Mattel implemented a shallow-dive analytics approach to gain visibility into key metrics and drive a more data-driven supply chain culture. Employees were overwhelmed by large amounts of data, so Mattel focused on a select few critical metrics in real-time, such as on-time delivery rates. This allowed executives to quickly identify issues and take action. The shallow-dive approach helped Mattel steer its large, complex supply chain and reinforce strategic goals using data rather than feelings. It also engaged employees by giving them access to the same real-time metrics seen by executives.
MIT report: How data analytics and machine learning reap competitive advantage.Nicolas Valenzuela
How Analytics and Machine Learning Help Organizations Reap Competitive Advantage
Produced MIT Technology Review, in Partnership with Google Analytics 360 Suite
The document discusses big data, including what it is, its history, current considerations, and importance. It notes that big data refers to large volumes of structured and unstructured data that businesses deal with daily. While the term is relatively new, collecting and storing large amounts of information for analysis has existed for a long time. Big data is now defined by its volume, velocity, and variety. Businesses can gain insights from big data analysis to make better decisions and strategic moves.
Information 3.0 - Data + Technology + PeopleHubbard One
The document provides an overview of big data and its transformational value. It discusses how big data can drive value through case studies in technology and collaboration between CTOs and CMOs. It also identifies impediments to realizing big data's transformational value and provides recommendations to overcome these impediments through enhanced data policies and security, infrastructure improvements, organizational change, access to data, and CTO-CMO collaboration.
Here in a single document is a compilation of my learnings and observations working with real customers over the past couple of years. My thought in consolidating these posts from LinkedIn was to provide an easy hyperlinked reference for leaders interested in breaking through the clutter to learn ways to leverage data for competitive advantage into 2017 and beyond.
The document discusses how most enterprises are investing in big data and real-time analytics initiatives to gain competitive advantages, but many IT organizations lack strategies to align these technologies with business goals. It describes how new data sources can provide richer customer insights and how real-time analytics can enable more timely operational decisions. However, organizations must evaluate whether their specific use cases require real-time data or would benefit more from traditional BI.
This white paper discusses criteria for evaluating strategic analytics platforms. It identifies 5 key questions: 1) Does the platform combine consumer-like cloud services with sophisticated analytics? 2) Can it access all relevant data? 3) Can the entire analytical process be completed in a single tool? 4) Does it allow for analysis of big data? 5) Does it provide the right analytics for decision making? The document argues that an ideal platform seamlessly integrates data access, analysis, and sharing capabilities to support rapid, data-driven decisions.
The document discusses how modern data analytics are transforming business. It introduces the topic and explains that data is doubling every two years and analytics are becoming more valuable. The rest of the document is organized into five sections that will discuss topics like how analytics are changing business models, new technology platforms, industry examples, research, and marketing. The introduction of each section provides a brief overview of what essays in that section will cover. The overall goal is to provide insights from different perspectives on how analytics are rapidly evolving and playing an increasingly important role.
This document discusses how businesses can use big data analytics to gain competitive advantages. It explains that big data refers to the massive amounts of data being generated every day from a variety of sources. By applying advanced analytics to big data, businesses can gain deeper insights into customer behavior and operations. The document provides examples of how industries like telecommunications, insurance, and entertainment are using big data analytics to improve customer service, detect fraud, and optimize marketing. It also outlines some of the key technologies that enable businesses to capture, store, and analyze big data at high volumes, velocities, and varieties.
MIT report: How data analytics and machine learning reap competitive advantage.Nicolas Valenzuela
How Analytics and Machine Learning Help Organizations Reap Competitive Advantage
Produced MIT Technology Review, in Partnership with Google Analytics 360 Suite
The document discusses big data, including what it is, its history, current considerations, and importance. It notes that big data refers to large volumes of structured and unstructured data that businesses deal with daily. While the term is relatively new, collecting and storing large amounts of information for analysis has existed for a long time. Big data is now defined by its volume, velocity, and variety. Businesses can gain insights from big data analysis to make better decisions and strategic moves.
Information 3.0 - Data + Technology + PeopleHubbard One
The document provides an overview of big data and its transformational value. It discusses how big data can drive value through case studies in technology and collaboration between CTOs and CMOs. It also identifies impediments to realizing big data's transformational value and provides recommendations to overcome these impediments through enhanced data policies and security, infrastructure improvements, organizational change, access to data, and CTO-CMO collaboration.
Here in a single document is a compilation of my learnings and observations working with real customers over the past couple of years. My thought in consolidating these posts from LinkedIn was to provide an easy hyperlinked reference for leaders interested in breaking through the clutter to learn ways to leverage data for competitive advantage into 2017 and beyond.
The document discusses how most enterprises are investing in big data and real-time analytics initiatives to gain competitive advantages, but many IT organizations lack strategies to align these technologies with business goals. It describes how new data sources can provide richer customer insights and how real-time analytics can enable more timely operational decisions. However, organizations must evaluate whether their specific use cases require real-time data or would benefit more from traditional BI.
This white paper discusses criteria for evaluating strategic analytics platforms. It identifies 5 key questions: 1) Does the platform combine consumer-like cloud services with sophisticated analytics? 2) Can it access all relevant data? 3) Can the entire analytical process be completed in a single tool? 4) Does it allow for analysis of big data? 5) Does it provide the right analytics for decision making? The document argues that an ideal platform seamlessly integrates data access, analysis, and sharing capabilities to support rapid, data-driven decisions.
The document discusses how modern data analytics are transforming business. It introduces the topic and explains that data is doubling every two years and analytics are becoming more valuable. The rest of the document is organized into five sections that will discuss topics like how analytics are changing business models, new technology platforms, industry examples, research, and marketing. The introduction of each section provides a brief overview of what essays in that section will cover. The overall goal is to provide insights from different perspectives on how analytics are rapidly evolving and playing an increasingly important role.
This document discusses how businesses can use big data analytics to gain competitive advantages. It explains that big data refers to the massive amounts of data being generated every day from a variety of sources. By applying advanced analytics to big data, businesses can gain deeper insights into customer behavior and operations. The document provides examples of how industries like telecommunications, insurance, and entertainment are using big data analytics to improve customer service, detect fraud, and optimize marketing. It also outlines some of the key technologies that enable businesses to capture, store, and analyze big data at high volumes, velocities, and varieties.
1) The document discusses how organizations need to develop data-driven decision making skills to capitalize on big data. MIT panelists said that relying on empirical data rather than intuition is important for success with big data.
2) The document outlines three basic business rules for capitalizing on big data according to Gartner analysts: define the value of big data for your company, take an inventory of your company's data sources, and adopt and adapt good big data ideas from other industries.
3) Education in statistical analysis and inference is important for making effective data-driven decisions with big data, but decisions should also be pushed closer to front-line workers where possible.
Unlocking the Value of Big Data (Innovation Summit 2014)Dun & Bradstreet
Big Data is central to the strategic thinking of today’s innovators and business executives as companies are scrambling to figure out the secret to transforming Big Data to Big Insight and that Insight into Action. As many companies struggle with the emerging technologies and nascent capabilities to discover and curate massive quantities of highly dynamic data, new problems are emerging in the form of how to ask meaningful questions that leverage the “V’s” of large amounts of data (e.g. volume, variety, velocity, veracity). In the Business-to-Business space, these challenges are creating both significant opportunity and ominous new types of risk. This presentation discusses how companies are reacting to these changes and provide valuable insight into new ways of thinking in a world with overwhelming quantities of data.
Analytics is all about course correcting the future. While this starts with accurate predictions of the future, without resultant actions steering the future toward company goals, knowing that future is academic. Successful companies must be grounded in successful data-based prescription. In this webinar, William will present a data maturity model with a focus on how analytic competitors outdo the competition by looking forward to a data-influenced future.
7 Steps for Applying Big Data Patterns to Decision MakingWiley
The document outlines a seven step method for applying big data patterns to decision making: 1) Understand existing data assets, 2) Explore the data to find patterns, 3) Design new decisions or business models based on patterns, 4) Design a data-driven business model if useful, 5) Transform business processes to leverage new insights, 6) Consider governance and security implications, and 7) Develop metrics and incentives to encourage fact-based decision making. The method involves building on each step with the goal of better decisions, new business models, or optimized processes.
Dimension Data is helping organizations accelerate their ambitions through technology innovation by providing expertise across data centers, networking, cloud, and cybersecurity. They take a services-led approach focused on understanding client needs and delivering business outcomes. Examples include creating a data analytics platform to transform the viewing experience of the Tour de France, adding IoT to monitor hospital equipment more closely, and implementing a connected conservation solution to help combat rhino poaching. Their goal is to optimize clients' digital transformations and hybrid IT environments.
Traditional approaches to handling disruptive change like big data analytics, such as resisting change or protecting existing business models, are ineffective in today's digital economy. By rapidly processing vast amounts of structured and unstructured data using big data tools, businesses can test new strategies faster through analytical sandboxes to better meet customer demands. Superfast in-memory computing is transforming industries by enabling new data-driven business models in areas like transportation. The ability to analyze unprecedented types and volumes of data in real time using tools like Apache Hadoop and Spark makes it possible to build more accurate predictive models and realize future gains.
How Companies Turn Data Into Business ValueJamie Hribal
This document discusses how businesses can capture, combine, and turn data into actionable insights. It summarizes Umbric Data Services, a company that provides data solutions to help businesses harness data to improve strategies, operations, and revenue. The document outlines common misconceptions about big data, how to ask the right questions to examine customer value, and ways companies are using data analytics, including to find new customers, increase retention, improve service, manage marketing, and track social media.
In this document, the five disruptive trends shaping the corporate IT landscape today are layed out. Out of the five, Big Data has the biggest potential to generate new sustainable competitive advantages. But the benefits will remain out of reach of many organizations as they struggle to adopt the technology, develop new capabilities, and manage the cultural change associated with the use of big data. This document offers a pragmatic approach to generating business value.
Practical analytics john enoch white paperJohn Enoch
This document discusses using data analytics to provide value to businesses. It recommends starting with smaller, more manageable data sets and business intelligence (BI) projects that have clear goals and can yield quick wins, like analyzing travel costs. While big data holds promise, the author advises focusing first on consolidating existing data that is stuck in silos and using BI to improve processes and save costs in areas employees already know need improvement. Starting small builds skills for larger initiatives and ensures analytics provides practical benefits.
Data is becoming an engine for many businesses in the information age, and every company needs to consider look at how that feels in their business model.
This an introductory guest lecture for students at Stockholm School of Entrepreneurship.
Creating a Data-Driven Organization, Crunchconf, October 2015Carl Anderson
Creating a data-driven organization requires developing a data-driven culture. Key aspects of a data-driven culture include having a strong testing culture that encourages hypothesis generation and experimentation, an open and sharing culture without data silos, a self-service culture where business units have necessary data access and analytical skills, and broad data literacy across all decision makers. Ultimately, an organization is data-driven when it uses data to drive impact and business results by pushing data through an analytics value chain from collection to analysis to decisions and actions. Maintaining a data-driven culture requires continuous effort as well as data leadership from a chief data or analytics officer.
Creating a Data-Driven Organization, Data Day Texas, January 2016Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
Fully embracing a BI tool can mean the difference between the full payoff of your data analytics and returns that are just so-so. Learn how to avoid BI pitfalls and boost BI adoption to become a truly data driven organisation.
Is Your Company Braced Up for handling Big Datahimanshu13jun
Has your company recently launched new product or company is concerned with the poor sales figure or want to reach new prospects and also reduce the existing customers' attrition, then this thought evoking short hand guide is available for you to explore.
While nearly 60% of executives expect big data to disrupt their industries, only 13% have full-scale big data initiatives and only 8% consider their initiatives very successful. Most organizations lack a well-defined roadmap with milestones and timelines for their initiatives, and 55% have scattered resources or a decentralized model. Additionally, 74% do not have well-defined criteria for selecting use-cases and 67% lack defined success metrics. In contrast, those organizations with a well-defined roadmap, criteria for selecting use-cases, and defined success metrics are tasting more success with their big data initiatives.
Recently, Oracle and Accenture polled some 200 CFOs and senior finance executives about
their strategies for improving the management reporting process. More than a third—41%— said selecting the right analytics tools and technologies was their top concern.
This webinar was hosted by Gramener's CEO/Co-Founder, Anand S, and Ganes Kesari, Head of Analytics/Co-Founder on how data can help firms recover quickly throughout the recession and recovery period.
Who should watch this webinar :
Analytics Leaders, Business Leaders, CDOs, CTOs, etc.
Few takeaways :
-Which aspects of your company could benefit the most from a data-driven response?
-A strategy for identifying use cases that will provide the most value for the money.
How to use data in creative ways to uncover new market opportunities and customers.
Objectives :
-Data's utility in COVID situation
-How data science may assist you in navigating the recession
-Gramener's industry case studies to assist businesses in responding to COVID-19
Full Webinar: https://info.gramener.com/recession-proofing-your-business-with-data
To know more from industry leaders visit our official website: https://gramener.com/
Baking analytics into the culture of an organization is not always the easiest thing because it doesn't come intuitively to humans. This presentation was given at Kumpul co-working space in Sanur, Bali and it involves a sharing of my team's experience in building a data-driven culture at TradeGecko.
Lecture on Data Science in a Data-Driven Culture Johan Himberg
The document discusses the importance of a data-driven culture for businesses. It provides the following key points:
1. Research has shown that companies that emphasize data-driven decision making have 5-6% higher productivity and output than comparable companies. This relationship also appears in other financial metrics like return on equity.
2. Data science draws from various fields like operations research, probability theory, analytics, and computer science. It is used for optimal decision making, handling uncertainties, generating insights from data, and implementing analytical solutions.
3. When adopting a data-driven approach, companies should focus on specific business goals and KPIs rather than just collecting data. Iterative testing is also important to measure impact
The New Data Dynamics How to turn data into a competitive advantageFiona Lew
This document discusses the new data dynamics that businesses face as data becomes more abundant, diverse, and interconnected. It argues that businesses need to shift from an app-centric view of data to a data-centric view where data is prepared and optimized for many uses across applications. Adopting the principles of the new data dynamics, such as embracing diverse data sources, capturing relationships between data, and automating data management, will allow businesses to gain strategic advantages from their data.
1) The document discusses how organizations need to develop data-driven decision making skills to capitalize on big data. MIT panelists said that relying on empirical data rather than intuition is important for success with big data.
2) The document outlines three basic business rules for capitalizing on big data according to Gartner analysts: define the value of big data for your company, take an inventory of your company's data sources, and adopt and adapt good big data ideas from other industries.
3) Education in statistical analysis and inference is important for making effective data-driven decisions with big data, but decisions should also be pushed closer to front-line workers where possible.
Unlocking the Value of Big Data (Innovation Summit 2014)Dun & Bradstreet
Big Data is central to the strategic thinking of today’s innovators and business executives as companies are scrambling to figure out the secret to transforming Big Data to Big Insight and that Insight into Action. As many companies struggle with the emerging technologies and nascent capabilities to discover and curate massive quantities of highly dynamic data, new problems are emerging in the form of how to ask meaningful questions that leverage the “V’s” of large amounts of data (e.g. volume, variety, velocity, veracity). In the Business-to-Business space, these challenges are creating both significant opportunity and ominous new types of risk. This presentation discusses how companies are reacting to these changes and provide valuable insight into new ways of thinking in a world with overwhelming quantities of data.
Analytics is all about course correcting the future. While this starts with accurate predictions of the future, without resultant actions steering the future toward company goals, knowing that future is academic. Successful companies must be grounded in successful data-based prescription. In this webinar, William will present a data maturity model with a focus on how analytic competitors outdo the competition by looking forward to a data-influenced future.
7 Steps for Applying Big Data Patterns to Decision MakingWiley
The document outlines a seven step method for applying big data patterns to decision making: 1) Understand existing data assets, 2) Explore the data to find patterns, 3) Design new decisions or business models based on patterns, 4) Design a data-driven business model if useful, 5) Transform business processes to leverage new insights, 6) Consider governance and security implications, and 7) Develop metrics and incentives to encourage fact-based decision making. The method involves building on each step with the goal of better decisions, new business models, or optimized processes.
Dimension Data is helping organizations accelerate their ambitions through technology innovation by providing expertise across data centers, networking, cloud, and cybersecurity. They take a services-led approach focused on understanding client needs and delivering business outcomes. Examples include creating a data analytics platform to transform the viewing experience of the Tour de France, adding IoT to monitor hospital equipment more closely, and implementing a connected conservation solution to help combat rhino poaching. Their goal is to optimize clients' digital transformations and hybrid IT environments.
Traditional approaches to handling disruptive change like big data analytics, such as resisting change or protecting existing business models, are ineffective in today's digital economy. By rapidly processing vast amounts of structured and unstructured data using big data tools, businesses can test new strategies faster through analytical sandboxes to better meet customer demands. Superfast in-memory computing is transforming industries by enabling new data-driven business models in areas like transportation. The ability to analyze unprecedented types and volumes of data in real time using tools like Apache Hadoop and Spark makes it possible to build more accurate predictive models and realize future gains.
How Companies Turn Data Into Business ValueJamie Hribal
This document discusses how businesses can capture, combine, and turn data into actionable insights. It summarizes Umbric Data Services, a company that provides data solutions to help businesses harness data to improve strategies, operations, and revenue. The document outlines common misconceptions about big data, how to ask the right questions to examine customer value, and ways companies are using data analytics, including to find new customers, increase retention, improve service, manage marketing, and track social media.
In this document, the five disruptive trends shaping the corporate IT landscape today are layed out. Out of the five, Big Data has the biggest potential to generate new sustainable competitive advantages. But the benefits will remain out of reach of many organizations as they struggle to adopt the technology, develop new capabilities, and manage the cultural change associated with the use of big data. This document offers a pragmatic approach to generating business value.
Practical analytics john enoch white paperJohn Enoch
This document discusses using data analytics to provide value to businesses. It recommends starting with smaller, more manageable data sets and business intelligence (BI) projects that have clear goals and can yield quick wins, like analyzing travel costs. While big data holds promise, the author advises focusing first on consolidating existing data that is stuck in silos and using BI to improve processes and save costs in areas employees already know need improvement. Starting small builds skills for larger initiatives and ensures analytics provides practical benefits.
Data is becoming an engine for many businesses in the information age, and every company needs to consider look at how that feels in their business model.
This an introductory guest lecture for students at Stockholm School of Entrepreneurship.
Creating a Data-Driven Organization, Crunchconf, October 2015Carl Anderson
Creating a data-driven organization requires developing a data-driven culture. Key aspects of a data-driven culture include having a strong testing culture that encourages hypothesis generation and experimentation, an open and sharing culture without data silos, a self-service culture where business units have necessary data access and analytical skills, and broad data literacy across all decision makers. Ultimately, an organization is data-driven when it uses data to drive impact and business results by pushing data through an analytics value chain from collection to analysis to decisions and actions. Maintaining a data-driven culture requires continuous effort as well as data leadership from a chief data or analytics officer.
Creating a Data-Driven Organization, Data Day Texas, January 2016Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
Fully embracing a BI tool can mean the difference between the full payoff of your data analytics and returns that are just so-so. Learn how to avoid BI pitfalls and boost BI adoption to become a truly data driven organisation.
Is Your Company Braced Up for handling Big Datahimanshu13jun
Has your company recently launched new product or company is concerned with the poor sales figure or want to reach new prospects and also reduce the existing customers' attrition, then this thought evoking short hand guide is available for you to explore.
While nearly 60% of executives expect big data to disrupt their industries, only 13% have full-scale big data initiatives and only 8% consider their initiatives very successful. Most organizations lack a well-defined roadmap with milestones and timelines for their initiatives, and 55% have scattered resources or a decentralized model. Additionally, 74% do not have well-defined criteria for selecting use-cases and 67% lack defined success metrics. In contrast, those organizations with a well-defined roadmap, criteria for selecting use-cases, and defined success metrics are tasting more success with their big data initiatives.
Recently, Oracle and Accenture polled some 200 CFOs and senior finance executives about
their strategies for improving the management reporting process. More than a third—41%— said selecting the right analytics tools and technologies was their top concern.
This webinar was hosted by Gramener's CEO/Co-Founder, Anand S, and Ganes Kesari, Head of Analytics/Co-Founder on how data can help firms recover quickly throughout the recession and recovery period.
Who should watch this webinar :
Analytics Leaders, Business Leaders, CDOs, CTOs, etc.
Few takeaways :
-Which aspects of your company could benefit the most from a data-driven response?
-A strategy for identifying use cases that will provide the most value for the money.
How to use data in creative ways to uncover new market opportunities and customers.
Objectives :
-Data's utility in COVID situation
-How data science may assist you in navigating the recession
-Gramener's industry case studies to assist businesses in responding to COVID-19
Full Webinar: https://info.gramener.com/recession-proofing-your-business-with-data
To know more from industry leaders visit our official website: https://gramener.com/
Baking analytics into the culture of an organization is not always the easiest thing because it doesn't come intuitively to humans. This presentation was given at Kumpul co-working space in Sanur, Bali and it involves a sharing of my team's experience in building a data-driven culture at TradeGecko.
Lecture on Data Science in a Data-Driven Culture Johan Himberg
The document discusses the importance of a data-driven culture for businesses. It provides the following key points:
1. Research has shown that companies that emphasize data-driven decision making have 5-6% higher productivity and output than comparable companies. This relationship also appears in other financial metrics like return on equity.
2. Data science draws from various fields like operations research, probability theory, analytics, and computer science. It is used for optimal decision making, handling uncertainties, generating insights from data, and implementing analytical solutions.
3. When adopting a data-driven approach, companies should focus on specific business goals and KPIs rather than just collecting data. Iterative testing is also important to measure impact
The New Data Dynamics How to turn data into a competitive advantageFiona Lew
This document discusses the new data dynamics that businesses face as data becomes more abundant, diverse, and interconnected. It argues that businesses need to shift from an app-centric view of data to a data-centric view where data is prepared and optimized for many uses across applications. Adopting the principles of the new data dynamics, such as embracing diverse data sources, capturing relationships between data, and automating data management, will allow businesses to gain strategic advantages from their data.
1. Percobaan ini bertujuan untuk mengukur nilai biner dan hexa-desimal dari rangkaian analog to digital converter ADC0804 dengan mengubah berbagai tegangan masukan menjadi kode keluaran digital.
2. Hasil pengukuran dicatat dalam tabel yang menunjukkan hubungan antara tegangan masukan analog dan nilai biner serta hexa-desimal yang dihasilkan.
3. Percobaan ini melibatkan pengaturan tegangan referensi dan masukan serta pengam
Ken Lockett is a web designer and developer who has pursued various creative passions through art, music, photography, and computer classes. He educated himself on computers and enrolled in programming school, but left to pursue corporate work before returning to his creative passion of web design and development. He has professional experience in graphic design, photography, and web design and development, and his ideal job position is as a full stack developer, hoping to join a new team.
Las hierbas se han utilizado durante miles de años para ayudar a perder peso de forma natural. Algunas hierbas como la onagra y la flor de la reina pueden suprimir el apetito y ayudar a controlar el peso cuando se usan junto con una dieta saludable y ejercicio. Las hierbas ofrecen nutrientes y pueden ser una alternativa eficaz para perder peso, aunque se debe tener precaución y no tomar demasiadas hierbas a la vez.
Asobancaria es una asociación gremial privada que representa los intereses del sector financiero colombiano. Está integrada por bancos comerciales nacionales y extranjeros, corporaciones financieras e instituciones oficiales especiales. Su objetivo es promover la modernización del sector financiero y apoyar su desarrollo.
Este proyecto de investigación busca obtener hidrógeno a partir del agua para usarlo como combustible alternativo. Los objetivos incluyen investigar métodos para transformar el agua en hidrógeno, realizar el procedimiento más adecuado para obtener hidrógeno, innovar métodos existentes, e investigar formas de almacenar el hidrógeno para su uso como combustible. El documento también revisa varios métodos para producir hidrógeno a partir del agua, incluyendo electrólisis y procesos biológicos y químicos
Dokumen tersebut memberikan beberapa cara spiritual untuk meraih berkah dan keberuntungan, mendapatkan pasangan hidup, serta mendapatkan wajah yang bercahaya dan menarik jodoh. Cara-cara tersebut meliputi membaca doa dan ayat-ayat suci Al-Qur'an selama 40 hari berturut-turut.
PRIMERA PARTE ENTREGABLE PRODUCCIÓN DE DOCUMENTOSLaura Mejia
Este documento presenta un proyecto realizado por el SENA y Remington para generar soluciones administrativas. El proyecto busca producir documentos siguiendo la normativa y legislación vigente. Se explican conceptos como certificados y constancias, incluyendo sus partes, estructura y utilidad.
Este documento resume información sobre varios importantes sitios turísticos mundiales como Machu Picchu, Chichen Itza, las Cataratas del Niágara, la Torre Eiffel, el Taj Mahal, el Burj Khalifa y el National Mall, describiendo brevemente sus características históricas y arquitectónicas.
El documento describe los miles de químicos venenosos que contiene un cigarrillo, incluyendo nicotina, arsénico, monóxido de carbono y cianuro de hidrógeno. Cada vez que se inhala el humo, estas sustancias viajan por la sangre y causan daño en todo el cuerpo. Los cigarrillos están diseñados para crear dependencia, y el fumador es la persona que con más frecuencia consume una droga cada 25 minutos.
La Unión Europea ha propuesto un nuevo paquete de sanciones contra Rusia que incluye un embargo al petróleo. El embargo gradual prohibiría las importaciones de petróleo ruso en seis meses y de productos refinados para finales de año. Los líderes de la UE debaten el paquete de sanciones esta semana con el objetivo de aumentar la presión sobre Rusia para que ponga fin a su invasión de Ucrania.
Este documento presenta a un grupo de amigos colombianos que estudian en el Colegio Cooperativo San Antonio de Prado en Medellín. El grupo desea crear videojuegos accesibles ya que algunos son caros o difíciles de descargar. Ellos tienen conocimientos básicos de desarrollo de videojuegos y planean usar programas como Unity 3D para crear juegos en 3D. Su meta es mejorar la experiencia de los jugadores y la industria de los videojuegos en general.
La calidad de la información en entornos digitales es importante evaluar usando criterios como la autoría, actualización, contenido, accesibilidad, funcionalidad, navegabilidad y diseño. La evaluación asegura que los usuarios puedan encontrar información fiable y relevante. Los métodos incluyen profesionales que evalúan sitios web y expertos que comparten recursos evaluados en sus áreas de especialización.
Dreamweaver es un software de edición web que permite crear páginas profesionales de forma visual y sencilla sin necesidad de codificar a mano. Ofrece funciones para diseñar sitios web incorporando elementos como tablas, marcos, capas y comportamientos JavaScript. Incluye también herramientas de FTP para trabajar y actualizar páginas en un servidor de manera integrada.
The document discusses the emerging role of the chief data officer (CDO) in organizations. It summarizes that as data and analytics have become more important, having a single leader dedicated to developing an enterprise-wide data strategy is necessary to fully leverage data. The CDO can envision how to use data across the organization, activate real change by using data to impact the business, and transform the culture to be more data-driven. The document outlines barriers to establishing the CDO role but emphasizes the value they provide in making organizations more competitive through their data.
CONNECTING THE DOTS - EPPM Board Write Up FinalYasser Mahmud
The Oracle EPPM Board discussed extracting strategic insights from project portfolio data. There was consensus that most companies have improved data generation but face challenges in analyzing patterns to predict outcomes and link insights to strategy. Executives need concise information to guide investment decisions, but also require softer contextual factors beyond numbers. The future of project management involves disseminating intelligence across organizations as knowledge centers rather than modifying data internally. Aligning information to consumption patterns will also be key as the next generation of workers expects freedom in accessing and sharing resources.
Thinking Small: Bringing the Power of Big Data to the MassesFlutterbyBarb
Thinking Small: Bringing the Power of Big Data to the Masses via Adobe with the results of improved access to insights, better user experiences, and greater productivity in the enterprise.
BIG DATA is having an enormous impact on the profile of workforces around the world. If you've ever seen the technology and experienced the impact it has on the pace of innovation in a business then the predictations made by McKinsey Global Institute will come as no surprise ( and just in case you've been on holiday for around two years, McKinsey is suggesting that by 2018 the US will face a shortfall of close to 200,000 analysts and 1.5 million managers with the right skills. In this presentation I outline the impact of BIG DATA on workforce design. I hope you find it informative and fun to read. Ian.
Ideal Marketing Solutions provides a business intelligence solution that helps companies access critical performance data to improve efficiency and competitiveness. The solution allows mid-sized businesses to access advanced analytics tools previously only affordable for large companies. It provides real-time access to data and customizable reporting and analytics to help executives make evidence-based decisions. The agile, web-based platform delivers actionable intelligence to the right people at the right time to optimize processes and strategies.
Ideal Marketing Solutions provides a business intelligence solution that helps companies access critical performance data to improve efficiency and competitiveness. The solution allows mid-sized businesses to access advanced analytics tools previously only affordable for large companies. It provides real-time access to data and customizable reporting and analytics to help executives make evidence-based decisions. The agile, web-based platform delivers actionable intelligence to the right people at the right time to optimize processes and strategies.
The document discusses how established companies can become more data-driven through a strategic transformation. It provides examples of how the Spanish hotel chain Ilunion and Transport for London used data analytics to improve decision making. The key steps for companies include linking data initiatives to business goals, creating a data-driven culture where all employees use data in their work, and implementing technology infrastructure to make relevant data and insights accessible. Becoming truly data-driven requires addressing cultural and technical barriers and viewing data as a strategic asset.
BIG DATA has to be the hottest topic in the boardrooms of blue chip companies - organizations with access to vast amounts of data that promises to have a massive impact on their businesses... But if you're not Amazon, Google, Walmart and Tesco what does it mean to your business? What about MOTOR DEALERS for example?
This whitepaper aims to assist Chief Data Officers in promoting a data-driven culture at their
organization, helping them lead the enterprise on a digital transformation journey backed by
analytical insights.
Few decades ago, Managers relied on their instincts to take business decisions. They could afford to make mistakes and learn from it. Today, the scope for learning from mistakes is very minimal. Instincts should be backed by data to minimise mistakes.
Technological advancements, in addition to opening new channels of communication with customers, have also enabled organizations to collect vital information about their businesses with customers. But, have these organizations fully leveraged this data?
Today, Organizations make use of data for business decisions, but the data is not close enough to the customer to reap maximum benefit. In many cases, importance is not given to the granularity of data. The probability of “customer centric” decisions being right could be high, if the top management makes better use of the end user customer data (such as point of sale data, voice of customer, social media buzz etc.) to devise business strategies.
Data analytics can immensely impact and improve a business’s decision-making processes. From better strategies to profits, explore the full scope of analytics.
Data analytics can immensely impact and improve a business’s decision-making processes. From better strategies to profits, explore the full scope of analytics.
How well do you measure the effectiveness of social media00000000A1
Organizations can better manage social media and big data growth through analytic technologies that save time and focus on innovation and strategy. The CPM metric measures advertising cost per thousand impressions and while imperfect, can prove the value of social media outreach. Managing social media posts and interactions is made easier through tools that analyze topics and customer interaction to adjust strategies. When dealing with large loyalty program data, overcoming big data challenges involves testing specific experiments and asking the right questions to solve issues. It is important to correctly measure analytics, identify false data and erratic patterns to derive return on investment and improve automation and data mining capabilities by learning more about customers.
How well do you measure the effectiveness of social media00000000A1
Organizations can save more time to focus on innovation, strategy and other growth areas by better managing social media and big data growth with analytic technologies. Senior managers can become change catalysts and see how initiatives evolve. It can also be difficult to understand the value of social media platforms like Facebook pages or Twitter, but tools can help provide a picture of social performance by indicating hot and cold topics to adjust strategies to generate more customer interaction. When dealing with large amounts of loyalty program or other customer data, identifying errors in measuring analytics and erratic patterns is better than no identification to resolve issues through testing specific experiments and acting as a problem solver.
Go Figure: Data Processing Is Needed but Analytical Insight Is the Real ValueStatPro Group
The document discusses the changing role of middle offices in asset management firms. Middle offices can no longer just process numbers and must provide strategic insights through data analysis. To do this effectively, middle offices need clean and accurate data as well as strong analytical capabilities. Smaller boutique asset management firms are well-positioned to transform their middle offices due to their flexibility and agility. Embracing new technologies, they can create a single, clean data set and provide the accurate analytics and tracking needed to inform strategic decision-making.
The document discusses plans by the HSCIC to develop a new Data Services Platform (DSP) that could transform how health and care data is managed and analyzed in the UK. The DSP is intended to create a modern infrastructure that allows the HSCIC to better utilize the growing amounts of data being generated, provide more valuable analytics and insights, and improve customer services. Interviews with HSCIC executives indicate they believe the DSP could enable more efficient operations, enhanced analytical capabilities, and help achieve the vision of a centralized national health data repository. There is optimism that lessons from past attempts can ensure successful delivery of the DSP to meet both current and future needs.
Everyone's talking about big data – getting our arms around it and putting it to work for us. This paper summarizes a panel discussion at the 2012 SAS Financial Services Executive Summit where industry leaders shared their ideas about big data and what their organizations are doing with it. Aditya Bhasin from Bank of America talked about how to extract more value from the data you already have, even if it's just a fraction of what's out there. Robert Kirkpatrick, who leads the UN Global Pulse initiative, talked about how data can help us better understand global economies and human welfare. Charles Thomas, a market research and analytics executive at USAA, described how his company is navigating the shift to more real-time and predictive analysis. Request the full whitepaper at: http://www.sas.com/reg/wp/corp/50060?&utm_source=NAFCUServices&utm_medium=landingpage&utm_campaign=SASwhitepaper82912. More info at: www.nafcu.org/sas
ISM Silicon Valley Webinar Spend Analysis Key to Purchasing SuccessBill Kohnen
Presentation including questions and answers from webinar cosponsored by ISM Silicon Valley and purchasing solution provider Cloud Buy. Discussion of why Spend Analysis is the most important process for business to business purchasing professionals and what criteria should be considered when considering options. Includes contact information for free trial.
The Food Safety Modernization Act (FSMA) aims to modernize food safety regulations in the US by shifting the focus from reactive responses to foodborne illness to preventative practices. The FDA has proposed revisions to four FSMA rules covering produce safety, preventive controls for human and animal food, and foreign supplier verification. Stakeholders have raised concerns that the rules could burden small farms and businesses. The final impact will depend on how flexible the rules are in accommodating different farming systems. The changes are also expected to increase liability for all parties in the food supply chain.
The passage describes Intel's Supply Chain and STEM Volunteer Outreach program, which aims to address the growing supply chain talent gap. It began as a grassroots effort led by Cheryl Dalsin and has expanded globally with the help of Intel volunteers. The program introduces K-12 students and educators to supply chain concepts through hands-on activities that highlight STEM principles. It hopes to inspire interest in supply chain careers and make "supply chain" a more common term. The program has experienced rapid growth but now seeks support from other companies and organizations to meet rising demand.
Jack Welch was the legendary CEO who led GE to immense success over two decades. In this interview, Welch discusses his management philosophies and strategies that contributed to GE's growth. He emphasizes building great teams, being candid with employees, and getting the best ideas from everyone. Welch also provides advice for advancing one's career, such as asking for feedback, taking on tough assignments, and overdelivering on responsibilities. The interview covers Welch's new book on getting an "real-life MBA" and practical career advice.
1) Supply chain management professionals face constantly changing challenges from heightened customer expectations, evolving business models, and pressure to increase productivity. New technologies can help with collaboration and efficiency but also increase complexity.
2) E-commerce is driving significant increases in shipping volume, with estimates of 20% growth by 2018. This is challenging carriers and companies to reinvent delivery approaches to meet demanding customer expectations.
3) To adapt successfully, companies must invest in their people through leadership development and skills training, fostering critical competencies like problem solving, flexibility, and creativity. Collaboration between companies can also help address complexities through data sharing and standardized processes.
This document discusses cross-training in organizations. It describes cross-training as providing employees training or experience in different areas of a company to gain new skills, promote information sharing, and allow companies to continue operating if an employee is absent. The benefits of cross-training include improved communication, collaboration, and filling skills gaps. Effective cross-training programs involve hands-on learning, identify strong teachers as trainers, and align with a company's culture and goals. The goal of cross-training should be clear, such as skills development that matches a company or career objective.
This document discusses product recalls and how companies can mitigate risks and losses. It describes Blue Bell Creameries' recall of all its ice cream products in 2015 after a listeriosis outbreak linked to its desserts caused illnesses and deaths. Blue Bell took corrective actions like thoroughly cleaning plants and improving sanitization procedures. The document also discusses a recall by Trek Bicycle of nearly 1 million bikes due to a risk of their front wheels separating. Both companies worked closely with regulators during their recalls. The impacts of recalls, importance of prevention, and role of social media are also addressed.
This document discusses the challenges facing global supply chains due to inadequate infrastructure in many countries. It notes that while trade and transportation infrastructure have enabled more flexible supply networks, growth is putting pressure on aging infrastructure in both developed and developing nations. Experts cite issues like traffic congestion, limited port and airport capacity, and insufficient road and rail systems. To address infrastructure constraints, the document advocates for collaborative planning among stakeholders and effective communication to policymakers about the economic impacts of infrastructure investments.
Business leaders must find new ways to maintain customer bases in today's competitive marketplace while reducing costs without compromising quality. An effective approach is to focus on the total customer experience through supply chain and operations management. Customer experience management requires integrating marketing, sales, technology, supply chain, and social media to create a consistent brand and be responsive to customers. Companies must listen to customer feedback through various channels to continuously improve processes and better satisfy customers. Maintaining loyal customers is important for generating repeat business and revenue growth.
2. in the Shallows
apics.org/magazine 45
Overcome the great barriers
to a data-driven supply chain
ByElizabethRennie
MultinationaltoymanufacturerMattelis
a company of dreams and aspirations.
“We’re all about children; we’re all
about play; we’re all about creativity,
imagination, and trust,” says Peter
Gibbons, chief supply chain officer
and executive vice president. “At the
same time, we run a supply chain
with 40,000 people and 11 factories.
Fifty percent of our product comes
from the outside. We make 20,000
injection-molding tools a year and
have 25,000 global [stockkeeping
units]. So, within this fantastic,
sensitive, engaged culture, we also
need to create an incredibly effective
supply chain machine.”
3. 46 September/October 2016
Because Mattel is an exceedingly seasonal business,
as many as 80 percent of its products are modified
annually. “We can’t just hope it all works out; we need
a data-driven mentality that allows us to make better
decisions and drive the right kind of improvement,”
Gibbons says.
To achieve this goal, Mattel leaders recently initiated
a shift to a more data-driven culture. Their goal is to
effectively use data to achieve a structured approach to
managing the supply chain. Gibbons explains that, prior
to this initiative, Mattel had “lost the knack of using
metrics” to improve performance. In fact, the company
did not employ a consistent set of criteria to drive its
supply chain function. Determining how to change that
and gain visibility into core metrics was an essential
conversation among company decision makers.
Gibbons and his colleagues made some key discoveries
during these dialogues: First, it was clear that employ-
ees were drowning in a sea of data, reports, emails, and
spreadsheets. Furthermore, people lacked a coherent
approach to what to measure, how to measure it, and
how these practices should drive business plans. Senior
managers saw that it would be necessary to reevaluate
metrics, dashboards, and overall strategy; get everyone
on the same page; reinvigorate interest in data; and create
consensus over the handful of metrics that matter most.
“Our supply chain is so big, so complicated—and it
changes so much—it was never going to be optimized
unless we could steer it with a data-driven mind-set,”
Gibbons says.
Calming the waters
Another critical goal for Mattel leaders is the ability to meas-
ure performance in a manner that provokes improvement.
Furthermore,they believe that it’s unnecessary to know
every level of detail in order to identify what deserves their
attention.As such,Gibbons says a shallow-dive approach
was the right choice because it provides just enough infor-
mation to recognize when they should to do something.
“We don’t need 10 different customer service metrics
if we take a core on-time-in-full metric. That gives us
enough of an indication of if we’re on track or not,”
Gibbons explains.“Same with things like first-pass yield.
… We just need to know if we are on track. Then we can
take a deep dive elsewhere by brand or by product group
as the data tells us.”
It was this desire to zero in on only the most essen-
tial metrics that led Gibbons to select Sage Clarity’s
cloud-based One View.“It really appealed to our team
that they weren’t going to be inundated with a massive
database; rather, they would have a practical solution for
choosing the core, vital few, real-time issues to focus on
and get absolutely right,” Gibbons says.“It also allows
us to talk numbers and data, rather than feelings and
instincts and stories.”
Shallow-dive analytics is a new approach to managing
the enormity of big data and the resulting informa-
tion overload via a one-click, quick review of only the
information that is most pertinent to business objec-
tives. By focusing on key performance indicators (KPIs),
proponents believe that the shallow-dive concept can
enhance supply chain performance through better and
less-time-consuming data management. Importantly,
this real-time information also enables organizations to
reduce the number of KPIs used to manage the business.
The basic idea is that users swim, rather than sink,
through the deep ocean of data and then decide where
to dive in. In this way, executives and knowledge workers
are better able to focus on crucial business metrics that
provide high-level insight and direction. These direct
and indirect KPIs can strengthen people’s understand-
ing of issues and provide essential findings for enhanced
decision making.
“A common misconception is that, the closer you get
a metric down to an individual, granular level, the more
real time it becomes; and then, conversely, the higher
level a metric is, the less real time it is,” says John Oskin,
CEO of Sage Clarity Solutions.“With today’s architec-
ture around data and solutions, the reality is that you
can get real-time data from any level.”
Oskin sees many businesses making a common
mistake with business intelligence: They treat data as
its own problem and act as if the same dashboards and
user experiences apply to everyone.“It really boils down
to the fact that [data] should be organized differently
for different stakeholders,” he explains.“Senior-level
Employees were drowning
in a sea of data, reports,
emails, and spreadsheets.
4. apics.org/magazine 47
managers don’t want a deep
dive. … They want to be able
to skim the information, quickly
draw a conclusion, and take action.”
At Mattel, this approach is cre-
ating a clearer understanding of the
most important metrics. “It’s reinforc-
ing our strategic imperatives and why
we’re focused so strongly in certain areas,”
Gibbons says. “And it’s reinforcing our mes-
saging because people are seeing in real time
with real data that that’s what we care about.”
Although the solution is targeted toward
executives, it can generate engagement and
responsiveness at every level of the organization
because real-time KPIs put information at people’s
fingertips. All employees know that senior managers
are looking at the KPIs, so everyone is motivated to
get in front of the data, Oskin explains.
“It drives behavior,” he adds.“Say an executive
looks into how much downtime a plant had on a
production line. He can pick up the phone and call
that plant manager and ask,‘Why is line four down
today?’ That’s pretty unsettling. People want to know
how the data got to the senior management suite. Then,
people want the information too so they can see what
[executives are] seeing and react.”
Sean McClure, director of data science at analytics
solutions provider Space-Time Insight, also sees the
value in making sure analytics results are readily avail-
able to people on the front lines. His firm aims to help
clients overcome their data-management struggles by
teaching users how to employ data to make valuable
operational improvements.“The best way to do this is
by embedding analytics into applications that are as
easy to use as possible … and understanding which
at-a-glance visualizations will accelerate decision
making,” he says.“Once applications and solu-
tions with these properties are developed, we find
customers are able to easily operationalize them
beyond their originally intended user base.”
McClure recognizes the value of the
shallow-dive concept, but also worries that
it could contradict a user’s ability to apply
certain machine learning and analytics
that are generally more effective with
large data sets. “Shallow diving has a
In addition to the shallow-dive movement,
Sage Clarity CEO John Oskin notes several
important developments that are changing
the supply chain landscape. “The biggest
trend we have seen is mobile,” he says. “How
data is consumed has really changed. People
want to review data anytime on their time.”
The prevalence of mobile devices in today’s
workforce is evident. But what Oskin finds
most interesting is the usability and general
adoption of mobile apps, such as metric
tools that can analyze individual key per-
formance indicators (KPIs). That provides
information at a faster interval, enabling
organizations to react to challenges more
swiftly. “Rather than making a poor-quality
product for one week,” he explains, “perhaps
this poor-quality production can be stopped
in one hour.”
Enabling teams to share these KPIs and
analytics across the organization is another
noteworthy shift that can bring about
greater supply chain productivity. Oskin
says this type of collaboration makes it
possible to transform meeting topics from,
“What happened?” to figuring out, “What
do we do?” He notes, “The best organiza-
tions review data in advance and focus on
action during the meetings.”
Key Data-Analytics Trends
apics.org/magazine 47
5. 48 September/October 2016
role that is dependent on the
information and insights
truly needed to solve a cus-
tomer's specific problems,”
he says. “And it needs
to support their pain
points and objectives
balanced against costs
and development time.”
An integral piece of the
data-overload dilemma
is context—an issue that
can be difficult for supply
chain organizations to solve.
McClure says that a clear
understanding of context can
ensure that only the essential
data is correlated and analyzed in
order to generate insights and alerts
that pinpoint useful information with-
out overwhelming end users. He suggests
that connecting employees with essential
data is an alternative approach to overtly skim-
ming the surface.“This is a very effective approach
that solves the data-management problem as well as the
‘How do we make quick and confident decisions?’ prob-
lem,” McClure adds.
He offers numerous real-world examples of this capa-
bility in action, including
• a utility company that is using Space-Time Insight's
analytics solution to stem operational losses and
electricity theft
• work crew managers who are able to more effectively
plan and supervise shift-work schedules
• dispatchers reducing vehicle trips and travel time by
accurately diagnosing problems prior to dispatch and
bundling tasks so that crews can complete several
items in a single trip
• the application of analytics to pinpoint the people, loca-
tions, times, and situations that pose the greatest risks in
order to reduce workplace accidents and injuries.
“People want to do the best job they can. Providing
them with information—whether it is data, insights,
intelligence, or all three—when they need it and ideally
on a self-serve basis empowers people to do their best and
to work efficiently with the least frustration and stress,”
McClure says.“These are key drivers of job satisfaction.”
Catch the value
Derek Nelson is a partner at supply chain analytics and
optimization firm OPS Rules. In this role, he sees many
companies failing to properly use available data. The
challenges include lack of a consistent view of data across
the organization, mistrusting data accuracy, ineffective
tools for managing and leveraging data, and the absence
of skilled users. Because of this, he says there are excellent
career opportunities out there for people who are able to
help create a truly data-driven culture.“I have seen this
in action with several companies I have worked with,” he
notes.“In these companies, the executives make it clear
that using data and analytics is an imperative, and people
who excel in this area have bright futures in the company.
This is supported through recruitment, education and
training, centers of excellence, et cetera.”
Nelson says the shallow-dive approach can be an
effective strategy for many companies—as long as
people don’t let “the perfect be the enemy of the good”
and thus get stuck when implementing the approach.
When considering potential opportunities, he suggests
thinking about which of the most important decisions
can be significantly improved with the application of a
“non-threatening amount of analytics.”
He says to start simply and build complexity. “If you
have important decisions that are made based on rule
of thumb or intuition, using a small amount of ana-
lytics can provide a significant chunk of the potential
benefits Nelson explains. “If people imagine a perfect
solution, they soon will find a million reasons why they
can’t get there.”
This anxiety is understandable, as there are numerous
potential impediments to analytics efforts. Jesse Treger,
senior director of product management and strategy at
predictive analytics solutions provider Compellon, sees
companies grappling with the technical challenges to
deployment; cross-organizational complications related
to the collection, management, and governance of data;
and other obstacles as they work to take previously
siloed information and make it available across their
organizations. Notably, he says the ability to maximize
the siloed data and put it to work in new ways can be a
significant business opportunity.
“For example, data that originated as monitor-
ing and alerting for the manufacturing or service
department can be used to develop a predictive
model to improve the product or incorporate
6. usage patterns in analysis of what drives customer
satisfaction or repurchase,” he explains. “Or transac-
tional data originally captured as part of the billing
process can be used to predict … which types of
customers are likely to buy.”
Furthermore, to overcome lack of time or exper-
tise, Treger says he often sees practitioners using
assumptions about what matters based on their past
experiences, conventional wisdom, or intuition.
Additionally, they tend to apply mathematical tech-
niques that intrinsically rely on simplifying assump-
tions. To address these inclinations, his company’s
solution, Compellon 20|20, bases all analytics solely
on evidence in the data. “The user need only to
provide data and frame the business problem using
an outcome of interest that can be measured in the
data,” he explains.
Taking the plunge
Unfortunately, even organizations such as Mattel,
which are moving diligently and enthusiastically
toward a more data-driven culture, can struggle to pull
value out of their time and resource investments. As
Gibbons says, “We are in the early stages of adoption
and use. … But it’s becoming clear to people that, if
you want to drive improvement, you are expected to
come up with the facts and the data, then come up
with an improvement plan and an action plan, and
then go execute that plan to get good results.”
Gibbons says his company’s strategy is straight-
forward: Raise service and quality, lower costs,
and develop talent. He is hopeful that taking a
shallow dive will support those parameters
by giving people easy access to great data
and enabling them to use it in a strategic
way. “I’m an admirer of this approach
to data collection,” he says. “Steer the
supertanker in the right direction.”
Along the journey, Compellon’s
Treger advises keeping in mind the
common barriers to moving beyond
publishing reports and dashboards.
Hurdles to achieving actionable
insights include lengthy data prepa-
ration and analysis, lack of skilled
workers, too much effort in the back and
forth between data analysts and business
units, inability to translate trusted results, and rapidly
changing environments leading to stale data.
He adds,“Despite major advances, it is not surprising
that analytics is viewed by many as still in its infancy.”
Elizabeth Rennie is managing editor of APICS magazine. She
may be contacted at erennie@apics.org.
To comment on this article, send a message to feedback@apics.org.
DigitalExclusive: Check out the APICS
magazine tablet app to read a Q&A with Neil
Wieloch, PhD, director of marketing strategy
and insights at 1-800 CONTACTS. He
recently spoke with with APICS magazine’s
Elizabeth Rennie about how 1-800 CONTACTS uses the
Compellon analytics tool to get a crystal-clear view of
its customers, processes, and business strategies. If
you haven’t downloaded the app yet, search for “APICS
mag” in the App Store or Google play.
apics.org/magazine 49