Big data skeleton key

Big data is a catch-all term but, broad­ly speak­ing, it refers to the large vol­ume of inter­nal and exter­nal data that can now be cap­tured and analysed to improve organ­i­sa­tion­al and finan­cial per­for­mance. Chief finan­cial offi­cers (CFOs) in UK busi­ness­es now have more data at their fin­ger­tips than ever before, and their role is chang­ing as a result.

Simon Bit­tle­stone, chief exec­u­tive of finan­cial ana­lyt­ics firm Metaprax­is, harks back 20 years to demon­strate how the role of the CFO has been affect­ed by the advent of big data. “You found more CFOs focus­ing most of their time on ensur­ing the num­bers for busi­ness report­ing were cor­rect, and ensur­ing the busi­ness was liq­uid and the risks were being man­aged. And that’s still an impor­tant part of the role of CFO,” says Mr Bit­tle­stone, who  explains that fol­low­ing the automa­tion of finan­cial report­ing, the focus became how can we improve the busi­ness using the data we have?

Commercial decision-making

Hav­ing access to data from across the busi­ness is one thing, but know­ing what to do with it brings anoth­er set of chal­lenges, which many CFOs are ris­ing to. Big data ana­lyt­ics pro­vide an impar­tial, sta­tis­ti­cal­ly accu­rate view across the whole busi­ness, which helps CFOs make more evi­dence-based deci­sions, accord­ing to Renaud Heyd, CFO at SAP UK and Ire­land. He adds: “Big data enhances the finance function’s abil­i­ty to steer, con­trol and devel­op the busi­ness.”

Ray­mon van Viegen, CFO at Onguard, points to an exam­ple of a large busi­ness which has suc­cess­ful­ly used big data to imple­ment cost-sav­ing ini­tia­tives. “This is some­thing we have seen from [ship­ping and logis­tics com­pa­ny] UPS, which used the wealth of data at its dis­pos­al to uncov­er that it could sig­nif­i­cant­ly reduce costs if dri­vers took few­er left turns,” Mr van Viegen explains. “As a result of this find­ing, the couri­er saved 38 mil­lion litres of fuel [in 2011] and the price tag attached to that.”

Big data can be used for much more than cost-cut­ting in a busi­ness. Air­swift CFO Tim Bri­ant says one of the areas where data has been dri­ving com­mer­cial deci­sions in his work­force solu­tions com­pa­ny is in hir­ing. “In recruit­ment, the addi­tion­al ana­lyt­ics from LinkedIn around the recruit­ment trends in a region, by skillset and organ­i­sa­tion, are real­ly allow­ing us to pro­vide insight to our cus­tomers,” he says, adding this enables the busi­ness to assess how long it will take to fill roles and what it should charge for its ser­vices.

Wide array of data

Peter Simons, asso­ciate tech­ni­cal direc­tor of research and devel­op­ment, man­age­ment account­ing, at the Asso­ci­a­tion of Inter­na­tion­al Cer­ti­fied Pro­fes­sion­al Accoun­tants (AICPA), notes that CFOs play a cen­tral role in con­tin­u­al­ly ensur­ing resources with­in a busi­ness are allo­cat­ed or real­lo­cat­ed to where the returns or prospects are best.

“To make these deci­sions, CFOs should of course have rel­e­vant finan­cial infor­ma­tion at their fin­ger­tips, but they should now also have on hand the salient data about the key dri­vers of finan­cial out­comes,” he says. This type of infor­ma­tion should be com­ing to them from teams across the busi­ness.

A recent sur­vey by Exa­s­ol of 500 deci­sion-mak­ers in enter­prise organ­i­sa­tions in the UK and Ger­many found the most fre­quent­ly request­ed data insights by busi­ness units in an organ­i­sa­tion were finan­cial out­looks (57 per cent) and prod­uct per­for­mance met­rics (50 per cent), fol­lowed by cus­tomer feed­back analy­sis and mar­ket trends at 46 per cent and 41 per cent respec­tive­ly.

David Wal­ters, head of data at busi­ness intel­li­gence spe­cial­ist Cred­it­safe, says CFOs might be expect­ed to han­dle finan­cial data in terms of how that can dri­ve val­ue out­side the finance func­tion, includ­ing in pro­cure­ment, and sales and mar­ket­ing. “They might also be expect­ed to exam­ine sup­ply chain-focused data and infor­ma­tion tech­nol­o­gy,” he adds.

This has changed per­cep­tions about who owns the data in an organ­i­sa­tion. Rather than sit­ting in silos, data sets from across finance, mar­ket­ing and cus­tomer ser­vice can be com­bined to cre­ate a big­ger pic­ture for use in pre­dict­ing cus­tomer behav­iours and pat­terns.

In this case, Mr Simons believes the CFO is the bro­ker of infor­ma­tion with­in the busi­ness. “CFOs should have a quan­ti­ta­tive, evi­dence-based under­stand­ing of the busi­ness mod­el and how it cre­ates val­ue for its stake­hold­ers. This includes every­thing from the tar­get­ed mar­ket seg­ment and val­ue propo­si­tion through to exter­nal resources and  rela­tion­ships, as well as inter­nal process­es and skills need­ed to deliv­er the tan­gi­ble and intan­gi­ble ben­e­fits expect­ed by cus­tomers,” he says.

There is now also an expec­ta­tion on CFOs to look beyond what might be deemed tra­di­tion­al sources of data, as Tim Vine, head of Euro­pean trade cred­it at Dun & Brad­street, points out. “Real-time infor­ma­tion is often pub­lished online before reach­ing offi­cial sources,” he says. “For exam­ple, 24-hour news sites might be the first ones to share exclu­sive devel­op­ments on busi­ness­es, which might impact their risk assess­ment or the wider sup­ply chain. It’s these non-tra­di­tion­al data sources that can pro­vide CFOs with auto­mat­ed, con­tex­tu­al insight from a vari­ety of sources, which is an excit­ing oppor­tu­ni­ty.”

Get it right and data will ensure the finance direc­tor con­tin­ues to hold a crit­i­cal strate­gic posi­tion at the heart of the busi­ness

Busi­ness­es have always made pre­dic­tions, par­tic­u­lar­ly when it comes to finan­cial per­for­mance. But thanks to big data and the use of pre­dic­tive ana­lyt­ics, CFOs have the oppor­tu­ni­ty to ensure those pre­dic­tions are even more accu­rate, cement­ing the finance team’s strate­gic val­ue with­in a busi­ness.

Mr Wal­ters explains: “Pre­dic­tive ana­lyt­ics is a form of advanced ana­lyt­ics used to make pre­dic­tions about unknown future events. It incor­po­rates many tech­niques, from sta­tis­tics to machine-learn­ing and arti­fi­cial intel­li­gence (AI). “Organ­i­sa­tions can use this tech­nique to become more proac­tive and for­ward think­ing by antic­i­pat­ing out­comes and behav­iours using mea­sur­able data, rather than just hunch­es or assump­tions.”

While this pre­dic­tive ana­lyt­ics is not new, many com­pa­nies are still unsure about how to use it. Mr Bit­tle­stone thinks it is not com­pli­cat­ed and points out there is a wealth of infor­ma­tion avail­able on how to approach busi­ness per­for­mance man­age­ment with pre­dic­tive and pre­scrip­tive ana­lyt­ics. “I don’t think the bar­ri­er is going to be the knowl­edge of how to do it. It’s either a case of not feel­ing it’s impor­tant, which is going to be a real miss in the next few years, or it’s a case of not know­ing how to approach it,” he says.

But what oth­er new tech­niques are CFOs embrac­ing as part of the chang­ing nature of their role? Mr Simons draws on research con­duct­ed by AICPA for its recent Agile Finance Unleashed report, pub­lished in part­ner­ship with Ora­cle, which shows that 21 per cent of finance lead­ers have already deployed data visu­al­i­sa­tion with­in their organ­i­sa­tion. “Yet, it also found that the use of more advanced tech­niques such as AI (11 per cent), machine-learn­ing (14 per cent) and neu­ro-lin­guis­tic pro­gram­ming (13 per cent) are still in the ear­ly adop­tion stage,” he adds.

Anoth­er trend observed by Mr Vine is com­pa­nies want­i­ng to inte­grate data and ana­lyt­ics into their cus­tomer rela­tion­ship man­age­ment and enter­prise resource plan­ning sys­tems.

Ulti­mate­ly, there is a lot rid­ing on CFOs’ abil­i­ty to crunch the data. “Get it right and data will ensure the finance direc­tor con­tin­ues to hold a crit­i­cal strate­gic posi­tion at the heart of the busi­ness,” Mr Vine con­cludes.

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Commercial decision-making

Wide array of data