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Forecasts are always wrong: The lesson from Yu Group's accounting disaster

21st May 2019
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The energy supplier Yu Group has recovered from the “serious accounting issues” which wiped out its profits and led to a dramatic share price plunge. But the utility company’s travails begs the question: how did they get their accounting so wrong?

The numbers in Yu Group’s latest trading update are mixed. Revenues increased by 77%, but it's in the losses column where the overall impact of Yu’s accounting annus horibilis is manifest: the company’s £711,000 profit from 2017 turned into a £6.2m loss.

The cause of this profit plunge emanates from, by the company’s own admission, accounting and system failings. Notably, the utility company made a slew of fairly rudimentary errors: it had underestimated the number of bills unlikely to be paid and overestimated some customers' consumption.

To the company’s credit, its trading update is honest about its accounting dysfunction. And Bobby Kalar, Yu’s co-founder, reassured shareholders that, “We have made significant progress in implementing new systems and processes and the Board is confident that we have weathered the storm”.

There seems to be a greater degree of certainty over its forecasts now. Further down in the trading update, the company explained, “Whilst consumption can vary from this forecast, the Board has a good level of certainty over the revenue to be expected from its contracts, following improvements to the management of data in relation to revenue recognition processes.”

Still, it’s remarkable that an AIM-listed energy supplier didn’t have this in place, to begin with. Especially since energy suppliers would seem uniquely well placed to do this well. “It is easy to sit on the side and make comments, but it is alarming that a company in that kind of business can get its forecast collections so wrong,” said Hugh Johnson, founder of Accounting Insights and AccountingWEB’s Power BI guru.

“They should be swimming in data about their customers' profiles, consumption and payment patterns. This should all be the basis of pretty robust forecasting. It's all relative, of course, and I am not sure of the proportionality of the error to their overall business.

“If a utility company cannot produce robust cash forecasts, what hope have the rest of us?”

The lesson from Yu Group’s forecasting snafu, according to Johnson, is simple: forecasts are always wrong, so they should be tracked and adjusted constantly.

“The takeaway I think for anyone working in finance is always to look at the numbers and ask the basic question 'do they look right?'. A forecasting error on this scale probably looked ‘wrong’ quite a long time ago, if only it were looked at. Spreadsheets (or any other reporting tools) don't refuse numbers. It is up to us to do that.

“Good practice would always be to have a rough mental idea of what to expect before you look at any numbers. That makes it so much easier to spot something that is way off target. It's a discipline that used to be engrained in us before we got technology and now technology sometimes makes us lazy. If Google Maps tells you that it will take you three hours to walk from Blackfriars Bridge to Liverpool Street you know, I hope, that something's wrong. It should be the same with your financial reports.”


Replies (5)

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By flightdeck
23rd May 2019 10:06

Could be for a few reasons

(1) the business is complex and forecasting is left to the finance people who do not really understand the business (as in, how it actually accomplishes its stuff). Forecasting must have input from the subject matter experts - who need to see it as important, not an admin chore to be skimmed over. Forecasting is really hard even on a good day. We should all just admit that.

(2) Yes! You should have some internal view as to the forecast is likely to be so that when you eyeball what the computer says you can immediately sense if it is broadly right or wrong. The trouble these days is that everyone wants the computer to do it for them (I do worry about the forecasting add-ons to accounting systems). People are no longer walking their talk, digging into their business and getting their hands dirty with its dynamics. So they don't really know if what the computer says is right or wrong. Everyone at the top table should have this internal compass and they should all have all been over those numbers.

Not sure how complex this business is though - isn't energy usage fairly predictable and, although energy wholesale costs can vary, you do know that they will vary so you can model that in. This does look like a business that should be awash with data points. But then again, lots of things look easy on the surface which aren't when you get inside them.

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Replying to flightdeck:
Hugh Johnson
By Hugh Johnson
23rd May 2019 16:00

An advantage of a computer-generated forecast is that it will apply a consistent methodology. It won't give a different answer because it had a row with its partner last night and is not feeling very good about the world.

A disadvantage of a computer-generated forecast is that it will apply a consistent methodology. It will not take into account something that you know but is not in its dataset.

What is best depends a lot on the business. But to me, the idea of a computer-generated forecast that self-adjusts every day, but is regularly (weekly?) reviewed and adjusted manually makes a lot of sense for many cases.

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By richards1
23rd May 2019 11:14

Cash flow forecast and tracking would have sent a red flag after all money in the bank is the key.

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By rememberscarborough
23rd May 2019 12:22

Strikes me the figures were made up to what the senior management wanted to see not what the actual performance warranted. If you put such undue pressure on the finance department to deliver these results then is it surprising you get them? Ask the bosses at Tesco when the City was demanding such astronomical growth and threatened to fire them if they didn't deliver....

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Chris M
By mr. mischief
23rd May 2019 15:52

I've had various clashes in my career in industry over forecasts. One time I ended up losing my job over it - seen as being the awkward bugher who won't trick up the numbers for it. Another time I managed the politics much better, made sure my boss's fingerprints were all over the tricking up and not mine, and he got fired.

If you are newly qualified or in your first senior finance role, it starts with a dodgy forecast. Then we come to the year-end and now you are under a ton of pressure to trick up the actuals. So it's important that your fingerprints are not on the forecast.

In the worst case, before I joined a manufacturing company the FD of a £10m site had just been fired. he had got himself in such a hole that he was unable to take part in a New Year party every year with his friends. Because he was in the warehouse, driving a fork-lift truck to make sure the auditors counted over £500k of stock twice.

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