Humans Theyre error-prone. This is the era of big data and FDs need to get with the programme.
Finance functions have been here before, of course. The arrival of the mainframe, the desktop accounting package, the humble spreadsheet all labour-saving devices that would take the grunt work out of finance and make it all the more strategic.
Forget, for a second, that people have been discussing the newly strategic finance function for 50 years or more. Remember, back in 1965 the first minicomputer the PDP-8 could run at 330,000 operations per second. The smartphone in your pocket can handle at least 75,000,000,000.
The fact that the compound annual growth rate in the number of accountants in the UK and Ireland from 2009 to 2013 was 2.7 per cent (for CIMA, with a focus on business, membership CAGR was actually 4.2 per cent) at a time when the economy has been more or less shrinking tells you all you need to know about how much labour these fantastic machines have saved.
Of course, the era of big data is just beginning, and as the machines get smarter, theres a chance they will start to undertake some of the analysis and interpretation currently in the hands of FDs and their teams.
But I wouldnt worry just yet. In a fascinating interview with US publicationIEEESpetrum, artificial intelligence guru Michael Jordan issues a stark warning to the big data neophyte: When you have large amounts of data, your appetite for hypotheses tends to get even larger. And if it’s growing faster than the statistical strength of the data, then many of your inferences are likely to be false. They are likely to be white noise
“You can’t be completely a skeptic or completely an optimist about this. It is somewhere in the middle. But if you list all the hypotheses that come out of some analysis of data, some fraction of them will be useful. You just won’t know which fraction. Unless you’re actually doing the full-scale engineering statistical analysis to provide some error bars and quantify the errors, it’s gambling. Its better than just gambling without data. Thats pure roulette.
Jordan worries there will be a big data winter when the hype-bubble bursts that valuable work on these problems will be lost as people cease to invest in systems that havent yet delivered.
So the advice for FDs is simple. Invest in systems and data but more importantly, invest in great finance people (and some statisticians!) to help analyse and interpret whats really valuable in making business decisions. That applies to areas like investment analysis, HR decisions and marketing the data is useful, but the people are critical.
Then when the winter comes keep investing. Organisations should be able to sweep away the hype and think calmly and coolly about the value of data (and the new ways of analysing it whether or not thats evenly remotely deserving of the AI” tag) and how it informs their own, human, financial decision making. Just because weve been talking about the changing face of the finance function for 50 years, that doesnt mean it isnt still evolving nor that it won’t need smart FDs at the top of it.