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We are very short on time, and I want to move on. Surely the proof would have been in the pudding, and as Mr Simpson said, outcomes for patients are what matter. Could you see a pattern of deterioration in outcomes? For example, your four-hour emergency access compliance is down at 50 per cent, which is way below the Scottish average and that dropped considerably over a period of time. Surely, all those performance issues in relation to the CAMHS statistics, the out-of-hours GP access and the 18-week waiting times for referral for psychological assessment would have been massive red flags to the board that it was in danger of escalation.

Can I move on to the present day? We could spend a lot of time on retrospect, but I am sure that lessons will be learned and that there is a lot of personal regret in the executive leadership team.

Ms Croft, where are you currently with some of the service improvements? It is still looking quite grim for patients in Forth Valley with regard to waiting times across a number of key metrics. At the risk of my questions needing a lengthy answer that we do not have time for, what are some of the steps that you are taking right now to improve, for example, performance with regard to the four-hour A and E turnaround and 18-week referrals for mental health assessments? What are the limiting factors? We have talked about workforce and finances, but what key barriers exist right now to making immediate improvements so that you can de-escalate out of level 4?

It is at 64 per cent, against a target of 80 per cent, so it is still—

A lot of very good ground has already been covered, and I have been listening intently. I want to mop up a few other areas where you might share your wisdom.

First, there is an overarching discussion about how we define fuel poverty in the modern world. The technical definition is that a household is in fuel poverty if it spends more than 10 per cent of its net household income on fuel/energy consumption. As we know, if that figure reaches 20 per cent, a household is defined as being in extreme fuel poverty. It does not take very much to fall into that category. Even someone on a fairly substantial income who might be in a higher tax bracket could quickly find themselves in a position in which their annual fuel bill was £2,500 or £3,000, which would very easily take them into that situation. Are you worried that there is an assumption that people on very low incomes or people on various benefits are the sole victims of the current fuel poverty situation?

Thank you. I appreciate that we are out of time, convener, so I will park my other questions.

Thank you, convener, and good morning, colleagues. I have no relevant interests to declare.

Thank you. I, too, look forward to it.

I will perhaps come on to that volatility. Your opening comments—repeated in the opening paragraphs of your report—gave quite a broad-brush overview in using phrases such as “continuing economic uncertainty”, “tax policy divergence”, “weaker economic performance”, and so on. Those are quite generic terms. What specific work has Audit Scotland done on the root causes of why that figure of £390 million was so vast?

I have been thrown in at the deep end. Thank you, convener, and good morning to our panel.

Before I move on to my line of questioning, I might just conclude the previous one. We have had a bit of discussion about the variance in outturns versus forecasts. That flags a concern to me with the 2022-23 estimation from HMRC of £14.9 billion and what variance we might see in that outturn. Surely there can only be one data set at the core of all this. No matter who you speak to—the Fiscal Commission, analysts, policy makers or HMRC—I presume that they are not using different data sources, so a robust set of data that can help to produce the forecasts must sit at their core. Given the huge variance in outturns this year, can we be confident that the data set and the analysis of it are sufficiently robust for policy makers and analysts to produce the forecasts that affect decisions about tax rates, for example?

Specifically and in comparison, is it possible to quantify that underperformance in numerical terms?