Andrew F. Brimmer College of Business and Information Science TM Andrew F. Brimmer College of Business and Information Science Jack Crumbly, PhD (Tuskegee University)

The Evolution of Structured and Unstructured Data: What’s the Impact on Supply Chain Management? 2

Agenda Introduction Partnership Motivation Example Findings Conclusion 3

Introduction Industries are adapting to innovations and improvements Omnichannel options Social Mobile Local Environment (SoMoLo) Internet of Things (IoT), Internet of Everything (IoE) Supply Chain Visibility Product Tracability 4

Introduction As firms adapt to these innovations, there is a struggle to adapt to increased demand streams. There is a need for candidates with the ability to make decisions with data using data analytics tools. 5

Introduction Data Analytics Environment Structured Data In-Memory Database Unstructured Data Clickstream Data Sentiment Data Geolocation Data Server Log Data Machine and Sensor Data 6

Big Data Partnerships SAP Project Propel Project Dream Initiative between SAP and HBCUs Providing access to SAP tools and training to initiate implementation of SAP Tools to curriculum Data from public domain SAP providing data to academic partners to provide opportunities for academics and students to gain access to tools and experience with data based decisions Presidential Candidates, additional data sources SAP Lumira and SAP Predictive Analysis 7

Big Data Partnerships Tuskegee University Big Data projects Introducing data analytics to all Sophomores business majors Students are given data or collaborate with a campus organization (example campus hotel and conference center) to develop decision using SAP Lumira or SAP Predictive analytics Areas of focus Predictive Model Cluster (SAP Predictive Analytics) Linear Regression (SAP Predictive Analytics) 8

Big Data Partnerships Tuskegee University Big Data projects continued Students are introduced to data analytics tools for use in business statistics course taken in the sophomore and junior year Discussing with statistics professors using SAP data analytics tools Current data analysis tools used Minitab Issues with renewal of license (Minitab) Administration encouraging statistics faculty to utilize SAP tools IBM interested in collaboration (IBM Watson Analytics) 9

Big Data Partnerships Marketing statistics opportunities using organizations recruiting candidates Large CPG organization visited Business Analytics course Discussed opportunities in the area of data analytics and data science Discussed data analytics project using open source tools (SAP, Python, R, etc) Professor Collaborate with organizations and educators Recruiting high performing students to work develop data analytics/data science projects Discussing opportunities to learn skills(R, Python and Hadoop) 10

Big Data Partnerships Hack Oregon (www.hackoregon.org) Assists Tuskegee University with data sciences initiatives Collaborate with local and state organizations Extract, Transform and Load data into open environment Provide novice, junior and senior talent with developing data science and analytics solutions using R, Scala, Python through Hadoop environment Provides Tuskegee University students with opportunities to descriptive, predictive and prescriptive methods to solve problems using data science tools 11

Next Steps Continued Collaboration with big data partners Development of Hack Tuskegee Collaboration with state and local organizations Develop parallel projects with Hack Oregon team Invite interested candidates to develop projects Knowledge based view predicts that information and learning will lead to competitive advantage. Perhaps that advantage could be Porter’s Product [Service] Innovation. Interfirm relationship theory suggests that relationships can provide special advantages such as information and rewards. Alternatively social capital theory offers differing predictions. Tight linkages versus loose linkages, structural holes. The Creativity Process model identifies important inputs such as domain specific knowledge, creative methods, and motivation that could originate in either organization, but need to wind up together for the creative process. The NSD literature brings these theories together by stressing process and relational inputs. Cannon, Joseph P. and William D. Perreault Jr. (1999), “Buyer-Seller Relationships in Business Markets,” Journal of Marketing Research, 36, November, pp. 439-460. Dwyer, F. Robert, Schurr, Paul, H., Oh, Sejo, “Developing Buyer-Seller Relationships,” Journal of Marketing, Vol. 51, No. 2, pp. 11-27. Cooper, Martha, Gardner, John, T., (1993), “Good Business Relationships: More Than Just Partnerships or Strategic Alliances?” International Journal of Physical Distribution and Logistics Management, Vol. 23, 6, pp 14-26.

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