Examples of Client Work
A. Leveraging Investments and Economies of Scale
 | Challenge:
Client wanted to capitalize on recent mergers and acquisitions.
Complexity:
How do we take advantage of economies of scale?
How do I institutionalize new ways of thinking about who we are?
Solution:
We built a management flight simulator to help decision-makers understand the options and investments that were previously unavailable. The application was presented as a “management game” that allowed managers to run the operations, make decisions, and compare results.
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B. Workforce Planning
 | Challenge:
A utilities client wanted to understand and make policy decisions around a key position in the workforce.
Complexity:
This need for this position was expected to be high demand; however, fewer workers were acquiring associated skills.
Solution:
By using a model that simulated the workforce, the client was able to run experiments and “what-if” scenarios. They were able to balance multiple objectives (service quality, overall costs, risks, overall image, etc.).
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C. Scheduling Work Crews
 | Challenge:
A mature oil production field’s MRO was responsible for scheduling ~100 crews across 1,000 well sites. Current scheduling was being performed manually through an elaborate spreadsheet. The result was an under-optimized schedule.
Complexity:
Different crews had different capabilities. For many jobs, the sequence of work was important.
Solution:
A schedule optimizer and interface allowed the schedulers to leverage their experience by concentrating on exceptions and urgent work orders.
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D. Parking at State Department of Motor Vehicles
 | Challenge:
Lack of parking and increased wait time caused political and dollar costs.
Complexity:
This is a highly political situation, with union labor, mandates from the governor. There were hundreds of locations and planning had to span decades.
Solution:
Using agent-based modeling, we built a model that incorporates actual data from the existing queuing system. The model allowed what-if experiments, including new experiments that could be designed in the future |
E. Materials Management and Delivery
 | Challenge:
A “super major” oil company wanted to investigate a complex supply chain to support some key decisions.
Complexity:
Conducting a pure numerical analysis did not yield the type of insight that was required for the problem. In addition, client needed a tool to communicate the analysis with different stakeholders.
Solution:
A visual 3D animated model allowed the client to ask the right questions and communicate key decision elements to a wide audience. |
F. Revenue Projections
 | Challenge:
Board was asking for revenue projections for a new subscription product.
Complexity:
Historical information would be a poor predictor of revenue. There would be cannibalization of higher-priced subscriptions.
Solution:
We built a Monte Carlo simulation to show the range of possible revenue projections. Ordering by magnitude allowed us to set the revenue target at a “80% likelihood”; a feasible but still aggressive goal. |
G. Capital Planning and Budgeting
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Challenge:
University was evaluating a 10-year capital plan associated with a 30% growth in the undergraduate population.
Complexity:
Not all projects would be funded. Sequence of projects mattered. This was a highly political situation.
Solution:
Our model allowed the client to analyze financial and non-financial aspects of the problem. The interactive model was used during the board meeting to communicate a recommendation and perform what-if analysis. |
H. Supply Vessel Cost Management and Scheduling
 | Challenge:
An offshore field with several production platforms were being serviced by a set of supply vessels. Overall utilization of supply vessels was low, but OIMs had demanding service and delivery requirements.
Complexity:
Different vessels had different capabilities. One vessel could not simply be switched out for another vessel.
Solution:
A model allowed us to test different scenarios and demonstrate that we could rightsize the number of vessels with no reduction in service.
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