Motivating, embedding and maintaining change

'What looks like resistance is often lack of clarity'

Chip Heath and Dan Heath

While it is easy to kick-start a KT 2.0 style programme, embedding change that lasts requires preparation and tactical consideration. Resistance to change is not inevitable but, as a body of behavioural economics suggests¹, when change is too complex, or the script is not clear enough, maintaining change can be exhausting. The new decisions required by embarking on any new approach often make it easier for us to default to the more familiar status quo. No matter how compelling the case for change, or how evident the return on investment, the likelihood of achieving successful change is increased if certain tactics are adopted.

Knowledge transfer (KT) is a complex process and the rationales for engaging in it are diffuse. Hence the likelihood that a radical re-engineering of the KT process will get bogged down in over-analysis and complexity is all the greater. The risk of reversion to the so-called 'status quo bias' is all the more pressing. Moreover, the staff engaged in KT are busy. Even though the new approach provides new and evident benefits, these benefits alone are not sufficient to ensure consistent take-up.

'People irrationally overvalue benefits they currently process relative to those they don't'

John Gourville

Experience from the early pilots suggest that some tactics are useful for the adoption and maintenance of new routines:

Simplify the metrics, and the number of metrics, used for measuring success.

The KPIs and dipstick tests for successful KT are numerous: they can range from the number of inventions recorded, the number of patents applied for and granted, through to the number of companies and deals done, through to investment gained and cash realised, and various KPIs in between. Trying to measure each of these, particularly as isolated indices (rather than conversion rates), can often confuse. Of course certain HEFCE metrics will need to be played to, but motivating a team successfully will require clarity, and easily visualised targets.

It's beyond the scope of this resource to suggest which are appropriate KPIs: this, as is addressed in the UKIPO's recent Guide to Managing Intellectual Assets in Universities, will flow from the institutional strategy and business model. It may help, however, to boil these down to at most two or three key metrics for your team. The closer these relate to generating resource and creating value (social or financial) the better. In this connection it is also worth noting Eric Ries's advice in Lean Startup: that it is essential to 'Build-Measure-Learn', though the 'build' in this context relates to the KT eco-system, it remains fundamental; measure how customers respond, and if greater value is created then learn whether to pivot or persevere. Accelerating that feedback loop will help.

Picking one place to start can also help. For example, a natural starting point may be setting a target around the generation of Proof of Concept income and other early investment income generated externally to make opportunities happen. This is only one factor in a long line of milestones required for a venture to succeed, but given that funding often follows enterprise - rather than the other way round - getting some action going is a good starting point.

Focus on the bright spots, not solely on failures or deficits.

It's natural to focus on weaknesses when looking to create change. It's unwise, however, to focus on areas of underperformance early on as not only will this diminish team motivation and commitment, but it will also hide areas of success that can be used as a springboard for progress. In particular focus on some early wins for the new process (be that more PoC income, or more licence activity) and seeing what works and doing more of it.

Achievement of some short-term goals can generate commitment and be a useful springboard activity. For example, early on at the University of Leeds the team moved from a 0% success rate in one funds scheme to near on 100% having adopted some of the KT 2.0 principles. That had an immediate impact on team morale and perception of the value of the new approach.

Make the metrics meaningful and compelling, not abstract.

Uninspiring and abstract performance figures will not motivate and remind the team of the objective. Goals should be able to pass the 'champagne test' - that is be recognisable and something that can be celebrated. The external funding of projects that have previously struggled to demonstrate value, public recognition of new ventures or impact in national or trade press is likely to have more impact than a series of graphs. Moreover this will serve as useful content for promotion via the community, serving to motivate the team and those inventors that might wish to emulate the success.

For longer-term focus, bold return on investment figures may be motivating but a destination - such as being able to accomplish self-sustainability or outperform a competitor - might be more engaging and easier to remember within the complex day to day activity of the KTO. Shining a light of a notable bright spot of the KTO's performance and making it clearly outperform any other, will give early meaningful feedback. For example the University of Edinburgh has staked a claim as having outperformed any other university in the number of ventures it has created is a clear and compelling metric.

If the metrics adopted contain an element of social good all the better. The impact of the 'free' provision of IP by the University of Glasgow has had national notice and demonstrated a desire to achieve maximum utilisation of publicly-funded research, whilst maintaining clear metrics.

Script the key approaches and routines, embed the change as 'rules of thumb'.

Most critically of all, even with understanding and with support, it will be all too easy to default to the old way of doing things. Be clear about how people should act and set a clear script - not multiple, detailed rules. It may be helpful to make clear, black and white, rules such as:

'We will not engage in direct business development - we will always seek better qualified externals to lead on business development'
'We will not substitute our own view for the selection of projects by the crowd - everything will require external validation'
'We will seek to generate resources externally and will only use internal resource to unlock external resources'
'We will share as much risk as possible'
'Everything we do we will ultimately increase capacity, scalability and remove bureaucratic pinch points'

In summary, the good news is that it's easy to get going, and to derive immediate benefit, but it is more challenging to ensure that the benefits are consistently achieved and that maximum advantage is gained from the new approach.

¹ See Nudge, Richard H Thaler & C R. Sunstein 2008, and Switch: How to Change Things When Change is Hard, C & D Heath 2010, amongst other popularizations of such research. This section has been heavily influenced by these works.