Decisions, dynamically

A new tool from Decision-Matrix is said to be based on a model for human thought and designed to minimize uncertainty from the decision-making life cycle. The namesake software has at its core a patent-pending probability engine that understands multi-dimensional and predefined relationships in a structured matrix.

Decision-Matrix developer Randy Frid explains that each node in the matrix also has the unique ability to participate in many different matrix nodes or different matrices themselves. This ability to participate in multiple states allows the matrix to grow to infinite size while massively reducing redundant data.o

Another benefit of a multiple-state based matrix, Frid adds, is its ability to be used to monitor and forecast trends based on movement in one part of the matrix affecting movement in another. He cites as an example a marketing department dealing with cash flow issues. If the engineering department is also dealing with cash flow, the changes made in the engineering department can be compared to changes made in the marketing department because each department is using the same matrix node but in a different fashion. The underlying information is different but the nature of the relationships remains the same.

The software also allows users to build a 10-year high-level or detailed financial model to accompany the probability results so management can generate a total picture of the potential outcome of any decision. The Decision-Matrix can grow into an infinite number of matrices to satisfy any aspect of society, Frid claims. All matrices can eventually be aggregated together to build a potentially global analysis engine spanning entire enterprises or governments.

The Decision-Matrix also captures team documents, threaded team discussions, team contacts and team links for each individual decision case. The software is Web-based, multi-tiered, and can utilize any ODBC-compliant back-end database.

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