By Daniel Bishop
Big data belongs to a set of technologies that are driving the digital transformation of society as a whole and the business world in particular.
One of the areas where big data started gaining traction recently is project management. As a field that thrives on information exchange, project management is a natural fit for big data, at least in theory. In practice, most business enterprises haven’t yet utilized the full potential of big data for project management.
The novelty of the concept is a natural barrier to the widespread adoption of big data technologies in project management. But it is not the only one. By and large, businesses are willing to utilize big data, but most are unsure how. This leaves them unprepared for project management challenges in the future. Not only that but failing to adapt to a business ecosystem based on big data means you will eventually get left behind in the tech race. Needless to say, this will jeopardize your ability to compete against businesses that took the effort to implement systems for handling big data.
Fortunately, in order to utilize big data for project management, you don’t need to understand the full technical details of the systems at work. What you do need is a working knowledge of how big data intersects with project management within a business context.
The following article will attempt to clarify the matter by providing a few pointers on how to effectively leverage big data for project management goals.
Prerequisites For Effective Use of Big Data
Before you can start utilizing big data in a meaningful capacity, you have to ensure your organization fulfills the necessary prerequisites. These have less to do with your technology stack (although this is certainly a factor) and more with the way your company is organized.
Here are some guidelines to consider.
Specify Your Objectives
Big data has little inherent utility. It is how you use it to further your organization’s objectives that matters. So what are these objectives?
Big data can help businesses find solutions to existing problems. A pertinent example of such a problem would be a high project failure rate. If your projects keep failing, taking a deeper dive into the data they have generated can help you understand why.
Inform Your Stakeholders
Big data has the potential to permanently alter the way your organization functions. Before you decide to implement such far-reaching changes, you need to ensure your stakeholders are on-board.
To do this, you need to communicate what you hope to accomplish with big data. This will take some convincing, especially if you’re dealing with people outside the tech industry.
Train Your Staff
Organizations that are just getting into big data are tempted to treat it as a separate department such as sales or marketing. Under this assumption, all you have to do is hire a couple of data scientists and you’re ready to start using it. Unfortunately, this approach doesn’t work.
Big data will change how your company operates as a whole. What this means is that your entire staff has to understand it on some basic level. You can accomplish this by encouraging data sharing among departments, enrolling staff in training seminars, and creating a knowledge-base for big data usage within your organization.
Big Data Use-cases in Project Management
Utilizing big data for project management is a relatively recent development, and yet there are already numerous use case scenarios to consider. Here are the ones we believe worth pursuing at the moment.
1. Streamlining Project Planning
All business processes leave a digital trail, and project planning is no different. Once collected, this data can be analyzed to find optimization opportunities. In practice, project managers use big data to streamline the planning process by finding new solutions for existing problems.
This kind of approach to project planning is seeing widespread use in industries such as software development, finance, manufacturing, and construction. The data organizations within these industries can generate is paving the way for a project management paradigm defined by creative solutions at scale.
2. Improving Team Composition
Measuring employee performance via digital tools is already standard practice. These measurements provide data on past job experiences, education, psychological traits, and others. By collecting this data in a unified repository, it becomes possible to derive insights relevant to project management. For example, it can help you better align your sales and marketing teams.
Big data makes it possible to predict things like likely points of conflict within a team, team members with leadership qualities, and the attrition cost of working as a team for longer periods of time. This information makes it possible to develop more effective team compositions.
3. Reducing Risk By Predicting Problems
Rarely does a project reach completion without some setbacks along the way. Disruptions often come as a result of unpredictable events that can produce both temporary and recurring issues. Handling these issues is what project management is ultimately about, and big data can make these tasks easier to solve.
By keeping an up-to-date database of project failings, businesses can create a valuable source of information for future projects. Analyzing this data with the right tools will yield new procedures for predicting problems in the future, as well as techniques needed to solve them.
4. Assuring Quality With Better Quality Frameworks
Quality management is one of the more demanding aspects of project management, which makes it the subject of substantive data-gathering efforts. These are accomplished via production logs, experiment data, reports, and others. Buried within this data are principles that can help you develop better quality assurance frameworks, making the job of quality managers much easier as a result.
Big data also stresses the connection between quality assurance and product development. By analyzing quality metrics, product development teams can pick up on ideas that are worth implementing in new products.
5. Allocating Resources Efficiently
Resource management is the linchpin that holds project management together. The availability of qualified workers, production machinery, factory, and office infrastructure, financial resources, and industry knowledge will ultimately determine the success or failure of a given project. And big data makes it possible to achieve more positive outcomes on average.
Big data analysis gives project managers the tools to discover patterns in resource allocation and use, and how they match up with past results. This makes it easy to design more streamlined methods of resource acquisition, storage, and allocation.
Manage Less With More Data
Big data has less to do with specific technologies (as these are subject to change over time) and more to do with the advantage organizations can achieve by analyzing large volumes of project data. Big data analysis enables project managers to discover trends hidden within the data, allowing them to make decisions that will ensure project success. The future of project management is inextricably tied with big data, and securing a competitive advantage means preparing your organization in time.