Big data has helped business gain useful insights on customer preferences and thereby help them fine-tune their business model. For instance, the airline industry can use large pools of booking data to estimate the number of bookings that are going to be forfeited, and thereby accommodate other passengers on the waiting list. Another place where big data finds its use is in project portfolio management.
Efficient project portfolio management
Big data analytic tools utilize algorithms to track patterns in large pools of data. You may have mounds of data on projects sitting idle and unused, and this can hold the keys to a more efficient project portfolio management. Making sense of these pools of data can help shed light on crucial project elements that can drive better decision-making. Of course, it is difficult for project managers to manually filter through these large data pools, which is where big data analytics comes in. Big data analytic tools help take the trouble out of breaking down the data manually, while ensuring better accuracy as there is no room for human error or miscalculations.
Big data can be used to make sense of pools and pools of project data that are available at your disposal. It can serve as a tangible means to determine project factors that would otherwise be guesses you base on just past experience or subject-matter expert advice. Now, we’re not saying that you should not be relying on the latter, but combined with big data, you have a better hold on your project portfolio management. Whether it is cost projections or resource allocations, big data analytics can break down the numbers and data to sensible information. Many project managers use big data tools to plan their maintenance schedule or milestones for the best returns.
Bird’s view and hidden correlations
Big data offers a helicopter’s view of the various project aspects. Chances are that you already have processes and other micro methods of the project in place. Big data can show you the bigger picture, so you can clearly see where the voids exist in the project and bridge the gap. Big data analytics helps project managers see one step ahead, so they can mitigate project risks before they escalate. It can point out hidden correlations that even project managers with a solid experience may otherwise miss, helping dodge project pitfalls.