Glossary

Drawn from the field of System Dynamics, the term Business Dependency Network (BDN), refers to the business dependencies that define how every business community within the organization impacts and is impacted by other business communities.
The BDN is manifested through a mathematical model of the organization’s business dependencies, forming a constraint propagation network.

Mathematical computations are maintained completely separately from the data, providing an unprecedented level of flexibility. The computations are defined using an intuitive Business Mathematics syntax, expressing the dependencies between Business Matrices. The set of dependencies among the Business Matrices and formulae results in a constraint propagation network; any change to a value of one of the Business Matrices is immediately propagated throughout the network, providing the basis for real-time business analytics.

Collected data is transformed and uploaded into memory, where it is stored in highly compact data structures called Sterna Business Matrices. A Business Matrix separates time from the raw data, enabling massive volumes of time-based data to be efficiently stored and processed. Moreover, data in the Business Matrices is maintained completely separately from the mathematical computations that are applied to the data, providing tremendous flexibility in defining and maintaining the Business Dependency Network.

Business Views provide insight into potential and actual deviations from target performance, and the financial impacts of such deviations. Business Views examine the business from a variety of angles, and enable drill down analysis and exploration capabilities such as filtering and sorting. Each Business View is comprised of three graphical components: Operational Position, Money Surface™, and Additional Insights.

The Business Dependency Network is manifested through a mathematical model of the organization’s business dependencies, forming a constraint propagation network; whereby any change in value of one of the data inputs to the system is instantaneously propagated throughout the network system and surfaced to the user as may be relevant.

When action is taken in one Business Community of the organization, its financial impact is immediately propagated throughout the network and exposed to interdependent Business Communities, to ensure that the entire organization is centrally aligned at all times.

Thus, Sterna BPS is able to process data updates at any refresh rate, effectively making real-time analytics a reality.

Drawn from the field of System Dynamics, Feed-forward is a term describing a kind of system which reacts to changes in its environment, usually to maintain some desired state of the system. A system which exhibits feed-forward behavior responds to a measured disturbance in a pre-defined way — contrast with a feedback system.  Read more

Sterna BPS Server bypasses the need to build time-consuming, costly and inherently inflexible OLAP cubes, by storing the organization’s data into an in-memory data-store. Data is read from the organization’s data stores via Data Collectors and transformed into Sterna Business Matrices– highly compact virtual data stores – utilizing 64-bit hardware.

By highlighting potential financial gains and losses in relation to the Operational Position, the Money Surface™ functions as the manager’s “money search engine”. It is used as a dynamic alerting mechanism to understand when and where action needs to be taken, what form it should take, and what its financial impact will be. Read more

Online Analytical Processing, or OLAP, is an approach to quickly provide answers to predefined analytical queries that are multidimensional in nature. Adequate OLAP performance is dependant on aggregation of data along the dimensions of the data model (OLAP cube);  the combination of all possible aggregations (or Views) and base data contain the answers to every query which can applied to the data. Due to the potentially large number of aggregations to be calculated, only a subset of aggregations is predefined. Queries that are not catered for by aggregation are calculated on-demand and will likely suffer from inadequate performance. Deciding which aggregations to calculate requires careful analysis of business requirements, data volumes,  the time to update the aggregations from changes in the base data, and more. OLAP cubes are therefore inherently complex to design, build, and maintain.

Operational BI is aimed to provide real-time actionable insights, which enable management intervention while the affected process is still ongoing, thus optimizing daily business operations. Read more

Based on Sterna BPS Business Matrix structure, mathematical capabilities, and prediction models Sterna BPS provides unique simulation capabilities, commonly referred to as “What-If Scenarios”. Since Sterna BPS Constraint Propagation Network reflects the organizational structure, the state of the organization can be extrapolated into the future, based on both statistical prediction algorithms and on the constraints and dependencies among the various Business Matrices. Simulation may be based on the most likely values given by the predictions. Alternatively, the user can inspect the probability distributions of future states, based on Monte Carlo simulations.

System Dynamics deals with the management of complex feedback systems. Feedback refers to the situation of X affecting Y and Y in turn affecting X. One cannot study the link between X and Y and, independently, the link between Y and X and predict how the system will behave. Only the study of the whole system as a feedback system will lead to correct results.

Information feedback-control loops are abundant in businesses. In supply chain organizations, for example, a marketing campaign may yield an unexpected surge in sales, leading to manufacturing and distribution decisions that are based on factors such as existing inventory levels and machine capacity; orders are filled, inventories adjusted, and competition may react by lowering prices, leading to new decisions. The regenerative process is continuous, and new results lead to new decisions which keep the system in continuous motion. Read more

Mediates between the organization’s Business Communities, and allows the user to perform strategic, operational, and predictive analysis in a single view. The Time Mediator™ allows the user to travel back and forth in time to designate and analyze information in any time resolution and range – past, present, or future.