At the same time, the bank was re-structuring. Business units were being consolidated, non-core businesses were being divested so the transformation program was constantly chasing a moving target. Plans that depended on a particular facility being transformed by a particular date routinely fell apart as that facility was marked for divestiture and removed from the program. Or a given region would need to fast-track video-conferencing, requiring that it be transformed to the new communications infrastructure months or years ahead of the original plan. All this “in-flight change” required resources with very specific skills to be re-assigned; complex circuit provisioning processes had to be expedited on one day, then put on hiatus the next; carefully planned transitions from existing communications providers to the new services had to be abandoned. Existing project management tools were not equipped to handle the rate of change, nor the many non-project related factors that had to be considered to keep up with the rapidly evolving environment.

All this was taking a toll on the program.

• The successful transformation rate (the percentage of sites successfully transformed by the planned date) was low.
• Each failed transformation introduced a complex array of new tasks, and required many completed tasks to be re-done. This made schedules more brittle, increasing the chances of further failures. An out-of-control chain reaction loomed
• Rather than reducing operating expenses, the program had the effect of temporarily increasing them;

Using Quantellia’s DEEPM^TM solution, the program management team was able to address their challenges and turn the program around to eventually exceed its return on investment targets.

1) “Over the horizon” risk assessment and real-time situational   awareness

When DEEPM^TM was installed, the program governance team, working with Quantellia, developed the rules that DEEPM^TM would run that defined the following:

• Variables from both the project and the operating business units that DEEPM^TM would monitor and/or include in its calculations.
• Conditions that had to be met for a task or sub-project to be successful.
• Conditions that put a task or sub-project at risk, along with a measure of that risk as low, medium or high.

These rules were continually run giving the management team a real-time validation and risk assessment dashboard for every task and sub-project they were tracking in DEEPM^TM.

2) Automated program rules assurance

A second real-time dashboard was provided highlighting tasks or sub-projects that had failed a rules validation check, including conditions that indicated the actual program issue would occur in the future.

3) Integration of program decisions with business outcomes

DEEPM^TM ran a forward model of likely operating expenses based on the current configuration of the project, assuring managers that their decisions did not undermine the primary goal of the program.

4) “What-if” change management simulator minimizes change-related risks
One of the most powerful features of the solution is the dynamic re-scheduler. This allows schedule items to be moved using a simple drag and drop operation. The power behind this is that as the item moves, the rules and forward model are run in real time and the user can see which decisions would increase risk or violate constraints, and which will lead to successful outcomes.

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Optimization of outcomes while satisfying all program constraints

DEEPM^TM can optimize program variables to achieve specified goals. This can be provided as a cloud service that continually runs alternative scenarios through the DEEPM^TM rules base, and searches for those that optimize the chosen criteria.