Technology needs people for agile supply chains

For many peo­ple, the past 18 months have con­sist­ed of work­ing remote­ly, watch­ing Net­flix and a lot of online shop­ping. Each activ­i­ty is made pos­si­ble through tech­nol­o­gy, which shapes the wider theme of the year: dig­i­tal trans­for­ma­tion. 

Quite fit­ting­ly, Coy­ote Logis­tics pub­lished a report, Sup­ply Chain Automa­tion in a Post-Covid World: how to bal­ance peo­ple & tech­nol­o­gy in logis­tics oper­a­tions. Unsur­pris­ing­ly, it found that Covid-19 sped up the adop­tion of dig­i­tal tech­nolo­gies. 

How­ev­er, it also found that both ship­pers and car­ri­ers relied more on human exper­tise in 2020 than in 2019. In 2019, ship­pers said the ide­al bal­ance between tech­nol­o­gy and peo­ple was 39% and 61% respec­tive­ly, while car­ri­ers said it was 41% and 59%. 

In 2020, that bal­ance had shift­ed to 42% and 58% for ship­pers and 44% and 56% for car­ri­ers.

Although the shift may not seem big, it speaks vol­umes dur­ing a time when dig­i­tal tech­nolo­gies have been pro­pelled for­ward. Clear­ly, the sup­ply chain indus­try still needs peo­ple. 

The report also found that while ship­pers are turn­ing to tech­nol­o­gy, not every aspect of sup­ply chain oper­a­tions can be auto­mat­ed and there are areas where peo­ple excel, or a com­bi­na­tion of both works best. Results showed that the top peo­ple or tech­nol­o­gy and peo­ple tasks for ship­pers are com­mu­ni­cat­ing with cus­tomers and logis­tics part­ners, and build­ing a long-term strat­e­gy. For car­ri­ers it is deal­ing with deliv­ery prob­lems, load sched­ul­ing, and com­mu­ni­cat­ing with part­ners and bro­kers.

Over­all, the report shows that the dis­tri­b­u­tion across peo­ple, tech­nol­o­gy or both, across 16 sup­ply chain tasks is rough­ly even. Such results indi­cate that logis­tics and sup­ply chain lead­ers want both automa­tion and peo­ple, and if sup­ply chains are to suc­ceed, the right bal­ance must be achieved.

People make technology work 

The main issue of an over-reliance on tech­nol­o­gy is that when some­thing goes wrong, peo­ple are need­ed to resolve it. “Man­u­al labour can have its advan­tages when com­pared with a com­plete reliance on tech­nol­o­gy – for exam­ple, if a machine breaks down, a whole sys­tem could go down, result­ing in a big­ger dis­rup­tion,” points out Hon­ey­well pres­i­dent for Cen­tral and East­ern Europe, Ronald Binkof­s­ki.

Full automa­tion doesn’t equal suc­cess and, more times than not, a suc­cess­ful sup­ply chain oper­a­tion com­bines peo­ple and tech­nol­o­gy to best effect. Although tech­nol­o­gy has brought huge ben­e­fits to sup­ply chains, par­tic­u­lar­ly in man­ag­ing dis­rup­tive events, it is the peo­ple involved who play the crit­i­cal role. 

“Tech­nol­o­gy gives essen­tial vis­i­bil­i­ty, but it is the high­ly skilled pro­fes­sion­als under­stand­ing the infor­ma­tion and mak­ing changes that is so valu­able for build­ing resilience,” says DHL sup­ply chain chief cus­tomer offi­cer and strat­e­gy direc­tor Philip Roe. “Data is noth­ing if it can’t be under­stood and applied by peo­ple.”

In an inter­view with man­age­ment con­sul­tant Oliv­er Wyman, asso­ciate pro­fes­sor of oper­a­tions, infor­ma­tion and deci­sions at the Uni­ver­si­ty of Penn­syl­va­nia Lynn Wu point­ed out that where deep learn­ing and machine learn­ing are large­ly pre­dic­tive tech­nolo­gies, they have less abil­i­ty to make causal infer­ences. Such tech­nolo­gies ref­er­ence his­tor­i­cal pat­terns and con­se­quent­ly can­not always dis­tin­guish cau­sa­tion from cor­re­la­tion. 

For exam­ple, Google Trends was good at pre­dict­ing flu out­breaks to start with but over time its search results includ­ed words like ‘bas­ket­ball’, which has noth­ing to do with the flu but also occurs in autumn. “You see lots of that in deci­sion-mak­ing as well. Some­thing seems plau­si­ble, but it’s a spu­ri­ous cor­re­la­tion,” she says.

“In a state of uncer­tain­ty, you need to make sure that A is real­ly caus­ing B, not just that A is cor­re­lat­ed with B,” says Wu. “Human judge­ment will always be involved when you use data to make impor­tant deci­sions.”

Technology helps people work 

At a time when there is a seem­ing­ly nev­er-end­ing list of demands that sup­ply chains need to adhere to, tech­nol­o­gy is imper­a­tive in sup­port­ing work­ers to achieve this. 

“Soft­ware or appli­ca­tions are real­ly built to sup­port employ­ees, mak­ing it eas­i­er to access data, glean insights, make deci­sions and observe out­comes,” says senior direc­tor of prod­uct and mar­ket strat­e­gy at Infor, Chris­tine Barn­hart.

“Deci­sion-mak­ers don’t have time to mine their own data or do detailed analy­sis, but they need their employ­ees to have this access and ensure trust in the results and the insights or rec­om­men­da­tions pro­vid­ed.”

There­fore, it is crit­i­cal that sup­ply chains have the right tools and tech­nol­o­gy. Reduc­ing the amount of time required to car­ry out tedious man­u­al jobs, such as data entry or sift­ing large data sets, frees up peo­ple to focus on more press­ing tasks such as dis­rup­tions or cus­tomer ser­vice.

“The focus isn’t on replac­ing peo­ple with machines but on mov­ing non-val­ue added or cum­ber­some activ­i­ties so that employ­ees and lead­ers can use their time on com­plex and intri­cate deci­sion-mak­ing,” adds Barn­hart. 

Changing times, changing skills 

Pre­vi­ous­ly the indus­try focus was on agili­ty, effi­cien­cy and achiev­ing max­i­mum val­ue at min­i­mum cost. How­ev­er, today’s volatile world has shown that adapt­abil­i­ty and quick think­ing are what dri­ve sup­ply chains. This new way of oper­at­ing sig­nals the need for sup­ply chain lead­ers to adapt and demon­strate new skills.

“To make rapid changes to an organ­i­sa­tion to man­age dis­rup­tion, col­lab­o­ra­tion and com­mu­ni­ca­tion, it is essen­tial to bring peo­ple along with you,” says Roe. “You have to be able to plan in a col­lab­o­ra­tive man­ner with your part­ners, cus­tomers, author­i­ties and maybe even com­peti­tors to get the out­come that you want.”

Like­wise, in the increas­ing­ly data-rich world of sup­ply chain, excep­tion man­age­ment and a deep under­stand­ing of data are key, says Roe. 

As much as tech­nol­o­gy can do for us, it is not what is behind deci­sion-mak­ing dur­ing times of dis­rup­tion – sup­ply chain resilience requires human adapt­abil­i­ty and fore­sight. “Imag­i­na­tion is an incred­i­bly pow­er­ful tool, as not only does it allow you to plan for dis­rup­tive events, but it’s also more like­ly to equip you with the abil­i­ty to work at speed and be adapt­able,” says Roe. 

To cre­ate resilient sup­ply chains, “Lead­ers need to embrace the right tech­nolo­gies for their busi­ness needs and ensure these tech­nolo­gies are seam­less­ly inte­grat­ed across oper­a­tions along­side human employ­ees. A holis­tic strat­e­gy will ensure their busi­ness is as resilient as pos­si­ble to meet demands in 2021 and beyond,” says Binkof­s­ki.