be analyzed manually. It also covers the data mining process, common data mining techniques like association rules and decision trees, applications of data mining in various domains, and some popular data mining tools.
Here are the answers to your questions:
1. FINER criteria of a good research question are: Feasible, Interesting, Novel, Ethical, Relevant.
2. A null hypothesis is a statistical hypothesis that predicts that no relationship exists between two variables.
3. The types of relationships that may exist between two variables are: positive, negative, or no relationship.
4. Read around comes first before read into. Read around gives a broad overview of the topic area, while read into involves an in-depth review.
5. The literature review is often called the "mother of the research" as it helps identify gaps and formulate the research question.
6. If we
This document provides an overview of key concepts for data gathering and analysis in interaction design. It discusses techniques for interviews, questionnaires, observations, and the analysis of both qualitative and quantitative data. The goal is to understand users and inform the design process. Techniques covered include interviews, questionnaires, observations, analysis frameworks like grounded theory, and presenting findings.
So how do online focus groups work? Learn how online focus groups are conducted. The presentation includes a high level overview of the various platform options available to conduct online focus groups. Learn how to make the most out of your research budget by utilizing online focus group software to meet your research objectives with ease and success.
Research seminar lecture_2_research_proposal__types_of_research_methods_stude...Daria Bogdanova
This document provides an outline of a research seminar on educational sciences. It discusses the structure of a research proposal, including the main sections and steps. The three main sections of a research proposal are: 1) why the research is being conducted, 2) what will be researched, and 3) how the research will be done. It then describes several common quantitative and qualitative research methods, including surveys, experiments, case studies, interviews, and content analysis. The document aims to help students understand how to develop and carry out an educational research study.
This document provides an overview of research methods. It defines research and describes the scientific research process. Research is defined as a systematic investigation to discover and develop knowledge. The scientific research process involves four stages: exploration, description, explanation, and prediction. It also outlines key aspects of different types of research methods, including quantitative and qualitative approaches, and discusses challenges in applying scientific methods to social science research. The document emphasizes that research requires a systematic, objective, and rigorous approach.
Monitoring And Evaluation Of Knowledge Management ElbEwen Le Borgne
Presentation from the IKM-Emergent group presenting work on M&E of knowledge management. Presentation given during the KMIC webinar organised by USAID.
This document provides an overview of business research methods. It discusses what business research is, common business research methods like questionnaires, interviews and analyzing public data. It also outlines the business research process from defining the problem to analyzing and reporting results. Specific sampling techniques are explained like simple random sampling and stratified sampling. Multivariate analysis methods and correlation are described. Different statistical tests are introduced, like t-tests, ANOVA tests and regression analysis.
The document introduces data mining and knowledge discovery in databases. It discusses why data mining is needed due to large datasets that cannot be analyzed manually. It also covers the data mining process, common data mining techniques like association rules and decision trees, applications of data mining in various domains, and some popular data mining tools.
Here are the answers to your questions:
1. FINER criteria of a good research question are: Feasible, Interesting, Novel, Ethical, Relevant.
2. A null hypothesis is a statistical hypothesis that predicts that no relationship exists between two variables.
3. The types of relationships that may exist between two variables are: positive, negative, or no relationship.
4. Read around comes first before read into. Read around gives a broad overview of the topic area, while read into involves an in-depth review.
5. The literature review is often called the "mother of the research" as it helps identify gaps and formulate the research question.
6. If we
This document provides an overview of key concepts for data gathering and analysis in interaction design. It discusses techniques for interviews, questionnaires, observations, and the analysis of both qualitative and quantitative data. The goal is to understand users and inform the design process. Techniques covered include interviews, questionnaires, observations, analysis frameworks like grounded theory, and presenting findings.
So how do online focus groups work? Learn how online focus groups are conducted. The presentation includes a high level overview of the various platform options available to conduct online focus groups. Learn how to make the most out of your research budget by utilizing online focus group software to meet your research objectives with ease and success.
Research seminar lecture_2_research_proposal__types_of_research_methods_stude...Daria Bogdanova
This document provides an outline of a research seminar on educational sciences. It discusses the structure of a research proposal, including the main sections and steps. The three main sections of a research proposal are: 1) why the research is being conducted, 2) what will be researched, and 3) how the research will be done. It then describes several common quantitative and qualitative research methods, including surveys, experiments, case studies, interviews, and content analysis. The document aims to help students understand how to develop and carry out an educational research study.
This document provides an overview of research methods. It defines research and describes the scientific research process. Research is defined as a systematic investigation to discover and develop knowledge. The scientific research process involves four stages: exploration, description, explanation, and prediction. It also outlines key aspects of different types of research methods, including quantitative and qualitative approaches, and discusses challenges in applying scientific methods to social science research. The document emphasizes that research requires a systematic, objective, and rigorous approach.
This document provides an overview of basics of data analysis. It discusses how data analysis involves turning raw data into useful information to answer questions. It also discusses key steps like data preparation, coding, and common statistical analysis techniques used. The conclusion emphasizes that the purpose of analysis is to provide answers to programmatic questions by describing samples and populations.
This document discusses different types of sampling methods used in research. It begins by defining key terms like target population, sample, and sampling frame. It then covers different sampling techniques including probability sampling methods like simple random sampling, stratified random sampling, and cluster sampling as well as non-probability sampling methods. For each method, it provides examples and discusses their advantages and disadvantages for representing populations. The document aims to help medical students understand how to select appropriate sampling methods based on their research questions.
This document discusses ethnographic research methods. It defines ethnography as the observation of groups of people or cultures in natural settings using qualitative research methods like observations and interviews. Ethnographies are long-term studies that allow researchers to experience regular patterns and routines of a community. The document outlines the typical steps of an ethnography, including identifying a research question, gaining access to subjects, collecting data through observations and interviews, analyzing data concurrently with collection, and writing a final report that brings the culture to life.
Quantitative, qualitative, and mixed method approachesmuryantinarima
The document discusses quantitative, qualitative, and mixed methods research approaches. Quantitative research aims to approve or disprove a hypothesis by collecting numerical data, while qualitative research aims to answer research questions by gathering non-numerical contextual data to explain phenomena. Mixed methods combines both approaches to balance efficient data collection with in-depth analysis.
This document discusses various methods for collecting primary data, including observation, interviews, questionnaires, and schedules. It outlines the key aspects of primary data collection such as structured vs. unstructured approaches, participant vs. non-participant observation, and open-ended vs. closed questions. Primary data collection allows researchers to gather targeted information directly from respondents but requires more time and resources than using secondary data.
Statistics is the science of collecting, analyzing, and interpreting data. It is important for planning as it provides information needed for decision making. Some key uses of statistics in planning include collecting demographic data to inform policy, using statistical analysis to forecast demand, and employing techniques like PERT and CPM to optimize project scheduling. Statistical planning is paramount in developing countries as it allows them to gather data and effectively allocate resources for growth.
Quantitative Methods of Research-Intro to research
Once a researcher has written the research question, the next step is to determine the appropriate research methodology necessary to study the question. The three main types of research design methods are qualitative, quantitative and mixed methods.
Quantitative research involves the systematic collection and analysis of data.
The Nature of Research
Prepared by:
Billones,Rich Antoinette B.
Guevarra, Rona Mae
Wahing, Ivy Grace
Canatoy, Charl Leo S.
Adapted from:
Zennifer L. Oberio
This document outlines an introduction to research methods course. The course covers key aspects of the research process including writing research proposals, reviewing literature, empirical research methods, ethics, and presentations. It aims to provide students the skills to successfully complete computer science research projects. The syllabus covers topics like the research process, writing and web skills, tools for experiments, and research management.
This document discusses data preprocessing techniques for transforming raw data into an understandable format. It describes measures for data quality such as accuracy, completeness, and consistency. The major tasks in data preprocessing are outlined as data cleaning, integration, reduction, transformation, and discretization. Data cleaning involves handling missing values, noise, and inconsistencies. Data integration merges data from multiple sources to reduce redundancies and inconsistencies. Data reduction techniques include aggregation, attribute selection, and dimensionality reduction to obtain a smaller data representation. Data transformation consolidates data into appropriate forms for mining through techniques like smoothing, aggregation, generalization, and normalization. Data discretization divides continuous attributes into intervals to reduce data size and prepare for further analysis.
Part of a course I run introducing quantitative methods. One of the slideshows on my site www.kevinmorrell.org.uk please reference the site if you use any of it - hope it is useful.
Significance of research - Research Methodology - Manu Melwin Joymanumelwin
“All progress is born of inquiry. Doubt is often better than overconfidence, for it leads to inquiry, and inquiry leads to invention” is a famous Hudson Maxim in context of which the significance of research can well be understood.
This document discusses reliability and validity in qualitative research methods. It begins by defining reliability, validity, and practicality for quantitative research. For qualitative research, it discusses evaluating studies based on their credibility, transferability, dependability, and confirmability rather than reliability and validity. Strategies for achieving these criteria like triangulation, thick description, and reflexivity are presented. The challenges of small sample sizes, researcher bias, and lack of generalizability in qualitative research are acknowledged. Criteria for evaluating the building of theories from qualitative data are also outlined.
This document defines and describes different types of research. It discusses research purposes including exploratory, descriptive, and explanatory research. It also covers research uses in basic and applied contexts. The time dimension of cross-sectional and longitudinal research is outlined. Finally, it details quantitative and qualitative data collection techniques.
The document discusses research idea generation and question formulation. It describes that generating research ideas is one of the most difficult aspects of research. Ideas can come from rational thinking such as examining strengths and interests or creative thinking such as keeping an idea notebook. Techniques like brainstorming and SCAMPERR can help stimulate new ideas. Once an idea is generated, it needs to be narrowed into a focused research topic and then further refined into a clear research question to guide the study. The research question should be feasible, interesting, novel, ethical, and relevant.
This document discusses the nature and types of scientific research. It defines scientific research as a systematic, objective, and empirical process of collecting and analyzing data to uncover facts and relationships. Scientific research follows the principles of being empirical, objective, systematic, public, replicable, and cumulative. The document outlines three main types of research: descriptive research which observes what people say, quantitative research which measures quantities and compares data, and qualitative research which does not express observations numerically. It also discusses five other types of research: basic research conducted in universities, applied research which aims to solve real problems, co-relational research which examines relationships between variables, and evaluative and action research.
Research Methodology Introduction ch1
MEANING OF RESEARCH, OBJECTIVES OF RESEARCH,TYPES OF RESEARCH,Research Approaches ,Research Methods versus Methodology,research process guideline:
Business research is a systematic process of inquiry that provides information to guide business decisions. It involves planning, collecting data, analyzing data, and reporting findings. The goal is to answer a research question, test a hypothesis, and reduce risk or predict outcomes for business decisions. Both qualitative and quantitative research methods can be used.
Marketing Automation + Communities= Customer Love Chicago Magnet 360
This document discusses how marketing automation and communities can be combined to create customer love. It notes that most companies lack an in-depth understanding of their customers. The presentation argues that customers are on a journey with brands and expect engagement at every step. It promotes building a single customer view, defining the customer journey, and delivering optimized content across touchpoints. Communities are presented as a way to increase sales, reduce costs, and build brand advocates through engagement.
Capability Maturity Model Integration (CMMI) is a process improvement approach that provides organizations with the essential elements of effective processes. It has five levels of process maturity: initial, managed, defined, quantitatively managed, and optimizing. As organizations advance through these levels, their processes become more predictable, measurable, and controlled. CMMI helps organizations improve quality, productivity, customer satisfaction, and return on investment. Large companies like Boeing, Tata Consultancy Services, and Accenture have achieved high levels of CMMI and realized significant benefits like increased productivity and reduced defects.
This document provides an overview of basics of data analysis. It discusses how data analysis involves turning raw data into useful information to answer questions. It also discusses key steps like data preparation, coding, and common statistical analysis techniques used. The conclusion emphasizes that the purpose of analysis is to provide answers to programmatic questions by describing samples and populations.
This document discusses different types of sampling methods used in research. It begins by defining key terms like target population, sample, and sampling frame. It then covers different sampling techniques including probability sampling methods like simple random sampling, stratified random sampling, and cluster sampling as well as non-probability sampling methods. For each method, it provides examples and discusses their advantages and disadvantages for representing populations. The document aims to help medical students understand how to select appropriate sampling methods based on their research questions.
This document discusses ethnographic research methods. It defines ethnography as the observation of groups of people or cultures in natural settings using qualitative research methods like observations and interviews. Ethnographies are long-term studies that allow researchers to experience regular patterns and routines of a community. The document outlines the typical steps of an ethnography, including identifying a research question, gaining access to subjects, collecting data through observations and interviews, analyzing data concurrently with collection, and writing a final report that brings the culture to life.
Quantitative, qualitative, and mixed method approachesmuryantinarima
The document discusses quantitative, qualitative, and mixed methods research approaches. Quantitative research aims to approve or disprove a hypothesis by collecting numerical data, while qualitative research aims to answer research questions by gathering non-numerical contextual data to explain phenomena. Mixed methods combines both approaches to balance efficient data collection with in-depth analysis.
This document discusses various methods for collecting primary data, including observation, interviews, questionnaires, and schedules. It outlines the key aspects of primary data collection such as structured vs. unstructured approaches, participant vs. non-participant observation, and open-ended vs. closed questions. Primary data collection allows researchers to gather targeted information directly from respondents but requires more time and resources than using secondary data.
Statistics is the science of collecting, analyzing, and interpreting data. It is important for planning as it provides information needed for decision making. Some key uses of statistics in planning include collecting demographic data to inform policy, using statistical analysis to forecast demand, and employing techniques like PERT and CPM to optimize project scheduling. Statistical planning is paramount in developing countries as it allows them to gather data and effectively allocate resources for growth.
Quantitative Methods of Research-Intro to research
Once a researcher has written the research question, the next step is to determine the appropriate research methodology necessary to study the question. The three main types of research design methods are qualitative, quantitative and mixed methods.
Quantitative research involves the systematic collection and analysis of data.
The Nature of Research
Prepared by:
Billones,Rich Antoinette B.
Guevarra, Rona Mae
Wahing, Ivy Grace
Canatoy, Charl Leo S.
Adapted from:
Zennifer L. Oberio
This document outlines an introduction to research methods course. The course covers key aspects of the research process including writing research proposals, reviewing literature, empirical research methods, ethics, and presentations. It aims to provide students the skills to successfully complete computer science research projects. The syllabus covers topics like the research process, writing and web skills, tools for experiments, and research management.
This document discusses data preprocessing techniques for transforming raw data into an understandable format. It describes measures for data quality such as accuracy, completeness, and consistency. The major tasks in data preprocessing are outlined as data cleaning, integration, reduction, transformation, and discretization. Data cleaning involves handling missing values, noise, and inconsistencies. Data integration merges data from multiple sources to reduce redundancies and inconsistencies. Data reduction techniques include aggregation, attribute selection, and dimensionality reduction to obtain a smaller data representation. Data transformation consolidates data into appropriate forms for mining through techniques like smoothing, aggregation, generalization, and normalization. Data discretization divides continuous attributes into intervals to reduce data size and prepare for further analysis.
Part of a course I run introducing quantitative methods. One of the slideshows on my site www.kevinmorrell.org.uk please reference the site if you use any of it - hope it is useful.
Significance of research - Research Methodology - Manu Melwin Joymanumelwin
“All progress is born of inquiry. Doubt is often better than overconfidence, for it leads to inquiry, and inquiry leads to invention” is a famous Hudson Maxim in context of which the significance of research can well be understood.
This document discusses reliability and validity in qualitative research methods. It begins by defining reliability, validity, and practicality for quantitative research. For qualitative research, it discusses evaluating studies based on their credibility, transferability, dependability, and confirmability rather than reliability and validity. Strategies for achieving these criteria like triangulation, thick description, and reflexivity are presented. The challenges of small sample sizes, researcher bias, and lack of generalizability in qualitative research are acknowledged. Criteria for evaluating the building of theories from qualitative data are also outlined.
This document defines and describes different types of research. It discusses research purposes including exploratory, descriptive, and explanatory research. It also covers research uses in basic and applied contexts. The time dimension of cross-sectional and longitudinal research is outlined. Finally, it details quantitative and qualitative data collection techniques.
The document discusses research idea generation and question formulation. It describes that generating research ideas is one of the most difficult aspects of research. Ideas can come from rational thinking such as examining strengths and interests or creative thinking such as keeping an idea notebook. Techniques like brainstorming and SCAMPERR can help stimulate new ideas. Once an idea is generated, it needs to be narrowed into a focused research topic and then further refined into a clear research question to guide the study. The research question should be feasible, interesting, novel, ethical, and relevant.
This document discusses the nature and types of scientific research. It defines scientific research as a systematic, objective, and empirical process of collecting and analyzing data to uncover facts and relationships. Scientific research follows the principles of being empirical, objective, systematic, public, replicable, and cumulative. The document outlines three main types of research: descriptive research which observes what people say, quantitative research which measures quantities and compares data, and qualitative research which does not express observations numerically. It also discusses five other types of research: basic research conducted in universities, applied research which aims to solve real problems, co-relational research which examines relationships between variables, and evaluative and action research.
Research Methodology Introduction ch1
MEANING OF RESEARCH, OBJECTIVES OF RESEARCH,TYPES OF RESEARCH,Research Approaches ,Research Methods versus Methodology,research process guideline:
Business research is a systematic process of inquiry that provides information to guide business decisions. It involves planning, collecting data, analyzing data, and reporting findings. The goal is to answer a research question, test a hypothesis, and reduce risk or predict outcomes for business decisions. Both qualitative and quantitative research methods can be used.
Marketing Automation + Communities= Customer Love Chicago Magnet 360
This document discusses how marketing automation and communities can be combined to create customer love. It notes that most companies lack an in-depth understanding of their customers. The presentation argues that customers are on a journey with brands and expect engagement at every step. It promotes building a single customer view, defining the customer journey, and delivering optimized content across touchpoints. Communities are presented as a way to increase sales, reduce costs, and build brand advocates through engagement.
Capability Maturity Model Integration (CMMI) is a process improvement approach that provides organizations with the essential elements of effective processes. It has five levels of process maturity: initial, managed, defined, quantitatively managed, and optimizing. As organizations advance through these levels, their processes become more predictable, measurable, and controlled. CMMI helps organizations improve quality, productivity, customer satisfaction, and return on investment. Large companies like Boeing, Tata Consultancy Services, and Accenture have achieved high levels of CMMI and realized significant benefits like increased productivity and reduced defects.
The document provides an overview of the Capability Maturity Model Integration (CMMI). It discusses key aspects of CMMI including its focus on process improvement, the two representations (staged and continuous), maturity/capability levels, process areas, and components such as goals and practices. It compares CMMI to its predecessor models and explains how CMMI integrates multiple disciplines like systems engineering, software engineering, and integrated product development.
The document provides an overview of the Capability Maturity Model Integration (CMMI) framework. CMMI is an industry standard for improving product quality and development processes. It consists of best practices for systems engineering, software engineering, integrated product and process development, and supplier sourcing. CMMI models an organization's processes at five maturity levels from initial to optimizing. Higher levels indicate more disciplined, defined, and quantitatively managed processes. The document outlines the CMMI components and structure, describes each maturity level and associated process areas, and discusses tips for successful CMMI implementation.
From recent data we know that customers no longer follow a direct path from engagement to purchase, they take on a more fluid and sporadic buying pattern, interacting at different points across the customer journey. The good news is; businesses are now able to influence the customer journey through well timed digital touchpoints to guide buyers and influence business outcomes. But to get there we must first understand the behaviour.
This document provides an overview of knowledge portals and their use for knowledge management. It defines knowledge and knowledge management, and discusses how portals can be used to create knowledge portals. Key points include that a knowledge portal provides single access to an organization's tacit and explicit knowledge. It discusses the functions, design, and tools of a knowledge portal including features for gathering, categorizing, distributing, publishing, and personalizing knowledge. Examples are given of open source content management systems like Joomla and Drupal that can be used to build knowledge portals. Challenges for librarians in managing knowledge and keeping portals up to date are also mentioned.
Infosys began efforts to distribute knowledge within the company in 1991 with the establishment of an Education and Research department. In 1999, Infosys launched K-shop to capture knowledge generated across projects, establishing a fully fledged KM program. The goal of KM at Infosys is to ensure all organizational learning benefits customers by moving towards a "Learn Once, Use Anywhere" paradigm. Knowledge management has helped Infosys connect dispersed work groups and create an enduring competitive advantage.
“If you have an apple and I have an apple and we exchange these apples then you and I will still each have one apple. But if you have an idea and I have an idea and we exchange these ideas, then each of us will have two ideas.” (George Bernard Shaw)
Unlike many other resources that get depleted when shared, an idea or a knowledge nugget only gets enriched. From an era where labor and capital ruled, we now have evolved to a period where knowledge is seen as the key, if not the sole differentiator.
A Simple Introduction To CMMI For BeginerManas Das
This slide contain an overall idea about cmmi and how to get started with cmmi levels. Also it is very good PPT for students who are giving seminar in colleges.
This presentation is dedicated to PCMM maturity model. People Capability Maturity Model is about restructuring organizations based on organization involved persons' capabilities which is one of the best methods in its own.
The document provides an overview of knowledge management practices at The Coca-Cola Company. It discusses the company's initial setup of knowledge management which involved decentralization and appointing local managers. The main knowledge management tools used are the intranet, business reviews, and informal networks. The implementation captures tacit knowledge among employees to create innovations. Technology used includes the intranet system and advanced systems like EDI to improve information access. A success story details how the digital archives system allows easy access to marketing assets. Revenue was uplifted through cost cutting and efficiency programs like Project MAX.
The document discusses several major knowledge management models:
- The Nonaka and Takeuchi Knowledge Spiral Model describes how tacit and explicit knowledge can be transformed within an organization through four modes of knowledge conversion.
- The von Krogh and Roos Model distinguishes between individual and social knowledge and analyzes how knowledge is acquired and shared in organizations.
- The Choo Sense-Making KM Model focuses on sense making, knowledge creation, and decision making to help organizations adapt strategically.
- The Wiig Model emphasizes organizing knowledge for usefulness and outlines types and degrees of internalization of knowledge.
- The Boisot KM model conceptualizes knowledge as an "information good" that spreads differently depending on its
The document discusses process improvement in software engineering. It describes the Capability Maturity Model (CMM) which has 5 levels for process improvement: initial, repeatable, defined, managed, and optimizing. Each level is associated with better project management practices, quality levels, and key process areas. Moving from lower to higher levels results in fewer defects, higher defect removal rates, and better ability to predict and manage costs, quality, and personnel needs. The CMM provides a framework for organizations to assess and improve their software development processes.
The document discusses CMMI (Capability Maturity Model Integration), a framework for process improvement and appraising the maturity of processes. It provides definitions of CMMI's key aspects including maturity levels, process areas, usage, benefits, and differences compared to other frameworks like ISO and Lean Six Sigma. CMMI aims to help organizations measure, monitor, and manage processes to improve performance, quality and reduce risks through a defined process improvement path.
This document provides an overview of knowledge management. It defines data, information, and knowledge and describes explicit and tacit knowledge. It discusses the history of knowledge management from the 1970s to present. It also outlines several common knowledge management models and describes the typical stages in the knowledge management life cycle including information mapping, storage, retrieval, use, and auditing. Finally, it discusses some key terms used in knowledge management.
To view recording: https://youtu.be/GP7rtDLAYEg or watch the video at end of the slide
The Balanced Scorecard Institute and partner Informa Middle East invite you to participate in our upcoming complimentary webinar, ‘KPI Best Practices’, which will discuss the relationship between strategy execution and KPIs.
Developing meaningful KPIs to measure strategy execution is both an art and a science, involving a deep understanding of what to measure, how to measure, how to analyze performance information, how to report and clearly inform others regarding desired results and performance, and how to use the information to make better decisions.
This webinar introduces one of the main topics at our upcoming Saudi KPI for Business Strategy & Transformation workshop.
Join the Balanced Scorecard Institute's Howard Rohm, Co-Founder and President, and Suzy Nisbet, Senior Associate and Consultant, as they discuss developing strategic, operational, project, and organizational capacity KPIs, aligning KPIs to strategy, measuring intangible goals, streamlining measurement and reporting processes, and creating derivative KPIs for employees at all organizational levels.
Sharing best KPI practices from their worldwide client experience, this 40-minute webinar (followed by a 20-minute Q&A session) will provide the knowledge and insight to better understand the relationship between strategy and KPI's.
Webinar participants will learn how to:
• Improve managers' and employees' perception of the value and importance of measuring performance
• Lift the skill level of managers and employees in selecting meaningful measures and using those measures to make better informed decisions
• Use KPIs to build individual and collective accountability for results
Provide Authority
Hold people accountable for what they can control
41
Effective Training
• Training is not just a one‐time event
• Training must be ongoing and reinforced
• Training must be relevant to job duties
• Training must be understood and applied
• Assess competency and provide feedback
• Training is an investment, not a cost
"Tell me and I'll forget; show me and I may remember; involve me and I'll
understand." - Chinese Proverb
42
Empowerment
• Empower employees to identify and correct issues
• Create environment where mistakes are opportunities to learn
• Provide tools and resources to solve problems
• Recognize
This document discusses benchmarking, which involves continuously comparing a company's strategies, products, and processes to world-class organizations in order to identify areas for improvement. It describes the benefits of benchmarking as cultural change towards new performance targets, performance improvement by defining gaps, and improving human resources through training. There are two types of benchmarking: strategic, which analyzes the environment and competition, and operational, which prioritizes key processes for cost reduction and differentiation. The benchmarking process involves measuring best-in-class performance, determining how it was achieved, and developing an improvement plan.
6 Areas Of Focus to Maximize the Success of Your Digital Marketing Analytics ...Webtrends
This document outlines 6 areas of focus to maximize the success of a digital marketing analytics program: 1) Define a measurement strategy aligned with business objectives, 2) Implement tagging and data integration, 3) Deliver visualizations and reports, 4) Adopt the analytics across teams, 5) Ongoing optimization of marketing efforts using the data, and 6) Continual improvement through exception analysis and alerts. The experts recommend starting with a blank slate rather than default reports, using custom tagging for complex sites, integrating additional data beyond campaigns, and leveraging analytics to provide timely insights and optimization opportunities.
If you don't know where you're going it doesn't matter how fast you get thereNicole Forsgren
The best-performing organizations have the highest quality, throughput, and reliability while also delivering value. They are able to achieve this by focusing on a few key measurement principles, which Nicole and Jez will outline in this talk. These include knowing your outcome measuring it, capturing metrics in tension, and collecting complementary measures… along with a few others. Nicole and Jez explain the importance of knowing how (and what) to measure—ensuring you catch successes and failures when they first show up, not just when they’re epic, so you can course correct rapidly. Measuring progress lets you focus on what’s important and helps you communicate this progress to peers, leaders, and stakeholders, and arms you for important conversations around targets such as SLOs. Great outcomes don’t realize themselves, after all, and having the right metrics gives us the data we need to be great SREs and move performance in the right direction.
Has your organization ever considered replacing a tester that did not write, for example, 15 test cases per day? Is the testing team blamed if defect leakage is greater than 5% into production? What drives decisions like these? The common thread in these examples is “Test Metrics”
Test Metrics... Everyone has an opinion about them. Some believe they are the most valuable way to communicate the results of testing. Some think that they are useless, misleading, and damaging to the communication of test results. Some believe that without measurement you are not managing the effort. And some believe that bad metrics are worse than no metrics at all.
Where does your organization fit in the metrics and measurement debates? Is your team aligned? Do you agree with the team? Do you use a reporting process for test results? Are you forced to report on metrics you don't believe are valuable? Do you have dozens of metrics that you are reporting periodically that no one looks at, and when they do look at them, there is room for misinterpretation?
In this session, Mike Lyles and Jay Philips will challenge the audience to discuss the topic of metrics and measurement, review multiple viewpoints on the topic, and address many of the questions that organizations have today around metrics and measurement.
Takeaways:
- Top metrics that are misused or misunderstood in most every organization.
- Metrics that you should you get rid of ASAP!
- Best and Worst metrics - based on opinions of the speakers & audience.
- Metrics that everyone should use – and how they compare to your organization’s metrics.
- Tools and processes that can help your organization better measure your testing.
** Presentation given at STPCon Spring 2014
The document discusses strategies for real-time fraud detection. It outlines best practices for turning data mining strategies into action, including involving key stakeholders from business, analytics, and IT to align incentives and goals. Specifically, it emphasizes that for fraud analysis, speed of model deployment is the most important factor, as improvements in accuracy may be lost if there are delays implementing new models. It also stresses communicating findings to business stakeholders in clear, non-technical terms focused on relevant metrics and expected results.
The Balanced Scorecard is a strategic planning and management system used to translate an organization's mission and strategy into a comprehensive set of performance measures. It provides top-level managers with a fast but comprehensive view of the organization from four important perspectives: financial, customer, internal business processes, and learning and growth. The document outlines the key components of a Balanced Scorecard including objectives, measures, initiatives and cause-and-effect linkages across the four perspectives. It also discusses how to cascade the Balanced Scorecard throughout an organization.
This document outlines a 5-step methodology for implementing business process reengineering (BPR). The steps are: 1) Developing a process vision and objectives, 2) Defining the processes to reengineer, 3) Understanding and measuring existing processes, 4) Identifying IT levers, and 5) Designing and building a prototype. The methodology focuses on understanding current processes, creating a vision for improved processes, identifying how IT can help, and testing changes through prototypes before full implementation.
SharePoint MoneyBall: The Art of Winning the SharePoint Metrics Game by Susan...SPTechCon
This document discusses metrics for measuring the success of a SharePoint implementation. It emphasizes establishing business objectives and stakeholder needs before selecting metrics. Both quantitative metrics like time savings and qualitative metrics like user stories are recommended to capture different types of impacts. The metrics should be presented to stakeholders in a way that is relevant and collected at low cost.
Measurement Strategy for Software Companiesnazlitemu
This document outlines a measurement strategy for software companies. It discusses the challenges of measurement including data collection and analysis issues. Benefits include better project planning and process improvement. A real world example of defining goals, collecting data, analyzing results, and publishing capabilities is provided. Establishing a measurement strategy is difficult to implement but provides strong planning power if companies start with accurate data and a focus on improvement. Tools can help with data integrity and automation while human intuition prevents misleading interpretations.
The Agile Manager: Empowerment and AlignmentSoftware Guru
In today’s business climate, change occurs at an ever-increasing pace. Managers and executives are increasingly challenged to build an organization that is able to respond effectively to this change. This is the essence of agility.
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An overview of Santander's data journey in developing its strategic roadmap using enterprise architecture thinking, best practice data management frameworks and model driven initiatives.
References are given to find information on theory and frameworks with case study examples from Santander.
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2. What Is a KM Maturity Model (KMMM)?
• Analytic tool derived from the Capability Maturity
Model (CMM)
– CCM = an evolutionary roadmap for implementing vital practices
from domains of organizational process
– Developed by Software Engineering Institute (SEI) at Carnegie
Mellon University
• CMM extended to a “People Capability Maturity Model”
• Eventually evolved into Capability Maturity Model
Integrated (CMMI)
– Combines best practices from numerous CMMs
• Adapted for KM by Infosys, Siemens and others
SEI CMMI: http://www.sei.cmu.edu/cmmi/background/conops.html
Siemens: https://www.ct.siemens.com/en/technologies/ic/beispiele/anlagen/kmmm_flyer_en.pdf
Infosys: http://www.infotoday.com/KMWorld2000/presentations/kochikar.ppt 2
Other KMMM: http://www.kmsk.or.kr/admin/symposium/r_upload/A1-3_kankanhalli.pdf
3. Infosys KMMM Levels and Characteristics
• Default (lowest)
– Undefined
• Reactive
– Basic repeatability
• Aware
– Restricted data-driven decision-making; restricted level of internal
expertise; ability to manage virtual teams well
• Convinced
– Quantitative decision-making; high leverage of expertise;
productivity through knowledge sharing; proactive change response
• Sharing (highest)
– Strong ROI-driven decision-making; high ability to leverage new
ideas; ability to shape change in technology and business
environment
3
4. Siemens KMMM Levels and Characteristics
• Initial (lowest)
– Processes aren’t consciously planned or controlled, or seen as
connected
• Repeatable
– KM is recognized as important; KM pilot projects
• Defined
– Stable and practiced KM activities are integrated into work
processes; KM technology maintained; KM roles defined
• Managed
– Common strategy and standardized approaches to KM; robust
measurement of KM activities
• Optimizing (highest)
– KM adaptable to new conditions without dropping a maturity
level; KM encompasses internal and external changes; KM
measurements integrated into business measurements
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5. What Is Phased Measurement?
• Measurement that’s consonant with maturity level
– Consonant with objectives
– Consonant with capabilities
– Consonant with resources
• Measurement that progresses from the anecdotal to
the quantitative
– Anecdotal measurements may have greater relevance at lower
levels
• Demonstrate early success
• Gain support, generate enthusiasm
– Quantitative measurements have greater relevance at higher
levels
• Establish trends, validate processes
• Demonstrate ROI
A metric is what numbers signify: visits, page views, downloads, members, alerts, hours,
network nodes, publications, dollars, test scores, etc. A measurement is what's being
measured: site traffic, collaboration, distribution, cycle time, networking, knowledge sharing,
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revenue, learning, etc. A kilometer is a metric in the measurement of distance.
6. Phased Measurement for a CoP
Level Infosys Siemens Consonant
Measurements
Innovation, Monetary Benefits,
Intellectual Capital, Process
5 Sharing Optimizing
Improvement
Lessons Learned, Systematic
M Knowledge Transfer (Best
4 Convinced Managed
M
AA
Practices), Process
Acceleration, KM Integration in
TT
Processes
UU
KM Performance Objectives,
External Collaboration, Special
3 Aware Defined
RR
Interest Groups, After Action
II
Reviews, Social Networking
Community Activity, Content
TT
Management, Publication,
2 Reactive Repeated
YY
Training, Expertise Location,
Internal Collaboration
Ad hoc or anecdotal
1 Default Initial
6
7. Measurement Process Steps
• Identify desired outcomes
• Identify measurements
• Identify methods
• Gather metrics
• Analyze results
• Report results
• Manage the process
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8. Identify Unit Outcomes
• Align with organization objectives
– The organization can be a department, agency or smaller entity
that a unit supports
• Derive from the unit’s mission
– Measurements should validate “mission accomplished”
Metrics and measurement aren’t
ends in themselves. They need to
serve a larger purpose.
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9. Identify Measurements
This involves posing and answering questions, such as:
• “Which measurements can show progress toward
achieving an outcome?”
• “Which measurements will validate whether an
outcome has been achieved?”
• “Which measurements can help validate the value of
an outcome?”
– Example: improved performance can validate a learning
outcome
• “Which measurements can point the way to
innovation and new outcomes?”
– These often emerge in analysis of results that suggests
previously unconsidered outcomes
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10. Identify Methods
• Methods need to produce accurate (statistically
valid) measurements
• Methods need to be repeatable to enable trend
analysis
• Methods need to be cost-efficient and practical
– The cost of developing a method shouldn’t exceed the value of
the measurement
– It’s impractical to employ a method for which there are
insufficient resources to execute it properly
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11. Gather Metrics
• Key issues: frequency, credibility and ease of
analysis
• Progress toward achieving an outcome requires
systematic measurement
• Higher-value outcomes require tighter measurement (greater
frequency)
• Lower-value outcomes may permit looser measurement
(lesser frequency)
• Big claims require big documentation
– Large survey samples, trends vs. snapshots, statistics from
multiple sources
• Ease of analysis argues for quantitative metrics
– Yet qualitative analysis often reveals insights (i.e., new
knowledge) that numbers can’t yield
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12. Analyze and Report Results
• Technology can assist analysis to the extent that
numbers can be gathered and charted to produce
trendlines and such.
• But analysis also needs to include narrative
explanations of what the trendlines actually mean
• Knowledge gained from measurement is useless if
it’s not:
– Credible and actionable
– Put into the hands of actors (e.g., managers)
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13. Manage the Measurement Process
• Goal: continuous process improvement
• Periodic assessments:
– Value of methods
– Value of measurements
– Frequency of measurement
– Efficiency and quality of tools and methods
• The best tool in 2009 may not be the best tool in 2012
• Over time, methods become refined through use, or get superseded
by other methods
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14. KM Measurement Paradox
• As KM becomes more integrated into business, it
becomes more transparent—it’s what the
organization “just does”
– Increasingly difficult to determine specific impact of KM
– Increasingly difficult to identify KM practices as discrete
activities
– Increasingly difficult to measure
• Anecdotal measurements gain renewed relevance
– Assign a dollar value, e.g., monetary savings in cycle time
• Causal models can measure KM impact on
processes
– But time-consuming and labor-intensive
Causal models:
http://www.apqc.org/portal/apqc/ksn;jsessionid=GWN2NFBGM04AFQFIAJNCFEQ?paf_gear_id=contentgearhom
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e&paf_dm=full&pageselect=detail&docid=120722
15. About Anecdotal Metrics
• Anecdotal metrics derived from free-text responses
in surveys can be used . . .
– To reinforce what the numbers say
– To fill gaps in the numbers
– To validate general activities with specific examples
– To project future states
– To garner support for initiatives in the absence of widely
accepted standards or statistically valid forecasts
• Anecdotal metrics include . . .
– Success stories
– Case studies
– Industry benchmarks
– Expert testimony
– Management kudos
15
16. Workshop Project
• Identify the current, expected or previously planned
maturity level of your initiative
• Identify which measurements you should be
gathering at that level
– Concentrate on high-value measurements
– Discard high-cost/low-benefit measurements
• Identify which measurements are currently being
gathered
– Systematically and/or rigorously
– Occasionally and/or casually
• Close the gaps
– If it’s worth measuring, it’s worth measuring systematically and
rigorously
16
17. Sample Phased Measurement Workbook
Community of Practice Maturity Level: 3
Maturity Level 3 Attributes: General knowledge of KM practices; CoP portal site deployed with external access; members
profiled and trained to publish content; content managed; KM performance objectives established; special interest groups
Workbook is
forming; After Action Reviews practiced
Measurements Capability? Resources? Current? Systematic? Managed?
simple, quick
Community participation tracked Yes Yes Yes Yes Yes
Community particpation analyzed Yes Yes Yes Yes Yes
Portal traffic tracked Yes Yes Yes Yes Yes
and clean,
Portal traffic analyzed Yes Yes Yes Yes Yes
Best Practice capture Yes Yes Yes
consisting of
Best practice transfer Yes
Best practice reuse Yes
binary
Lessons learned capture Yes Yes
Lessons learned transfer Yes
checklists, like
Lessons learned reuse Yes
KM performance objectives Yes Yes Yes Yes
the Discrete
Internal collaboration Yes Yes Yes Yes Yes
External collaboration Yes Yes Yes
KM integration Yes Yes Yes
Data Analysis
Members profiled Yes Yes Yes
SME directories established Yes Yes Yes
Method used in
Education/training required Yes Yes
Process acceleration (anecdotal) Yes Yes
Six Sigma Lean
Process acceleration (quantified)
Innovation (anecdotal) Yes Yes
Innovation (quantified)
Monetary benefits (anecdotal)
Monetary benefits (quantified)
Intellectual capital (anecdotal) Yes Yes
Intellectual capital (quantified)
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18. Contact
Patrick Murphy
E-mail: patrick.murphy.email@gmail.com
LinkedIn: http://www.linkedin.com/pub/3/789/275
This presentation is licensed under the Creative Commons Attribution 3.0
Unported License: http://creativecommons.org/licenses/by/3.0/
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