The conventional explanation highlights issues of competence, management oversight, risk management and governance. It is a natural human reaction to seek to blame someone when there is a major problem or failure in an organization. Conventionally, the bigger the problem the greater the blunder some individual is deemed to have made. Current thinking in the project management community is highlighting governance issues and poor and inadequate risk management. Failings typically involve the 7 factors listed below:
- Poor initial planning
- Lack of clear objectives and deliverables.
- Poor understanding of priorities
- Lack of understanding of dependencies
- Inadequate resource allocation
- Poor risk analysis
- Poor change management.
The vast majority of the individuals managing projects are well qualified, well trained and highly committed. Therefore the percentage of programme failures clearly suggests a cause outside the sphere of human competence. Something basic and fundamental is wrong. The key finding that we wish to advance here is that the projects have become opaque to those managing them.
The Way Forward: New Technology
Above we listed 7 factors that contribute to project failure. We will now show how a different approach to planning can resolve some of these issues and improve project performance. To run projects efficiently it is necessary to put accurate values into the design iteration cycle and to understand dependencies. We contend that tools are required that can adequately model the full complexity of the iterative design cycle on large projects, as well as representing the work breakdown structure in a clear and user-friendly fashion. As we have argued above the existing major project planning tools, such as critical path method (CPM) and programme evaluation review technique (PERT), use an underlying logic that was originally developed over 50 years ago. It is clear that large, complex projects exceed the capabilities of current project management tools and the representation on which they are based.
The Need to Model Iterations
In most engineering projects iterative activities can be construed as a feedback “loop”. Within this loop interdependencies exist and there is no explicit order or sequence for the relevant activities. For this reason existing planning tools cannot permit such constructs and they are treated as errors in the network that need to be removed. This is highly problematic in engineering as improving project performance requires accurate sequencing of design dependencies. In order to conduct design activity in a more efficient manner a tool and planning process is required that can offer the following:
- It must not be reliant on the judgement of a project manager to determine how many iterations are required within iterative loops;
- It must give a very efficient and compact network representation;
- In order to connect with established practice it must offer compact Gantt chart representation, which can show multiple iterations on the same activity line;
- The Planner must automatically work out how many iterations are required to best meet project objectives;
- It must be able to cope with a complex network containing a large number of intersecting iterative loops typical of real project dependencies.
We return to this theme many times, but the underlying problem of project management we have identified is an inability to accurately model the real tasks that comprise project work and the dependencies between them. Current generation project management tools cannot represent the new reality of large, complex and globally distributed projects. But in the design phase of projects the process of iteration has never been adequately captured by tools that plot a linear critical path along a line of dependencies. Information/action dependencies are very complex and characterised by a circular iterative process that gradually establishes better quality information, allowing the required design action to be completed. Planning how the design process will evolve is far from straightforward.
- Improving the planning process.
- Realistic Representation
- Re-use of Data and knowledge management
- Clear Objectives and Deliverables via Lean Thinking
- Detailed understanding of Dependencies
- Detailed Resource Allocation
- Sophisticated Risk Analysis
- Accelerated Change Management
- Ranking priorities.