Operations Management
Operations management is about decision-making in planning, coordination and improvement in the design, implementation, and execution of the organization's work processes for creating and delivering value (products and services) to customers. The operations management analytics engine is concerned with helping managers and key operations staff in gaining insight into the "real world" situations facing the company and improving their understanding of the factors that affect operation performance. The engine is driven by customer events and operations decisions and choices i.e., choices to questions such as:
Operations Management Analytics Engine is a discrete-event simulation system concerned with quantifying the use of the organization's "Operations System" to provide value to customers. It involves determining the best match (fit) of supply (of tangible resources) and demand, and understanding of the impact of product/service mix, and changes on effective capacity of the Operations System. Resources or real assets can be divided into two groups: tangible and intangible assets. Tangible real assets are human resources (people) and capital assets (property, plants, and equipment as shown on the balance sheet). Intangible assets include relationships with suppliers and customers, intellectual property, reputation and brands, and knowledge and experience in processing, technology, and markets. Often tangible real assets do the work, while intangible assets embody the know-how to do the work.
Operations simulation through process analytics informs management understanding and decisions on resource utilization (labor and equipment and storage), process coordination and activation in creating and delivering products and/or services to customers, and competency development - operations system effective capacity for a given product mix. Process analytics provides participants, decision-makers, and stakeholders with understanding of interplay of process concepts and elements, and constraints, as well as insight into the influence on future performance (efficiency and effectiveness) of organization processes. Typical simulation solutions focus on experiments to help understand impact of changes at:
Operations management is about decision-making in planning, coordination and improvement in the design, implementation, and execution of the organization's work processes for creating and delivering value (products and services) to customers. The operations management analytics engine is concerned with helping managers and key operations staff in gaining insight into the "real world" situations facing the company and improving their understanding of the factors that affect operation performance. The engine is driven by customer events and operations decisions and choices i.e., choices to questions such as:
- How does the company produce its products, or service now?
- How does the company respond to customer demand?
- How does the company improve efficiencies in their production and payment systems?
- How does the company drive costs down and maximize profitability?
- How does the company sell to current customers?
Operations Management Analytics Engine is a discrete-event simulation system concerned with quantifying the use of the organization's "Operations System" to provide value to customers. It involves determining the best match (fit) of supply (of tangible resources) and demand, and understanding of the impact of product/service mix, and changes on effective capacity of the Operations System. Resources or real assets can be divided into two groups: tangible and intangible assets. Tangible real assets are human resources (people) and capital assets (property, plants, and equipment as shown on the balance sheet). Intangible assets include relationships with suppliers and customers, intellectual property, reputation and brands, and knowledge and experience in processing, technology, and markets. Often tangible real assets do the work, while intangible assets embody the know-how to do the work.
Operations simulation through process analytics informs management understanding and decisions on resource utilization (labor and equipment and storage), process coordination and activation in creating and delivering products and/or services to customers, and competency development - operations system effective capacity for a given product mix. Process analytics provides participants, decision-makers, and stakeholders with understanding of interplay of process concepts and elements, and constraints, as well as insight into the influence on future performance (efficiency and effectiveness) of organization processes. Typical simulation solutions focus on experiments to help understand impact of changes at:
- The resource level (e.g., what if the organization bought a faster check sorter?),
- The process structure level (e.g., what if the organization allowed existing customers to skip the credit check activity?), or
- The process context level (e.g., what if the customer demand increased dramatically because of marketing campaign?).
Workforce Analytics
The resource view of an organization or any of its parts as a bundle of resources (real assets). Viewing operations as a bundle of real assets is most useful when the decision is on amounts human resources of particular role types that the operation needs. This investment or capital budgeting decision, along with the allocation of resources to activities, is one of the major tasks of management.
The resource view of an organization or any of its parts as a bundle of resources (real assets). Viewing operations as a bundle of real assets is most useful when the decision is on amounts human resources of particular role types that the operation needs. This investment or capital budgeting decision, along with the allocation of resources to activities, is one of the major tasks of management.
Human Resource - Workforce Simulation Analytics
The workforce or human resource analytics involves simulation of business operations to inform workforce decisions such as staffing and rightsizing decisions. Rightsizing means managing employees as human resources, at a level that better fits your organizational needs. Estimating the right staffing levels and labor requirements (rightsizing) is an operational planning function which involves systematic review of staffing mix and levels, tasks and work processes to determine the appropriate number (quantity) and mix of staff (workers) needed to meet organizational goals in areas such as medical practice, quick service and full service restaurants, barber shops and salons, etc.
Creating Workforce Simulation Analytics Models
Creating a simulation experiment to investigate workforce and staffing needs involves:
Simulation Output & Analysis
The simulation output product is an interactive visualization model of the organization's production operations systems. Users can interact with the visualization to explore and examine the simulation results in areas such as:
The simulation output provides staffing resource utilization and workload information, and associated overall business (throughput) performance information to inform staffing decisions. Operations Analytics Simulation provides you the evidence to allow you to make bold, confident decisions because you are sure you are making the right choice.
The Rightsizing Example
The staffing/rightsizing analytics is organization-specific (i.e., for a specific medical practice for example) and is influenced by the expectations of the organization, internal limiting factors (constraints), organizational culture, strategic goals and objectives, and operational goals. Rightsizing analysis involves creating a simulation model of the business operations that enables evaluation of the organization's value creation and delivery systems including staffing needs. The evaluation involves analysis of simulation results in the form of output models that inform decisions in the following areas:
Visualization of operations management simulation output enables managers and key operations staff to gain insight into the "real world" situations facing the company and improve their understanding of the factors that affect operational performance.
The workforce or human resource analytics involves simulation of business operations to inform workforce decisions such as staffing and rightsizing decisions. Rightsizing means managing employees as human resources, at a level that better fits your organizational needs. Estimating the right staffing levels and labor requirements (rightsizing) is an operational planning function which involves systematic review of staffing mix and levels, tasks and work processes to determine the appropriate number (quantity) and mix of staff (workers) needed to meet organizational goals in areas such as medical practice, quick service and full service restaurants, barber shops and salons, etc.
Creating Workforce Simulation Analytics Models
Creating a simulation experiment to investigate workforce and staffing needs involves:
- Create product/service demand forecast model for products and services - This includes information about the average rates at which customers request for products and/or services including the breakdown of customer order request types (e.g., for a coffee shop regular coffee vs. espresso, for a barbershop haircut vs. shaves, etc.) – at different times of the day, and the orders' sizes
- Create configuration model for the production and/or service delivery functional unit including the configuration model of the people and equipment resources.
- Create configuration model for the products and services mix offered by the organization
- Create configuration model for the workforce (people) and their roles as well as their schedules
- Create configuration model for the equipment including operations and maintenance schedules
- Create schedules for the organization's operating times and holidays.
- Generate/Run operations process simulation models
Simulation Output & Analysis
The simulation output product is an interactive visualization model of the organization's production operations systems. Users can interact with the visualization to explore and examine the simulation results in areas such as:
- Production output and throughput.
- Resource utilization and load factors - Labor utilization and load factors; Equipment utilization and load factors; Storage utilization and load factors.
- WIP (Work-in-Progress) Inventory Levels and Control Policy Standards.
- Process capacity utilization and load/idle factors.
- Process bottlenecks and product delays.
The simulation output provides staffing resource utilization and workload information, and associated overall business (throughput) performance information to inform staffing decisions. Operations Analytics Simulation provides you the evidence to allow you to make bold, confident decisions because you are sure you are making the right choice.
The Rightsizing Example
The staffing/rightsizing analytics is organization-specific (i.e., for a specific medical practice for example) and is influenced by the expectations of the organization, internal limiting factors (constraints), organizational culture, strategic goals and objectives, and operational goals. Rightsizing analysis involves creating a simulation model of the business operations that enables evaluation of the organization's value creation and delivery systems including staffing needs. The evaluation involves analysis of simulation results in the form of output models that inform decisions in the following areas:
- Analyzing current productivity - Understanding the current productivity levels of staff and support staff.
- Analyze current operating system - Determine the model by which the organization operates. This includes the staff number and function allocated to each position/role, customer (patient) check-in and check-out processes, customer record management, scheduling procedures and communication processes.
- Analyze process performance - Monitor and review performance measures to identify resource bottlenecks and areas of capacity improvements.
Visualization of operations management simulation output enables managers and key operations staff to gain insight into the "real world" situations facing the company and improve their understanding of the factors that affect operational performance.
Facility and Equipment Capacity Analysis
Businesses typically have a mix of production and services that collectively define the the value creation and delivery processes. Product-mix decisions are usually supported by analytical methods such as Linear Programming (LP). These decisions are usually made so that the market demand is met and the firm profit is maximized. However, the complexity, and stochastic and dynamic nature of real-world production and business systems often lead to production levels that are different from those determined by analytical methods. Analytical methods also have problems coping with the dynamic changes in the product-mix which usually requires enhancing system parameters and/or configuration 0f value creation and delivery processes.
Businesses typically have a mix of production and services that collectively define the the value creation and delivery processes. Product-mix decisions are usually supported by analytical methods such as Linear Programming (LP). These decisions are usually made so that the market demand is met and the firm profit is maximized. However, the complexity, and stochastic and dynamic nature of real-world production and business systems often lead to production levels that are different from those determined by analytical methods. Analytical methods also have problems coping with the dynamic changes in the product-mix which usually requires enhancing system parameters and/or configuration 0f value creation and delivery processes.
Simulation Output & Analysis
The simulation output provides information on facility and equipment resources' utilization and workloads, and associated overall business (throughput) performance information to inform equipment decisions. Operations Analytics Simulation provides you the evidence to allow you to make bold, confident decisions because you are sure you are making the right choice.
The simulation output provides information on facility and equipment resources' utilization and workloads, and associated overall business (throughput) performance information to inform equipment decisions. Operations Analytics Simulation provides you the evidence to allow you to make bold, confident decisions because you are sure you are making the right choice.
Manufacturing Process Analytics
Manufacturing processes are structured, recurrent activities that transform inputs into outputs (products). A process is a network of activities with specific precedence relationships among activities - the relationships that specify which activities must be finished before another activity can begin. The process view considers an organization as a whole (system) or any of its parts to be an activity network or a collection of processes. A process can refer to detailed workflow, such as billing a customer, or implementing an engineering change order, or to aggregate activities of new product development, or customer service. Adopting a process view means that we visualize instances of work, called flow units (e.g., consulting engagements, hospital patients, barbershop patrons, hotel guests, or products/parts, service orders) flowing through a network of activities and buffers. The primary workflow is typically accomplished by an information flow to coordinate the activities, and a cash flow to support and reward them.
Manufacturing processes are structured, recurrent activities that transform inputs into outputs (products). A process is a network of activities with specific precedence relationships among activities - the relationships that specify which activities must be finished before another activity can begin. The process view considers an organization as a whole (system) or any of its parts to be an activity network or a collection of processes. A process can refer to detailed workflow, such as billing a customer, or implementing an engineering change order, or to aggregate activities of new product development, or customer service. Adopting a process view means that we visualize instances of work, called flow units (e.g., consulting engagements, hospital patients, barbershop patrons, hotel guests, or products/parts, service orders) flowing through a network of activities and buffers. The primary workflow is typically accomplished by an information flow to coordinate the activities, and a cash flow to support and reward them.
Manufacturing Sysems Process Analytics
Manufacturing processes create and deliver products and/or parts that are delivered to customers. The capacity of these processes is defined in terms of the output of products/parts per some specified interval. The manufacturing and/or service delivery system processes define a network of manufacturing and/or service centers connected and coordinated by the processes. Manufacturing work centers are augmented with WIP inventory stores that act as buffers to bottleneck resources and work centers that constrain the flow of products through the system. These manufacturing and service delivery systems can be analyzed systematically as part of organization workflow analysis through production systems simulation methods, to identify potential bottlenecks and inefficiencies for improvements. Simulation enables users to explore maximizing organization output subject to minimizing delays through reducing/eliminating waiting times, improving labor and equipment utilization, etc.
Production System Simulation & Analytics
Creating a simulation experiment to investigate production (product manufacturing) effective capacity, and capacity decisions related to creation and delivery of value to customers involves:
These production and service delivery systems processes can be analyzed systematically as part of whole organization workflow through simulation methods, to identify potential bottlenecks and inefficiencies for improvements. Simulation enables users to explore maximizing organization output subject to minimizing delays through reducing/eliminating waiting times, improving labor and equipment utilization, etc.
Simulation Output Analysis & Visualization
The Production and/or service systems simulation enable managers and key operations staff to gain insight into the "real world" capacity problems facing the company, and improves their understanding of the factors that affect production and service delivery performance. The simulation and visualization informs decisions on:
Simulation informs decisions on the optimum configuration of processes such as:
Manufacturing processes create and deliver products and/or parts that are delivered to customers. The capacity of these processes is defined in terms of the output of products/parts per some specified interval. The manufacturing and/or service delivery system processes define a network of manufacturing and/or service centers connected and coordinated by the processes. Manufacturing work centers are augmented with WIP inventory stores that act as buffers to bottleneck resources and work centers that constrain the flow of products through the system. These manufacturing and service delivery systems can be analyzed systematically as part of organization workflow analysis through production systems simulation methods, to identify potential bottlenecks and inefficiencies for improvements. Simulation enables users to explore maximizing organization output subject to minimizing delays through reducing/eliminating waiting times, improving labor and equipment utilization, etc.
Production System Simulation & Analytics
Creating a simulation experiment to investigate production (product manufacturing) effective capacity, and capacity decisions related to creation and delivery of value to customers involves:
- Creating product demand forecast model for products and services - This includes information about the average rates at which customers request for products and/or services including the breakdown of customer order request types (e.g., for a coffee shop regular coffee vs. espresso, for a barbershop haircut vs. shaves, etc.) – at different times of the day, and the orders' sizes
- Creating configuration model for the production and/or service delivery functional unit including the configuration model of the people and equipment resources.
- Creating configuration model for the products and services mix offered by the organization
- Creating configuration model for the workforce (people) and their roles as well as their schedules
- Creating configuration model for the equipment including operations and maintenance schedules
- Creating schedules for the organization's operating calendar - workdays, times and holidays.
- Generate/Run operations process simulation models
These production and service delivery systems processes can be analyzed systematically as part of whole organization workflow through simulation methods, to identify potential bottlenecks and inefficiencies for improvements. Simulation enables users to explore maximizing organization output subject to minimizing delays through reducing/eliminating waiting times, improving labor and equipment utilization, etc.
Simulation Output Analysis & Visualization
The Production and/or service systems simulation enable managers and key operations staff to gain insight into the "real world" capacity problems facing the company, and improves their understanding of the factors that affect production and service delivery performance. The simulation and visualization informs decisions on:
- Demand Management - Specifying how to match demand to available resources; and tactical allocation of capacity.
- Process Network Structure - Decision of the layout of the activity network in terms of locations of activities, buffers and interconnections. For example, processes can be organized by activity, or by product line; job shops such as consulting companies, and tool-die-shops often have a functional or process layout, while flow shops such as assembly plants, and chemical processing plants usually have a product layout.
- Coordination and Information technology decisions on how to coordinate, communicate, and plan execution throughout the network. Coordination is typically a managerial activity and includes assignment of responsibility, incentives, measurements and control.
- Product architecture decisions on structure and parts to facilitate production.
- Transportation technology decisions on how goods are exchanged among different activities in the network. This is a key driver in logistics and supply chain management, as well as how insurance policies are moved between the different processing steps.
Simulation informs decisions on the optimum configuration of processes such as:
- Supply or Sourcing Decisions - These decisions specify which activities are performed internally, and which activities are outsourced, and how to manage suppliers. Decisions involve defining the process boundaries and interfaces. It includes strategic sourcing decisions, vertical integration, and supply network configuration.
- Technology Decisions - These decisions characterize how to process inputs into outputs. It includes the methods and systems employed, as well as the know-how and intellectual property. The technology decisions can be grouped into the following key categories: a) coordination and information technology decisions such as assignment of responsibility, incentives, measurement, and control; b) product technology decisions in product philosophy, product architecture, and product capabilities; c) process technology decisions on how to structure the conversion processes and methods used in execution; and d) transportation technology decisions on how goods are exchanged among different activities in the network.
- Demand Forecast Decisions - These decisions specify how to match demand to available supply. These decisions characterize the interfaces and relationships with customers and include demand planning and forecasting, as well as tactical capacity allocation and order management. Demand management is an important driver in inflexible supply processes that cannot quickly adapt to changes in demand such as the core processes in airlines, hotels, hospital wards, and car rental companies, It also relates to service and customer relationship management.
- Improvements and Innovation Decisions - These are decisions on characterizing the processes and incentives to improve and innovate products and processes.
Organization Competency Analytics
The competency view characterizes the abilities of the assemble of the organization's resources, processes, and values The resource (human resource and equipment) and process (production and service delivery) views are complementary; the process view focuses on how work is done, while the resource view focuses on who or what performs the work. Both are necessary to understand operations well. The specific choices of resources and processes affects what the operations system can and cannot do well. Besides resources and processes, values are the third factor that affects what an operation - and thus the organization - can and cannot do. Values are the standards by which employees set priorities. Some priorities are embodied or programmed into a process, but many are not. Examples include judging whether an order or customer is attractive or not, whether a suggestion to improve a product or process is attractive or marginal, and whether an investment is worth making or not. The competencies determine the set of outputs, products, and services that the operation will be particularly good at providing, and influences the "product mix" decisions.
The competency view characterizes the abilities of the assemble of the organization's resources, processes, and values The resource (human resource and equipment) and process (production and service delivery) views are complementary; the process view focuses on how work is done, while the resource view focuses on who or what performs the work. Both are necessary to understand operations well. The specific choices of resources and processes affects what the operations system can and cannot do well. Besides resources and processes, values are the third factor that affects what an operation - and thus the organization - can and cannot do. Values are the standards by which employees set priorities. Some priorities are embodied or programmed into a process, but many are not. Examples include judging whether an order or customer is attractive or not, whether a suggestion to improve a product or process is attractive or marginal, and whether an investment is worth making or not. The competencies determine the set of outputs, products, and services that the operation will be particularly good at providing, and influences the "product mix" decisions.
Competency Analytics
The competency view characterizes the abilities of the ensemble of the organization's resources, processes, and values. Competency determine the set of outputs, products, and services that the operation will be particularly good at providing. Competencies can be measured along multiple dimensions including:
The competency view is the most "outward looking" and begs the important question: which competencies should an operation have, nurture, or develop? This naturally connects to competitive strategy.
Comperency Simulation Analytics
Businesses typically have a mix of products and services requiring product-mix decisions which are usually supported by analytical methods such as Linear Programming (LP). These decisions are usually made so that the market demand is met and the firm profit is maximized. However, the complexity, and stochastic and dynamic nature of real-world production and business systems often lead to production levels that are different from those determined by analytical methods. Analytical methods also have problems coping with the dynamic changes in the product-mix which usually requires enhancing system parameters and/or configuration 0f value creation and delivery processes.
Analyzing the impact of product/service-mix on operating system capacity involves creating simulation models of the joint configuration of resources and processes and ensuring the resulting competencies are aligned with the organization's market positioning for demand of products and services. Operating System Capacity refers to the organization system's potential to produce goods and services over a specified time interval.
Creating Competency Simulation Analytics Models
Creating a simulation experiment to investigate organization Operations System capacity for creating and delivering value defined in terms of product/service-mix involves:
Operations Simulation Output Analysis
Operations simulation enables management to analyze and evaluate operations output with respect to the relevant competency measures such as cost. time, quality, etc. Analysis involves evaluating and assessing the impact (cost/benefit) on production capacity plan (or schedule) optimization of different alternative resource schedules/plans. The simulation output product is an interactive visualization model of the organization's production operations systems. Users can interact with the visualization to explore and examine the simulation results in areas such as:
Visualization of operations system simulation output enables managers and key operations staff to gain insight into the "real world" situations facing the company and improve their understanding of the factors that affect operational performance.
The competency view characterizes the abilities of the ensemble of the organization's resources, processes, and values. Competency determine the set of outputs, products, and services that the operation will be particularly good at providing. Competencies can be measured along multiple dimensions including:
- Cost - The marginal and total cost of operating, including variable and fixed costs are particularly important in competitive markets such as commodities and low margin businesses. Cost is a relevant factor in all activities, but this competency most naturally reflects scale economies (capacity sizing), and complexity costs (capacity types).
- Time - The total flow, response, and lead times characterize the time needed to transform inputs into outputs, to fill a customer order, to receive inputs, respectively. Flow time and lead time determine working capital requirements and forecasting accuracy; responsiveness is important in service and convenience-driven businesses, as well as in rapidly changing environments.
- Quality - Quality refers to the degree of excellence of the process, product, or service. It has design related dimensions such as performance and features, as well as process related dimensions such as durability and reliability. Quality is a key differentiator in luxury and high precision businesses, and a required competency in mature industries.
- Flexibility - Flexibility measures the ability to change inputs, activities, volumes, or outputs? Flexibility has several dimensions such as scope - scope flexibility is the selection or range of products and services offered, including the level of customization, volume flexibility, and robustness. It is also a key risk mitigation driver.
- Innovation - This is the ability of the operation to change, improve, and innovate.
The competency view is the most "outward looking" and begs the important question: which competencies should an operation have, nurture, or develop? This naturally connects to competitive strategy.
Comperency Simulation Analytics
Businesses typically have a mix of products and services requiring product-mix decisions which are usually supported by analytical methods such as Linear Programming (LP). These decisions are usually made so that the market demand is met and the firm profit is maximized. However, the complexity, and stochastic and dynamic nature of real-world production and business systems often lead to production levels that are different from those determined by analytical methods. Analytical methods also have problems coping with the dynamic changes in the product-mix which usually requires enhancing system parameters and/or configuration 0f value creation and delivery processes.
Analyzing the impact of product/service-mix on operating system capacity involves creating simulation models of the joint configuration of resources and processes and ensuring the resulting competencies are aligned with the organization's market positioning for demand of products and services. Operating System Capacity refers to the organization system's potential to produce goods and services over a specified time interval.
Creating Competency Simulation Analytics Models
Creating a simulation experiment to investigate organization Operations System capacity for creating and delivering value defined in terms of product/service-mix involves:
- Create product demand forecast model for products and services - This includes information about the average rates at which customers request for products and/or services including the breakdown of customer order request types (e.g., for a coffee shop regular coffee vs. espresso, for a barbershop haircut vs. shaves, etc.) – at different times of the day, and the orders' sizes
- Create configuration model for the production and/or service delivery functional unit including the configuration model of the people and equipment resources.
- Create configuration model for the products and services mix offered by the organization
- Create configuration model for the workforce (people) and their roles as well as their schedules
- Create configuration model for the equipment including operations and maintenance schedules
- Create schedules for the organization's operating times and holidays.
- Generate/Run operations process simulation models
Operations Simulation Output Analysis
Operations simulation enables management to analyze and evaluate operations output with respect to the relevant competency measures such as cost. time, quality, etc. Analysis involves evaluating and assessing the impact (cost/benefit) on production capacity plan (or schedule) optimization of different alternative resource schedules/plans. The simulation output product is an interactive visualization model of the organization's production operations systems. Users can interact with the visualization to explore and examine the simulation results in areas such as:
- Production output and throughput.
- Resource utilization and load factors - Labor utilization and load factors; Equipment utilization and load factors; Storage utilization and load factors.
- WIP (Work-in-Progress) Inventory Levels and Control Policy Standards.
- Process capacity utilization and load/idle factors.
- Process bottlenecks and product delays.
Visualization of operations system simulation output enables managers and key operations staff to gain insight into the "real world" situations facing the company and improve their understanding of the factors that affect operational performance.
Production Equipment Analytics
The resource view of an organization or any of its parts as a bundle of resources (real assets). Viewing operations as a bundle of real assets is most useful when the decision is on amounts and types of equipment resources the operation needs. This investment or capital budgeting decision, along with the allocation of resources to activities, is one of the major tasks of management.
The resource view of an organization or any of its parts as a bundle of resources (real assets). Viewing operations as a bundle of real assets is most useful when the decision is on amounts and types of equipment resources the operation needs. This investment or capital budgeting decision, along with the allocation of resources to activities, is one of the major tasks of management.
Equipment Capacity Simulation Analytics
Determining the facility and equipment capacity to match production involves simulation of business operations to inform equipment capacity needs decisions. Capacity planning and coordination of work is essentially concerned with the best match of supply with demand in the creation and delivery of products and services to customers. Operations management simulation is concerned with quantifying the utilization of the organization's "Operating System" and providing the best match (fit) of supply (of tangible resources) and demand. Operations simulation techniques can be used to determine the impact of product/service mix changes on effective operating system capacity in terms of system throughput (effective capacity), utilization of tangible resources, product/service delays, etc. Operations simulation enables managers and key operations staff to gain insight into the "real world" situations facing the company and improve their understanding of the factors that affect operational performance.
Users can examine the influence of changes to demand for products in the product mix as well as removal/addition of new products to the mix to be evaluated. Product mix decisions must often satisfy some capacity constraints such as:
Creating Equipment Capacity Simulation Analytics Models
Analyzing the impact of product/service-mix on operating system capacity involves creating simulation models of the joint configuration of resources and processes and ensuring the resulting competencies are aligned with the organization's market positioning for demand of products and services. Operating System Capacity refers to the organization system's potential to produce goods and services over a specified time interval.
Creating a simulation experiment to investigate organization Operating System capacity for creating and delivering value defined in terms of product/service-mix involves:
Simulation Output & Analysis
The simulation output product is an interactive visualization model of the organization's production operations systems. Users can interact with the visualization to explore and examine the simulation results in areas such as:
The simulation output provides information on facility and equipment resources' utilization and workloads, and associated overall business (throughput) performance information to inform equipment decisions. Operations Analytics Simulation provides you the evidence to allow you to make bold, confident decisions because you are sure you are making the right choice.
Visualization of operations management simulation output enables managers and key operations staff to gain insight into the "real world" situations facing the company and improve their understanding of the factors that affect operational performance.
Determining the facility and equipment capacity to match production involves simulation of business operations to inform equipment capacity needs decisions. Capacity planning and coordination of work is essentially concerned with the best match of supply with demand in the creation and delivery of products and services to customers. Operations management simulation is concerned with quantifying the utilization of the organization's "Operating System" and providing the best match (fit) of supply (of tangible resources) and demand. Operations simulation techniques can be used to determine the impact of product/service mix changes on effective operating system capacity in terms of system throughput (effective capacity), utilization of tangible resources, product/service delays, etc. Operations simulation enables managers and key operations staff to gain insight into the "real world" situations facing the company and improve their understanding of the factors that affect operational performance.
Users can examine the influence of changes to demand for products in the product mix as well as removal/addition of new products to the mix to be evaluated. Product mix decisions must often satisfy some capacity constraints such as:
- Resource capacity – Production to meet the product mix demands cannot use more resources than are available.
- Demand – Customer (end user and/or stock) demand for each product is limited, and production should not produce more of a product than is demanded because the excess production is wasted.
Creating Equipment Capacity Simulation Analytics Models
Analyzing the impact of product/service-mix on operating system capacity involves creating simulation models of the joint configuration of resources and processes and ensuring the resulting competencies are aligned with the organization's market positioning for demand of products and services. Operating System Capacity refers to the organization system's potential to produce goods and services over a specified time interval.
Creating a simulation experiment to investigate organization Operating System capacity for creating and delivering value defined in terms of product/service-mix involves:
- Create product demand forecast model for products and services - This includes information about the average rates at which customers request for products and/or services including the breakdown of customer order request types (e.g., for a coffee shop regular coffee vs. espresso, for a barbershop haircut vs. shaves, etc.) – at different times of the day, and the orders' sizes
- Create configuration model for the production and/or service delivery functional unit including the configuration model of the people and equipment resources.
- Create configuration model for the products and services mix offered by the organization
- Create configuration model for the workforce (people) and their roles as well as their schedules
- Create configuration model for the equipment including operations and maintenance schedules
- Create schedules for the organization's operating times and holidays.
- Generate/Run operations process simulation models
Simulation Output & Analysis
The simulation output product is an interactive visualization model of the organization's production operations systems. Users can interact with the visualization to explore and examine the simulation results in areas such as:
- Production output and throughput.
- Resource utilization and load factors - Labor utilization and load factors; Equipment utilization and load factors; Storage utilization and load factors.
- WIP (Work-in-Progress) Inventory Levels and Control Policy Standards.
- Process capacity utilization and load/idle factors.
- Process bottlenecks and product delays.
The simulation output provides information on facility and equipment resources' utilization and workloads, and associated overall business (throughput) performance information to inform equipment decisions. Operations Analytics Simulation provides you the evidence to allow you to make bold, confident decisions because you are sure you are making the right choice.
Visualization of operations management simulation output enables managers and key operations staff to gain insight into the "real world" situations facing the company and improve their understanding of the factors that affect operational performance.
Service Delivery Systems Analticss
Service delivery system processes provide services to customers. The process view considers an organization (or any of its parts) to be an activity network or a collection of processes. A process can refer to detailed workflow, such as billing a customer, or implementing an engineering change order, or to aggregate activities of new product development, or customer service. Adopting a process view means that we visualize instances of work, called flow units (e.g., consulting engagements, hospital patients, barbershop patrons, hotel guests, or service orders) flowing through a network of activities and buffers. The primary workflow is typically accomplished by an information flow (to coordinate the activities), and a cash flow (to support and reward them). Processes are structured, recurrent activities that transform inputs into outputs. A process is a network of activities with specific precedence relationships among activities - the relationships that specify which activities must be finished before another activity can begin.
Service delivery system processes provide services to customers. The process view considers an organization (or any of its parts) to be an activity network or a collection of processes. A process can refer to detailed workflow, such as billing a customer, or implementing an engineering change order, or to aggregate activities of new product development, or customer service. Adopting a process view means that we visualize instances of work, called flow units (e.g., consulting engagements, hospital patients, barbershop patrons, hotel guests, or service orders) flowing through a network of activities and buffers. The primary workflow is typically accomplished by an information flow (to coordinate the activities), and a cash flow (to support and reward them). Processes are structured, recurrent activities that transform inputs into outputs. A process is a network of activities with specific precedence relationships among activities - the relationships that specify which activities must be finished before another activity can begin.
Service Delivery System Analytics
Service delivery system processes provide services to customers. The service process capacity is defined holistically in terms of the throughput of the flow of customers (e.g., in retail, patients in health care, clients in barbershops/salons, guests in hotels, etc.) per specified time interval, Servicing centers are augmented with waiting areas; waiting areas may be introduced to act as buffers to bottleneck service centers that constrain the flow of customers in the service network. Anything that eases throughput by releasing the bottleneck potentially adds value to the system.
Distinctive Features of Service Delivery Systems
Although many of the principles of good management in a manufacturing/production environment also apply in organizations that provide services, service businesses such as banking, professional firms of accountants, etc., do have a number of distinctive features which have implications on how they are managed.
Service Delivery System Simulation Analytics
The process view of operation shows how the resource portfolio is utilized and allocated to activities with the intent of adding value. These production and service delivery systems processes can be analyzed systematically as part of whole organization workflow through simulation methods, to identify potential bottlenecks and inefficiencies for improvements. Simulation enables users to explore maximizing organization output subject to minimizing delays through reducing/eliminating waiting times, improving labor and equipment utilization, etc.
Creating Service Delivery System Simulation Analytics Models
Creating a simulation experiment to investigate service delivery effective capacity, and capacity decisions related to services to deliver of value to customers involves:
These production and service delivery systems processes can be analyzed systematically as part of whole organization workflow through simulation methods, to identify potential bottlenecks and inefficiencies for improvements. Simulation enables users to explore maximizing organization output subject to minimizing delays through reducing/eliminating waiting times, improving labor and equipment utilization, etc.
Simulation Output Analysis & Visualization
The Production and/or service systems simulation enable managers and key operations staff to gain insight into the "real world" capacity problems facing the company, and improves their understanding of the factors that affect production and service delivery performance. The simulation and visualization informs decisions on:
Simulation informs decisions on the optimum configuration of processes such as:
Service delivery system processes provide services to customers. The service process capacity is defined holistically in terms of the throughput of the flow of customers (e.g., in retail, patients in health care, clients in barbershops/salons, guests in hotels, etc.) per specified time interval, Servicing centers are augmented with waiting areas; waiting areas may be introduced to act as buffers to bottleneck service centers that constrain the flow of customers in the service network. Anything that eases throughput by releasing the bottleneck potentially adds value to the system.
Distinctive Features of Service Delivery Systems
Although many of the principles of good management in a manufacturing/production environment also apply in organizations that provide services, service businesses such as banking, professional firms of accountants, etc., do have a number of distinctive features which have implications on how they are managed.
- Services are less easily standardized than products and so service quality tends to be more variable. This makes human resource management and motivation more critical.
- Services are often intangible and multi-dimensional; this can make attracting customers more difficult as it often depends on promoting an intangible item.
- Unlike manufactured products, services cannot be stored, but must be consumed as they are produced or they are wasted. This creates additional problems matching productive capacity with customer demand. This is reflected in for example, the marginal cost to fill empty seats - a plane flying empty to New York is a service provided but wasted.
- Ascertaining the cost of individual services is often also problematic, as the cost structure of many services business is such that costs are often shared among different services. This makes pricing and analysis of profitability of different services more difficult.
Service Delivery System Simulation Analytics
The process view of operation shows how the resource portfolio is utilized and allocated to activities with the intent of adding value. These production and service delivery systems processes can be analyzed systematically as part of whole organization workflow through simulation methods, to identify potential bottlenecks and inefficiencies for improvements. Simulation enables users to explore maximizing organization output subject to minimizing delays through reducing/eliminating waiting times, improving labor and equipment utilization, etc.
Creating Service Delivery System Simulation Analytics Models
Creating a simulation experiment to investigate service delivery effective capacity, and capacity decisions related to services to deliver of value to customers involves:
- Creating service demand forecast model - This includes information about the average rates at which customers request for services including the breakdown of customer order request types (e.g., for a coffee shop regular coffee vs. espresso, for a barbershop haircut vs. shaves, etc.) – at different times of the day, and the orders' sizes
- Creating configuration model for the service delivery operation including the configuration model of the groups of people and equipment resources.
- Creating configuration model for the services mix offered by the organization
- Creating configuration model for the workforce (people) and their roles as well as their schedules
- Creating configuration model for the equipment including operations and maintenance schedules
- Creating schedules for the organization's operating calendar - workdays, times and holidays.
- Generate/Run operations process simulation models
These production and service delivery systems processes can be analyzed systematically as part of whole organization workflow through simulation methods, to identify potential bottlenecks and inefficiencies for improvements. Simulation enables users to explore maximizing organization output subject to minimizing delays through reducing/eliminating waiting times, improving labor and equipment utilization, etc.
Simulation Output Analysis & Visualization
The Production and/or service systems simulation enable managers and key operations staff to gain insight into the "real world" capacity problems facing the company, and improves their understanding of the factors that affect production and service delivery performance. The simulation and visualization informs decisions on:
- Demand Management - Specifying how to match demand to available resources; and tactical allocation of capacity.
- Process Network Structure - Decision of the layout of the activity network in terms of locations of activities, buffers and interconnections. For example, processes can be organized by activity, or by product line; job shops such as consulting companies, and tool-die-shops often have a functional or process layout, while flow shops such as assembly plants, and chemical processing plants usually have a product layout.
- Coordination and Information technology decisions on how to coordinate, communicate, and plan execution throughout the network. Coordination is typically a managerial activity and includes assignment of responsibility, incentives, measurements and control.
- Product architecture decisions on structure and parts to facilitate production.
- Transportation technology decisions on how goods are exchanged among different activities in the network. This is a key driver in logistics and supply chain management, as well as how insurance policies are moved between the different processing steps.
Simulation informs decisions on the optimum configuration of processes such as:
- Supply or Sourcing Decisions - These decisions specify which activities are performed internally, and which activities are outsourced, and how to manage suppliers. Decisions involve defining the process boundaries and interfaces. It includes strategic sourcing decisions, vertical integration, and supply network configuration.
- Technology Decisions - These decisions characterize how to process inputs into outputs. It includes the methods and systems employed, as well as the know-how and intellectual property. The technology decisions can be grouped into the following key categories: a) coordination and information technology decisions such as assignment of responsibility, incentives, measurement, and control; b) product technology decisions in product philosophy, product architecture, and product capabilities; c) process technology decisions on how to structure the conversion processes and methods used in execution; and d) transportation technology decisions on how goods are exchanged among different activities in the network.
- Demand Forecast Decisions - These decisions specify how to match demand to available supply. These decisions characterize the interfaces and relationships with customers and include demand planning and forecasting, as well as tactical capacity allocation and order management. Demand management is an important driver in inflexible supply processes that cannot quickly adapt to changes in demand such as the core processes in airlines, hotels, hospital wards, and car rental companies, It also relates to service and customer relationship management.
- Improvements and Innovation Decisions - These are decisions on characterizing the processes and incentives to improve and innovate products and processes.
