UIW System Exemplars for Use It Wisely (UIW)

by Professor Stefan Grösser, Bern University of Applied Sciences

As referenced in D2.2, BUAS has introduced the cluster organizations to a tutorial using a generic business structure. The generic business model structure includes all major elements of business with generic values. The tutorial has been used by some of the cluster organizations as part of the preparation for the modeling process of cluster specific models. This work provided the basis for the development of the UIW System Exemplars.

UIW System Exemplars are basic structures of System Dynamics models created during the UIW project. As part of the UIW platform (WP1), BUAS contributes with UIW System Exemplars to answer the UIW challenge. We develop the UIW System Exemplars by means of an inductive process of extracting them from the causal context models (CCM) produced by the cluster members. The UIW System Exemplars should illustrate the basic understanding of upgrading and its effects for producers as well as users of upgradable assets. The structures form the basis of reflection for cluster members on how to describe and model the benefits of shortening upgrade cycles and the power of upgrading.

All UIW System Exemplars consist of two parts:

  1. The System Structure Diagram: This is a qualitative description of the System Exemplar derived from the Causal Context Models developed by the cluster members as part of D2.1 and D2.2
  2. The Simulation Model: This is an extension of the System Structure Diagram and populated with generic values to illustrate the upgrading concepts in a quantitative way.

The UIW System Exemplars will be publicly available and can be used as first steps in the modeling process identifying the simple underlying structures of a potential upgrading problem a user of the platform has. The provided UIW System Exemplars are the first element of any UIW related System Dynamics model and allow practitioners to start modeling their own upgrading challenges using the UIW System Exemplars as a stepping stone for a more specific model directly applied to their challenge.

Click on each of the titles below to read more on that topic.

1. Criteria for UIW System Exemplars

The criteria for the development of the UIW System Exemplars for the UIW project are as follows:

  • Most simple underlying models to explain benefits and challenges, as well as organizational constraints to upgrading
  • Recurring upgrading structures found in multiple models or with possible application in multiple models.
  • Limited to a small number of stocks

2. Notational elements of generic UIW structures

  • Causal relationships: Displayed as blue arrows where a change in X causes a change in Y. Can have a positive (+) or negative (-) polarity.
    • Positive polarity: All else equal, if X increases (decreases), then Y increases (decreases) above (below) what it would have been.
    • Negative polarity: All else equal, if X increases (decreases), then Y decreases (increases) below (above) what it would have been.
  • Causal Loops: A causal loop diagram is a simple map of a system with all its constituent components and their interactions. By capturing interactions and consequently the feedback loops (see figure below), a causal loop diagram reveals the structure of a system. By understanding the structure of a system, it becomes possible to ascertain a system’s behavior over a certain time period. Causal loops can be reinforcing (R) or balancing (B).
    • Reinforcing means that an increasing/decreasing effect on one variable of the loop produces a further increasing/decreasing effect on that variable through the feedback of the loop.
    • Balancing means that an increasing/decreasing effect on a variable in the loop has a decreasing/increasing effect through the feedback of the loop.
  • Stocks: A stock is the term for any entity that accumulates or depletes over time. A flow is the rate of change in a stock.

3. UIW System Exemplar #1: Product attractiveness at termination of contract

3.1. System Structure Diagram

Figure 1: UIW System Exemplars 1 – Product attractiveness at moment of liquidation. (Click image to enlarge)

Figure 1: UIW System Exemplars 1 – Product attractiveness at moment of liquidation. (Click image to enlarge)

UIW System Exemplar #1 focuses on the effect of upgrading on customer flows. In the center in Figure 1 the structure consists of two stocks: “Potential customers” and “Customers of Company A”. Company A can gain (customers move from potential to company A) and lose customers (customers move from company A to potential). The time a customer stays a customer of company A is determined by the “Product use time”. The definition of customers in this model therefore differs from the definition of customers in business, where customers mostly are considered to have purchased a product or service during the accounting period applied, as the customer stays a customer for the time they use the product. This difference in definitions is however crucial. This difference only applies to businesses which do not maintain a relationship with its customers through maintenance or upgrading services for the duration of the product use time. For these companies, once the product has been used, the customer returns to the stock of potential customers. Customers are gained and regained in a competition of who has the most attractive product (“Product attractiveness at purchase”).

In the UIW scenario the relationship with the customer is ideally ongoing. Products could be maintained and/or upgraded increasing the interaction with customers over the entire use time. Upgrading the product leads to an increase in “product attractiveness at termination of contract”. This in turn leads to an increase in “retained customers” because customers are more likely to be satisfied with the product and therefore are more likely to repurchase from company A without considering the offers of competitors as would be the case if the customer returned to the stock of “potential customers”.

3.2. Simulation Model

Figure 2 shows the simulation model of the UIW System Exemplar #1. The structure has 3 reinforcing loops: R1 shows the returning customers to Company A, R2 the “normal” customer gains for company A and R3 the customer gains for the competition.

Figure 2: Simulation model to UIW System Exemplars #1. (Click image to enlarge)

Figure 2: Simulation model to UIW System Exemplars #1. (Click image to enlarge)

We will run 2 scenarios, one with no upgrades (“number of upgrades” = 0) and one with a high number of upgrades (“number of upgrades” = 12) and compare both of them to the base run (“number of upgrades” = 6).

Figure 3: Comparing the base run with different levels of upgrading. (Click image to enlarge)


Figure 3: Comparing the base run with different levels of upgrading. (Click image to enlarge)

In Figure 3 can be seen that there is a slight difference in numbers of customers between the base run and the scenario with no upgrades. In contrast, the scenario with a high number of upgrades shows a steadily increasing number of “customers for company A”. This is due to the fact that the high number of upgrades retains a high product attractiveness and results in a “product attractiveness at termination of the contract” close to the “product attractiveness at purchase”. In the base run the “product attractiveness at termination of contract” is lower and in the case of no upgrades the product is used up and the attractiveness is 0 (Figure 4).

Figure 4: Product attractiveness at termination of contract. (Click image to enlarge)

Figure 4: Product attractiveness at termination of contract. (Click image to enlarge)

This leads to “percentage of customers of company A being retained” values of 55%, 12% and 0% for the highupgrades, base and noupgrades run respectively and leads to the customer growth from Figure 3.

The cost of these updates has not been included in the model, meaning that the cost of having a high number of upgrades might outweigh the revenues generated through additional customers. However, it is also reasonable to assume that returning customers are satisfied customers and therefore word of mouth could also increase the “normal market share of company A”, meaning the fraction of customers gained from the “potential customers”.

4. UIW System Exemplars #2: Appropriateness of maintenance

4.1. System Structure Diagram

Figure 5: UIW System Exemplars #2 – Appropriateness of maintenance. (Click image to enlarge)

Figure 5: UIW System Exemplars #2 – Appropriateness of maintenance. (Click image to enlarge)

UIW System Exemplars #2 focuses on upgrading the information technology to provide more accurate information on the state of the asset in question. The increased quality of the information increases the appropriateness of the maintenance work executed on the asset. This is particularly important in cases where maintenance leads to a shutdown of the asset.

“Appropriateness of maintenance” considers two aspects of maintenance in this UIW System Exemplars. One element is temporal while the other addresses depth. The temporal aspect is to plan and adapt the number of maintenance occurrences over time, i.e. to only run maintenance when it is required and thereby leading to fewer maintenance occurrences and decreasing costs which in turn increase the “profits produced through the use of the asset”. The depth element of the maintenance considers whether the extent of the maintenance was appropriate and therefore the productivity of the asset has been returned to initial levels or above which in turn also has an increasing effect on the “profits produced through the use of the asset”.

4.2. Simulation Model

The simulation model for UIW System Exemplar #2 consists of two loops showing the double effect of “appropriateness of maintenance”: a) The “maintenance cost” is reduced due to the elimination of unnecessary maintenance and b) the “revenue of asset” increases due to reduced downtime. In order to achieve a high level of “appropriateness of maintenance” the information technology has to be on a high level to provide decision makers with accurate and adequate data. This requires a certain level of investment which is modelled in this case as a percentage of the profit generated by the asset (“investment fraction”). Both R1 and R2 are reinforcing loops that have an amplifying effect on the investment.

Figure 6: Simulation model for UIW System Exemplars #2. (Click image to enlarge)

Figure 6: Simulation model for UIW System Exemplars #2. (Click image to enlarge)

We chose to run two scenarios and compare them to the base run. The scenario variable is “investment fraction” with a base value of 0.12. The two scenarios are high investment (“investment fraction” = 0.18) and low investment (“investment fraction” = 0.06).

Figure 7: Comparing the base run with different levels of investment. (Click image to enlarge)


Figure 7: Comparing the base run with different levels of investment. (Click image to enlarge)

All three runs improve the profit over time. Not surprisingly, high investment (run 3) improves the fastest and achieves the highest level (Figure 7). The parallel growth initially (Months 0 to 35) for all runs is due to the “normal investment” which is executed regardless of the level of profit the asset generates. The low investment scenario continues growth along these lines because 6% reinvestment seems to be an insufficient policy to accelerate the improvement of the Information Technology.

Figure 8: Showing the effects on information technology. (Click image to enlarge)


Figure 8: Showing the effects on information technology. (Click image to enlarge)

The description above is confirmed in Figure 8. The high investment policy generates a more rapid growth of the “quality of the information technology”.

Figure 9: Showing the interplay between the upgrading of information technology and profits. (Click image to enlarge)


Figure 9: Showing the interplay between the upgrading of information technology and profits. (Click image to enlarge)

In Figure 9 the reinforcing effect between upgrading and profits is shown. Only the high investment run is shown in the graph. In the first part until month 30 the profits are very low and the company invests at a normal rate of 5 EUR/month. The “quality of the information system” steadily increases. After around 30 months however the informant system starts to decrease downtime and increase “appropriateness of maintenance” that results in increase profits and thus increased reinvestments. This lasts until month 50 when the upgrading reaches a maximum. This is due to the fact that the “quality of the information system” cannot be improved indefinitely and the company starts to reduce the “investment fraction” for the information system. After around month 70 the upgrading levels off indicating that the company invests enough to maintain the “quality of information technology” and profits continue to grow steadily.

5. UIW System Exemplars #3: Increasing duration of asset usage

5.1. System Structure Diagram

Figure 10: UIW System Exemplars #3 – Increasing duration of asset usage. (Click image to enlarge)

Figure 10: UIW System Exemplars #3 – Increasing duration of asset usage. (Click image to enlarge)

UIW System Exemplar #3 addresses the issue of extending the product life time through upgrading. The more flexible an asset is, i.e. the more easily the asset can be adapted to the production of a new product line, the less upgrading a product needs which decreases the “cost of upgrading assets” and increases the “duration of asset usage”. This has a positive effect for the customer who uses the asset because the “total cost of using the asset” decreases while it has a negative effect for the producer because the income generated through upgrades will decrease. Therefore this increased asset flexibility should be reflected in the “price of the asset” to recover the lost upgrading income.

5.2. Simulation Model

The system shows the two sides of the user (left) and producer (right). The producer invests into increased flexibility of the asset in order to enable the user to use the asset more flexibly. This can for example be a production chain that can be adjusted more easily and quickly to new demands. To achieve that, the producer has to invest into “asset usage flexibility”.

Figure 11: Simulation model for UIW System Exemplars #3. (Click image to enlarge)

Figure 11: Simulation model for UIW System Exemplars #3. (Click image to enlarge)

In this model we develop 2 scenarios. One consists of low investment (“normal investment in flexibility of asset” = 100) and one with high investment (=300) and compared them both to the base run (=200).

Figure 12: Showing the number of adaptations in the life time of the asset. (Click image to enlarge)

Figure 12: Showing the number of adaptations in the life time of the asset. (Click image to enlarge)

In Figure 12 the number of adaptations executed on the asset over its life time is shown. This is the result of two effects: a) An increase in “asset usage flexibility index” increases the “duration of asset usage” which increases the “lifetime number of adaptations” and b) an increased flexibility increases the “adaptation frequency” and thus decreases the amount of adaptations. For all runs the number of lifetime adaptations first increases, suggesting that the first effect is stronger initially. Over time however, in order of high investment, base and finally low investment runs, the “lifetime number of adaptations” decreases. This results in cost savings for the customer as for example in the high investment run the customer runs 8 adaptations over an asset lifetime of 26 months initially while at the end of the simulation they run 8 adaptations over an asset lifetime of 47 months (s. Figure 13).

Figure 13: Duration of asset for the three runs of UIW System Exemplar #3. (Click image to enlarge)

Figure 13: Duration of asset for the three runs of UIW System Exemplar #3. (Click image to enlarge)

As can be seen in Figure 14, this is beneficial for the customer as the “monthly cost of using the asset” continually decreases. However, until month 80 the high investment run is the most expensive for the customer, and thus the least desirable. When a certain level of flexibility is reached however the monthly cost drops and becomes the cheapest for the customer. The producer on the other hand profits from the investment in flexibility through an increased sales price, where the sales price increases from 2007 Euro to 3126 Euro, from 1229 to 1680 and from 2789 to 4704 for base, low investment and high investment runs respectively.-Therefore upgrading the flexibility results in gains for both actors in the system.

Figure 14: Monthly costs of using the asset. (Click image to enlarge)

Figure 14: Monthly costs of using the asset. (Click image to enlarge)

6. UIW System Exemplars #4: Market agility

6.1. System Structure Diagram

Figure 15: UIW System Exemplars #4 – market agility. (Click image to enlarge)

Figure 15: UIW System Exemplars #4 – market agility. (Click image to enlarge)

UIW System Exemplars #4 addresses the upgrading topic from a user’s perspective. The more upgrades an asset receives the more the “total costs of asset” increases which in turn reduces the “profit”. However, an increasing number of upgrades also allows the user to react more quickly to differing market demands. This means that the asset can be more compatible with different uses. This in turn provides the user with a competitive advantage which has a positive impact on the “revenue” and the “profit”. By allowing the user to apply the asset to different purposes, for example product lines, the asset also can be utilized more effectively and the costs of upgrading can be distributed across more units produced which also improves the “margin”.

6.2. Simulation Model

UIW System Exemplars #4 does not contain any feedback loops. The objective is to maximize utilization with regard to changing trends. The changing trends require a certain agility from the provider, which is provided by upgrades. In the simulation model the revenue side is shown on the left and the cost side on the right.

Figure 16: Simulation model for UIW System Exemplars #3. (Click image to enlarge)

Figure 16: Simulation model for UIW System Exemplars #3. (Click image to enlarge)

For this UIW System Exemplar the two scenarios are high number of upgrades and low number of upgrades with 7 and 3 upgrades over the cycle time of the asset and are compared to the base run of 5 upgrades (Figure 17).

Figure 17: Utilization of asset for UIW System Exemplars #4. (Click image to enlarge)

Figure 17: Utilization of asset for UIW System Exemplars #4. (Click image to enlarge)

As is expected the asset is utilized more when it is more flexible to adapt to the “number of changing trends”, which is constant. The flattening off in high number of upgrades suggests that fewer upgrades might achieve the same overall result, since utilization cannot go above 1 (=100%). In the scenario with high number of upgrades the investment in upgrades would, in reality, decrease to a maintenance level (i.e. matching the “market agility decrease”), but this control loop has not been included in this UIW System Exemplar. Low number of upgrades however keeps the asset in a state of being unable to adapt to new trends quickly enough and stays idle about 50% of the time.

Figure 18: Monthly profit for the user for UIW System Exemplars #4. (Click image to enlarge)

Figure 18: Monthly profit for the user for UIW System Exemplars #4. (Click image to enlarge)

In Figure 18 the “monthly profit” for the user is shown. The monthly profit directly correlates with the utilization rate as the asset produces costs regardless of utilization while revenues are only generated when the asset is used. Therefore even though an increased number of upgrades increases the cost of the asset, the increase in utilization makes it a worthwhile investment.

7. UIW System Exemplars #5: Investment in product upgrades

7.1. System Structure Diagram

Figure 19: UIW System Exemplars #5: Investment in product upgrades, (Click image to enlarge)

Figure 19: UIW System Exemplars #5: Investment in product upgrades, (Click image to enlarge)

UIW System Exemplar #5 addresses the investment in upgrading the product in order to make it more attractive. By this investment, “Product attractiveness” increases which makes the product of the company more attractive in comparison to the products of the competitors (“relative product attractiveness”). A higher “relative product attractiveness” leads to a higher “number of customers” because more customers chose the company’s product which in turn leads to a higher “total revenue”. By having a fix investment policy (“investment fraction”), the company increases its investment in upgrading the product which in turn increases the “Product attractiveness”.

7.2. Simulation Model

Figure 20: Simulation model for UIW System Exemplars #3. (Click to enlarge)

Figure 20: Simulation model for UIW System Exemplars #3. (Click to enlarge)

The simulation model for UIW System Exemplars shows two mirrored loops (Figure 20). On the left hand side (R1), the customer gain of the company is shown and on the right side (R2) the customer gain of the competitors. For both loops the values of “cost per unit of product attractiveness” as well as the “revenue per customer” are equal. The “total number of customers” is also constant, which means that every month the same amount of new customers purchase the product. The customers are distributed between the company and the competitors according to the “relative product attractiveness”. The only difference between the two sides is the “investment fraction”, meaning how much of the total revenue is invested into increasing the product attractiveness.

For the simulation we chose 2 scenarios, low investment and high investment, with “investment fraction” of 0.05 and 0.1 respectively to compare with the base run of an “investment fraction” of 0.075 which is equal to the investment fraction of the competitors. This means that the “relative product attractiveness”, meaning the product attractiveness of the company relative to the product attractiveness of the competitors, stays at 0.5 for the entire simulation in the base run as shown in Figure 21.

Figure 21: Relative product attractiveness. (Click to enlarge)


Figure 21: Relative product attractiveness. (Click to enlarge)

In the case of high investment the “relative product attractiveness” increases while in the case of low investment it decreases. The objective must therefore be to match or exceed the investment fraction of the competitors.

While this might be seen as quite straight forward, there are additional effects that investing in upgrading product attractiveness has. The difference in investment fraction between the company and the competitors in the case of high investment is 2.5%. In this example, the market size is 1000 Euro per month, meaning that 2.5% would be 25 Euro per month. However, the investment into product attractiveness difference between the company and the competitors is much larger, as can be seen in Figure 22.

Figure 22: Comparing investment in product upgrades between the company and the competitors in the high investment run. (Click image to enlarge)

Figure 22: Comparing investment in product upgrades between the company and the competitors in the high investment run. (Click image to enlarge)

By the end of the simulation the difference is more than 39 Euro. This effect is due to the fact that not only the “investment fraction” determines the investment but also the “total revenue”. An increase in “product attractiveness” leads to more customers, which leads to more revenue and to more investment. This development accelerates the difference in “product attractiveness” between the company and the competitors as can be seen in Figure 23. Although the gap between the investment fractions remains constant, the gap between the product attractiveness of the company and the competitors continues to increase. Investing in “product attractiveness” therefore generates a considerable first mover advantage and closing the gap would require a disproportionate amount of funds for the competitors.

Figure 23: Comparing the product attractiveness between the company and competitors in the high investment run. (Click image to enlarge)

Figure 23: Comparing the product attractiveness between the company and competitors in the high investment run. (Click image to enlarge)

8. UIW System Exemplars #6: Refurbishment of products

8.1. System Structure Diagram

Figure 24: UIW System Exemplars #6 - refurbishment of products. (Click image to enlarge)

Figure 24: UIW System Exemplars #6 – refurbishment of products. (Click image to enlarge)

UIW System Exemplar #6 addresses the topic of circular economy. New products are produced and sold to customers who use it for a certain period of time (“products in use”). After the products lifetime expires, the products are discarded. A fraction of the discarded products is returned and refurbished/ remanufactured (“products refurbished/ remanufactured”). The refurbished/ remanufactured products can then substitute partially the “new products produced”. This reuse of input materials generates a more efficient use of resources and, if the refurbishment/ remanufacturing is cheaper than producing new products, can also produce a financial benefit.

8.2. Simulation Model

Figure 25: Simulation model for UIW System Exemplars #6. (Click image to enlarge)

Figure 25: Simulation model for UIW System Exemplars #6. (Click image to enlarge)

The simulation model shows in the centre the circular flow of products from “products in use” to “returned products” and back, which is the only loop in this model. This circular flow is completed by two flows to “products in use”: “newly produced products” and “discarded products”. “Newly produced products” do not have any inputs from returned products. In this UIW System Exemplar we will assume that the “sales price” and “cost of newly produced products” is equal to 100 Euro per product. This means that the company will sell its products at cost. The “cost per refurbished/remanufactured product” however is 50 Euro and we assume that there is no difference between newly produced or refurbished/remanufactured products. This means that the company makes a profit when selling remanufactured and refurbished products and thus will only produce new products if there are not enough returned products available. Finally we assume that the implementation of the business model will take time and not all products are returned immediately but that “fraction of products to be returned” increases over time.

This UIW System Exemplar is somewhat different from the previous ones in the sense that the scenario input is not a change of a single variable but a typical market growth pattern. To test the effectiveness of circular economy three market demand patterns are tested. In the base scenario the market growth remains constant at 10 products demanded, in the run constant growth the “total number of products demanded” increases steadily and in the run cyclical demand the “total number of products demanded” is cyclical. To facilitate a comparison the patterns were chosen in a way that over the entire simulation period the average number of products demanded is 10 products per month as can be seen in Figure 26.

Figure 26: Market demand patterns for UIW System Exemplar #6. (Click image to enlarge)

Figure 26: Market demand patterns for UIW System Exemplar #6. (Click image to enlarge)

To evaluate the business model of circular economy, the accumulated profit over the entire simulation period of the three runs is compared in Figure 27.

Figure 27: Accumulated profit for the three runs in UIW System Exemplar #6. (Click image to enlarge)

Figure 27: Accumulated profit for the three runs in UIW System Exemplar #6. (Click image to enlarge)

Initially all products are newly produced so none of the scenarios generates any profit. Slowly the accumulated profit for both the base run as well as cyclical demand start increasing while the constant growth run remains close to 0 for nearly the double amount of time. This is due to the fact that the constant growth run starts at 0 products demanded. That means that for a while there are very few products in the market that could be returned. Since only the refurbished/remanufactured products can be sold at profit, the constant growth run achieves very little profit until month 40. After that the circular growth effects start having an effect this results in accumulated profits. The cyclical demand run follows the base run closely but periodically underperforms the base run when demand is high. This is particularly important considering that storage costs for returned, but not yet resold products are not included. If that cost were included, the cyclical demand would perform worse than the base run. The storage demand can be seen in Figure 28.

Figure 28: Returned products for the three runs in UIW System Exemplar #6. (Click image to enlarge)

Figure 28: Returned products for the three runs in UIW System Exemplar #6. (Click image to enlarge)

The cyclical demand has by far the largest storage as the number of “returned products” peaks periodically and that does not coincide with peaks in products demanded. This is further illustrated in Figure 29 where the “percent of products refurbished/remanufactured” are shown. Given that in cyclical demand products are stored and there are periods with very low demand it achieves quickly the level of 100% of the products sold being refurbished/remanufactured (around month 15) but just as quickly the percentage is reduced when the demand increases because the number of stored products is reduced.

Figure 29: Percent of products refurbished/remanufactured for the three runs in UIW System Exemplar #6. (Click image to enlarge)

Figure 29: Percent of products refurbished/remanufactured for the three runs in UIW System Exemplar #6. (Click image to enlarge)

Further Information

For further information on UIW System Exemplars for Use-It-Wisely please contact the author, Professor Stefan Grösser, through his web site at http://strategysimulationlab.org.