cscmp 2014 :exploring scm big data cscmp
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- 1. Understanding the What, How andWhy of Big Data in Supply ChainRelationships:A Structure, Process, andPerformance StudyUniversity of AlabamaRobert Glenn Richey, Ph.D.Tyler R. Morgan, Ph.D. CandidateMississippi State UniversityFrank G. Adams, Ph.D.
2. Defining Big Data The world seems abuzz with the discussion of theimportance of Big Data. Big Data is defined according to the three aspects thatdifferentiate it from other analytics: the volume ofinformation produced, the velocity at which it is created andthe variety of forms it takes (McAfee and Brynjolfsson 2012). Confusion exists over other potential dimensions - Variabilityor Complexity or Veracity or . Big data has been suggested to be useful in targetingcustomer needs, eliminating service created waste,improving forecasting, economizing reverse logistics,improving partnering, etc. (McAfee and Brynjolfsson 2012).There is no common definition!1 of 20 3. Research Questions What the state of the art is in Supply Chain Big Data? Where managers should look for specific types of data? What data sources & technologies support specific types ofperformance? How are Big Data relationships governed? What level of safeguarding/transparency is being used and issuggested for Big Data laden relationships. How do partnerships perform better through Big Data; can a BigData culture be created? How do global needs and implications of Big Data partnering differacross different parts of the world.2 of 20 4. Method Processes-oriented approach: We have a substantial basison what Big Data is, but avoided forced definitions. A qualitative multiple case study approach with +8 (31)cases (Eisenhardt, 1989; Eisenhardt & Graebner, 2007; Yin,2009) Purposeful selection - CSCMP Organizations andNominations Validity from multiple sources: multiple levels of company,multiple industries, and documentation audit trail Emergent and iterative 4 person coding and categorizing,refining constructs from the literature, to identify patterns,but sensitive to context of the firms (Welch et al, 2011)3 of 20 5. Going Native: A Qualitative Approach 6. Sample: n=31/ N=6Country Sample Size SC ClassificationChina 3 ManufacturingGermany 6 3PL/4PL/ConsultingSupplier/DistributorManufacturingTransportationIndia 3 ManufacturingSouth Korea 3 3PL/4PL/ConsultingRetailingTurkey 3 ManufacturingRetailingUSA 11 ManufacturingRetailingBrazil 1 ManufacturingSouth Africa 1 3PL/4PL/Consulting5 of 20 7. Results: WorldwideQuote of the Country (QoC):So how do you define big data?Opportunities: More effective forecasting More effective production planning Cost reduction (logistics)Obstacles Finding Meaningful Data Finding People (Scientists) Fear of Risk and Regulation Finding Storage Partner Transparency National Culture6 of 20 8. Results: USA (n = 11)QoC: so, I don't see this going away in the next 5 to 10 years.I actually see it growing, and I see people who have the skillset and have that knowledge, and who can bring some ofthese answers to the table, I see that as a competitiveadvantage for a company who can figure that out"Opportunity Searching for competitive advantage Sharing of data for improvementObstaclesIf each party uses a differentsystem to collect andprocess the Big Data, it willbe redundant and wasteful. Resistance to new technology Protecting information Finding central and sizable storage Effective presentation and communication Cross functional inflexibility Not forward looking/Speed to irrelevance7 of 20 9. Results: Germany (n=6)QoCBig data does not create innovation, that comes from littledataOpportunity Little data improvements Measurement precision Expat facilitation Customer focusObstacles National culture and communication Time and time zones Ease of access/safeguarding One version of the truth System integration Competitive risk of sharing dataIs there one version of thetruth? I think there is no bigend to this story. So, I thinkthe challenge is to makesure that we limit thenumber of systems in ourlandscape to be sure thatwe have quality ofinformation.8 of 20 10. Results: Turkey (n=3)QoC: Dont even think about sharing consumer data withanyone, thats crazy!Opportunities Technology based decision making (less guessing) Process improvement Delivery, reverse logistics, barcode use In company system integrationObstacles Partner fit, Trust and disclosure Sharing with outsourced SBU No road map Top management understandingHaving Big Data andrevealing hidden patternsis so important if you wantto offer customized,personalized service andthis creates an edge overthe competitors."9 of 20 11. Results: China (n=3)QoC:Market data yes, but Big Data, why???Opportunities Single systems Retail level forecasting Incremental innovation Logistics cost reductionObstacles" I think with the Big Data, we will have theopportunity to create something innovative,not necessarily new generation intechnology, you know, but in better ways toforecasting, to physically distribute ourproducts, to redesign the working terms ofdistribution. Things like that will also bepossible. Labor costs trump technological investment Weak collaboration National culture issue: risk and boundaries (we wont tell you what we dont share)10 of 20 12. Results: India (n=3)QoC: The sources can be anything that comes in, yourcustomer touch points, your business touch points, how yourindustry data has a factor in your older customer [data], yourolder business [data], your software.Opportunity Procurement forecasting New product/service development Trend managementObstacles How to pull and use flexibly Level of understanding across firm(s) Fine grained vs. usefulness Long-term data managementObstacle, the primeobstacle that we faceis the level ofunderstanding of thevarious people who arecapturing the data.11 of 20 13. Results: S. Korea (n=3)QoC: using the quantitative data that have objective validitywill help partners make a more informed decisionOpportunities Risk reduction Informed decision making Data refinement Overstock reductionObstacles Dirty data Lack of data scientists What is the ROI? Privacy laws HR and Systems"With Big Data, we willbe able to clarifyconsumers every needand their attribute andeventually make themspend more money.12 of 20 14. Results: Single RespondentsSouth AfricaOpportunities Quicker upstream data into assessment ResponsivenessObstacles Big Bully Misaligned readinessBig Data is the data that gets generated by those systems that areimplemented, that I just described. Really, it's more about running thosesystems, like the modern ERP or warehousing system or distributionsystems. So, as you generate data, it happens merely by existing andrunning the operations that way....It's a by-product of what you normallydo.13 of 20 15. Results: Single RespondentsBrazilOpportunities Reduced cost of design InspirationObstacles Creative laziness Strategic blindnessUsing a lot of Big Data, as a matter of design, can create a littlebit of blindness on being creative and follow the trend or creatingsomething that it's not, like from scratch. On the other hand, theuse of Big Data for production skills or machinery is amazing...14 of 20 16. TakeawaysA practical definition and understanding of big data does notexist internationally (period). I would say that it is a large amount of data that has to be analyzed.The sources can be anything that comes in USA, Engineering Data that contain a wide variety. Everyone needs their owndefinition of big data in order to use big data in a productive way.South Korea, Automotive Research Institute the material compared to the limits. These are the informationthat we should get together and talk about. Germany, IndustrialConsulting15 of 20 17. TakeawaysSharing of data exists somewhere between operationalminimums and not at all. This is dependent upon the company,relationship, and country. what we see is that the big bully keeps all or most ofthe benefits for himself South Africa, IndustrialConsulting financial information is not available for everybody inthe organization, for examplethere are different levelsof authorization. Germany, Retail Distribution For our company, we do not share Big Data with ourcustomer. China, Electronics16 of 20 18. TakeawaysOpportunities currently seem focused on process improvementand logistical cost reduction with a future hope of finding astrategic use. Who is not only making the most money, but is sticking to theircontractual obligations? USA, Healthcare we do go and look at history and pull that out and try to determinewhat to anticipate and where the future is going to come from.Especially, in things like what things are costing. South Africa,Logistics Consulting number 1, for each of the systems and to make sure that we havethe right capabilities to make the individual system work moreefficiently. Number 2 is truly to integrate all the systems to the othersthat we have, so we can make better use of the data availableChina, Manufacutring17 of 20 19. TakeawaysTremendous obstacles exist within companies, countries andacross countries. Companies need help! Before we can start using some of the elements of [Big Data], youneed to have other things in your own company in place first.Germany, Consumer Packaged Goods we need a combination of all of the information ... so it's stressedgetting all that data. It is a challenge to get all of it, By far, the trustin getting the data is the biggest thing. USA, Agricultural Products we send the data as it is in English from here to Korea thetranslated data is sometimes not perfectly understood by Koreanreaders. Also, the time difference in these countries is an obstacle.USA, Automotive Manufacturing19 of 20 20. Future WorkWhat do you need to know? Relationship Governance: type, trust, commitment, andopportunism Knowledge/information sharing and safeguarding Risk, Privacy and Law HR and TMTs Transparency National Differences/Cultural Differences Performance: Logistics, ROI, Mark