Companies rely on successful delivery of projects to remain competitive. As a company board member, how do you identify the real risks affecting the projects that you tender and deliver?
Recent headlines around companies who have been unsuccessful in delivering projects are adding up, creating reputational damage and legal friction. At worst, companies go into administration. Some lose significant shareholder value, some are sold, and others move away from high risk project revenue.
Cultural change can be an overused term, though project management and delivery teach us what is perceived as best practice. Despite the huge range of project management, cost control, scheduling, risk and safety management systems, tools, procedures, and standards, they still fail to rectify under-performances.
A new project will be as good as the team appointed to manage it. They will bring their own experience and personal data biases to the project. People are optimistic by nature and suffer what is termed optimism bias.
It is an enlightening experience when customers realise that our AI technology works, and that is has the capacity to identify problem projects. Reaching this point is a significant milestone. Octant AI’s predictions are then referenced in project review meetings to analyse the differences in AI and traditional predictions.
These early warnings highlight the importance of project managers exploring the details and taking an involved approach with this technology.
The journey of AI adoption is gathering pace as the company moves forward through piloting and testing Octant AI. Target customers are led by very experienced professionals and they seek information on how the technology operates. We run several tests to demonstrate what Octant AI can predict on projects it has never seen nor been trained on. The test results demonstrate predictive accuracy.
Showing individual project managers AI predictions for past projects they managed, truly demonstrates the power of Octant AI. It helps overcome the perception that AI is just a black box.
After gaining customer interest in Octant AI we inquire about their data. Where is your data stored, how is it stored, do you have consistent data, what sort of data is available? These questions along with many others help us develop an understanding of how their data structures influence practical business challenges.
Many potential customers are unable to answer these questions. Therefore, they suffer from what we call ‘data embarrassment’ regarding the perception of the quality and completeness of their data. Many believe that feeding the AI ‘bad’ data predictions causes inaccuracies.
As Endeavour Programme engages with customers in the construction sector about Artificial Intelligence (AI), and Octant AI more specially, there has been an understanding of the concept of AI, but a limited depth of comprehension, until now. The success of Octant AI with our foundation customer has been crucial in demonstrating the benefits of AI.
There are many hurdles to overcome in forming or changing the perceptions of AI; from gaining initial interest to moving forward to the actual adoption phase. A common negative perception of AI is that it is a distraction from the important day jobs, or even just a costly gimmick. However, when projects are negatively affected by budgets or deadlines, the construction industry becomes consumed with trying to make a difference. Organisations are utilising the same information and assumptions that previous decisions were made from. Unless the information can be interpreted more accurately, how can the decisions improve?
Endeavour Programme’s unique AI solution “Octant AI” uses a process called Reference Class Forecasting to learn from existing historical project data. It uses this knowledge to predict future performances. Our tailored algorithms have undergone comprehensive testing and can provide the following business benefits:
Together with advanced analysis of business data, analytics dashboards, and embedment of AI enhancements the value to the business is assessed as at least equivalent to margin increase of 1% of turnover.
New norms of conducting business in an environment where social distancing is necessary are leading to less efficient methods of working. This is causing a level of disruption and associated loss in productivity and efficiency at every level. It ranges from how many men can work in a trench, to the logistics of having three men in a 12-man hoist for vertical construction.
This complexity makes it very difficult to foresee the future, when the cumulative knowledge is based on traditional ways of working. Unfortunately, these ways do not reflect the current environment.
Big idea pioneer David Porter envisions a world where our $10 trillion project construction industry is no longer burdened by cost and time overruns. David said it’s the typical story we see in the media; massive infrastructure projects running millions or billions of dollars over budget and years late.
“These projects inevitably become the focus of political and media scrutiny, and so they should. If airlines had the track record of major projects, there wouldn’t be an airline industry,” David said.
Artificial Intelligence – Prediction in a Construction Environment
We have come to recognise that infrastructure projects run over time and budget. This point has been well documented by the University of Oxford based expert on mega-projects Professor Bent Flyvbjerg who maintains a global database of the performance of thousands of large projects (see Figure 1).