Over the last few years we hear more about the use of AI (artificial intelligence), big data, and IoT (Internet of things). All of these will have an effect on how we perform in our jobs. In the future some of the advances will mean the replacement of existing jobs. Artificial intelligence could possibly perform much of the project manager’s role. Even if it does not immediately replace project managers. This would lead us to assume that the current technology trends will greatly impact the project manager’s contribution to change.
A brief history of project management
Project management has only been recently defined and refined. Some form of project management has taken place for hundreds, if not thousands of years. Many of the challenges seen to remain the same today. If you take big constructions like the pyramids as a project, then they had the same need to control people and materials. They also needed to plan how resources were used and record progress in order to refine the path of the project.
In the last few decades, work has taken place to advance project management. Computerised tools have made planning and tracking easier. Adjustments to the approach has changed with agile and lean methods. But with all the changes in methodology the role remains the same of controlling a team to deliver a solution over a set period of time.
The core issue with todays approach
One of the core problems project managers have had is collecting honest, accurate and complete information about projects. Systems have help that, but the core problem remains that project teams for a range of reasons will only provide a subset of the information required. An example of this is simple recording of timesheets. Even in the best run project they are subjective lies; they might be expected to add up to 8 hour days. But in reality, the person may have worked longer than that, giving an underestimate of the effort involved. In other cases people will not remove the breaks they took or the time talking to colleagues about the latest sports event, or coffee and other breaks; thus over recording the time needed. Because of these issues the human entry of data is always likely to be flawed.
Using artificial intelligence in conjunction with the wider range of data capture across the project will remove many of the data capture flaws. Establish consistent recording of project data and then you can extend the process into many project support activities like planning, resource management, risk recording, tracking and reporting. At the same time this improves feeds into financial control and allows automated project governance.
Planning and risk assessment
Planning is a core element of project management. Creating and maintaining a plan that is a practical model of the project is a challenge. Although we have tools to help, most projects have plans that poorly reflect the project’s real path. But having even a general plan is useful.
Applying approaches from big data trend analysis will help. As well as having the possibility to call upon a wealth of completed projects; which means over time planning can become more automated. This approach will also allow better analysis of risks. Risk management will be improved as risk reduction and contingency approaches are better informed. The old general plan of the past will become more exact over time. The planning system will be able to call on a vast wealth of data well beyond what even the most experience of project managers can offer.
It is not a huge leap of imagination to see the planning systems suggested above linked into HR systems. The HR resource model providing all the necessary information for internal resources. While cloud services and AI allow enquiry of external resources in the open market (via tools like a future Linkedin maybe). From that data, a schedule to be compiled, and the likely resources can be suggested. The resources could be suggested to the project manager, because the system knows who is available and can top that up with external resource if needed.
It’s not a big jump to see that planning systems could very quickly cut out the project manager and assign all the required resources. In a fully connected world, depending on the acceptance of AI and global feeds, the advance solutions currently being designed could forecast resource for changes; allowing adjustment of plans and tailoring a range of short term effective resource assignments.
Today’s resourcing constraints are removed and resourcing bottlenecks need only happen on extremely rare resources.
The data on resource performance can be used to confirm that the team is delivering effectively.
Tracking and reporting
With today’s patchy and incomplete data in tracking projects the maintenance of the project plan is time consuming and prone to rework. With more complete data available, exactly when needed; the adjustments and tuning of the project become easier. This will lead to more time to focus on risks and improving outcomes that can benefit the whole process.
With systems measuring the quality of project governance and definition as well as the quality of deliverables, clear measure of progress is automatically available. With other tools and devices recording the effort taken to produce these items, there is no need for timesheets and old fashioned progress tracking.
There are possible benefits to project teams too. The feedback on performance can allow better working processes. Completeness of data when required means that the project team can better understand what is happening.
The combination of recording and almost instant plan adjustment means that automated project dashboards can provide instant and immediate project reporting. This could lead to the elimination of the project team reporting red, the project manager watering that down to amber, and senior management reporting it as green when it gets to the executive team. The same data will be agreed and consistent rules would be used at all levels.
Governance and PMO Audit
With the complete recording of every element of the project old fashion project audit is not needed. The assessment of project status against a corporate life cycle or governance model would be instantly available. The PMO can then focus on helping to identify where the process can be improved and streamlined.
Workflows will control approvals from project customers and other stakeholders. Artificial intelligence can highlight areas that block progress.
Reviewing and tuning process over time will help to evolve future project methods that can take us forward in project timescales and costs.
Many of the systems and approaches to start this process are available now. The will to install and use them is a blocker. But a time will come in the not to distance future when the full capability of artificial intelligence and supporting technologies will be demanded by all organisations running projects.