Speed to Solution: Are There Shortcuts to ROI?
By: Ben Averch
If you need big data solutions, chances are you need them now, not after a three-year development cycle. Big data business analytics solutions are big undertakings, but the right strategy will cut down on wasted time and take you from conception to early-stage ROI in the shortest time possible.
The main thing to remember at the outset of a big data analytics project is that it is only as successful as the business says it is. This is why forming a strong relationship with your business stakeholders is so important at the start of your project. Identifying a key stakeholder from the business with a vested interest in the project’s success will help in a number of ways: coordinating active participation in the project from the business, defining the project and the metrics for its success, and managing expectations about what can and can’t be delivered during a given timeframe.
With agreement from the business as to what the project should entail and what success will look like, you are prepared to establish a regular cadence of weekly sync-up meetings between the IT team and the business stakeholders to share progress, demonstrate new capabilities, and address any issues that may have arisen over the last week.
Quantifying the ROI on analytics projects can be a difficult challenge, but it’s important to be able to identify and measure a set of ROI metrics for your project. We often say that big data infrastructures enable better decision making by business users, but these are hard to quantify. It may work best to define key use cases that your business stakeholders buy into; they will function as the measuring stick for your project
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