Business Models

These models and simulations have been tagged “Business”.

Related tagsTechnology

This simulation mimics the flow of projects through an organization. The organization consists of teams that idependently or collaboratively work on projects. Many of the projects have a mulit-team dependency.    If you want to understand more in depth what this simulation is all about, read this bl
This simulation mimics the flow of projects through an organization. The organization consists of teams that idependently or collaboratively work on projects. Many of the projects have a mulit-team dependency.

If you want to understand more in depth what this simulation is all about, read this blog post: https://stefan-willuda.medium.com/super-powerful-how-full-kitting-will-speed-up-your-cross-team-projects-1598d55fa9d7
 ​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
​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.  



 Bottom-Up Sales Forecasting for Startups     The purpose of this simulation is to demonstrate the implications of forecasting sales without consideration for how much it cost you to acquire a lead and how much you have available to spend. A common mistake in sales forecasting is to define your # of
Bottom-Up Sales Forecasting for Startups

The purpose of this simulation is to demonstrate the implications of forecasting sales without consideration for how much it cost you to acquire a lead and how much you have available to spend. A common mistake in sales forecasting is to define your # of expected sales leads based on your total market size and your assumption regarding the % of that market you can reach. 

This model demonstrates the forecasting impact to defining the # of expect leads based on how much it cost you to acquire a lead and how much you have available to spend. 

Important Variables:
1. [UseLAC?] (set to 1 to use the lead acquisition cost to define your reachable market; use 0 to set the reachable market to equal the total available market size)
2. LAC (should equal what it cost you to acquire a lead)
3. SalesMarketingBudget : how much you have available to spend on customer acquisition

Other Variables:
4. Price : Avg spending amount per new customer
5. Total Available Market : Total available market size
6. Conversion Rate : the % of your target market that will become a lead


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 pe
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. 
Process of petrol from a petrol pump being used to fuel vehicles
Process of petrol from a petrol pump being used to fuel vehicles
 ​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 Dis

​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.

DRAFT  a small model of a "generic" company.
DRAFT

a small model of a "generic" company.
 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 
  

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

 

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

Still a work in progress.
 Dynamic system underlying project life cycles From Roberts Edward B The Dynamics of Research and Development p5 Harper & Row NY 1964

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

 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 su
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.
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.
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.
This causal loop diagram is the first step in looking at the relationship between business analysis performance and organizational performance. Over time it will be extended by IIBA R&I to form a simulation.    © International Institute of Business Analysis
This causal loop diagram is the first step in looking at the relationship between business analysis performance and organizational performance. Over time it will be extended by IIBA R&I to form a simulation.

© International Institute of Business Analysis
 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 
  

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