InVizion LLC: A Response to the Challenges of Capital Planning & Execution in Asset-Intensive Industries

Then, applying the customer’s business rules and workflows, the solution is deployed to stakeholders for collaborative planning and budgeting. “InVizion quickly automates manual steps that were previously required to stitch together planning data from spreadsheets and legacy systems,” says Ms. Neckowicz. The solution provides a much needed “middle ground” between the traditional project management solutions—with their daily execution focus—and the transaction-oriented, inflexible “back office” ERP solutions. This solution sits in-between back office and daily management applications to provide holistic, robust planning, and dynamic execution capabilities.

“We give organizations the visibility they need to achieve their business goals, much like solving a Rubik’s cube,” mentions Ms. Neckowicz. The solution has the unique ability to perform a ‘what-if’ analysis while factoring in detailed inter- and intra-project relationships and dependencies. Referring to the Rubik’s cube analogy, Ms. Neckowicz explains, “InVizion effectively gives analysts the ability to see all the sides of the cube in order to understand the overall impacts of a change that is made at a department, resource or project level.” In addition, analysts can set thresholds for funding and deadlines to be alerted when their program exceeds a critical level. The solution makes it easy to create lookup tables and rule-based formulas that tie the multiple program facets together, eliminating error-prone tasks in manual spreadsheets. Through InVizion dashboards, views, and reports, clients can accurately communicate up-to-date program status and compare different portfolio scenarios.

While transforming the capital planning and execution process in utilities, energy, infrastructure, and other asset-intensive industries, the firm continues to expand, and enhance, features and functions of the solution. Most notably, they’re developing capabilities that predict future performance based on past performance. “Machine Learning is the natural next step, as we are being asked by clients to support the increasing demand for predictive capabilities,” adds Ms. Neckowicz.