How to care for your remote workforce

As remote work­ing becomes increas­ing­ly com­mon­place, keep­ing employ­ees engaged and inter­est­ed in their work, while strug­gling with the stress­es and strains of life dur­ing a pan­dem­ic, is no easy task. But AI and employ­ee engage­ment can dove­tail togeth­er to pro­vide employ­ers with an overview of how to ensure well­ness runs through an organ­i­sa­tion and pick up on issues before they arise.

All of us are being test­ed in ways we have nev­er been before, as we strug­gle under the pres­sure of rolling lock­downs, time away from fam­i­ly and jug­gling work-life bal­ances. Sen­ti­ment analy­sis can help ensure an engaged employ­ee remains engaged, and can pick up on issues with health and well­be­ing from those who feel uncom­fort­able, at a time when unem­ploy­ment is reach­ing record highs, about com­ing for­ward.

The move­ment in AI and employ­ee engage­ment is being spear­head­ed by a range of star­tups that are work­ing with major employ­ers, help­ing them feel more able to get a grip on where employ­ees are fac­ing issues, and offer­ing solu­tions to prob­lems when they arise.

Tackling mental health at work

“We’ve built an exten­sion arm, an anonymised dash­board, which aggre­gates this pool of data that says, ‘It looks like in your pop­u­la­tion of employ­ees in Lon­don, 67 per cent are at risk of stress or anx­i­ety, 43 per cent of dia­betes. And lit­er­al­ly 100 per cent of your peo­ple are at risk of mus­cu­lo-skele­tal con­di­tions,’” explains Lore­na Puica, chief exec­u­tive of iamYi­am, a big data ana­lyt­ics firm.

The com­pa­ny takes count­less anonymised data points and, using machine-learn­ing, trans­lates them into a pre­dict­ed cost of what­ev­er the issues raised will be to an organ­i­sa­tion, pro­vid­ing sug­ges­tions on how to sup­port employ­ees from the top down. “The idea is to have this inte­grat­ed end-to-end, from the employ­ee to the cor­po­rate and then back to the employ­ee,” says Puica, whose clients include large con­sult­ing organ­i­sa­tions, law firms, insur­ance com­pa­nies, and health­care ser­vices and enter­pris­es world­wide.

The real chal­lenge is tack­ling the pro­duc­tiv­i­ty cri­sis in work­forces and ensur­ing work­ers feel sup­port­ed at a time when things are high­ly uncer­tain and a num­ber of dif­fer­ent aspects of life tug and pull at their time. The UK has some of the worst rates of absen­teeism and pre­sen­teeism in the world, accord­ing to the Char­tered Insti­tute of Per­son­nel and Devel­op­ment, which has a knock-on effect on pro­duc­tiv­i­ty.

Improving experience through wellbeing programmes

iamYi­am has man­aged to reduce absen­teeism in the com­pa­nies with which it works by between one and two days per per­son a year. But pre­sen­teeism, where peo­ple turn up but aren’t engaged with their work, is a big­ger drag on busi­ness­es’ bot­tom lines. Here iamYi­am claims to improve pre­sen­teeism by between ten and twen­ty days a year.

“Pro­duc­tiv­i­ty is that elu­sive term every­one talks about, but no one can grasp,” says Puica. But iamYiam’s analy­sis of key per­for­mance indi­ca­tors in a com­pa­ny, and sug­ges­tions on how to improve it, can increase pro­duc­tiv­i­ty by 10 per cent in pro­fes­sion­al ser­vices firms and by between 5 and 7 per cent in retail.

The twinned roles of AI and employ­ee engage­ment are known by many peo­ple. Bupa, the pri­vate health­care provider, uses AI to mon­i­tor health and well­be­ing among its employ­ees world­wide, with a tool devel­oped by Glint, a Sil­i­con Val­ley start­up.

“In the past, you had to employ data sci­en­tists to under­stand what’s going on in your organ­i­sa­tion,” says Nigel Sul­li­van, chief peo­ple offi­cer at Bupa. “You try and pull out the dri­vers of engage­ment. They are things spe­cif­ic to your organ­i­sa­tion that might have a dis­pro­por­tion­ate effect on engage­ment. It might be com­mu­ni­ca­tion or the prospects of the firm. It’ll be dif­fer­ent depend­ing on the cir­cum­stances.” But AI enables Bupa to get to the heart of what’s trou­bling employ­ees and offers sug­ges­tions how to fix it.

Personalised advice depends on employee experience

“It’s like skit­tles: you hit one and get the whole she­bang,” says Sul­li­van. “Your bang for your buck is a lot bet­ter if you can find out what the dri­vers are. AI helps you get that.” Bupa uses nat­ur­al lan­guage pro­cess­ing to fil­ter through free text respons­es, in eight lan­guages world­wide, to its sur­vey of 83,000 work­ers and pin­point what are each of their con­cerns. Three quar­ters of Bupa’s employ­ees com­plet­ed the most recent sur­vey, con­duct­ed in late-Novem­ber, pro­vid­ing 68,500 com­ments.

“We can real­ly analyse that and find out what it is peo­ple are think­ing about and what’s on their mind,” says Sul­li­van. “What’s impor­tant to peo­ple work­ing in our hos­pi­tals in Spain or insur­ance com­pa­nies in Hong Kong? What do they think?” Glint enables Bupa’s team man­agers to iden­ti­fy the dri­vers of employ­ee engage­ment and pro­vides advice on how to main­tain or improve them.

Using AI and employee engagement through bots

Oth­er com­pa­nies rely on bots to com­mu­ni­cate with work­ers and col­late their respons­es. Mon­eypen­ny, which man­ages call cen­tres and live chat envi­ron­ments for 21,000 clients in the UK and Unit­ed States, has rolled out the use of bots on Work­place from Face­book to keep in touch with work­ers, iden­ti­fy their issues and com­mu­ni­cate changes.

“For our peo­ple, it helped that true human inter­ac­tion con­tin­ued as we embraced this new nor­mal, recre­at­ing those water-cool­er moments, which are the life­line for a peo­ple-focused busi­ness like ours,” says Joan­na Swash, Moneypenny’s chief exec­u­tive. “We have used it proac­tive­ly to dis­trib­ute pos­i­tive and uplift­ing news and mes­sages.

“We try to not impose too many top-down ini­tia­tives, but use Work­place as a tool to get feed­back and ask ques­tions about how the man­age­ment teams can bet­ter sup­port front­line staff.”

And this is the con­cern, that the shift to AI and employ­ee engage­ment could back­fire as already stressed work­ers begin to wor­ry about sup­port turn­ing into sur­veil­lance. Some have expressed con­cerns with the roll­out of what detrac­tors say is “employ­ee sur­veil­lance” soft­ware.

Improving engagement while maintaining trust

Demand for such tools is up 51 per cent since the start of the coro­n­avirus pan­dem­ic, accord­ing to data com­piled by Top10VPN. Search traf­fic for “employ­ee mon­i­tor­ing soft­ware” has risen 65 per cent between March and Sep­tem­ber, while search­es for “work-from-home mon­i­tor­ing tools” are 2,000 per cent high­er than they were pre-pan­dem­ic.

Some com­pa­nies, strug­gling to keep tabs on their employ­ees and wor­ry­ing about a decline in pro­duc­tiv­i­ty as the pan­dem­ic bites, are chang­ing their approach to using AI and employ­ee engage­ment from one that ben­e­fits employ­ees to ben­e­fit­ing boss­es.

It’s being exac­er­bat­ed by the unprece­dent­ed sit­u­a­tion in which we find our­selves dur­ing the pan­dem­ic and the sheer new­ness of the tech­nol­o­gy. “The speed of change in this space is tru­ly unprece­dent­ed,” says Puica at iamYi­am. “When you have some­thing that changes so fast, the chal­lenge is you’re not catch­ing down­sides or mis­takes fast enough.”

Cau­tion is required and clear think­ing about why you’re rolling out the use of AI. Employ­ees may be dis­com­fit­ed by the immense changes going on in their work­place and need reas­sur­ance and sta­bil­i­ty. “We need to cre­ate a val­ue set that dri­ves poli­cies,” says Puica, before we jump into the unknown.