--- title: "Why a green dashboard doesn't always mean a healthy project" date: 2026-10-26T09:53:00+00:00 author: Alex Chisholm canonical_url: "https://kentplc.com/news-insights/why-a-green-dashboard-doesnt-always-mean-a-healthy-project" section: Blog --- 26 Oct 2026 Insights & Opinions # Why a green dashboard doesn't always mean a healthy project ![Web Banner 30]() We have become very good at measuring project progress. With increasingly sophisticated reporting systems, we can track cost, schedule, engineering, procurement and risk in extraordinary detail. Yet one question remains surprisingly difficult to answer: how healthy is the project? I've seen projects reporting healthy progress while significant challenges were developing beneath the surface, and the project was drifting out of control. Engineering might be meeting its planned completion targets, but outstanding technical queries could be affecting procurement. Construction activities might be progressing to schedule, while unresolved interfaces threaten the next phase of work. The individual reports aren't necessarily wrong. The problem is that each tells only part of the story. For me, this is one of the biggest opportunities in project management today. We have the information, increasingly we have the technology to connect it, and we have decades of delivery experience to help us understand what it means. The challenge is bringing those elements together in a way that improves decisions. Major projects are complex because everything is connected. A delay in engineering can affect procurement, which in turn influences construction sequencing, productivity, and ultimately cost. These relationships are well understood by experienced project professionals, but they're not always apparent in conventional reporting. Consider a project where engineering progress is on target and procurement reports that purchase orders have been placed as planned. Both indicators might be green. However, if critical vendor information is arriving later than anticipated, engineering deliverables may need to be revised, creating potential disruption to construction. The warning signs exist, but they sit across different disciplines and reporting systems. Traditionally, identifying these connections has depended heavily on people reviewing large volumes of information, comparing reports, and recognising inconsistencies. It's valuable work, but it takes time, particularly on projects involving multiple contractors and thousands of interdependent activities. This is where technology offers a significant opportunity. Advances in digital platforms, analytics, and artificial intelligence are changing what we can do with project information. By bringing together data from different disciplines, we can begin to examine the relationships between activities rather than simply measuring their individual progress. AI-enabled analysis can help identify patterns, highlight inconsistencies, and draw attention to emerging risks that might otherwise take considerable effort to uncover. It also creates opportunities to apply lessons from previous projects and assurance reviews to the challenges we're facing today. That matters because the earlier we recognise a potential problem, the greater our opportunity to influence the outcome. But the real value isn't simply having access to more information or producing increasingly sophisticated dashboards. It's being able to turn that information into something useful for people making decisions. A system might highlight a growing difference between planned and actual progress, for example. Understanding whether that represents a temporary disruption, a weakness in the baseline or a more fundamental delivery problem requires a closer examination of the circumstances. Essentially, technology can help direct our attention. Experience helps us understand what we're looking at. One of the things I've learned about major projects is that the assumptions behind a plan deserve as much attention as the progress being reported against it. A schedule may be mathematically sound but based on unrealistic productivity expectations. A cost forecast may be accurate against the current scope while failing to reflect the consequences of unresolved technical issues. These are the kinds of questions that experienced delivery professionals are accustomed to asking. The opportunity now is to support that judgement with better, more connected intelligence. When information from different parts of a project can be examined together, it becomes easier to test assumptions, understand dependencies and focus attention on the areas that warrant further investigation. It also makes constructive challenge more effective. Rather than relying solely on experience or instinct, project teams can explore concerns using evidence drawn from across the project. That combination of data, technology, and practical experience can strengthen the quality of conversations between project owners, contractors, and delivery teams. Ultimately, the purpose of understanding project performance is to make better decisions while there's still time to influence the outcome. Recognising an emerging risk is useful. But understanding its potential consequences, identifying the available options and acting before it becomes a significant problem is where the real value lies. I believe this is where project management is heading. As our ability to connect and analyse information improves, we have an opportunity to move beyond reporting what has happened towards understanding what may be developing and where intervention could make a difference. That doesn't diminish the importance of established project controls or experienced professionals. It makes both more valuable by giving us a richer understanding of how projects are performing. The next time a dashboard shows everything green, I'd be encouraged by the result. But I'd be even more interested in what the information behind it is telling us about the work ahead. 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