Operations Analytics

Here we apply any of a number of powerful mathematical and statistical tools to maximize the efficiency or profitability, or minimize the cost, of various types of operations processes; or to manage risk; or assist with decision analysis or project management.

Operations Optimization

If you need to maximize the efficiency of a process to save time or money, maximize profit, etc., we use powerful analytic tools to achieve the optimal outcome. Here are some examples of typical optimization solution areas:

• Make vs. Buy Decisions
• Determining Minimum Order/Purchase Size
• Transportation Route Optimization
• Production and Inventory Planning
• Data Envelopment Analysis (e.g., determining the operating efficiencies of various units within a company, or of various companies within an industry)
• Employee Scheduling
• Contract Awarding
• Capital Budgeting
• Nonlinear Network Flow Problems
• Facilities Location Problems

Depending on the situation, we might emply any of a variety of analytic tools and techniques to solve such problems, including, but not limited to:

• Linear or Mixed-Integer Linear Programming
• Nonlinear Programming
• Evolutionary Optimization
• Goal Programming and Multiple Objective Optimization

Risk Analysis via Simulation Modeling and Advanced Statistical Analysis

Unlike optimization problems, where the inputs are known, risk simulation solves problems where the exact parameters are unknown and may fluctuate randomly within a range of uncertainty. And while there are other methods of risk analysis, such as traditional Best-Case/Worst-Case and What-If analysis, Simulation Modeling is far superior because it uses powerful mathematical and statistical processes instead of relying heavily on intuition or guessing.

We employ sophisticated modeling techniques such as Monte Carlo simulation analysis to help you manage risk. And we can build models based on a wide variety of random variables. So whatever your risk-analysis situation, we have the tools to assist you.

Here are just a few examples of how risk simulation analysis can be applied:

• For a growing company that has decided to switch from using a private health insurance company to self-insuring its employees, risk simulation can help determine how much money should be accrued in the next year to cover employees' health insurance claims.
• In a manufacturing environment, simulation modeling can help estimate the most cost- and time-efficient servicing intervals for equipment.
• When considering siting facilities in a region that has a potential for natural disasters such as floods, earthquakes or forest fires, risk analysis can assist with the decision.
• For a company that accepts customer reservations for services, risk simulation can help manage available resources to achieve acceptable levels of under- and over-booking, thus helping to sustain both profitability and customer satisfaction.
• Risk analysis can help management understand the financial risk associated with undertaking a particular project, which might be affected by things such as personnel or budget problems, vendor or customer problems, scheduling complications, etc.
• Risk modeling can assist management with inventory control, helping to determine:
• • The best level of inventory to maintain
  • When goods should be reordered/manufactured
  • How much safety stock needs to be held in inventory

Decision Analysis

We have many tools and techniques to assist with decision making. These include things such as payoff matrices and single- and multi-stage decision trees, combined with sophisticated decision rules such as Expected Monetary Value (EMV), Utility Functions and Multicriteria Decision Making. Our models can incorporate Bayesian analysis and other forms of conditional probability analysis to take into account real-world uncertainties. And we can also perform sensitivity analysis to determine how strongly decisions are impacted by changes in the model's values.

Examples of the application of decision analysis include determining:

• How large a manufacturing plant to build
• Which parcel of commercial real estate to purchase
• Whether a consulting firm should invest resources developing a complex grant proposal
• Other areas of application might include environmental remediation, healthcare management, litigation or dispute resolution, etc. Back to Top 

Project Planning and Management

Whether your project is relatively straightforward or much more complicated, we can assist with project planning and scheduling. For simpler projects, time-tested techniques such as Critical Path Method (CPM) and Program Evaluation and Review Technique (PERT) analysis might suffice. But each of these approaches has limitations. So for more complicated projects, we offer sophisticated simulation modeling techniques. We can also employ powerful optimization solutions if you need to understand the tradeoffs and overall impact of "crashing" a project by throwing more resources at the problem to finish it faster. Back to Top