6  EXAMPLE: Strategic Loop Team Proposal

Note, this is just a sample and does not reflect the operations managment area’s final Strategic Loop Team Proposal (i.e. white paper).

6.1 Aspirational Strategic Statement - Operations & Decision Analytics area (formerly Operations Management)

In five years, UD will be home to a regionally-renowned industry-aligned analytics community which is:

  • focused on innovation and education in prescriptive modelling and associated analytic tools used to improve operations and decisions,
  • offers an easily discovered, attractive, and early-immersion major - Operations and Decision Analytics - to Lerner college applicants, freshmen, and sophomores, graduating 90 students per year, and offering courses that make FSAN, MBA, and BAIM graduate degrees more valuable to students, and
  • deploys student and faculty talent to deliver value to organizations both in Delaware and regionally along the DC to NYC I-95 corridor.

6.2 Three Key Ideas to Proposed Strategy

Three strategic ideas have emerged as part of our loop team’s proposal:

  1. Rebrand area and major to Operations & Decision Analytics.
  2. Facilitate earlier major immersion via easier discovery of major, simplified messaging, adjusted curriculum sequencing, and less time-consuming intro courses.
  3. Align with industry by facilitating regionally-renowned industry-aligned analytics community that deploys student and faculty talent to deliver value.

These ideas are elaborated below.

6.2.1 Rebranding to Operations & Decision Analytics

While operations management is an important part of any business, the area’s collective passion and research has become much more analytics-focused, echoing the larger societal role analytics is playing in more recent years. Hence, as opposed to pursuing strategic focus around traditional operations management activities like supply chains, inventory management, or lean management systems, the area is moving in a potentially more future-proof analytics direction.

The rebranding and choice of name to Operations & Decision Analytics is notable for three reasons:

  1. Easily understood: Prospective, incoming, and new students require extensive education just to understand what operations management is. Analytics is a much more familiar term conveying the notion of using data and computational tools. So then, applying data analysis and tools to decisions and operations seems much easier to comprehend.
  2. Synergistic with Business Analytics and MIS Faculty: The focus allows greater exploration of joint efforts with MIS, allowing all of us to coordinate and better serve our student body with larger representation for our analytics offerings.
  3. Conveys Scope: Our area, in contrast to the MIS-area’s offerings in analytics, is very focused on prescriptive analytics that uses mathematical modelling to advocate for one action or set of actions over other possiblities. In contrast, the analytics MIS-faculty have focused more on data-driven and machine learning techniques associated with exploratory, predictive, and prescriptive analytics. Together, the two departments provide the complete scope of an analytics education, both modelling-based and data-driven.

6.2.2 Facilitating Earlier Major Immersion

Over 30% of our Lerner students enter as business undeclared and historically our major is a discovery major - not differentiated or understood enough to attract high school students to the major at the time of enrollment. Being such, it makes sense to move introductory courses to freshman or sophomore year to facilitate discovery. Two key ideas emerge for quicker discovery:

  1. Move intro course to freshman or sophomore year: This is self-evident why this would help with earlier discovery of the major.
  2. Team teach intro courses: In a 15-credit semester, students maybe have room for one or two introductory business courses that expose them to more depth than BUAD110. Now imagine we halve the content of the introductory courses, then in a single semester, a student can be exposed to 7-weeks of content from two to four introductory courses. This should be enough content to see if they might want to major in the topic and also be exposed to the fundamentals should they choose a different path. Its a win-win for faculty and students. Imagine MIS and OM faculty team teaching two sections of an “Intro to OM and MIS” course. The OM faculty might get the first 7 weeks of the semester and the MIS faculty the last 7-weeks. Each faculty member would then complete a 1-course teaching requirement in 7 weeks (because they teach 2 sections).

The intent of these changes, i.e. introductions to major courses being only 7-weeks of content, has a nice cascading effect. Intro courses being taken during freshman/sophomore years leads to earlier decisions about majors, leading to earlier major immersion, leading to major-specific courses being completed in time for post-junior year internships, leading to better workforce placements. In addition, it frees up capacity for students to delve deeper into their majors of interest and minimizes disengagement of students in the classroom during those latter weeks of an intro course they deem less relevant to their career aspirations.

6.3 Align With Industry

Our faculty and students shine best when exposed to and challenged by real-world problems whose solutions add value to the world. Our innovators should be pushing the knowledge frontier and our students competent and challenged solving real-world problems.

Our group will actively seek-out collaborative and paid research opportunities, government grants, and donor funding to strengthen UD’s ties to industry/government in regards to applying prescriptive analytics to real-world challenges. This might possibly be done in conjunction with UD’s Data Science Institute, the Institute of Financial Services Analytics, and/or other units within Lerner.

Since student job placement and ongoing career-success is the most important criteria of our largest funding source, it makes sense to target our efforts at the regional companies who might hire our students and for whom our students have geographical preference; typically this means offices are along the DC to NYC I-95 corridor. Faculty engagement with these organizations is also strengthened by the geographical proximity.

6.4 Flywheel Potential, Economic Viability, and Passion

6.4.1 Flywheel Potential

6.4.1.1 Inclusive Communities

The above strategic ideas center around developing/strengthening a community of analytics students, faculty, and industry professionals. To stress an even more inclusive community we will try to partner with regional colleges/universities with special efforts for outreach and coordinated efforts with historically black colleges like Delaware State and Lincoln University. This community is where industry and academia mix to get the right minds working on the most relevant issues.

6.4.1.2 Business and Societal Impact

Impact will come from these avenues:

  • Competent and value-creating students being placed in jobs where they will succeed and shine.
  • Diverse communities of analytics professionals, academics, and students will gather and find community through Lerner-affiliation.
  • Faculty will work on real-world relevant problems to do inspired innovation and idea dissemination through publications, seminars, open-source software, and other relevant avenues for diffusing UD-orignated innovations.
  • A well-funded community fueled by like-minded donors and grants.

6.4.1.3 Pioneering Scholarship

Our scholarship will be real-world inspired, ensuring the relevance and impact of faculty work. Research output will be reflected in top UTD24 journals and inspired by our analytics community. Innovation diffusion through other less traditional sources will also be encouraged and this might include software packages, YouTube videos, paid workshops, etc.

6.4.1.4 Inspirational Education

Faculty engaging with industry and pursuing innovations where their passions lie will be inspiring in the classroom. Opportunities for student-exposure to real-world problems will add meaning to classrom experiences. Competence-based assessment, maybe using specification-based grading, will be used to hold our students accountable for improving their abilities. A single bad student placed in a strategic industry partner is capable fo ruining a relationship; ceasing future recruiting of our students. As faculty, we promise to be inspiring, challenging, fair, and to teach real-world relevant skillsets. We also promise to ensure student competence so that if they graduate with our major, employers know they are getting an impressive employee who knows how to add value using analytics.

6.4.2 Economic Viability

Since undergraduate enrollment is zero-sum to the University, our best avenues for growth seem to be in Master’s programs, donations, and grants. Our community will actively seek more donations/grants and work hard to contribute enrollment-increasing courses across all analytics-related Master’s degrees.

6.4.3 Passion

The area has only included content in this proposal that we are truly excited to help facilitate. While areas like supply chain are potentially attractive, our hearts are now mostly captured by the analytics and data science areas.

6.5 Limitations

This proposal only represents the brain power of a potentially biased subset of Ops Managment people - it is just a strawman draft right now for our team. It also feels like we should put more thought into AI.