Are we moving towards a science of valuations? Will we ever reach a point when there is an agreed, rational and mathematical method of determining how to put a £ sign on a business?
There are two indicators that we might be getting closer. The first is the rise of forensic valuations for some of the trickiest metrics. One of the hardest to put a price tag on is brand value. How much is the name and logo of say Lagavulin whisky worth, as distinct from the expertise, barrels, bottles and other bits?
The accounting techniques for valuing brands are set out by the International Organization for Standardization in the ISO 10668 standard. The ISO is considered robust enough to be mandated by HM Revenue & Customs, which is not a body known for dealing in shades of grey. Other tricky areas of valuation are getting the same rigorous treatment.
Algorithmic valuations
Second, we have the rise of algorithmic valuation services, such as Bizdaq and BizEquity. Input the numbers, hit compute and out comes the company value.
BizEquity has run valuations for 204,500 business and harnesses data from almost 30 million companies worldwide.
The BizEquity formula sucks in between 11 and 56 data elements per valuation. An algorithm crunches the numbers. Five minutes later you’ve got a number. The process is reliable enough for 90 financial institutions to offer to clients as a white-label service.
So are we travelling towards the promised land? According to more than a dozen leading mergers and acquisitions (M&A) advisers, the answer is a unanimous no.
Andy Parker, partner at Cooper Parry Corporate Finance, puts it best: “Ultimately, valuation comes down to a negotiated deal between a willing buyer and willing seller.
“Arriving at that value differs by sector, by growth within that sector, with opportunity for the business. It differs where the quality of management varies between one company and its competitors. It can vary by geography, local competition, potential, innovation and many more factors.”
Highlighting potential
A chat with a buyer shows how this works in practice. Robert Legge, chief executive Europe of facilities manager Servest Group, has made eight major acquisitions in the past four years. He explains: “The balance sheets, the accounts and the quantitative data in general tend to get the lion’s share of our attention. However, any dictionary will tell you that ‘value’ cannot be confined to the realm of numbers and statistics.”
Mr Legge points to his acquisition of energy efficiency consultancy Llewellyn Smith. “The numbers alone might not have highlighted the full potential,” he recalls. But the synergy was sensational. He could cross-sell to all his new clients. The skills he acquired meant he could pitch new services to his existing roster.
Discrepancies highlight that what is supposed to be a hard currency of brand measurement is indeed a very relative value
“The value here is fourfold. The acquisition has boosted revenue, staff morale, business prospects as well as our reputation in the sector,” he says. No accountant could have put that into a spreadsheet.
There’s another big reason to doubt there will ever be a perfect science of valuation. Namely we still don’t have consensus on how to value some pretty basic components.
Take brand value, mentioned earlier. Flick through the valuation literature and it looks like science. ISO 10668 lists seven approved methods, such as the “price and volume premium method”. For example, the drug Nurofen is pure ibuprofen, yet costs three times as much as generic ibuprofen. In this case it is pretty clear how much the brand contributes. Agencies such as Millward Brown, Brand Finance and Interbrand claim to offer reliable brand valuations using these standards.
Yet when you look at the valuations by differing agencies, there is astonishing variation. Kirsten Foster of marketing agency Landor observes: “The three most widely used are valuing the Apple brand at $246 billion, $170 billion or $128 billion.
“Depending on who you ask, Google is worth $120 billion, $173 billion or $76 billion. These are not marginal differences. These are differences of up to 100 per cent. These discrepancies highlight that what is supposed to be a hard currency of brand measurement is indeed a very relative value.”
The final price
If components like this are fuzzy, then arriving at a final price for the company as a whole is going to be fraught with problems.
Company valuations are so volatile that even sticking to a valuation post-deal can be hard. Patrick Sarch, M&A partner at law firm Clifford Chance, says 68 per cent of transactions featuring a private equity firm now use so-called “locked box” structure.
“In these cases the company is valued based on a fixed price at a certain date and there is no post-completion adjustment,” he says. “While generally regarded as seller-friendly, as the buyer takes economic risk on the business from the reference date, these mechanisms have the benefit of certainty and simplicity, which reduces advisory costs when compared to complex completion accounts.”
Of course, M&A experts won’t give up. They will strive to iron out the glitches. Simon Browning, partner at UHY Hacker Young, sees more M&A involving management due diligence, which may include an evaluation of the role of the owner.
“Are they fundamental to the business?” he asks. “Will their departure detrimentally impact the business and its value? Do they need to be tied in for a period after disposal?” Management due diligence is still a young discipline. The validity of psychometric tests, for example, is hotly disputed.
Algorithmic models will grow in sophistication. Certainly, for mid-sized firms that don’t want to pay for a full sale valuation, a service like BizEquity can offer a considered and benchmarked number for a tenth of the usual cost.
But can M&A be boiled down to numbers? Doug McPhee, global head of valuation services at KPMG, sums it up: “When it comes to judgment, even the most technically correct valuation is dependent on what a potential buyer would pay for a business in the current situation.
“Business-specific discounts and assessment of the potential buyer audience, and their appetite for the particular type of asset, are vital and cannot be easily captured through algorithmic models.”
Or as the great statistician George Box put it: “All models are wrong, but some are useful.” We may never get further than that.
