Design in Business Education: A Square Peg in a Round World? By Thomas Lockwood
Bibliographic record
Abstract
I was pleased to re‐read Tom's 2002 article for two reasons: First, because I am impressed by how spot‐on his assessment was at the time; and second, because it is no longer (completely) true. What a relief! In today's United States, programs such as the Strategic Design MBA at Philadelphia University, as well as the design MBA degrees at the California College of Art in San Francisco, the Institute of Design in Chicago, and MICA/Johns Hopkins in Baltimore are resounding proof of integrative approaches in an MBA context. Design thinking and systems thinking are interwoven into the ways these programs teach leadership, operations, marketing, and finance. Additionally, business schools such as Rotman at the University of Toronto and Darden at the University of Virginia have robust business design studios and design thinking modules. Other traditional MBA programs are at least now offering one course in design thinking, if not integrating it throughout their program; and their students, if not the faculty at large, have formed “innovation clubs”—code for “This is a safe space for creativity and design thinking.” It is no longer the rule that graduate business education draws a deep demarcation between creativity and strategy. That is a false dichotomy and, as Tom wrote, there is a “rising importance of corporate creativity.” Of course, relative to the UK, Europe, and Asia, the democratization of design in business‐school curricula is still novel. But the “gridlock of curriculum tradition” and accreditation metrics that impeded innovation in graduate business education are melting away and becoming more fluid. This is mainly because the gaps that Tom so rightly identified between design practitioners and business managers, and between industry's embrace of design thinking and academia's reluctant gaze, has been bridged by academic upstarts who are responding to the market's demand to “give us more than a SWOT analysis!” Tom concluded that it could take 10 years before business educators embraced the value of design. He was pretty close. Although it is still true that academia lags behind the current of industry, it is encouraging that there are an increasing number of tributaries in business education forging ahead.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".