Over the last 10-20 years there’s been a revolution in academic science (or should that be ‘coup’?) where many aspects of the job have been professionalised and formalised, especially project management but management in general. This generally includes tools like GANTTs, milestones, workload models, targets and many other things previously unmentionable in academia but common in industry, especially large organisations. Lots of academics will tell you they think it’s bureaucratic overkill, intrusive, a waste of time, and worse (to put it mildly) but the awkward truth is that, as lab groups steadily increased in size (as fewer, larger grants went to increasingly senior PIs or consortia) many of the limitations of the collegiate style of the past, centred on a single academic with a tight-knit group, have been exposed.
Frequently the introduction of ‘management practices’, often after hiring expensive consultants, is accompanied by compulsory management training. Sometimes it can be an improvement. More normally (in my experience) whether an improvement in outcomes (as distinct from ‘efficiency’) has been achieved probably depends on whether you cost in staff time (or overtime) and morale. You can make arguments either way.
But I can’t help thinking: why are we attempting to replicate practices from big/massive private sector organisations, anyway? I suspect, the answer in part is because those are the clients management consultants have the most experience working with. More seriously, those organisations differ in fundamental respects from even the largest universities, let alone individual research projects. This is because large companies:
- Add value to inputs to create physical goods or services that are easily costed by the market mechanism (this is the big one)
- Usually have large cash reserves, or easy access to finance (tellingly when this ends they usually get liquidated)
- Keep an eye on longer-term outcomes, but primarily focus on the 5-10 year horizon
- Compete directly with others for customers (in some respects an infinite resource)
- Are answerable, at least, yearly, to shareholders – with share value and dividends being the primary drivers of shareholder satisfaction.
Meanwhile, universities (and to an even greater extreme, research groups/PIs):
- Produce knowledge outputs with zero market value*
- Live hand-to-mouth on short grants
- Need long-term, strategic thinking to succeed (really, this is why we get paid at all)
- Compete indirectly for finite resources grants and publications, based partly on track record and partly on potential.
- Answer, ultimately, to posterity, their families, and their Head Of Department
I want to be clear here – I’m not saying, by any means, that previous management techniques (ie, ‘none’) work well in today’s science environment – but I do think we should probably look to other models than, say General Motors, or GlaxoSmithKline. The problem is often compounded because PIs have no business experience (certainly not in startups) while consultants often come from big business – their ability to meet in the middle is limited.
Instead small and medium enterprises (SME)s are a much closer model to how science works. Here good management of resources and people is extremely important, but the scale is much smaller, permitting different management methods, often focussing on flexibility and results, not hierarchies and systems. For instance, project goals are often still designed to be SMART (specific, measurable, achievable, realistic, time-scaled) but these will be revisited often and informally, and adjusted whenever necessary. Failure is a recognised part of the ongoing process. This is the exact opposite to how a GANTT, say, is used in academia: often drawn up at the project proposal (design) stage, it is then ignored until the end of the grant, when the PI scrabbles to fudge the outcomes, goals, or both to make the work actually carried out fit, so they don’t get a black mark from the funder/HoD for missing targets.
There are plenty of other models, and they vary not just by organisation size/type (e.g. tech startup, games studio, SkunkWorks, logistics distributor, niche construction subcontractor) but you see what I mean: copying ‘big business’ wholesale without looking at the whole ecosystem of business practices makes little sense…
*Obviously not all, or even most, scientific output will never realise any economic value – but it can be years, or centuries removed from the work to create it. And spin-outs are relevant to a tiny proportion of PI’s work, even in applied fields.