Risk Management

4 Methods to Save Your Big Data Project from Failure

You invest valuable time and resources into developing a project, only to watch it abandoned in the beginning phases. In an article for ZDNet, Steve Ranger explores exactly why this predicament continually occurs and how to best prevent such failure.

There are four practices that help to guide analytics projects away from the rocks of despair and into the horizon of success. The first of these actions is to select a problem in which there is an actual benefit when resolved. Keep in mind the issues that have the largest impact or the ones that could have the hastiest payback. The second movement involves addressing the problems by either buying or outsourcing help to get them resolved swiftly. External service providers offer the resources and tools that may be better suited for a quick resolve rather than building a solution from scratch.

The final two steps involve looking internally and adapting the right personnel to successfully achieve a solution using their preexisting skills. It is imperative that those who are hesitant or not completely convinced of the project’s validity be won over. When every member is not on board with the idea, they may purposefully or even unintentionally derail the entire operation.

Only after everyone is adamantly on board with the decision, managers can start analyzing their employees and uncover who holds the proper skills that will prove beneficial to the outcome. If the project has favorable implications across the board for a plethora of departments, then it strategically makes sense to use the organization’s time and resources to accomplish the goal. A team should be selected that have a variety of skills, including expertise in the business and IT sectors. No one person has the knowledge and skills to accomplish everything satisfactorily; however, collectively they can make the change.

You can read the original article here: http://www.zdnet.com/article/your-big-data-projects-will-probably-fail-and-heres-why/

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