With project failure rates remaining troublesome, many project managers are turning to data for help. Proper use of data can take the guesswork out of decision-making and provide tangible support project managers can use to guide their teams. Data can also prove value in helping project managers schedule work, allocate resources, increase efficiency, reduce costs, and more effectively manage risks.
The key means by which project managers leverage data is through use of business intelligence and business analytics. Business intelligence (BI) is a combination of software and process used to gather, store, and analyze big data from various sources and to convert that data into useful information. BI is considered a descriptive form of data analytics, in that it focuses leverages past and present data to glean insights into what has happened or what is currently happening in a particular process. BI gives companies and project management offices (PMOs) access to real-time metrics to support better and faster decision-making, and to achieve increased visibility into projects, processes, and their outcomes.
Business analytics (BA), on the other hand, is considered predictive, in that it focuses on the “why” to help make more informed predictions about the future. With BA, data is analyzed to better predict challenges and adapt to provide improved outcomes.
Forward-thinking PMOs are recognizing the need for project decisions and actions to be supported by solid factual data. To become a truly data-driven project manager means stepping up your game in all aspects of project planning and execution — especially when it comes to allocating and managing scarce yet valuable resources.
Here is a look at how integrating data analytics into project management practices can greatly benefit project outcomes.
Matching, allocating, and scheduling resources
Resource management is a tricky area for project managers because resources are often scarce and always changing, making it difficult to plan and allocate resource usage in any given project, let alone when multiple projects compete for resources. Data is key in driving effective decisions around resource availability and allocation. The success of projects rests on being able to match skills, allocate the best resources, and schedule available resources.
Having access to data from past and current projects enables project managers to better allocate resources for current projects and better plan for future ones. By gathering and analyzing data in one place, project managers can identify which resources are being underutilized or overutilized, enabling them to shift resources where necessary and schedule accordingly.
Companies using standalone Excel sheets rather than BI tools integrated into their project management suites are often at a disadvantage. Integrated BI tools can not only reduce the chances of staff being overutilized, and thus stretched beyond their means and possibly burnt out, they also can help ensure project scheduling timelines are realistic and identify risk factors that might become obstacles to achieving those timelines. Project managers can use data to develop resource management KPIs such as indicators of resource conflicts or on-time task completions.
BI can help PMOs discover and improve cumbersome internal workflows or technology-based efficiencies, thereby alerting project managers to changes that need to be undertaken to improve how stakeholders and project teams connect, work together, and communicate. By uncovering and addressing inefficiencies, project teams can focus on higher-value work and faster deliver projects.
It’s only in being able to gather data about existing processes and inefficiencies that project managers can identify bottlenecks and other process-based obstacles and forge a path towards change. BI can isolate ineffective or inefficient processes and improve overall decision-making efficiency. It also helps to develop KPIs such as planned versus actual time spent on tasks, human errors, or the number of change requests.
Risks can come in many different forms and from both internal and external sources. The threat a risk can pose can have a minor or major impact on projects, an entire program, or a portfolio. Many companies remain in reactionary mode when it comes to risk and compliance rather than getting ahead of potential risks using BI tools.
Risk and compliance management is one of the most critical areas where BI can play a key role in identifying issues. Data provides project managers with concrete information that can isolate many types of risks from past and current projects, and enable them to rethink their risk management strategies to move beyond being reactive.
Making use of BI and BA tools
The key to gaining actionable insight is to determine the types of data that are needed to make pivotal decisions — especially during times of uncertainty. It’s essential to carefully evaluate the features of BI and BA tools to make sure they provide PMOs with the relevant real-time insight to support your company’s project and portfolio goals. Here are some key features to look for.
Having a plethora of BI and BA features built into or integrated with project management tools shouldn’t be a top priority; instead, it’s more beneficial to focus on having the right features, including:
- The ability to import and update data with the click of a button
- The ability to have integrated “what if” analysis for resource planning and management
- Modeling and forecasting capabilities
- Real-time customizable at-a-glance dashboarding
- Secure role-based access
- Clear visual charting and graphics
- Simple drag and drop interface
- Easy drill-down to detail capabilities
- Seamless integration with other applications
- Secure mobile access for those working remotely
- Quick and easy self-service options for all user roles
- Ability to easily share information with other stakeholders
- Reporting capabilities
While the BI features and capabilities might differ depending on the project, project managers should ensure that capabilities essential to improving their particular project outcomes are emphasized in their data strategies. Doing so will enable them to leverage business intelligence effectively in gaining actionable insights, whether that is a matter of resource management, risk assessment, or establishing more efficient processes and communication.
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