Abstract: Mechanisms are provided for forecasting information technology (IT) and environmental impacts on key performance indicators (KPIs). Machine learning (ML) computer model(s) are trained on historical data representing IT events and KPIs of organizational processes (OPs). The ML computer model(s) forecast IT events given KPIs, or KPI impact given IT events. Correlation graph data structure(s) are generated that map at least one of IT events to IT computing resources, or KPI impacts to OPs. The trained ML computer model(s) process input data to generate a forecast output that specifies at least one of a forecasted IT event or a KPI impact. The forecasted output is correlated with at least one of IT computing resource(s) or OP(s), at least by applying the correlation graph data structure(s) to the forecast output to generate a correlation output. A remedial action recommendation is generated based on the forecast output and correlation output.

Abstract: Provided is a computer-implemented method, system, and computer program product for process mining asynchronous support conversations using attributed directly follows graphing. A processor may collect a plurality of conversation threads from an asynchronous data stream. The processor may label each utterance of a plurality of utterances from the plurality of conversation threads with an event label. The processor may analyze the event label for each utterance of the plurality of utterances. The processor may generate, based on the analyzing of the event label for each utterance, an attributed directly follows graph (DFG).

Abstract: Methods, systems, and computer program products for generating organizational goal-oriented and process conformant recommendation models using artificial intelligence techniques are provided herein.

Abstract: Methods and arrangements for performing a tree-based asset search. An asset model is assimilated. The asset model is transformed into an asset tree search model. An asset search query is accepted and the asset search query is parsed. An asset search is conducted via applying the parsed asset search query to the asset tree model.

Abstract: Methods and arrangements for dynamic trendline generation. Input data are assimilated at a capture timepoint from an estimation tool. The input data are filtered, and an estimation-centric map is created from the filtered data ; this creating of a map includes generating an estimation data tree. A trendline is dynamically generated responsive to a request, wherein this generating of a trendline includes applying the estimation data tree to the input data. The dynamically generated trendline is supplied to the estimation tool.

Abstract: Methods and systems for automatically generating a service oriented architecture (SOA) design. A set of business process maps for the domain under consideration is defined and a design quality goal (function) that should be met (optimized) is specified. The design goal/function involves SOA metrics like coupling, cohesion, granularity, etc., which the system under consideration is pre-programmed to compute on any SOA design. The system takes as input the set of business process maps and the design quality goal/functions. It first generates semantic business process maps by identifying key concepts that occur in the task and business item descriptions. Next, it efficiently searches the service design space by starting with a seed design and employing a sequence of moves to iteratively optimize it. It outputs a set of possible SOA designs that meet the specified quality goals or optimizes the specified function, from where a user may select the final design.

Abstract: Methods and arrangements for performing a tree-based asset search. An asset model is assimilated. The asset model is transformed into an asset tree search model. An asset search query is accepted and the asset search query is parsed. An asset search is conducted via applying the parsed asset search query to the asset tree model.