Nicus designed M-PWR for the most demanding enterprise chargeback/showback requirements. No other product on the market provides process modeling capability like M-PWR.
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Many organizations seek a better understanding of the relationship between IT expenses and service consumption.
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How would you describe your IT budgeting process? How would you describe the cooperation between IT and business managers to develop a budget? How accurate are your forecasts?
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WEBINAR SCHEDULE
Select a link below to register:
Improving Your IT Financial Management with Nicus M-PWR
Thursday, February 16, 2012 2pm EST
N E W S
Deciphering the Buzz About IT Cost Visibility - Thursday, December 1st, 2011
Salem, Va. (December 1, 2011) – For several years, the buzz in IT financial circles has been about the need for transparency through cost visibility, but misperceptions continue to exist about how to successfully implement a Cost Visibility project that will provide a solid return on investment and reinforce accountability. “Accountability is top of mind in today’s IT environment,” says Mischianti. “Managers are expected to apply concrete, proven solutions to identify, manage, report, and predict charges that will ultimately benefit the bottom line. Understanding the complexities and implications of successful Cost Visibility projects is critical, but many still don’t know how to get started. Nicus can equip IT financial managers with fundamental knowledge and skills that they can then apply to meet their departments’ specific challenges.”
Detailed, Actionable Data - Friday, November 4th, 2011
Actionable data is at the crux of IT financial management. The question is, where is the data? Data such as cost, utilization, level of service, performance, application, service, platform, and organizational elements are all necessary. It is important to acquire enough detail in the data to be able to provide utilization metrics for all available services, as well as the consumers of each service. This level of detail will allow for consolidation and normalization of the data.