How predictive analytics could future-proof your supply chain

How much would it cost your busi­ness if your sup­ply chain suf­fered just a sin­gle day of dis­rup­tion? How quick­ly could you iden­ti­fy the cause of the prob­lem and imple­ment the right solu­tion before your sup­ply chain returned to breakeven? And is there a way of pre­dict­ing risk before dis­rup­tion occurs and sav­ing your busi­ness from dam­ag­ing finan­cial loss­es?

Those are the three big ques­tions being asked by busi­ness lead­ers in board­rooms and offices world­wide, who want to future-proof their sup­ply chains from dis­rup­tions at glob­al, region­al and inter­nal lev­el. Glob­al trade issues, nat­ur­al dis­as­ters and cyber­se­cu­ri­ty breach­es are just three of a grow­ing num­ber of threats to sup­ply chains that can and have stunt­ed rev­enue growth and wiped out the prof­its of busi­ness­es big and small, some­times in a mat­ter of hours.

The costs of inac­tion can be fatal. Sup­ply chain issues erode cus­tomer trust, pub­lic per­cep­tion and, even­tu­al­ly, share­hold­er val­ue. The Economist’s Busi­ness Costs of Sup­ply Chain Dis­rup­tion report revealed that two-thirds of par­tic­i­pants suf­fered rev­enue loss­es of between 6% and 20% due to pan­dem­ic-relat­ed dis­rup­tion. McK­in­sey has pre­dict­ed that in as lit­tle as 10 years, dis­rup­tion could cost some com­pa­nies 45% of annu­al prof­its.

Busi­ness­es across almost every indus­try are tak­ing action. They are turn­ing to machine learn­ing to gain vis­i­bil­i­ty beyond tier one and two sup­pli­ers, and use sup­ply chain ana­lyt­ics to pre­dict and nav­i­gate dis­rup­tion weeks, or even months, in advance of crises occur­ring. Many com­pa­nies have already saved mil­lions of pounds in poten­tial loss­es and increased rev­enue by min­imis­ing sup­ply chain costs.

Ever­stream Ana­lyt­ics helps some of the world’s largest com­pa­nies, includ­ing Google, Anheuser-Busch InBev and DuPont, to do just that. Ever­stream cal­cu­lates what it calls ‘the val­ue of a sin­gle day’ to show the true impact of dis­rup­tion to a company’s sup­ply chain. This is the finan­cial cost of just one day of dis­rup­tion and high­lights the val­ue for a busi­ness in invest­ing in ana­lyt­ics to boost sup­ply chain vis­i­bil­i­ty and dis­rup­tion response time.

The gross mar­gin impact of a sin­gle day’s dis­rup­tion at one of Everstream’s cus­tomers was recent­ly cal­cu­lat­ed at almost $275,000 (£228,000). In this instance, just one minor dis­rup­tion trans­lat­ed to a drop in share­hold­er val­ue of more than $6m (£4.9m). This poten­tial loss would also cre­ate non-quan­tifi­able issues, such as sink­ing pub­lic per­cep­tion and con­sumer trust, which would only wors­en if com­peti­tors avoid­ed delays and seized mar­ket share.

Julie Gerde­man, CEO at Ever­stream Ana­lyt­ics, believes this lev­el of detail and insight is now imper­a­tive at C‑suite lev­el. “Sup­ply chain vis­i­bil­i­ty is mis­sion crit­i­cal — exec­u­tives are expect­ed to pro­vide these insights to their CEO and board,” she says. “Man­u­al sup­ply chain risk man­age­ment is cat­a­stroph­ic for some busi­ness­es because they can’t react fast enough. Time and again we’ve seen com­pa­nies fail to meet rev­enue tar­gets because of sup­ply chain issues. The ques­tion is: can you afford not to invest in your sup­ply chain?”

For one of the world’s largest auto­mo­tive man­u­fac­tur­ers, the answer was no. The com­pa­ny part­nered with Ever­stream and set a clear goal: to cre­ate a sys­tem that iden­ti­fied ear­ly risk indi­ca­tors of sup­pli­er dis­tress to save on work­ing cap­i­tal and avoid pro­duc­tion out­ages.
Ever­stream used a com­bi­na­tion of AI and human analy­ses to iden­ti­fy more than 1,000 sub-tier sup­pli­ers so the com­pa­ny could respond at speed to dis­rup­tion before it occurred. The move paid off. Soon after, they were alert­ed to a cyber attack on a sup­pli­er and sourced alu­mini­um from the spot mar­ket ear­li­er than com­peti­tors. The com­pa­ny saved more than €1m (£845,000) by pur­chas­ing before the price of alu­mini­um rose.

Gerde­man says an ana­lyt­i­cal, data-dri­ven approach is giv­ing busi­ness­es the abil­i­ty to be proac­tive, rather than reac­tive, and use sup­ply chains to gain a com­pet­i­tive advan­tage. She says: “Being able to see things well in advance and make deci­sions doesn’t just help to stop dis­rup­tion and build resilien­cy, it also helps to cap­i­talise on oppor­tu­ni­ties ahead of com­peti­tors.”

Ever­stream pro­vides this vis­i­bil­i­ty, as well as pre­dic­tive, and pre­scrip­tive, ana­lyt­ics by har­vest­ing data from a mul­ti­tude of pro­pri­etary sources. The com­pa­ny uses mete­o­rol­o­gists and a 20-year bank of envi­ron­men­tal data to pre­dict future weath­er pat­terns and cli­mate-relat­ed dis­as­ters such as hur­ri­canes, wild­fires and flood­ing to warn cus­tomers to change course. A pro­pri­etary rela­tion­ship with DHL and its half a mil­lion work­ers around the world pro­vides valu­able, real-time logis­tics data. It also pulls togeth­er pro­pri­etary and pub­lic data from ports to mon­i­tor poten­tial ship­ping days.

But with moun­tains of data to sift through, select­ing the right data is cru­cial. A truck man­u­fac­tur­er may need bet­ter sup­ply-chain vis­i­bil­i­ty and trans­paren­cy on logis­tics flows, right down to com­po­nent lev­el (for exam­ple axles and tyres), and a detailed view of high-risk glob­al events (strikes, weath­er alerts) that could impact their pro­duc­tion sites or glob­al sup­pli­er base. In con­trast, a cot­ton man­u­fac­tur­er may require his­tor­i­cal and pre­dic­tive tem­per­a­ture data to pre­dict weath­er pat­terns that could affect farm­ing or help them to save mon­ey on tem­per­a­ture sen­si­tive freight costs to avoid spoilage dur­ing trans­porta­tion.

The Ever­stream plat­form is able to make sense of all this data and tell clients clear­ly what it means for their oper­a­tions and advise on how best to respond. “It’s about pro­vid­ing insights, not just more data,” says Gerde­man. “There is no short­age of data, but that can cre­ate a lot of noise and con­fu­sion for busi­ness­es. Every busi­ness requires dif­fer­ent types of data to achieve dif­fer­ent goals, so rel­e­vance and qual­i­ty is key.”

These pre­dic­tive insights are giv­ing busi­ness­es the tools to map out sup­ply chains of the future and pro­tect rev­enue and prof­its. Water short­ages have prompt­ed com­pa­nies that rely on access to water pro­duc­tion to use Everstream’s cli­mate data to con­sid­er where best to build man­u­fac­tur­ing facil­i­ties. They’re also help­ing to inform sus­tain­abil­i­ty deci­sions and give com­pa­nies the vis­i­bil­i­ty to part­ner with eth­i­cal sup­pli­ers.

Those busi­ness­es that don’t tap into the pow­er of ana­lyt­ics could face a test­ing future as sup­ply chains come under increas­ing pres­sure in the months and years ahead.

For more infor­ma­tion please vis­it everstream.ai

Pro­mot­ed by Ever­stream