New in DecisionTools Suite 6: Integration with Microsoft Project for project risk modeling

@RISK (risk analysis software using Monte Carlo simulation) is now a truly cross-platform tool, enabling risk modeling of your Microsoft Project schedules using the same @RISK you use for risk analysis modeling in Microsoft Excel!  You can now do your project risk modeling in Excel rather than Microsoft Project, providing a new world of flexibility. […]

The analytical business of innovation: DMUU at Unilever

Innovation is the lifeblood of most enterprises – and given the inherent high uncertainty, a high level of decision quality is essential.  Many parties are involved in the decision-making process, and often they have conflicting values, motivations, perspectives, personalities and power bases.  These organisational issues are reinforced with analytical complexities such as the large number […]

New in DecisionTools Suite 6: Time-series modeling

@RISK now offers a new set of functions for simulating time series processes, or values that change over time. Any future projection of time series values has inherent uncertainty, and @RISK now lets you account for that uncertainty by looking at the whole range of possible time series projections in your model. This is particularly […]

Value Management Strategies: How Risk Analysis is Utilized in Managing Risk on Projects and Programs

Like the inner workings of an intricate timepiece, major projects are made up of a number of parts—often moving in different directions—that must all work in concert to keep accurate time. The functioning interconnectivity of the smaller projects is greatly impacted by an organization’s ability to accurately forecast the risk, both major and detailed.  For […]

Simple Oil and Gas Production Forecasting

@RISK can be very effectively used to forecast the production of oil and gas reserves about which little is known. This is a simple model forecasting production for a particular oil well. The estimated reserves within the well are uncertain and are represented with a Lognormal distribution function. The mean is 500,000 STB and the […]

Modeling Insurance Claims with Simulation, the Compound Function, and Resampling

It is important for an insurance company to estimate the amount of claims it will incur in a given year. This series of models assumes that there are three types of claims: auto, general liability, and worker's comp. Historical data for the company is included. The top section lists the numbers of claims for the […]