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.

Finance Business

Causal loop diagram illustrating one of the contributing factors to employee hiring.

Business Hiring Employment

​The Problem: What is the true cost of escalating too many Tier 1/Level 1 tickets to Level 2/3 engineers?
Things to measure: How does this impact:1. (MONEY) Cost per incident - what does this cost the business? 2. (TIME) Service Level - how does this impact desired service levels/SLAs? 3. (PEOPLE) Agent utilization - how does this impact backlog? are we overworking engineers? Does this contribute to staff burnout?

Business Help Desk Technology

Business

ABM approach to Bass Model of diffusion with a detractor state.
Still a work in progress.

Marketing Business Bass

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

Business

Business Stock Management

​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.

Business System Dynamics

Rich Picture with Simulation

Business

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.

Business Logistics Supply Chain

The Simple Retail Sector model from Section 1.7 of DYNAMO User's Manual by Alexander L Pugh III, which is adapted from one from Industrial Dynamics by Jay Forrester.
http://www.amazon.com/DYNAMO-Manual-Edition-System-Dynamics/dp/0262660296 (I bought the 5th edition without realising there was a later one, hopefully it's still the same model in there.)

A tweaked version with slightly more explicit stocks is here: http://insightmaker.com/insight/14467

DYNAMO Retail Business

Dynamic system underlying project life cycles From Roberts Edward B The Dynamics of Research and Development p5 Harper & Row NY 1964

Business Health Care Technology Project

Business Stock Management

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

 

Business Health Care Services Clinical Care Work

Business Stock Management

​Purpose
Enables the different components in the 5 capability model in a visual manner for Enterprise and Business Architecture stakeholders.  
Enter volumes based on transactions from all your applications based on the business process layer.  Actual transaction volumes recorded for your expense or revenue stream.  Example; how many applications are sponsored by engineering that allow CREATE and UPDATE of a supplier or customer.  Enter the number of transactions in the engineering variable.  The engineering group has no authority to create either a supplier or customer.  All organizations are allowed to submit a certain set of inputs for a super user group to review and then those super users create and update the master record.  

Food for thought, the difference between the records created by the super user group and the volume of created party management records is the opportunity to scale and protect the reputation of your client.  
Now lets do the same for every update to a party management record.  All changes to a supplier or customer could effect pricing and tax or duty fees and each must use the formal change management process with many changes needing to have an authorized representative from the supplier or customer.  Digital records are in need of key control designs.  These are monitored and reported to the SEC.  

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.  

Business Technology Quality 5 Capability Model Application As Is To Be Enterprise And Business Architecture

Business Stock Management

​The Problem: What is the true cost of escalating too many Tier 1/Level 1 tickets to Level 2/3 engineers?
Things to measure: How does this impact:1. (MONEY) Cost per incident - what does this cost the business? 2. (TIME) Service Level - how does this impact desired service levels/SLAs? 3. (PEOPLE) Agent utilization - how does this impact backlog? are we overworking engineers? Does this contribute to staff burnout?

Business Help Desk Technology

This model is based off Meadows economic capital with reinforcing growth loop constrained by a renewable resource model.

Business Environment

Business

Business Stock Management

Business Management

Business Stock Management

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. 

Business Logistics Supply Chain