Maufacturig White Paper See through the Supply Chai: Ehace Visibility ad Reduce Risk
About the Authors Sharad Jadhav Sharad Jadhav is a Lead Cosultat for the supply chai domai. He is a part of the Iovatio ad Trasformatio Group of the Maufacturig busiess uit at Tata Cosultacy Services (TCS). Sharad has over 15 years of experiece i various supply chai busiess fuctios across idustries such as maufacturig, retail, telecom, ad oil ad gas. These iclude sales, marketig, distributio, procuremet, product cofiguratio, ivetory maagemet, logistics, ad CRM. He has bee with TCS for over three years, servig i various capacities such as Strategy Cosultat, Advisory Cosultat, Project ad Program Maager, Domai Cosultat, ad Pre-sales Cosultat. Praav Pedse Praav Pedse is a Busiess Aalyst with the Iovatio ad Trasformatio Group withi the Maufacturig busiess uit at TCS. He has over five years of experiece across busiess fuctios such as demad forecastig, sales ad marketig, distributio maagemet, ad cosultig i the IT, telecom, ad maufacturig idustries. Praav has hadled multiple roles i the maufacturig domai spaig busiess process mappig, busiess aalysis, ad pre-sales. He has also led a variety of supply chai projects from material requiremets plaig (MRP) to productio plaig, ivetory maagemet, ad supplier paymets. Praav is a Six Sigma Gree Belt certified cosultat.
Abstract Global expasio, shrikig product lifecycles, costatly evolvig customer expectatios, ad the rise of multi-chael commerce are compellig maufacturig orgaizatios to build more agile ad resposive supply chais. Supply chai visibility is provig to be a importat focus area that couters the risks associated with ucertaity ad volatile atural, ecoomic, ad busiess coditios. It also supports a orgaizatio s growth plas, icreases profitability, ad improves operatioal efficiecies. I this paper, we discuss the key elemets of supply chai visibility ad how they should be ehaced through techologies such as social media, Big Data, aalytics, ad geospatial iformatio systems. From gaiig cotrol across the supply chai etwork to capacity plaig ad demad forecastig, improvig supply chai visibility proves beeficial for the top lie as well as the bottom lie.
Cotets Uderstadig supply chai risk 5 Improvig visibility across the supply chai 6 Gai cotrol over the etwork 7 Improved i-trasit visibility for a global auto OEM 8 Track ad maage supplier capacity 9 Be prepared for demad variability 11 Leverage techology to build a resposive supply chai 12 Improvig supply chai operatios through greater visibility 13 More visibility, more power 14
Uderstadig supply chai risk I a study coducted by the America Productivity ad Quality Ceter (APQC) i 2013, 83 per cet of orgaizatios surveyed were caught off guard by a uexpected supply chai disruptio over the last 24 moths.¹ A report by the World Ecoomic Forum o supply chai ad trasportatio states that atural disasters cotribute heavily to supply chai disruptios, ad costitute 59 percet of disruptios attributed to evirometal factors.² The 2010 earthquake i Japa, for istace, placed immese pressure o the supply chais of compaies such as Toyota. It also opeed up broader questios aroud upredictable supply chai risks. While atural calamities ad their impact o the supply chai have bee receivig a lot of attetio, orgaizatios caot afford to igore everyday realities. Day-to-day operatioal risks such as customs clearace ad delayed shipmets from suppliers also pose major challeges to a orgaizatio s supply chai. Large orgaizatios are expadig operatios across the globe with a wide supplier, productio, ad distributio etwork. Accordig to the APQC survey, i the last five years, 74 per cet of orgaizatios have egaged suppliers located i low cost coutries. Material supply from these locatios takes betwee 24 to 48 hours ad up to 60 days of lead time i case of air ocea shippig respectively. This meas that Origial Equipmet Maufacturers (OEMs) eed to store up to 60 days of ivetory for parts sourced from low-cost coutries, which impacts cash flow ad icreases the risk of ivetory obsolescece. Similar challeges may crop up i distributio. With risig customer expectatios ad icreased competitio, the cost of lost sales has icreased sigificatly. Customers are more coscious ad better iformed about product value ad quality as well as after-sales services. With the emergece of omichael retail ad its gradual adoptio by maufacturers, flexible supply chais are required for faster ad more predictable delivery. It is therefore importat to uderstad all the critical supply chai elemets that have both fiacial ad operatioal implicatios. The key questio is: how ca orgaizatios gai visibility across the supply chai, predict potetial risks, ad effectively reduce ad maage disruptios to avoid lost sales ad reveue? [1] APQC, Supply Chai Disruptios What Your Orgaizatio Should Kow About Maagig Risk i Supply Chai, Jue 2013. http://www.apqc.org/kowledge-base/documets/supply-chai-disruptio-what-your-orgaizatio-should-kow-about-maagig-r [2] World Ecoomic Forum, New Models for Addressig Supply Chai ad Trasport Risk, 2012. http://www.weforum.org/issues/supply-chai-risk 5
Improvig visibility across the supply chai Most orgaizatios today have a multi-tiered supply chai that is highly complex. Cosequetly, the risks of disruptio are higher. Visibility is therefore critical for a more agile ad resposive supply chai. Based o our cosultig egagemets with Fortue 500 maufacturers ad our iteractios with leadig idustry aalysts, we recommed the Supply Chai Visibility Framework depicted i Figure 1. The eight elemets are key to improvig visibility across the value chai. Visibility Elemets: Overall Risks ad Opportuities i Delivery Timelie iboud & outboud Logistics** Quality Material Ivetory / Capacity Fiacial Suppliers Demad Customer Chaels OEM Tier 1 Dealer SCM New Product Itroductio Tier 2 Source Make Deliver* Sales /Marketig Service Plaig Customer Distributor Tier Outsourcig Parters Demad Visibility Supply Visibility Goverace, Risk ad Evet Maagemet Figure 1: Key elemets for gaiig visibility across the supply chai By focusig o these elemets, orgaizatios ca idetify, aalyze, ad maage supply chai risks associated with each of them, as idicated i Table 1. Supply chai elemet Risks Timelies Quality Network Delays i lauch of ew products Delays i delivery of products ad sub-assemblies to plats Delays i delivery to customers Effect o brad image Chages to warraty policies Cost of poor quality due to rework, premium freight, ad other additioal costs Lost sales Distributio: lack of visibility ito trasportatio, precludig dyamic re-routig, ad warehousig challeges, prevetig accurate estimatio of lead times Table 1: Key Elemets of Supply Chai Visibility 6
Supply chai elemet Material/Ivetory Capacity Risks Ivetory obsolescece Iefficiet capacity utilizatio across productio plats ad suppliers Iaccuracy i forecastig the volume of busiess Fiacial Demad Customer Isufficiet et workig capital Poor product margis ad profitability Lack of fiacial stability amog suppliers Iaccurate forecasts Lack of aligmet with market treds Reduced customer satisfactio Erosio of brad loyalty Table 1: Key Elemets of Supply Chai Visibility Accordig to IDC, supply chais of maufacturig orgaizatios ca be broadly categorized ito asset, brad, egieerig, ad techology-orieted supply chais.³ The sigificace of a elemet of visibility varies depedig o the ature of the supply chai. I the followig sectios, we take a closer look at how orgaizatios ca leverage techology to ehace visibility ito the etwork, capacity, ad demad, ad thereby mitigate supply chai risks. Gai cotrol over the etwork Improved i-trasit visibility for a global auto OEM A large, global automotive OEM wated to reduce lead time variability ad reduce supply chai risk. The compay implemeted advaced alerts for potetial disruptios with geographic visualizatio for each shipmet, ad the capability of dyamic re-routig aalysis ad executio. Dyamic modelig of estimated time of arrival (ETA) eabled easy compariso of actual to expected delivery performace. As a result, the compay gaied systematic risk idetificatio ad mitigatio capabilities. All of this eabled the OEM to improve overall equipmet effectiveess ad avoid lost sales. Plaig ad executig the movemet of materials throughout the etwork is a essetial compoet of supply chai maagemet. This meas havig complete cotrol of material movemets ad receivig proactive risk alerts to esure timely delivery at the right place ad cost. Spreadsheets ad databases are givig way to geospatial iformatio systems (GIS) that are used for real-time visualizatio of the supply chai. GIS helps uderstad the risks political, evirometal, related to traffic, or other risks associated with a specific locatio ad assess the impact of geopolitical evets o the supply chai. Whe combied with mappig tools ad overlaid data, such iformatio ca help orgaizatios make better operatioal [3] Supply Chai Digest, IDC s Maufacturig Isights Supply Chai Predictios, February 2010. http://www.scdigest.com/assets/ewsviews/10-02-16-1.pdf 7
decisios, such as o routig, i real time. It ca also be used to aalyze the impact of evets o shipmets ad defie a proactive correctio pla. GIS based solutios, such as those from the Evirometal Systems Research Istitute, Ic. (Esri), are also itegratig real-time evet alerts from differet websites, eablig RSS feeds withi the logistics etwork.⁴ Figure 2 shows how GIS ca be used to improve supply chai visibility, while Table 2 has examples of real-time iformatio ad how it ca be obtaied. Logistics Plaig ad Operatios team Solutios Key Fuctioality USERS - Specialist, AM, Maager, GM View Locate Routig Alerts Web GIS Applicatio Aalysis GIS Services Reports Query GIS Applicatio Server Geocodig Service Geoprocessig Service Routig Service Map Service Locator Service Third Party Iteret Web Services rvices Legeds eb Se me W Cosu GIS Data Supplier Locatio Locatios Boudaries Routes Iterface GIS Database Server Supplier Database LDAP Server Mail Server Figure 2: Leveragig GIS for supply chai visibility 8 [4] Esri, ArcGIS Eables Real-Time GIS, 2013, http://www.esri.com/esri-ews/arcews/sprig13articles/arcgis-eables-real-time-gis
Data Category Suggested Source World maps, geo feces (boudaries) ad address data (such as street ames, desigator) Esri, http://www.esri.com/software/arcgis/arcgisolie Traffic iformatio Esri, http://resources.arcgis.com/e/help/mai/10.2/idex.html#//0047000001v5000000 U.S. Geological Survey, Earthquake Hazards Program, http://earthquake.usgs.gov Natural disasters ArcGIS, http://www.arcgis.com/home/search.html?q=oaa&t=cotet, http://www.arcgis.com/home/search.html?q=fire&t=cotet Crimial icidets ArcGIS, http://www.arcgis.com/home/search.html?q=crime%20compariso&t=cotet UN, http://www.u.org/depts/cartographic/eglish/htmai.htm Political situatios Maplecroft, http://maplecroft.com/themes/pr/ Table 2: Sample Sources of Big Data Track ad maage supplier capacity With orgaizatios scalig operatios across the globe at a rapid pace ad demad becomig highly volatile, gaiig visibility ito supplier capacity is critical to prevet market share loss. Buildig strog relatioships with suppliers will ot oly help orgaizatios keep up with growth plas but also miimize ay possible disruptios. For istace, let s cosider automotive OEMs who have multiple tiers of suppliers. It is primarily the OEM s resposibility to track the Tier-1 supplier s cotracted capacity. To this ed, may OEMs have to collaborate ad commuicate closely with Tier-1 suppliers. Followig the three-step process i Figure 3 will help i creatig capacity visibility across suppliers. Defie supplier capacity by part, plat, supplier, combiatio. Track supplier capacity based o supplier release iformatio. Defie ad Track Simulate ad Aalyze Simulate the Tier 1 supplier s capacity by chagig demad. Aalyze supplier resposes to demad chages. Aalyze exteral risks associated with suppliers, e.g., Tier II supplier capacity ad other related data elemets. Determie ad implemet corrective actio pla to cotrol, maage, ad mitigate the aticipated risks. Cotrol, Maage ad Mitigate Figure 3: Three-step process to improvig suppler capacity visibility 9
Step 1: Defie ad track The OEM ca defie supplier capacity through a database that captures the supplier s cotracted capacity for each part that is supposed to be produced ad delivered. Table 3 presets sample data for a OEM s supplier capacity database. Part Category Part Plat Supplier Capacity / Week Productio P001 1000 Service P001 500 Prototype PS01 10 Table 3: Sample Supplier Capacity Data i Step 1 Sice tier 1 suppliers are strategic to their success, OEMs typically provide them visibility ito demad for the ext 24 moths. So, based o the capacity database ad demad release, orgaizatios ca track capacity o a weekly basis through a supplier collaboratio platform. The same capacity database ca be used to track supplier capacity through the supply chai lifecycle ad predict supply chai risks associated with supplier capacity. This is depicted i Tables 4 ad 5. Part Category Part Plat Supplier Cotracted Capacity Week 1 Remarks Demad Release Supplier Respose Productio P001 1000 1000 1000 OK Service P001 500 200 100 Bakig Prototype Ps01 10 7 7 OK Table 4: Sample Supplier Capacity Data vs. Demad i Step 1 Step 2: Simulate supplier capacity Simulatio ivolves performig what if aalysis to mitigate the supply risk. It helps uderstad the supplier s respose to chages i demad. Through early idetificatio of the supplier s cotracted capacity, orgaizatios ca take proactive actios to mitigate capacity risk ad esure supply cotiuity. Part Category Part Plat Supplier Cotracted Capacity Week 1 Remarks Demad Release Supplier Respose Productio P001 1000 1200 950 Overtime Service P001 500 200 100 OK Prototype Ps01 10 7 7 OK Table 5: Sample Supplier Capacity Data vs. Demad i Step 2 10
Step 3: Cotrol, maage ad mitigate A actio pla mechaism with collaborative decisio workflow will help maage the predicted supplier capacity risk. The methodology described above requires costat iteractio with suppliers. Its success also depeds o icetivizig suppliers ad providig them a easy-to-use platform to provide the iputs. With suppliers servicig multiple OEMs, it may be difficult for them to log ito the OEM s portal to provide iputs regardig capacity. Social media has the aswer to this challege. Imagie a supplier social etwork through which suppliers get otificatios o their smart devices, thereby facilitatig a istataeous respose. Maufacturers will icreasigly rely o advaced techologies such as Big Data (for example, Hadoop, MapReduce, data warehouse, stream computig, text aalytics egie, master data maagemet) ad secured social media. A secured social media app (depicted i Figure 4) eables ext-geeratio collaboratio to cotrol, maage, ad mitigate risks associated with supplier capacity while esurig data privacy. The data protectio ca actually work both ways. While you eed to be careful about the data you collect from suppliers, this discussio focuses o how to protect your compay s data. Oce privacy settigs are olie, take techical cotrol by utilizig ecryptio. Social Media Home page Corporate Commuities ABC Corporatio Supplier Collaboratio Mail Supplier: 1234: XYZ Corp. Logout Chat Widow Supplier Evets Ibox Outbox Set Trash Figure 4: A Sample Layout of a Secured Social Media Site Be prepared for demad variability Demad variability is a major challege for supply chai maagers ad impacts both the bottom ad top lies. From maagig ivetory levels to improvig customer service, orgaizatios eed to aticipate ad pla for umerous demad ad supply scearios. This is becomig icreasigly challegig give the rapid itroductio of ew products, proliferatio of SKUs, ad the use of specialized retail promotios. Traditioally, orgaizatios would egage their customers i collaborative plaig forecastig ad repleishmet (CPFR) to create a demad forecast. Upo fializatio, the pla gets coverted ito customer orders. Some orgaizatios have a multiyear plaig horizo for sales ad operatios. Various statistical methods are used to project the sales forecast by customer ad product combiatio. Oe of these methods uses the last 12 moths percetage of absorptio by product. However, the questio is: how ca orgaizatios accurately forecast sales by product, market (geography), ad customer? 11
I order to couter demad variability ad icreasig competitio, some orgaizatios have started leveragig social media, Big Data, ad predictive aalytics for better demad plaig ad forecastig. Social media offers iformatio o product ratigs ad reviews, which ca serve as valuable iputs for setimet aalysis. Aalysis of social ad web data reveal demad sigals i real time. Such isights reflect the marketplace opiio ad are useful for demad plaig durig ew product lauches. Reviews ad buyig guides from recogized agecies such as the JD Power Survey ca help i demad forecastig. News ad idustry aalyses are also useful for forecastig. For example, a ews report with the headlie Domestic car sales declie 2.9 percet i Jauary idicates market coditios ad ca help predict what kid of vehicles are more likely to be sold. News reports o competitors the largest auto maker i Idia lauches a ew seda startig at 6.5 lakh are helpful to idetify competitor activities ad pricig. Big Data, i terms of both market ad geopolitical treds ad competitive, operatioal, ad fiacial data ca support a wide variety of sales ad marketig strategies. For example, uderstadig competitors product features ad pricig will help create better promotio campaigs. By combiig Big Data with a predictive aalytics model leveragig market itelligece, social media, Big Data, ad historical sales data, orgaizatios ca icrease forecast accuracy ad demad visibility across the supply chai. Leverage techology to build a resposive supply chai Digital forces such as social media, mobility, ad aalytics have a strog impact o maufacturig value chai ad visibility. This is depicted i Figure 5. Digital Impact Top Forces Customer Experiece Social Media Mobility & Pervasive Social Media Aalytics & Big Data Mobility & Pervasive Aalytics & Big Data Mobility & Pervasive Aalytics & Big Data New Product Itroductio Maufacturig Supply Chai Very low Low Medium High Very High Figure 5: The impact of digital forces o supply chai visibility 12
Table 6 idicates how these techologies help improve supply chai visibility. The techology selectio will deped o the orgaizatio s supply chai category (asset, brad, egieerig, or techology-orieted). Techology Big Data ad social media Examples How it impacts the supply chai Facebook Twitter LikedI Surveys by agecies such as JD Power Product reviews GIS such as ArcGIS Mobility Custom built mobile apps Access to istat iformatio ad approvals for seamless supply chai operatios Radio Frequecy Idetificatio (RFID) Active RFID Passive RFID Gai real-time material visibility i supply chai operatios to avoid productio loss Electroic Data Iterchage (EDI) Direct EDI EDI via VAN EDI via AS2 EDI via FTP, SFTP, FTPS Web EDI Mobile EDI EDI outsourcig Near real-time or real-time material visibility to avoid productio loss ad improve iformatio availability across the supply chai. Data warehouse Qlikview Cogos Busiess Objects Iformatics Used for supply chai operatios reportig, ad predictios based o historic data. Busiess itelligece ad aalytics Uderstad customer eeds for ew product desig Leverage product reviews ad customer opiios for demad plaig Uderstad suppliers' fiacial coditio to avoid supply disruptios Be aware of evirometal threats to aticipate ad mitigate supply chai risk Icrease awareess of geopolitical situatios to predict material cost based o raw material sourcig locatios Table 6: Leveragig techology to improve supply chai visibility Improvig supply chai operatios through greater visibility By ehacig visibility across the supply chai, orgaizatios ca improve supply chai operatios ad overall busiess outcomes. The beefits iclude: Product pull to drive sales: The traditioal supply chai was largely push based. By leveragig sales treds, Big Data ad aalytics orgaizatios ca create a pull-based or demad-drive supply chai. Proactive risk detectio ad mitigatio: With real-time access to the latest iformatio through social media, Big Data, mobility ad aalytics, orgaizatios ca proactively idetify risks across the supply chai. They ca take corrective actios to mitigate or miimize the impact o busiess. Reduced supply chai cost: By ehacig visibility through aalytics, orgaizatios ca reduce ivetory levels ad the associated carryig costs. This also simplifies procuremet decisios such as make versus buy. Better margis: Social media ad setimet aalysis ca help determie the right price for products, to esure both competitiveess ad icreased margis. Icreased et workig capital: Optimal ivetory levels helps cotais costs ad improve margis. This i tur icreases the workig capital. Improved service levels: Better visibility allows orgaizatios to track shipmets i real time ad commit to realistic delivery schedules. 13
Ehaced customer satisfactio: By leveragig iputs from social media, orgaizatios ca desig the right product at the most appropriate price to icrease customer satisfactio. More visibility, more power Ulockig the potetial of digital forces such as social media, Big Data, aalytics, ad GIS will offer orgaizatios ew ad iovative ways to rethik the supply chai. By improvig visibility, these techologies allow maufacturig busiesses to sese market chages ad idetify demad triggers, thereby creatig a more efficiet ad resposive supply chai. By itroducig ew digital capabilities across supply chai operatios ad collaboratig with busiess parters ad customers, orgaizatios ca gai a competitive edge ad effectively mitigate risks to become more profitable. While digital add-os may work i the short-term, we believe the future will require orgaizatios to completely reimagie their supply chais to geerate more value. Material visibility for a global maufacturer Uplaed cost visibility for a large OEM A large egie maufacturer implemeted a solutio to track materials shipped from its Joit Veture to customers. The solutio offered real-time shipmet updates, ad provided capabilities to ackowledge orders ad commuicate with suppliers through electroic data iterchage (EDI), as well as measure the supplier cycle time. As a result, the waitig time ad ivetory holdig cost at customs was reduced. This also improved o-time delivery performace for the maufacturig compay. For a automotive OEM, log lead times, schedule variability, ad egieerig chages due to demad variability led to large uplaed logistics costs through shipmet expeditio, premium freight, ad obsolescece. A aalytics solutio helped the compay idetify these root causes ad achieve orgaizatio-wide visibility o how supply chais decisios impact cost. This helped the auto OEM to improve its sourcig strategy ad optimize the total laded cost. 14
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