Business Models

These models and simulations have been tagged “Business”.

Related tagsTechnology

Insight diagram

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
Insight diagram

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
Insight diagram
EEIS Health App
Insight diagram
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


Clone of Bottom-up Sales Forecasting
Insight diagram

Harvested fishery with endogenous investment. Ch 9 p340-345 John Morecroft (2007) Strategic Modelling and Business Dynamics

Harvested Fishery with Endogenous Investment
Insight diagram
Clone of Inventarios
Insight diagram
This model is based off Meadows economic capital with reinforcing growth loop constrained by a renewable resource model.
Clone of Tourism Simulator
Insight diagram
Clone 2 of Grocery Store System - Stock & Flow Diagram/SD Model
Insight diagram
Clone of Inventarios
Insight diagram
Coffee making process.
Café Coffee Simulation Deliverable 2
Insight diagram
Clone of Clone of Grocery Store System - Stock & Flow Diagram/SD Model
11 months ago
Insight diagram
Clone of Grocery Store System - Stock & Flow Diagram/SD Model
4 11 months ago
Insight diagram
ABM approach to Bass Model of diffusion with a detractor state.

Still a work in progress.
Clone of ABM Bass Diffusion with Detractors
Insight diagram
Clone of Inventarios
Insight diagram

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
Insight diagram

Scenario cliente per valutare strategia di risposta agli eventi o la strategia di sviluppo 

Mondo chiuso (trascura il resto del mondo)

Customer scenario
Insight diagram
product life cycle
Clone of SD generic behavior S-shaped SIM
Insight diagram

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

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.  

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
Insight diagram
The need to spend time doing chargeable work, in balance and/or conflict with the need to spend time doing marketing to ensure a continuing workload into the future.
Clone of Spending time on chargeable billings vs. marketing
Insight diagram
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
Insight diagram
Clone of Inventory model with delays
Insight diagram
This is the model I developed within the scope of my article titled "System dynamics and geometric compromise programming: assessing the impact of entrepreneurship wage subsidies on macroeconomic objectives".
You can access my published article via this link: http://doi.org/10.1111/itor.13601
System dynamics and geometric compromise programming: assessing the impact of entrepreneurship wage subsidies on macroeconomic objectives (Article)
9 months ago
Insight diagram
Clone of Grocery Store System - Stock & Flow Diagram/SD Model
11 months ago