Science, Technology, Engineering and Math skills are undergoing a period of increased emphasis in our schools. Some might argue it’s at the expense of Art subjects. Does it have to be a zero-sum game?
Science hypothesises, experiments and interprets. Art creates directly, with no underlying rules or logic to adhere to. Science is structured simulation. Art is role play and improvisation. To reach human markets (voters or buyers) needs emotion, not just product features. Art and Science should therefore be seen as a partnership.
Secondly, at school, can we engage more students in STEM subjects, by emphasising it as a means to an Art end? Invite students to come on the STEM journey to empower Art.
Thirdly, great science discoveries utilise Psychology and thought experiments. Or sudden leaps of insight (realisations). Great thinking is arguably as much an art as utilising the science.
Old World Innovation chain
Researchers spend their life finding new insights.
Valuers (funders, financiers, analysts & appraisers) spend their life pricing the things that researchers uncover, so that Traders can exchange value.
Sometimes traders can also be researchers, but innovation impact (on society) is secondary to the direct value of the exchange.
New World Innovation chain?
Valuer’s set the innovation priorities based on innovation impact.
Researchers get to work and traders then exchange the outputs.
The word on Flip Learning; grade headlines you win, grade tailings you loose?
Flip; outside-in to inside-out
Flip the classroom; video killed the textbook star?
Flip learning; Allow enough time at the workstation, so the training can leave on time with you onboard.
Conventional learning; walls with sentries and checkpoints. Flip learning; walls with ears.
Flip Learning; One insight is worth a thousand repeats.
Flip Learning; one substance, many styles.
Flip Learning; like You Tube breaking news, not museum captions
Flip Learning; time and space are relative. Assessment is absolute.
Flip learning; art integrating life and life integrating art?
Conventional teaching; inherit raw materials and hope to convert to saleable finished goods, using scheduled production runs.
Flip teaching; sell raw materials for students to convert into saleable finished goods, using flexible production runs.
In the world of manufacturing, manufacturing cycle efficiency (MCE) = processing time/throughput time. This ratio is less than or at best equal to 1. This is because:
Throughput time = Processing time + Inspection time + Movement time + Waiting & Storage time.
From the customer perspective, processing time has value while the other 3 components are non value-adding. From the organisation’s perspective, it wants to reduce throughput time in its entirety and especially in the customer-perceived ‘non value adding’ aspects.
In a Higher Education (HE) context, what are some examples of ‘Processing time’? Teaching and Research activities.
What are examples of ‘Inspection time’? Research time spend screening, comparing and filtering the results.
What are examples of ‘Movement time’? Shipping physical samples between research subcontractors and College research teams, or between collaborating institutions or departments within the College.
What are examples of ‘Waiting & Storage time’? This is the time lapsed between periods of research or teaching activity, not already covered as inspection time or movement time. For the College, if it wants to improve College process efficiency (CPE), Waiting & Storage time likely offers the biggest opportunity for improvement (cost reduction without loss of quality).
Why is improving CPE desirable?
- It will help the College reach its surplus targets on a sustainable basis,
- It will help the College differentiate itself against competitor institutions,
- It may increase the research grants won to grant applications submitted ratio,
- It may lead to raising the standard of academic entry to the College’s taught programmes,
- And most importantly, it better meets the needs of both research funders and students.
To elaborate on meeting funder and student needs better, the sooner a student graduates, the quicker they can pay off their student debt and the less debt incurred. Meanwhile, the sooner the research funder gets the research results from the College, the sooner they can commercialise them for economic benefit. And the sooner the College research team can publish their findings.
Financially, if the College became World-class at fast delivery of Research and Teaching through improved CPE, it would:
- increase the College asset yields,
- use working capital more productively,
- generate surpluses faster than at present
- allow the College to average up its research grant rates (overhead recovery) sooner.
Cost rates ($/period) would increase with increased throughput, but fixed costs would be covered faster. With effective marketing (to optimise price & volume combinations), the College surpluses would accrue faster than the overall costs would rise.
How can a University or College improve its CPE?
The object would be to systematically review every process that impacts the overall throughput time in research and teaching, to realise a goal of shortening the cycle of both by say 25%.
Teaching time (processing time) can be shortened in various ways without compromising quality. For example writing high quality/interactive teaching content & distributing it online to students, with follow up in-class sessions on workshops, case studies and role playing (the in class hours would in total be only 75% of current in class time and done in a condensed period).
Research time (processing time) could be sped up by investing in the latest generating, screening & filtering research technologies, with success defined upfront and relentless testing until a breakthrough is achieved.
Inspection time could be automated and merged into processing time in the case of research activity.
Movement time probably isn’t significant but there may be ways to shorten and reduce the movements of research samples and research information between various parties.
Shortening waiting & storage time for research work might include a variety of tactics. For example using animal & microbial species with fast multiplication rates (short breeding cycles), using more powerful testing simulation programmes, writing software code more efficiently, and/or doing research in more agile ways. In teaching, shortening waiting time could come with online content distribution, writing assessment templates concurrently with teaching content updates, providing fast turnaround on test and examination results and reducing the delays in the course between content assimilation, testing & graduation. The content itself could be better customised for different learning styles.
What barriers to change might arise within the College, to the concept of competing on time?
- Senior management may already be committed to undertaking process reviews explicitly to improve quality, but not explicitly aimed at reducing cycle time in operational processes.
- There may be academic resistance to conducting Research & Teaching activities any faster than at present, citing risks to the quality perception of the College brand, objecting to the reasons why cycle time improvements are needed at all (universities aren’t about generating contributions greater than zero, universiites aren’t in a competition with other universities etc), or voicing other concerns.
- The short term monetary investment required, may be a disincentive to initiating such changes.
- A consensus view might emerge that the benefits are not certain enough to justify the change.
 Funders, given a choice between research applications from equally well-respected research teams (from different Higher Education Institutions) will likely choose based on who can credibly deliver the required results in the shortest time. Funders probably won’t insist that the College improves its cycle time. Instead they will reward those leading HE’s that do reduce cycle time, with research grants.
With future advances in intelligent networks and their peripherals (robotics), will the people most valued economically in a society cease being energy-field owners/entertainment celebs/hedge fund managers? And instead be the entrepreneurs – those who can generate and sell brilliant ideas (to the intelligent networks and between each other), in return for goods and services?
If so, smart governments would be wise to plan ahead. They can introduce policies that actively encourage the creation of a nation of designers and inventors – challenge everyone to relentlessly practice their design and inventive skills to benefit themselves & the nation (idea entrepreneurship). Then eventually, with the rise of intelligent networks (self-organising), people will have something of value to trade – the more brilliant the human idea, the greater the resulting payment from the intelligent system.
It’s reasonable to assume that Intelligent networks & their peripherals will eventually do the engineering/commercialisation (simulation, translation, prototype fabrication, scale production and marketing work), leaving people to add value through imaginative design.
Universities, R&D Institutes, Corporate skunkworks & garage inventors (including the maker movement) – they all deserve accolades far in excess of their current image in society. Smart governments will find ways to foster innovation, not just in the ivory towers & skunkworks, but in the channels that link ivory tower innovation with garage invention too (who says university academics are the only ones with good ideas and why can’t the gov funding incentives change to reward research cultures to innovate themselves?).
Design solves inflexibility problems, environmental pollution problems, over-crowding problems, awareness & perception problems and security problems. It both creates opportunities and exploits them. Even politics at its heart is about clever design. Although sadly, too many politicians aren’t clever designers – leading by example and keeping their policy-makers on their toes.
Of course design is hard, taking energy, commitment and persistence. However, as everything else gets automated, hard design is our future as a species. Food for thought?