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Record W336210447

Change: Embrace It, Don't Deny It: Tools and Techniques Inspired by Software Development Can Introduce the Flexibility Needed to Make Changes during Product Development with Minimal Disruption

2008· article· en· W336210447 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueResearch-Technology Management · 2008
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Techniques and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsNew product developmentDilemmaMarketingPaceCompetitor analysisProduct (mathematics)Flexibility (engineering)BusinessMarket shareComputer scienceTelecommunicationsEconomicsManagement
DOInot available

Abstract

fetched live from OpenAlex

Change from plans during a new-product development project is a topic that increasingly places developers and their managers in a dilemma. On the one hand, change is becoming increasingly commonplace. Customers, who are presented with more and more options today and can turn to the Internet for competitive product information, change their minds more frequently and are more insistent on being satisfied. Such changes by customers put pressure on development programs to make changes accordingly. In addition, markets shift more often and abruptly as the competitive arena becomes more turbulent and complex. For example, as globalization flattens the Earth, competitors appear from unexpected places, and they often bring with them new, disruptive business models. For example, Huawei appeared from nowhere in China to become a major threat to telecommunications equipment giants such as Cisco and Alcatel-Lucent, and Haier likewise has given Whirlpool a rough ride (1). Another market shift is the one in consumer goods regarding the relative power between manufacturers (Procter & Gamble and Rubbermaid, for example) and retailers (such as Walmart and Home Depot) (2). Such market shifts raise the likelihood of changes midstream in a development project. Finally, technology--both the technology that goes into the product and the technology (like computer-aided design tools) used to develop it--is changing at an accelerating pace. New technologies appear and existing ones become obsolete or simply passe. Sometimes a new technology provides unexpected benefits that one would like to exploit during a project, such as the enthusiastic reception of portable music players by runners and others exercising physically, which, in turn, demands unexpected changes during product development to incorporate resistance to rain, perspiration and vibration. Alternatively, sometimes the benefits touted by the purveyors of the new technology don't pan out. This opens more opportunities for change in the midst of development. On the other hand, many managers, at all levels, do not welcome change during a project. For them, mid-project changes open the door to product cost and development budget overruns, schedule slippage and product defects. Hard-pressed to deliver profit on a quarterly basis, managers, especially at higher levels, rightly see change as disruptive. Consequently, management has built development systems aimed at predictability and certain success, such as: phased development (including StageGate[R]), Six Sigma and Project Office. Although such systems clearly have benefits, their gains in predictability come with a corresponding side effect of rigidity. In summary, although change during development is increasingly common, I instead see managements adopting systems that are increasingly resistant to change. This article shows how to introduce the flexibility needed to make changes during product development with minimal disruption, which I believe will separate the future winners from the losers. Consider this example of turbulence encountered by Quadrus, a Calgary-based software development company, in developing an application for a Canadian online drugstore. This is a volatile market driven by ongoing supplier, political, regulatory, and legal thrusts. Extreme change was the essence of the management challenge Quadrus faced. In addition, its client was coming from behind in a bid to become a market leader. Quadrus responded by using very short (two-day) development iterations--each producing working software--and weekly online deployments, which not only kept up with the changing environment but aggressively led the change. By having a positive attitude toward change and employing systems that could reorient quickly, Quadrus' client could respond to competitive challenges and regulatory demands faster than competitors, thus leading the change to gain competitive advantage (3, p. 249). …

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.082
GPT teacher head0.326
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it