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Manufacturer Manages Workforce Using System Dynamics and OR

A system dynamics model to investigate field service issues was developed for a major producer of equipment for semiconductor manufacturing. This strategic model has a broad scope and multi-year time horizon, and treats variables in an aggregate and deterministic way that is typical for such models. The high-level approach is adequate in most respects, but lacks the detail necessary to resolve a key issue regarding the impact of product cross-training on service readiness.

As a result, it proved useful to supplement the strategic ‘macro’ model with a ‘micro’, OR-type model that portrays the daily queuing and assignment of service jobs. The micro model provides detailed what-if results that were used for calibrating the strategic model and may also be used for making tactical manpower decisions at the local level. Traditional OR tools may have a role to play in supporting strategic modeling efforts when important operations-level relationships are not adequately understood.

Client Major producer of diagnostic equipment used in semiconductor wafer fabrication
Author/Consultant Homer J

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Publication

Homer J.  Macro- and Micro-Modeling of Field Service DynamicsSystem Dynamics Review, 15(2): 139-162, 1999.

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ETS Reduces Costs With Questions Inventory Management

In the mid-1990s, ETS started a transition from paper-and-pencil testing to computer-based testing for all of its graduate-level tests.  Computer-based tests, offered on an almost daily basis at many test locations around the world and throughout the year, draw questions from a weekly pool of test items many times larger than the test itself, and that weekly pool itself gets refreshed from an even larger inventory of items.  This inventory represents a substantial investment to ETS, because the items must be written and honed for precision, reviewed for cultural and gender bias, and pre-tested on large samples of test takers. Both item security and millions of dollars in item development costs are affected by the way in which the item inventory is managed. 

An SD model was developed to project the number of available test items under different assumptions about security risk, and also to look at policies for more cost-effective inventory management.  The model revealed that in cases of higher security risk, under existing policies, the number of available items could stagnate at an unacceptably low level.  Model tests showed that a modest and safe amount of “recycling” items used in the past could neutralize this potential problem.  Moreover, the model showed that, even when security risk was not high, the policy of recycling could effectively reduce ETS item creation costs and help their bottom line.  The model analysis was presented to the ETS executive board and affected their decisions regarding test item inventory policy.

Client Educational Testing Service (ETS), the world’s leading developer and provider of standardized educational tests
Author/Consultant Homer J

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Publication

Homer J.  Structure, Data, and Compelling Conclusions: Notes from the FieldSystem Dynamics Review, 13(4): 293-309, 1997.

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TeleComputing Saves Millions Not Investing in Surplus Capacity

The Issue You Tackled

TeleComputing, now called Visolit, is a leading provider of centralized IT operation services, based in Norway. The project developed a System Dynamics model that would enable continuing estimation of the point in time at which the processing capacity limit of the company’s data center in Oslo would be reached.

The work was done in close cooperation with the Chief Technical Officer of the company, with regular in-depth meetings where model progress and results were presented and potential improvements discussed.

What You Actually Did

The model includes a relatively detailed representation of the development and growth in the company’s main assets, namely servers and storage spindles, and shows how the company’s growth objectives, together with its service level and inventory policies, lead to the historic and likely future growth patterns in its assets. Once the model was shown to replicate the observed behavior patterns for the right reasons, it was used to test future business development scenarios, and plan future investment in data-center capacity, valued at many millions of Norwegian Krone.

The Results

Previously, the likely future availability of processing power in the data center had been projected by using intuitive extrapolation. However, the model demonstrated that such extrapolations are completely misleading, because of a shift in the system’s behavior mode due to advances in technology. Consequently, the model fundamentally changed the company’s estimates concerning the project’s central question – when the limit of the data center capacity would be reached, and how much to invest, when, to ensure that capacity will continue to be adequate, but without excessive investment.

Development of the System Dynamics model also discovered faulty data, and led to the devising of useful time-charted performance indicators, which resulted in otherwise unattainable insights.

Name Data Center Capacity Planning
Modelers Kaveh Dianati
Contact kaveh.dianati.15@ucl.ac.uk
Client/Participant Telecomputing, Norway
Client Type Corporation

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Related Publications

A System Dynamics Approach to Data Center Capacity Planning – A Case Study (Full Thesis) Download
A System Dynamics Approach to Data Center Capacity Planning – A Case Study (ISDC Conference Paper) Download
A System Dynamics Approach to Data Center Capacity Planning – A Case Study (Power Point Slides) Download

Did You Know?

Updates on the case

The authors contacted the CTO of the company for follow up three years after their final deliverable. The positive and valuable outcomes that emerged throughout the project, together with the ability to see their business performance in a visual, structured and rigorous manner, led the client to engage with the project enthusiastically from the start. As he remarked “I can confirm that the projections [from the model] are definitely true. We now know that virtualizing the majority of our servers means there’s no need to expand the data center for the foreseeable future, as we had previously expected we would need to do!

Although of substantial commercial value, this project was carried out as a requirement of the European Master in System Dynamics (EMSD) program at the University of Bergen, Norway, under the supervision of Professor Pål Davidsen.

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Dell Increases Adoption of SupportAssist with Smart Strategies

The Issue You Tackled

Dell faced a challenge where the market adoption of their high-tech and smart predictive maintenance system, SupportAssist, was not at the desired level. SupportAssist has the capability to continuously receive data from millions of Dell devices globally, store it in the cloud, and predict the likelihood of failure in Dell devices through its intelligent engine. It is a useful tool that can prevent computer failures, which is especially critical in high-risk industries such as energy and healthcare. Despite all the benefits, SupportAssist was not gaining traction in the market.

What You Actually Did

We were engaged to develop a system dynamics model to analyze the market adoption and performance of Dell’s SupportAssist. Our models were built based on the past successful cases of system dynamics applications to market adoption problems, as well as expert knowledge from the field. Throughout the process with a duration of 2 years, the client was engaged and multiple iterations of the model were offered, utilizing various data sources from the company.

We validated the model by replicating past data from Dell and also developed a user-friendly interface using Forio that works as a flight simulator for decision makers. The interface allows decision makers to compare different strategies through “what-if” analysis, and can inform strategic decision making. In addition, our models were informed by supplementary statistical techniques and textual analysis of their archival data.

The Results

Our simulation models challenged the client’s mental model on several of their strategies, such as their focus on promoting evaluation, short-term marketing campaigns, retention of disconnected clients, and sole focus on design features and marketing resources. The model pointed to a major “leakage” in the pipeline of their customers. We offered a combination of strategies with a focus on mass penetration (few customers using SupportAssist in more devices) and periodic value generation beyond fixing failure. The benefits of the new strategies are estimated to be in the order of M over a period of 5 years.

In addition, the entire discussion around the model helped Dell to have a different dynamic perspective on the problem of market adoption, and promoted more effective dialogue within the organization.

Name Dell’s SupportAssist customer adoption model: enhancing the next generation of data-intensive support services
Modelers Navid Ghaffarzadegan, Armin Ashouri Rad, Ran Xu, Sarah Mostafavi
Client/Participant Dell, Inc.
Client Type Corporate

Do you want to know more?

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Dell’s SupportAssist customer adoption model: enhancing the next generation of data-intensive support services Download
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Upcoming Events