Demand Forecasting, undeniably, is the single most important component of any organizations Supply Chain. It determines the estimated demand for the future and sets the level of preparedness that is required on the supply side to match the demand. It goes without saying that if an organization doesnt get its forecasting accurate to a reasonable level, the whole supply chain gets affected. Understandably, Over/Under forecasting has deteriorating impact on any organizations Supply Chain and thereby on P and L. Having ascertained the importance of Demand Forecasting, it is only fair to discuss about the forecasting techniqueswhichareusedtopredictthefuturevaluesofdemand. The input that goes in and the modeling engine which it goes through are equally important in generating the correct forecasts and determining the Forecast Accuracy. Here, we present a very unique model that not only pre-processes the input data, but also ensembles the output of two parallel advanced forecasting engines which uses state-of-the-art Machine Learning algorithms and Time-Series algorithms to generate future forecasts. Our technique uses data-driven statistical techniques to clean the data of any potential errors or outliers and impute missing values if any. Once the forecast is generated, it is post processed with Seasonality and Trend corrections, if required.Since the final forecast is the result of statistically pre-validated ensemble of multiple models, the forecasts are stable and accuracy variation is very minimal across periods and forecast horizons. Hence it is better at estimating the future demand than the conventional techniques.
A Survey of Synergistic Relationships For Designing Architecture: Scenarios, ...ijbuiiir1
Software Architectures are generally designed with particular functional and nonfunctional requirements. Organizations often need to choose Software Architecture for future development from several contending candidate architectures. Several methods have been proposed to design, analyze, selecting architectures with respect to hoped quality attributes to identify their restrictions. Most of these methods encourage the use of architectural patterns to develop architectures with known characteristics and apply scenarios to evaluate those architectures for desired quality attributes (e.g., reliability, modifiability). In case of Architecting a complex design activity, it involves making decisions about a number of inter-dependent design choices that relate to a range of design concerns. Each decision requires selecting among a number of alternatives; each of which impacts differently on various quality attributes (e.g., real-time, reliability, and performance). This paper discusses a selection framework based on multiattribute decision making using Hypothetical Equivalents, Architectural Information in a format that can support design decisions, ArchDesigner as a taxonomic approach along with GB case study and a Reasoning Framework which is encapsulation mechanism, can be used by nonexperts to examine a specific quality (e.g., performance, modifiability, availability) of a system.
GPS for Chemical Space - Digital Assistants to Support Molecule Design - Chem...ChemAxon
Boehringer Ingelheim's Nils Weskamp discusses eDesign: a computational platform for molecule design and optimization. This presentation explaing how to combine data, algorithms and user experience to impact compound design, and gives a glimpse into the agile and interdisciplinary teamwork as facilitated by Design Hub as a success factor for the development of digital tools.
Concept of systemThe word “system” has a very wide connotation. B.pdfsutharbharat59
Concept of system:
The word “system” has a very wide connotation. Broadly speaking, we have a wide variety of
systems around us. Several of them have been created by man to satisfy his needs while others
exist in nature. Natural systems are those that came into existence through natural processes
whereas man-made systems are those in which human beings intervene through components,
attributes, or relationships. Examples of man-made systems are highways, railways, waterways,
marine and air transport, space projects, chemical plants, nuclear plants, electrical power
generation, distribution and utilization, housing and office complexes, mining and oil extraction,
etc
Systems engineering:
Systems engineering is an interdisciplinary field of engineering and engineering management
that focuses on how to design and manage complex systems over their life cycles. At its core
systems engineering utilizes systems thinking principles to organize this body of knowledge.
Issues such as requirements engineering, reliability, logistics, coordination of different teams,
testing and evaluation, maintainability and many other disciplines necessary for successful
system development, design, implementation, and ultimate decommission become more difficult
when dealing with large or complex projects. Systems engineering deals with work-processes,
optimization methods, and risk management tools in such projects. It overlaps technical and
human-centred disciplines such as industrial engineering, mechanical engineering,
manufacturing engineering, control engineering, software engineering, electrical engineering,
cybernetics, organizational studies, engineering management and project management. Systems
engineering ensures that all likely aspects of a project or system are considered, and integrated
into a whole.
The systems engineering process is a discovery process that is quite unlike a manufacturing
process. A manufacturing process is focused on repetitive activities that achieve high quality
outputs with minimum cost and time. The systems engineering process must begin by
discovering the real problems that need to be resolved, and identify the most probable or highest
impact failures that can occur – systems engineering involves finding elegant solutions to these
problems. That’s why Systems engineering is sometimes called process engineering.
Systems engineering over-all systems design:
The need for systems engineering arose with the increase in complexity of systems and projects
in turn exponentially increasing the possibility of component friction, and therefore the
unreliability of the design. When speaking in this context, complexity incorporates not only
engineering systems, but also the logical human organization of data. At the same time, a system
can become more complex due to an increase in size as well as with an increase in the amount of
data, variables, or the number of fields that are involved in the design. The International Space
Station is an exa.
Demand Forecasting, undeniably, is the single most important component of any organizations Supply Chain. It determines the estimated demand for the future and sets the level of preparedness that is required on the supply side to match the demand. It goes without saying that if an organization doesnt get its forecasting accurate to a reasonable level, the whole supply chain gets affected. Understandably, Over/Under forecasting has deteriorating impact on any organizations Supply Chain and thereby on P and L. Having ascertained the importance of Demand Forecasting, it is only fair to discuss about the forecasting techniqueswhichareusedtopredictthefuturevaluesofdemand. The input that goes in and the modeling engine which it goes through are equally important in generating the correct forecasts and determining the Forecast Accuracy. Here, we present a very unique model that not only pre-processes the input data, but also ensembles the output of two parallel advanced forecasting engines which uses state-of-the-art Machine Learning algorithms and Time-Series algorithms to generate future forecasts. Our technique uses data-driven statistical techniques to clean the data of any potential errors or outliers and impute missing values if any. Once the forecast is generated, it is post processed with Seasonality and Trend corrections, if required.Since the final forecast is the result of statistically pre-validated ensemble of multiple models, the forecasts are stable and accuracy variation is very minimal across periods and forecast horizons. Hence it is better at estimating the future demand than the conventional techniques.
A Survey of Synergistic Relationships For Designing Architecture: Scenarios, ...ijbuiiir1
Software Architectures are generally designed with particular functional and nonfunctional requirements. Organizations often need to choose Software Architecture for future development from several contending candidate architectures. Several methods have been proposed to design, analyze, selecting architectures with respect to hoped quality attributes to identify their restrictions. Most of these methods encourage the use of architectural patterns to develop architectures with known characteristics and apply scenarios to evaluate those architectures for desired quality attributes (e.g., reliability, modifiability). In case of Architecting a complex design activity, it involves making decisions about a number of inter-dependent design choices that relate to a range of design concerns. Each decision requires selecting among a number of alternatives; each of which impacts differently on various quality attributes (e.g., real-time, reliability, and performance). This paper discusses a selection framework based on multiattribute decision making using Hypothetical Equivalents, Architectural Information in a format that can support design decisions, ArchDesigner as a taxonomic approach along with GB case study and a Reasoning Framework which is encapsulation mechanism, can be used by nonexperts to examine a specific quality (e.g., performance, modifiability, availability) of a system.
GPS for Chemical Space - Digital Assistants to Support Molecule Design - Chem...ChemAxon
Boehringer Ingelheim's Nils Weskamp discusses eDesign: a computational platform for molecule design and optimization. This presentation explaing how to combine data, algorithms and user experience to impact compound design, and gives a glimpse into the agile and interdisciplinary teamwork as facilitated by Design Hub as a success factor for the development of digital tools.
Concept of systemThe word “system” has a very wide connotation. B.pdfsutharbharat59
Concept of system:
The word “system” has a very wide connotation. Broadly speaking, we have a wide variety of
systems around us. Several of them have been created by man to satisfy his needs while others
exist in nature. Natural systems are those that came into existence through natural processes
whereas man-made systems are those in which human beings intervene through components,
attributes, or relationships. Examples of man-made systems are highways, railways, waterways,
marine and air transport, space projects, chemical plants, nuclear plants, electrical power
generation, distribution and utilization, housing and office complexes, mining and oil extraction,
etc
Systems engineering:
Systems engineering is an interdisciplinary field of engineering and engineering management
that focuses on how to design and manage complex systems over their life cycles. At its core
systems engineering utilizes systems thinking principles to organize this body of knowledge.
Issues such as requirements engineering, reliability, logistics, coordination of different teams,
testing and evaluation, maintainability and many other disciplines necessary for successful
system development, design, implementation, and ultimate decommission become more difficult
when dealing with large or complex projects. Systems engineering deals with work-processes,
optimization methods, and risk management tools in such projects. It overlaps technical and
human-centred disciplines such as industrial engineering, mechanical engineering,
manufacturing engineering, control engineering, software engineering, electrical engineering,
cybernetics, organizational studies, engineering management and project management. Systems
engineering ensures that all likely aspects of a project or system are considered, and integrated
into a whole.
The systems engineering process is a discovery process that is quite unlike a manufacturing
process. A manufacturing process is focused on repetitive activities that achieve high quality
outputs with minimum cost and time. The systems engineering process must begin by
discovering the real problems that need to be resolved, and identify the most probable or highest
impact failures that can occur – systems engineering involves finding elegant solutions to these
problems. That’s why Systems engineering is sometimes called process engineering.
Systems engineering over-all systems design:
The need for systems engineering arose with the increase in complexity of systems and projects
in turn exponentially increasing the possibility of component friction, and therefore the
unreliability of the design. When speaking in this context, complexity incorporates not only
engineering systems, but also the logical human organization of data. At the same time, a system
can become more complex due to an increase in size as well as with an increase in the amount of
data, variables, or the number of fields that are involved in the design. The International Space
Station is an exa.
Building Your Employer Brand with Social MediaLuanWise
Presented at The Global HR Summit, 6th June 2024
In this keynote, Luan Wise will provide invaluable insights to elevate your employer brand on social media platforms including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok. You'll learn how compelling content can authentically showcase your company culture, values, and employee experiences to support your talent acquisition and retention objectives. Additionally, you'll understand the power of employee advocacy to amplify reach and engagement – helping to position your organization as an employer of choice in today's competitive talent landscape.
[Note: This is a partial preview. To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
Sustainability has become an increasingly critical topic as the world recognizes the need to protect our planet and its resources for future generations. Sustainability means meeting our current needs without compromising the ability of future generations to meet theirs. It involves long-term planning and consideration of the consequences of our actions. The goal is to create strategies that ensure the long-term viability of People, Planet, and Profit.
Leading companies such as Nike, Toyota, and Siemens are prioritizing sustainable innovation in their business models, setting an example for others to follow. In this Sustainability training presentation, you will learn key concepts, principles, and practices of sustainability applicable across industries. This training aims to create awareness and educate employees, senior executives, consultants, and other key stakeholders, including investors, policymakers, and supply chain partners, on the importance and implementation of sustainability.
LEARNING OBJECTIVES
1. Develop a comprehensive understanding of the fundamental principles and concepts that form the foundation of sustainability within corporate environments.
2. Explore the sustainability implementation model, focusing on effective measures and reporting strategies to track and communicate sustainability efforts.
3. Identify and define best practices and critical success factors essential for achieving sustainability goals within organizations.
CONTENTS
1. Introduction and Key Concepts of Sustainability
2. Principles and Practices of Sustainability
3. Measures and Reporting in Sustainability
4. Sustainability Implementation & Best Practices
To download the complete presentation, visit: https://www.oeconsulting.com.sg/training-presentations
The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
Personal Brand Statement:
As an Army veteran dedicated to lifelong learning, I bring a disciplined, strategic mindset to my pursuits. I am constantly expanding my knowledge to innovate and lead effectively. My journey is driven by a commitment to excellence, and to make a meaningful impact in the world.
Understanding User Needs and Satisfying ThemAggregage
https://www.productmanagementtoday.com/frs/26903918/understanding-user-needs-and-satisfying-them
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
In this webinar, we won't focus on the research methods for discovering user-needs. We will focus on synthesis of the needs we discover, communication and alignment tools, and how we operationalize addressing those needs.
Industry expert Scott Sehlhorst will:
• Introduce a taxonomy for user goals with real world examples
• Present the Onion Diagram, a tool for contextualizing task-level goals
• Illustrate how customer journey maps capture activity-level and task-level goals
• Demonstrate the best approach to selection and prioritization of user-goals to address
• Highlight the crucial benchmarks, observable changes, in ensuring fulfillment of customer needs
Event Report - SAP Sapphire 2024 Orlando - lots of innovation and old challengesHolger Mueller
Holger Mueller of Constellation Research shares his key takeaways from SAP's Sapphire confernece, held in Orlando, June 3rd till 5th 2024, in the Orange Convention Center.
Digital Transformation and IT Strategy Toolkit and TemplatesAurelien Domont, MBA
This Digital Transformation and IT Strategy Toolkit was created by ex-McKinsey, Deloitte and BCG Management Consultants, after more than 5,000 hours of work. It is considered the world's best & most comprehensive Digital Transformation and IT Strategy Toolkit. It includes all the Frameworks, Best Practices & Templates required to successfully undertake the Digital Transformation of your organization and define a robust IT Strategy.
Editable Toolkit to help you reuse our content: 700 Powerpoint slides | 35 Excel sheets | 84 minutes of Video training
This PowerPoint presentation is only a small preview of our Toolkits. For more details, visit www.domontconsulting.com
Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
10. -Mission statement:
For a junior high school
To create an educational
Facility that support 7th
8th
9th
Graders in
making an easy transition
from childhood to young
adulthood
-Types of goals
Process and resource goals
Personal Goals
Project Specific goals
-Methods of articulating goals
Interviews
Scenarios
Observation