Improve decision-making by transforming raw data into information and insight. Leverage the right analytic tools and techniques to produce knowledge.
Clients achieve improved decision-making by leveraging Computech’s Operations Research (OR) expertise. Our ability to understand interrelated data, identify appropriate problem-solving techniques and suggest practical conclusions based on sound analysis provides numerous strategic and tactical advantages. Benefits provided by our OR capabilities include:
- Business insight: Quantitative analysis of complex problems
- Improved performance: Embedding model-driven intelligence into information systems to improve decision making
- Cost reduction: Finding areas to decrease cost or investment
- Decision making: Assessing likely outcomes and uncovering better alternatives
- Forecasting: Providing more accurate forecasting and planning
- Improved scheduling: Mathematical models to efficiently scheduling staff, equipment, events, and more
- Improved planning: Quantitative techniques to support operations, and tactical and strategic planning
- Productivity: Analysis to make processes and people more productive
- Improved quality: Quantifying and balancing qualitative factors
- Resource utilization: Statistical analysis to achieve greater utilization from limited equipment, facilities, budget, and personnel
- Reduced risk: Measuring risk quantitatively and uncovering factors critical to managing and reducing risk
Our Operations Research expertise includes exploratory data analysis, statistical analysis, optimization, probability theory, decision analysis, mathematical modeling, predictive analytics and simulation. Operations research has multiple facets and approaches that incorporate diverse techniques. Computech’s operational researchers determine which techniques are the most appropriate given the nature, goals and constraints of the problem being addressed.
As described in the graphic above, Computech’s OR team performs its work in three phases: Assessment -Analysis -Presentation. Each phase contains several steps that are pertinent to performing accurate, thorough and efficient analyses. Specifically:
Assessment Phase — We familiarize ourselves with the raw data and transform it into a usable format. Steps include: data inspection (quantitative, qualitative, geospatial, etc.); data cleansing; and data transformation.
For example, on the National Broadband Map project, we received over 25 million data points, in a variety of formats and levels of geographic aggregation, from 50 states that had to be consolidated, cleansed, and standardized.
Analysis Phase — We select the appropriate OR methodology and computational software, conduct an analysis of the data, and then interpret and validate the results.
For example, on the DTV transition project, we used data from numerous market tests, created a model, accurately forecasted call volumes for the call center, and optimized staffing at DTV call centers throughout the country.
PresentationPhase — We determine the most effective way to disseminate the results of the analysis to each type of stakeholder and create reports using the appropriate tools.
For example, on a recent Speedtest project, we developed a range of data visualization templates to support the needs of various stakeholders, including consumers, regulators and policymakers.