- High Tech & Manufacturing, Digital PMO
A leading logistics company in the UK manages a highly diverse portfolio of projects spanning construction, business change, and new technology. Recurring issues such as budget overruns, schedule delays, and poor-quality data were impacting reliable forecasting and proactive decision-making. The organisation needed a way to improve project performance, strengthen confidence in decision-making, and establish the foundations for AI adoption.
MIGSO-PCUBED (MP) with greyfly.ai partnered with the client to introduce Intelligent Project Prediction (IPP), measuring success against three targets: data quality, projects over budget, and overspend.
The impact was clear, reduction in total budget overrun. This award-winning approach, recognised by the Innovation in Project Management awards, shows how predictive analytics can unlock smarter, more sustainable project delivery.
Table of Contents
Hurdles to overcome
The organisation faced multiple hurdles before the project began:
- Recurring issues in project performance, particularly budget overruns and schedule delays.
- Inconsistent, poor-quality data was impacting the delivery of reliable forecasting and proactive decision-making.
Alongside from the performance and data issues, this project also needed to address:
- A lack of experience in data-driven Project Controls.
- Cultural resistance to AI adoption, stemming over whether artificial intelligence could provide accurate and actionable insights.
Overcoming these challenges would require not just technology but a significant cultural and organisational shift towards data-driven project management.
How we made it work
The client partnered with MIGSO-PCUBED (MP) and their partner greyfly.ai to launch a transformative programme to embed artificial intelligence and predictive analytics into their portfolio management practices, driving a shift towards a data-driven culture.
MP introduced their Intelligent Project Prediction (IPP) platform, a machine learning solution that predicts project outcomes and identifies key risk drivers.
Together, we delivered transformation through three key focus areas:
1. Building capability
An integrated team was created, bringing together the client's PMO and project teams with MP's Delivery Manage, data specialists, and changed expert. Senior sponsorship and visible leadership helped drive adoption, while knowledge transfer ensured the organisation could sustain and expand IPP beyond the project.
2. A clear path to delivery
We followed a six-step delivery lifecycle, from data discovery through to infrastructure build and configure, handover and review, and finally support.
This delivery methodology was supported and guided by a typical set of Project Controls; a project schedule, a risk / opportunity register, an issue register, and a change log. These were all owned and managed by our Delivery Manager. Weekly progress reporting and a monthly project board chaired by the sponsor ensured accountability and focus on adoption.
3. Winning stakeholder confidence
We followed a six-step delivery lifecycle, from data discovery through to infrastructure build and configure, handover and review, and finally support.
This delivery methodology was supported and guided by a typical set of Project Controls; a project schedule, a risk / opportunity register, an issue register, and a change log. These were all owned and managed by our Delivery Manager. Weekly progress reporting and a monthly project board chaired by the sponsor ensured accountability and focus on adoption.
Demonstrated value
After the project completed, results exceed expectations, especially in the three key parameters measuring project success:
- Poor-quality data reduced from 78% → 9%
- Projects exceeding original budget cut from 33% → 6%
- Average overspend reduced from 74% → 33
Combined, these delivered a 22% overall reduction in total budget overrun.
In addition to these financial benefits, this project also delivered:
- Higher-quality reporting and clearer communication.
- More confident, data-driven decision-making.
- Better resource utilisation through streamlined operations.
- Strengthened organisational confidence in AI, laying foundations for wider AI adoption.
- Contribution to thier sustainability objectives by reducing waste and failure.
Lesson for future digital transformation
This project demonstrated that a combination of AI technology and strong project management practices can drive significant innovation and efficiency. Key takeaways for any digital transformation include:
- Consistent executive sponsorship is vital.
- A robust data quality and ownership strategy underpins success.
- Change Management must be front and centre for AI adoption.
- Effective Project Controls sustain long-term improvements.
This case study shows how a leading logistics company, working with MIGSO-PCUBED and greyfly.ai, used Intelligent Project Prediction (IPP) to resolve long-standing project challenges. By improving data quality, building team capability, and strengthening trust, the organisation reduced budget overruns and delays, while also building confidence in AI. The results demonstrate that combining new technology with smart strategy and strong teamwork is key to delivering lasting transformation.
Award winning impact
The partnership between the client, MIGSO-PCUBED, and greyfly.ai was recognised by the Association for Project Management (APM), winning:
- Technology Project of the Year
- Innovation in Project Management
Thank you Ian Radcliffe for your contributions to this article.
Key results
Poor-quality data reduced: 78% → 9%
Projects over budget cut: 33% → 6%
Average overspend reduced: 74% → 33%
Delivered a 22% overall reduction in budget overrun.
