Along with machine learning, big data is changing how companies function across all industries. Both large and small organizations can benefit from the insights gained from the large volumes of data that are out there. If data management is not handled correctly, it can cost a business up to 35 percent of its operating revenue. So, in a snapshot, it seems like recognizing the role big data can play in your company is the smart thing to do.
But how do we understand big data? What makes data ‘big’ and does it relate to how project managers get their jobs done? Our blog today has the answers you need.
First, we must understand what makes data ‘big.’ The measurements for big data are often set out as ‘the 5 V’s of big data and they include volume, velocity, variety, veracity, and value.
Volume
Volume is the first of the 5 V’s of big data. There is a vast amount of data being created and collected every day. The data produced in 2020 will be 44 times greater than it was in 2009. That shows you the increase we are looking at and it isn’t slowing down. Traditional data tools are unable to handle the enormity of the volume and so big data tools have emerged as their replacements – these tools are helping businesses to make more incisive decisions about their processes.
Velocity
Data is being generated at incredibly high speeds making speed an essential part of the 5 V’s of big data. The way we use information today is faster than at any other time. Think of applying for a loan or another banking transaction. Data analysis and processing now take seconds rather than hours or days.
Variety
Variety is a crucial part of the 5 V’s of big data. After all, there are many different types of data out there. Previously, data was usually something that fits easily into tables and charts. Today, data is much more unstructured. For example, data could mean the photos we take and share on our Google accounts, the social media engagements we make, the stories we post, and the videos we upload or watch. The right big data tools and advancements in technology can take these different types of data and bring them together for analysis
Veracity
Veracity is a critical part of the 5 V’s of big data, especially in a climate saturated with information and analytics. With so much data and information floating around, it can be difficult to ensure what is quality, true, false, accurate, etc. Data contains typos, slang, and unreliable sources. Again, big data tools can take veracity into account when data is being analyzed.
Value
The bottom line for big data is the ability to convert it into something of value. Collecting new data for its own sake is not going to be of much benefit to a business. But if they can collect the right data and analyze it correctly, they can draw all-important conclusions and make better business decisions. Value is the “V” in big data 5 V’s that combines all other big data v’s, resulting in real, quantifiable solutions.
How big data is transforming project management
So, what about big data in project management? Big data can have a positive effect on how the project management office (PMO) goes about its job. From reducing project costs and increasing project efficiencies to improving resource allocation, big data has a major impact on the improvement of project and resource management.
Let’s look at some of the ways the 5 V of big data can help an organization accelerate its project processes to meet its goals:
Boost to project intelligence
Business intelligence and the tools that enable effective analysis were rather restricted before the emergence of big data. Big data is the rocket fuel that allows business intelligence tools to work to their best. For project managers, it means having access to improved knowledge of each project they are working on, from timelines to resource allocation. This leads to better decision-making.
Reduces project costs
By collecting more and more data, project managers can more easily predict trends and future events within their industries. Resource forecasts and planning can be made more efficient. This leads to more efficient output; workers are given the jobs they are best at and better information to complete their tasks.
Improves project efficiency
Big data gives organizations important information about their processes, their products, or their services. Project bottlenecks and other issues can be discovered quickly and resolved, helping to keep each project and the business working optimally.
Better resource management
With the right information, a project manager can understand what their project needs, see the available resources, and how these match up. The issue is there is often a lot of moving parts in any project and changes in the budget can affect multiple areas like deadlines or resources. Using insights from big data and the right resource management solution, a project manager can more easily deal with changes to project plans and predict outcomes when certain decisions are made.
Big data is only as smart as the tools you use
Tempus Resource allows you to leverage big data and improve the resource management capabilities of your PMO. It is made up of sophisticated tools that make planning and executing a project much more efficient. Using the solution with high volumes of project and resource data enables you to make on-the-spot decisions regarding resource allocation, as you’re dealing with up-to-the-minute information.
If you are searching for ways to take the data you have and use it to improve your resource management planning, Tempus Resource is available right now. Get started with the solution today.
Quick look at how Tempus Resource leverages big data:
- Ability to add and import big data at the click of a button
- Cutting-edge ‘what if’ analysis
- Intelligent modeling and forecasting
- Up-to-the-minute reporting
- A browser-based platform that’s ready to use instantly
To find out more about Tempus Resource and how the solution can ensure you make the most of the big data boom, and enable more efficient and effective project executions, get in contact with ProSymmetry today.
