3 Ways DX Improves Project Management
Digital transformation (DX) is becoming a matter of survival for businesses rather than just a way towards improvement. Businesses that fail to keep up with the evolving digital trends might fall victim to “Digital Darwinism.” Evidence suggests that an efficient and intelligent project management process yields significant benefits, yet only 46% of organizations prioritize project management improvement. Therefore, companies need to put more effort towards digitally transforming their project to improve management functions.
This article explores 3 ways how digital technologies can help improve project management in your business.
1. Improving collaboration and communication
Strong communication is one of the most important elements of a successful project because it enables collaboration. Using a cloud-based and user-friendly communication tool can enable fluent dialogue between team members and help keep the project scope in line. Businesses can also implement cloud-based all-inclusive project management software to increase work synergy.
It is vital to ensure that the chosen collaboration platform allows top-to-bottom collaboration and connects the c-suite to the project managers and the operational teams. The top-to-bottom collaboration increases the team’s motivation and ownership of the project, resulting in overall better performance.
Prior to implementing expensive project management software, a project manager should also understand the business needs, project scope, and budget. It is also worthwhile to provide relevant training to employees to avoid employee pushback and hesitation of adopting the technology.
2. Increasing efficiency and performance
Implementing project management software
An important objective of a successful project management strategy is to focus on the deliverables, and an all-inclusive cloud-based project management software can help maintain that focus. However, according to a survey, only 25% of organizations use project management software. Consequently, 54% of the organizations can not track their key performance indicators (KPIs) in real-time, resulting in inefficiencies and failures.
According to another survey, 54% of participants stated that they are spending more than 5 hours a day doing repetitive tasks, which is killing their productivity. Therefore, companies need to invest more in automating these tasks to increase productivity and efficiency. Automating tasks such as scheduling, progress monitoring, and employee work overload monitoring through tools based on robotic process automation (RPA) and artificial intelligence (AI) can give more time to the management team to focus on the project deliverables.
Currently, automation does not have the capabilities to replace human input in project management, but Gartner predicts that “80% of the functional project management tasks such as data collection, tracking, and reporting will be taken over by AI and ML”.
Implementing automation into your project can be expensive; therefore, the project manager must consider the following question before moving forward,
What tasks are most error-prone and time-consuming?
Which processes are repetitive with less / no variations?
Does the automation tool require human inspections?
What is the overall impact of the task on the project in case of failure?
Which tool integrates best with the existing project management software?
How can the budget be adjusted?
The answers to these questions can help a business successfully implement automation and other digital solutions into the project management process.
3. Improving analytical strength
Big data and advanced analytics are revolutionizing businesses in every sector. Advanced analytics tools can give a stronger analytical capability to project managers in the following ways:
Descriptive and predictive analytics
Data analytics tools can generate comprehensive reports to better measure and track performance. They can also provide insights on budget with real-time cost data and labor analysis features. Similarly, these tools can also provide insights for long-term project planning and accurate risk assessment.
Advanced analytics tools can also help improve resource management by providing resource availability and optimal resource allocation information to reduce waste in the project. Modern business analytics tools can generate easy-to-understand reports which can be shared with all stakeholders for data-driven and collaborative decision making. Large-scale projects involve vast datasets which require strong analytical and processing ability. In addition, these projects can run for many years requiring accurate long-term forecasts and planning, which are not possible without the aid of advanced analytics.
Leveraging advanced project analytics
Prior to investing in advanced analytics tools, project managers should build a robust analytics strategy aligned with the objectives and goals of the project. Figure 1 illustrates the six areas of focus while creating a robust project analytics strategy:
Figure 1. Six Pillars of an advanced analytics strategy for project management
1. Identify project objectives: Understanding the project objectives and KPIs can help in collecting data and identifying the processes that need to be optimized.
2. Stakeholder analysis and alignment: It is crucial to carefully consider the requirements of all the stakeholders before making an analytics model. It can help in gathering data, avoiding scope creep, and providing updates to the stakeholders. You can do this by adding questions specific to the stakeholder’s needs while constructing the analytical model.
3. Data engineering: Executing a robust analytics strategy requires gathering, documenting, processing, and storing data in accessible applications. Project managers can use low-cost cloud applications to perform these tasks.
4. Analytics models and techniques: Creating and understanding an analytics model is crucial to a robust project analytics strategy. Project managers need to ensure that their teams have the statistical knowledge to understand and use these models in project analytics applications.
5. Visualization, reporting, and storytelling: The project team needs to be able to understand and convert the data into actionable insights. Project professionals must know how to study reports and dashboards and project these insights in a storytelling manner to all stakeholders.
6. Team and skill development: Investing in employee training for digital skills is as important as investing in new technology. Executives need to reskill their employees to ensure a seamless and successful implementation of advanced project analytics.
Digital transformation should not only be considered as buying expensive digital software; it should instead be approached as a journey in which the company needs to evolve its organizational culture and structure towards more flexibility and resilience.
Ref: AI Multiple