Muzeable Thinking

Our blog, occasional white papers and case studies represent the foundation of Muzeable Thinking… enjoy

Sharing the input: responding to some of the comments on our piece on breakthrough claims…

Posted by on Oct 9th, 2017 in muzeable thinking | 0 comments

Muzeable Thinking No.25 posted by Tim Brooks 9th October 2017


Our piece[1] on new approaches to consumer healthcare claims and real-world outcomes data was read by over 2000 people, thanks!!

Several weeks have passed and we thought it would be interesting to share some of the questions/discussions and insight it generated.

Overall, healthcare marketers seem to share our optimism – the approach has legs. But, we would like more input from our clinical/regulatory colleagues, so don’t be shy! The whole point is to create collaboration across disciplines and experience tells us you will add value. Key inputs so far:

  • Hybrid approach. To the previous point, everyone agreed that it requires a ‘hybrid’ approach blending the best qualities of clinical study and data expertise alongside hands-on commercial/marketing and ‘innovation’ experience. Most also felt this was, if not unique, different from most available input. People shared personal stories of ‘clinical’ work that lacked the behavioural insight required to deliver commercial value and creative/ideation approaches that simply did not understand or failed to meet the technical/clinical hurdles the business/regulators needed to be truly  ‘usable’. Or people who offered both, but lacked the suite of skills.
  • One ‘killer’ question keeps popping up. It’s a good one, it goes like this…

‘Ok. So, I get that we can drive strong communications claims in a market like the UK, but will this approach produce data that can go on the label and therefore be used in other markets and/or go on the pack’.

  • Honest answer. This is tough!!! Given the ‘boxes’ on the standard SPCs/PILs in Europe it is hard to see where to physically put PROM-type data [another example of the regulatory approach not really matching self-medication needs given that these data could potentially be helpful to consumers/patients making choices.]
  • The Wirkungsweise box on a German label, for example, where the data that explains what the drug does is presented, could theoretically include other useful usage information on the ‘operation’ of the product in the ‘real world’ beyond the ingredient modes of action. But, we all know this runs counter to the philosophical position of most regulators.
  • That said, since the output will be robust, well produced [to clinical standards], published data and a well-run project would produce a data-set, not a single paper it has the potential to pass the basic acceptance hurdles of the regulators/clinicians and be worthy of discussion.
  • Big Pharma is not using PROM on labels, though they are using it for serious purposes with regulators/government to explain value/justify pricing and show differences/patient benefits in an attempt to influence prescribing behaviour.
  • In effect, that is similar to the aim here – to show brand difference/distinctiveness to influence choices via robust, supportable data/claims – but, we need the data be ‘publicly’ usable with people not just used in-camera with HCPs. Currently, in most of Europe, that needs it to be on the label.
  • So to be honest this requires a brand owner to run up the hill, innovate and have the patience to ‘work with the authorities’ to get relevant data on the label and build a test case. This is a long-term commitment with no guarantee of success. But, we struggle to see what the alternative is for brands? If they do not take on the challenge of changing regulations to facilitate better self-medication and more marketing they are on a long, slow slippery slope to a universe filled with Amazon own-label!!
  • The industry should [and it isn’t really] tackle the fundamental challenges around the ‘future of self-medication’. Our small innovation is at the heart of this. We [brands/own label/generics etc.] need self-medication labelling regulation etc. that is specifically designed for self-medication, not a sub-set of Rx with its completely different needs/safety issues. WE DO NOT CURRENTLY HAVE THIS… industry needs to take a deep breath and FIGHT FOR IT! Yes, it’s better than it was, but…
  • So, creating a box on the label outlining relevant, proven, robust behavioural data outlining how people using the brand/product in the pack they have bought or are thinking of buying have got best results or positive outcomes – including PROM studies – seems relevant. Dare we say… helpful even! It is part of the need to put people at the heart of healthcare and explain the benefits [not just the actions] of the product to people to enable them to see its relevance. Yes, this is marketing, but as long as it is based on good data and it all happens on a level playing field [e.g. companies that invest in the data can protect it] and own label/generics can play too, where is the issue?


  • Evidence Portfolios. The idea of building a brand specific [owned] data set versus a single study approach also resonated – we call this evidence portfolio   creation.[2] It is what R&D plans to do anyway, yet, when we review our own experience of OTC clinical work (infrequent as it is) we have seen little evidence of the approach we propose. We rarely focus data creation on the end user outcomes and using that to build a multi-layered portfolio of evidence seeded in public domain and cross referenced to maximum effect. Data is usually targeted against a specific need. Nothing wrong with that, but it might not be optimising the opportunity of the investment. We are perhaps most excited about the potential to repurpose and add value to this existing data – it seems a cost-effective shot to nothing!
  • Many people felt this was a big behavioural change for brands/marketing who see communications as an ‘FMCG’ consumer/emotional engagement task – and it is – but this usually positions data/claims as ‘content’ to improve their ads. Since we usually advertise our NPD this can make it very short term. To start with a consumer experiential model to drive relevance and distinctiveness is a big change requiring investment decisions/changes. That said, real world outcome claims around NPD sounds like a good idea.
  • Social media? Lots of cynical questions about the use of social media data to build a quantitative frame of reference. What the discussion showed is [apologies to anyone who thinks we might mean them!] how little marketers understand about the potential of these data. Clinicians understand even less. Done properly this is a massively valuable input. Don’t imagine this would be a bit of blunt, possibly interesting, but completely unactionable slice of social-listening data. We see lots of this, and apologies to clients who do it, but save your money. Clever people with proprietary approaches, mashing together multiple data sources and using/analysing the data and connections are producing some of the most powerful insight, influence and targeting work we’ve ever seen[3]!
  • Methods? Lots of questions on methods etc. firstly, it isn’t off the shelf, so it is hard to put into a box. But, since none of the basic methods – sample creation; mobile data capture; questionnaires; product use; statistical analysis etc. etc. are ‘new’ – it’s the packaging up and outputs that are innovative – we don’t see this as the area for debate. If we set up and agree outcomes the study/trial will behave in a similar way to other work you’ve done. It’s the outputs that are different, based on a fresh way of looking at data and how they work.
  • How much will it cost? Lots of questions on cost. How long is a piece of string? As said, definitely much cheaper than full scale clinical work and with a better PTS; more expensive than a few workshops for sure. Two comments… the journey can be started slowly [i.e. proof of principle before a major study] and the ‘pre-work’ gives you a milestone to say go/no-go before the button is pressed whilst building a powerful input on your existing claims potential/landscape. You can even write up and publish the pre-work! In the end, having done claims work for a few decades now, we have a reasonably high confidence on some ROI.

Again, we think the answer is to talk about this stuff in the context of specific needs vs theoretical constructs. We’d rather jump through a few hoops to demonstrate the value than write articles; in reality a few documents and blogs are frankly irrelevant versus a SPECIFIC exploration/discussion of your brands and categories.

Contact us… you know it makes sense.

[1] Join the revolution: new ways to deliver breakthrough OTC/healthcare claims 21/07/2017

[2] Tom Kenny blog on evidence portfolios.

[3] We work with Four Engage. Check them out, it might just change your life…


‘I wouldn’t start from here!’ – Efficiently Creating an Enhanced Evidence Portfolio.

Posted by on Oct 4th, 2017 in muzeable thinking | 0 comments

Muzeable Thinking No.24 posted by Tim Brooks 4th October 2017


This is a guest piece from Dr Tom Kenny of Dune Consulting. Muzeable has had the pleasure of working with Tom and find the mix of his expert, clinical perspective and our marketing/brand views has the potential to deliver genuinely fresh thinking. Thanks Tom.

Using finite resources and the available data to build a compelling story that creates and defends a value proposition or tries to deliver distinctive claims for a medicine (POM or OTC) is one of the most important – and difficult – tasks for anyone managing a healthcare business.

Yet, we are repeatedly shocked by the poor use of evidence companies make when it comes to constructing a value story for their healthcare brands.

Too frequently the company who are aiming to promote a medicine do not put enough energy into seeing the world from the perspective of a payer (and that includes people shopping for medicines) at the beginning of their clinical trial programme – the focus is single-mindedly on the regulator and the ‘hurdles’ they need to jump.

We understand the pressures that drive this, but as they say, “if wishes were horses, beggars would ride” and at the late stages of your positioning around pricing and reimbursement, or creation of a value proposition, or a setting of marketing or promotional messages it is a little churlish to be wishing that some deeper, or different, thinking had been done earlier. At this point the more appropriate saying often appears to be “beggars can’t be choosers”. It is was it is, we need to work with the evidence portfolio that we already have…

…or do we?

Our experience is that, unlike the old saying, you actually can ‘start from here’ i.e. with the data you have. An evidence portfolio/framework can actually be enhanced relatively simply, quickly and cost effectively. These thoughts come from a long experience of working with, often imperfect, data sets in order to design care pathways, choose between different medicines or make a reimbursement decision. All of this is equally applicable in the self-medication environment, even if the scale of the data and clinical investment might be smaller. In fact, it is particularly relevant to the competitive world of differentiating OTCs with evidence beyond marketing spin and in the absence of large clinical investment. But, firstly a couple of, perhaps, obvious things to remember about clinical studies and real-world research:

  1. It is rare that any single study provides ‘the answer’. Even when beautifully designed, bias, chance and simple errors can, and do, occur.
  2. There is no such thing as a perfect study design. A well-designed study will set out to answer a question and be specifically designed to do just that, this will mean it will have strengths and weaknesses. Pose a different question and these strengths and weaknesses will be different. The weaknesses, especially, become obvious and magnified when it starts to consider answering multiple questions.
  3. A study lives or dies on its methodology. We may or may not like the results, but whether we trust them or can use them depends entirely on the methodology used to get them. Research is often designed in such a way that it undermines its own results. For example; multiple outcome measures and designs that allow for a multitude of explanations of the data.

So, here are 5 things that you should consider when you are faced with a weak portfolio, generic data or when you want to build a data-set to differentiate or support your brand and you lack the money – or time – to run a large study program:

  1. Trawl & Steal. Systematically draw together the other work that has been done in the same field; the work that has asked similar or related questions. This is by far the most cost-effective way to get a large number of robust enhance insights and a clear data baseline.
  2. Polish. Prospectively re-analyse a study’s results; this can yield valuable insights without the cost of setting up and running a whole new trial. Get relevant associated/secondary data in the public domain [gray papers etc.] and use it!
  3. Strengthen. Run simple studies in parallel to provide a basis for comparison and defend against alternative explanations; this maximises the insights from the investments and supports the production of great claims. It’s like a puzzle and the creativity comes from how you fit the pieces [data] together.
  4. People first. Use simple studies of Patient Reported Outcomes Measures (PROMs) to uncover outcomes that are meaningful for patients and compelling for payers; data that enhances the proposition/claims. To date PROMs have been poorly understood and little used for OTC medicines.
  5. Build a context. Capture the natural history or epidemiology of the condition to provide comparisons data that are often otherwise lacking.

This is not a tick box exercise. This approach needs to be wedded to practical, expert input to pull together a roadmap to evolve and build stronger evidence in a finite resources environment. A hybrid commercial/clinical input model is at its heart. And start small. A few weeks of analysis could quickly confirm the potential and define the benefits/outcomes.

If you would like to talk to Tom and Tim about building an evidence portfolio to drive claims and growth please contact us.

Dr Tom Kenny started life as a GP, he then moved into NHS/Public Health Medicine. He is expert in clinical drug/data evaluation and building real-world data/studies to enhance patient/consumer experience & outcomes. As well as running his own consultancy, Dune, he leads the core team delivering clinical research programmes at Spoonful of Sugar the behavioural data consultancy at Imperial College, University of London.


‘Because an appeal makes logical sense is no guarantee that it will work.’ Bill Bernbach

Posted by on Jul 18th, 2017 in muzeable thinking | Comments Off on ‘Because an appeal makes logical sense is no guarantee that it will work.’ Bill Bernbach

Muzeable Thinking No.23 posted by Tim Brooks 18th July 2017

It’s a near miss.

No, not Bill’s quote[1]. That’s fab. Spot on. The near miss follows…

A week or so back an interesting and important new piece of research was published by The Academy of Medical Sciences entitled ‘Enhancing the use of scientific evidence to judge the potential benefits and harms of medicines.[2]’ It raises a host of critical issues, but in the end, relating to communication with the ‘general public’, it almost misses the point.

The research’s key soundbite – which BBC Radio Four’s Today programme focused on – is that ‘one-third (37%) of the public said they trusted evidence derived from medical research, but around two-thirds (65%) trusted the experiences of friends and family’. The report runs to 116 pages and goes well beyond a soundbite and makes valuable and relevant recommendations, 12 in all.

Think about it. It has to be scary that only a third of us trust medical data – even the good stuff – yet two-thirds of us trust in anecdote. Though, as a brilliant medical director I worked with often said… ‘Tim, the plural of anecdote is… data!’ Seriously, whilst reported outcomes produced in a clinical context are relevant and undervalued[3], friends’ data has usually gone through a complex filter of Chinese whispers, myth and misinterpretation before it lands i.e. it can be critical/valuable, but it is a curate’s egg/lottery.

Moreover, for data produced by the pharmaceutical industry it reports a staggering 82% of GPs and 67% of British adults ‘agreed with the statement that clinical trials funded by the industry were often biased to produce a positive outcome.’ Worrying, since industry funds much of the new research.

‘Houston, we have a problem’. So, why does this positive piece of work almost miss the point?

Well… although it starts by acknowledging the behavioural/real world component of the ‘issue’ and that healthcare systems often ignore people’s actual needs, it then repeatedly reverts to a solutions framework that focuses on education and rationally-based solutions to change the outcome. The argument is that better information and clearer presentation will change people’s acceptance of science per se and, ultimately, make us all more rational. Doh. It simply will not work. It is an example of expecting a better version of the wrong solution to deliver dramatically different results.

To change this, we need to start and end with a 100% focus on responding to real world needs/behaviour. People doubt experts [witness recent political upheavals] for many reasons, but most of them are fast, emotional responses, built on doubt, fear, mistrust and denial, NOT usually an intellectual inability to understand a rational message.

Of course, we need better/more consistent data that is better presented, but we also need a step change throughout our whole clinical, medical and regulatory framework. Don’t just ‘acknowledge’ real world behaviour – construct the entire universe around it. The ‘data’ has no role other than to enhance/facilitate this[4]. This is scary. But don’t hold your breath, because the health eco-system is still founded on a deeply paternalistic [with a capital ‘P’] world view and here lies the problem.

So, implement ALL the great recommendations around improving the data/presentation, but reconsider the desired end game. Stop seeing the output as a more rational – homo pharmaceuticus[5] – general public, making informed decisions. THIS IS ALMOST CERTAINLY A NAÏVE THEORETICAL CONCEPT. It will never happen. Reason? End users are not interested in the data per se, but in the benefits/ experiences/outcomes they receive and how this meets their needsas they see them. Until we approach public/health data through this lens we will never change anything.

Take packaging and labelling – a personal passion. It’s bad enough in prescription medicines, but in OTC/self-medication, where we are asking people to make their own choices, often at a supermarket shelf, it would appear that the MHRA [Medicines and Healthcare products Regulatory Agency] has never actually met a real person, let alone tried to understand how they behave and feel about their needs. We need even more fundamental changes than this paper’s sensible ‘Recommendation 8’. We must start with needs – not active ingredients, doses, pharmaceutical forms and modes of action etc[6]. [arghhhhhhhhhhhhhhhh!] – as the user would express it and stating benefits in their language. And yes, sometimes this might start to sound a bit ‘unscientific’ or ‘promotional’, but so be it if it helps people and gives no-one an unfair commercial advantage. This is fundamental, not a tweak from the excellent Plain English Campaign[7] or PIF[8]. [NB totally agree on a UK equivalent to US Drugs Facts Box… people would appreciate it, we’ve even done the research and have developed a working style guide available to those who are interested!]

All of this requires one particular group to change more than any other – medics, regulators and academics. It is a gross, unfair generalisation, but they need to stop telling us to be more rational and do the right things – e.g. losing weight, giving up smoking etc. and dramatically change THEIR approach to making it happen. Work harder to make their input more – sometimes, even at all – relevant to its recipients. I think it was Dale Carnegie who said ‘that people buy what they are buying, not what you’re selling’ – it was never truer here. Let’s start with what people are buying.

Rant over. Well done AMS this is good work and we hope it sparks change/debate, but until we truly, madly, deeply put PEOPLE @ THE HEART of our healthcare debate – especially in self-medication situations – we will only move at a snail’s pace. If that. If at all.

And finally, a plea. The people who can really make this change happen are rarely asked to contribute. The medical community/MHRA/academics generally see them as personas non-gratis; they look down their noses at them; they don’t trust them; they are not represented on the oversight committees; they are ignored. But, it’s the tawdry old commercial marketing community who is the most qualified to change people’s behaviour. Aggressively protect people from lies and sharp practice, but beyond that we need to let business talk to people about healthcare solutions without one hand tied behind their back. It’s another near miss.




[1] Bill Bernbach one of the true greats of advertising and communication. The agency that bears his name is still going strong.


[3] Our current crusade on new ways to produce breakthrough claims reflects this.

[4] Obviously, much data exists, beyond this context, in a purely scientific/academic environment and contributes beyond patient information.

[5] Muzeable blog on self-medication and homo-pharmaceuticus.

[6] NB this/safety data is VERY important, but only needed/helpful on the back of pack; leaflet… not front of pack.


[8] Patient Information Forum


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