Business | Insight Maker

The issue is how to select and keep optometry students. The main theme is balance out expectations with reality especially when many students use optometry as a proxy for later entry into a medical course. The second problem is that the current entry demographic does not meet the needs in terms of culture and expected practice location

Clone of optometry student recruitment, training, retention and expectations

Terry Flynn

Clone of Simulação Computacional

Nilo Guimaraes

Morecroft, John (2015) Strategic Modelling and Business Dynamics, Ch 1 p13 -14

Fish Banks

Adrien

How the Lean Startup method, developed by Eric Reis, works as a business system.

Clone of Lean Startup Business System

Giorgos Arampatzis

Simple model used to assess the likely outcome of Revenue and Profit due to variability of purchase price, price impact on Units Sold, and Units Sold impact on Unit Cost.

Clone of Impact of variable price on revenue & profit

Richard Auger

Rich picture version of Causal loop diagram based on Jack Homer's paper Worker burnout: a dynamic model with implications for prevention and control System Dynamics Review 1985 1(1)42-62 See IM-333 for the Simulation model and IM-2178 for a related Causal Loop Diagram of Project Turnover

Clone of Burnout Dynamics CLD rich pic

Micha Newman

Clone of Inventarios

Gabriel Márquez Sagastume

model

Clone of model

KEVIN LEWIS O'CARROLL

Purpose
Enables the different components in the 5 capability model in a visual manner for Enterprise and Business Architecture stakeholders.

BUSINESS ARCHITECTURE

5 Capability Model
The 5 capability model has many stock and flow children which each organization will need to model based on their current state.

Aligns to APQC Process Framework
Aligns to Principles in ISO 9001, 26000 and 27001

ENTERPRISE ARCHITECTURE
Aligns Zachman Framework Enterprise and Business Architecture with Executive and Leaders from a business management level across any organization.

A method in which to align and benchmark any organization or agency, with the system(s) logic required from Architects in Row 3, to enable Row 4 engineers who need to supply physics.

Semantic
Getting terms to align to the generic objects can be a trying task, unless you simply list the stakeholders "semantic" term below the stakeholder in the presentation layer by order shown in the business process management section above the capability management group.

Clone of To Be Business and Technology Architecture

Steven van Hekelen

Fragmenteret it landskab

Heidi Christiansen

Rich picture version of Causal loop diagram based on Jack Homer's paper Worker burnout: a dynamic model with implications for prevention and control System Dynamics Review 1985 1(1)42-62 See IM-333 for the Simulation model and IM-2178 for a related Causal Loop Diagram of Project Turnover

Clone of Burnout Dynamics CLD rich pic

Shane Michael Thomas

Multi-echelon inventory optimization (sounds like a complicated phrase!) looks at the way we are placing the inventory buffers in the supply chain. The traditional practice has been to compute the safety stock looking at the lead times and the standard deviation of the demand at each node of the supply chain. The so called classical formula computes safety stock at each node as Safety Stock = Z value of the service level* standard deviation * square root (Lead time). Does it sound complicated? It is not. It is only saying, if you know how much of the variability is there from your average, keep some 'x' times of that variability so that you are well covered. It is just the maths in arriving at it that looks a bit daunting.

While we all computed safety stock with the above formula and maintained it at each node of the supply chain, the recent theory says, you can do better than that when you see the whole chain holistically.

Let us say your network is plant->stocking point-> Distributor-> Retailer. You can do the above safety stock computation for 95% service level at each of the nodes (classical way of doing it) or compute it holistically. This simulation is to demonstrate how multi-echelon provides better service level & lower inventory. The network has only one stocking point/one distributor/one retailer and the same demand & variability propagates up the supply chain. For a mean demand of 100 and standard deviation of 30 and a lead time of 1, the stock at each node works out to be 149 units (cycle stock + safety stock) for a 95% service level. You can start with 149 units at each level as per the classical formula and see the product shortage. Then, reduce the safety stock at the stocking point and the distributor levels to see the impact on the service level. If it does not get impacted, it means, you can actually manage with lesser inventory than your classical calculations.

That's what your multi-echelon inventory optimization calculations do. They reduce the inventory (compared to classical computations) without impacting your service levels.

Hint: Try with the safety stocks at distributor (SS_Distributor) and stocking point (SS_Stocking Point) as 149 each. Check the number of stock outs in the simulation. Now, increase the safety stock at the upper node (SS_stocking point) slowly upto 160. Correspondingly keep decreasing the safety stock at the distributor (SS_Distributor). You will see that for the same #stock outs, by increasing a little inventory at the upper node, you can reduce more inventory at the lower node.

Clone of Multi-echelon Inventory Optimization

Ananya Jain

This model attempts to understand the behavior of average lifetime of companies in the S&P500 index. The reference mode for the model is a graph available at this link: https://static-cdn.blinkist.com/ebooks/Blinkracy-Blinkist.pdf (page 5) which was discussed in the System Thinking World Discussion forum.

Mergers & Acquisitions can be one of the reasons for older companies to be replaced with newer companies in the Index. With M&A of older companies, the empty slots are taken over by newer companies. However, overtime, these new companies themselves become old. With steady M&A, the stock of older companies decreases and stock of newer companies increases. The result is that average age of the companies in the S&P Index decreases.

The oscillations in the diagram, according to me, is due to oscillations in the M&A activity.

There are two negative feedback loops in the model. (1) As stock of new companies increases, the number of companies getting older increases which in turn decreases the stock. (2) As M&A increases, stock of older companies decreases which in turn decreases M&A activities.

Limits of the model

The model does not consider factors other than M&A in the increase in number of new companies in the Index. New companies themselves may have exceptional performance which will result in their inclusion in the Index. Changes in technology for example Information Technology can usher in new companies.

Assumptions

1. It is assumed that M&A results in addition of new companies to the Index. There could be other older companies too, which given the opportunity, can move into the Index. Emergence of new technologies brings in new companies.

Clone of Age of companies in S&P500

David Horgan

Clone of Clone of Grocery Store System - Stock & Flow Diagram/SD Model

Henry Weber

BLACK_WALL_STREET_ROXBURY

Innocentia Ashai

model

Clone of model

Monisha Yuvaraj

ABM approach to Bass Model of diffusion with a detractor state.

Still a work in progress.

ABM Bass Diffusion with Detractors

Jess Laventall

DRAFT

a small model of a "generic" company.

Clone of small model company draft

Mi_Ko

product life cycle

Clone of Clone of SD generic behavior S-shaped SIM

Alena Peskova

With Cloud becoming the operating word, many Purchasing Managers have to deal with a variety of contracting types. At a basic level, there are two kinds - subscription contracts and consumption contracts.

Subscription contracts require you to commit to a certain volume upfront for the contracting period. This does not depend on the actual consumption. In contrast, consumption contracts let you pay based on the actual consumption.

On the face of it, it looks like Consumption Contracts are better. However, consumption contracts come at a premium. The question is - how much of the premium is justified for the consumption contracts given certain demand uncertainty?

This is a basic model that lets you understand the dynamics. The demand has uniform distribution between a minimum of 90 and a maximum of 100. Subscription contract is priced at a monetary unit of 100. Consumption contracts command a premium for the flexibility they are offering. You can play with the premium (it is a premium you are paying over 100) by moving on the slide bar and see how the costs of subscription and consumption are shaping up.

Hope you enjoy it.

Consumption Contracts vs Subscription Contracts