This post discusses a form of research we increasingly find ourselves asked to perform by private equity clients. Analogue analysis is when you look for parallels in adjacent markets that might offer a roadmap, or at least an indication, of what trajectory a product may take. Analogue analysis can be very helpful for forecasting demand, uptake, time to product/market fit, hiring requirements, and any challenges to growth.
Other sectors where this type of analysis is popular are manufacturing and healthcare. Industry analogues are used regularly in the medical research sector to model price and health technology assessment outcomes for future pharmaceuticals. In manufacturing, ‘lead user’ research in adjacent industries is responsible for an incredibly high hit rate in new category product innovation. It is also responsible for the adoption or integration of technologies that have allowed rapid leaps forward in safety, security and consumer experience. An obvious example we’ll return to is the adoption of ABS (automated breaking systems) by the automotive industry. This was already a mature technology in aviation before it was ever built into a production car.
What is analogue analysis?
As with any bit of jargon, ‘analogue analysis’ makes a simple concept we all attempt regularly – with varying degrees of success – sound complicated. Fundamentally, analogue analysis is simply the process of reasoning by analogy. We look for information about another product or service similar in some respect to the one we want to deliver that has succeeded (or failed) in another market with characteristics that approximately resemble our own. Often lead users in other markets are experiencing a need that is more pronounced than those faced by any users in our target market.
To flesh out the example given in the introduction, ABS was originally an invention of the aviation industry. In the present case, this represents a useful example of an advanced analogue market for researchers in the automotive industry. Whereas lead users within the automotive market may have reported – had they been surveyed – that they had adopted techniques such as pumping their breaks to control the skidding process, that would still have left our R&D team looking for solutions to automate that process. Perhaps these would have come with a lengthy and expensive testing and approval timeline. By identifying a complete solution already active in an advanced analogue market – where planes are heavier and faster and their breaks must also disperse far greater amounts of energy rapidly – car manufacturers were able to learn far more, far more quickly, than they possibly could have from their own target market.
Analogue analysis, though simple in principle, relies on us making good analogies. This is not always as simple as it may seem. Studies on human psychology as well as empirical evidence from well known companies making costly – or even fatal – errors show time and again that intelligent people are not immune from drawing bad analogies.
The example of Enron is instructive. Though many factors were at play in their rapid collapse, one key driver was their rate of diversification based on analogy into a whole host of markets that had surface similarities but were not in fact as similar as careful examination would have shown. Their initial success in gas and electricity led to them entering markets for everything from coal through to weather derivatives and broadband. While all these had some similar market characteristics, such as highly fragmented demand or lengthy sales cycles, the differences in these markets were pronounced, entrenched, and ultimately required different solutions from the ones appropriate in the gas and electric power vertical.
Who should do analogue analysis?
There are a couple of circumstances when analogue analysis is particularly appropriate, and we will examine both below:
– Formulating an investment hypothesis
– Launching a new pharmaceutical
We’ve been involved directly in all three – supporting investors, as researchers for manufacturers and pharma companies, and as product creators. Through this experience, we’ve created a systemic approach to analogue analysis which we’ll describe below. First, we’ll touch on the objectives of each of these research disciplines and the key ways they differ from each other.
The R&D process in complex manufacturing often draws on analogue analysis. This is not just for product iteration – such as in the case of our ABS example above – but for new category creation. Lead users in adjacent industries provide a powerful source for product innovation for R&D teams.
It is a potentially complex process, as finding lead users in advanced analogue markets is a secondary act to identifying the relevance of a particular analogue. That in itself can require some ingenuity on the part of the research team. One proven way to shortcut this process is to ask lead users in the target market for suggestions on who the lead users may be in the adjacent markets. This is logical, as these users have often struggled with a particular problem for some period of time. They are likely to have searched beyond the existing market already for expertise in other markets.
This is a process known as pyramiding. This itself is analogous to a technique often used by sociologists to identify ‘in-group’ members or to acquire responses from harder to reach respondents. This leverages a phenomenon whereby people with niche interests often know people with the same set of passions or frustrations.
This was turned into a formal technique, used to great effect, by the R&D team at 3M. An experiment conducted in 2002 at 3M looked at lead user research projects as well as conventional market research projects and their effectiveness in unearthing new product lines. Over a 6 year period 3M had conducted 7 lead user projects, and of these, selected 5 for further funding. The same divisions had also conducted 42 ‘find a need and fill it’ idea generation projects (conventional market research). The results of the two project types can be seen in the figure below. In summary, the 5 lead user projects had projected Y5 sales that were a factor of 8 greater than the conventional market research projects – $146m:$18m. More on this fascinating study and the research behind it can be found here.
For private equity no such study exists for the role of lead user research and analogue analysis in forming investment hypotheses. However, when we consider the pressures on investors to pick winners – particularly in markets where the number of good companies available for acquisition at any point is low – not to mention the time and expense of the due diligence process, the value of analogue analysis in hypothesis formation is clear.
The use of analogues allows an investor to reliably model outcomes for a target based on similar acquisitions and subsequent improvements in adjacent verticals to the target. The approach an investor takes is likely to bear some similarities to that of the R&D team at a manufacturer. Like with manufacturing, the creative act is required – not simply to recognise an opportunity, but to realise that analogues for that opportunity exist that can usefully be investigated.
However, in our experience the process differs somewhat for investors from a strict R&D research approach. Because investors are not looking to innovate, but rather to back winning innovators, they do not need the same depth of exposure to lead users in adjacent markets. Being one step removed from the product innovation lifecycle, investors generally have a shallower pool of questions around use and adoption of existing technologies with similarities to a target acquisition. Essentially their questions are primarily commercial, aimed at sharpening sales forecasts, time to product-market fit, and any road bumps on the way to get there.
A recent project we took on for a mid-market private equity client looked at technology adoption in the consumer services space – B2B software for the B2C services market. The investor in question was struggling to model an opportunity – they could see the attraction and potential, but the data environment in the target market was very poor. By looking at analogue markets, we were able to identify several with strong similarities, both in types of software and the deep structural features of the markets themselves. This allowed us to create a data rich environment from which our client could then build models they felt confident in.
Healthcare is an interesting area where the research process of investors and drug producers often looks very much alike. We’ve seen this both in modelling work we’ve supported investors with, and on the R&D side too.
Given the timeframes and significant upfront investment for developing a new drug – from discovery through to FDA review – it is essential that investors and producers alike have a clear-eyed understanding of the potential returns, what the adoption curve is likely to look like, the prospects of licensing approval, and the price tolerance of the market for the treatment – the historical willingness of a group of patients to pay for certain types of drugs.
Analogues are frequently used to determine future pricing and health technology assessment outcomes for future pharmaceuticals. This is highly relevant as payers in many countries use price benchmarking for pharmaceuticals. Equally, outliers where there has been rapid uptake can help make a compelling case that approvals or adoption might be expedited.
We recently supported on a project that looked at an investment into a gene therapy drug that had completed Phase II trials and been approved to begin Phase III. The previous leading drug for treating this unusual condition – which affected only ~2,000 people per year in the United States – had seen rapid adoption prior to issues with its delivery mechanism leading to it being withdrawn by the manufacturer. This provided a very useful analogue for what the target investment’s drug might achieve. In this specific example, there were other factors that needed to be factored in, such as other drugs reaching the market ahead of the target company’s, and different deliver mechanisms making adherence harder or easier than the target company’s. In the end the investment went ahead, and was for well over $100m.
Build a system for analogue analysis
The importance of starting with a good analogy cannot be understated. Garbage in leads to garbage out. Our process generally looks something like this:
– Start with an industry you already understand well
– Look for enough cues to ensure there’s a resemblance of a past experience
– Establish a logical connection between two products or services
– Distinguish between deep structural features and superficial characteristics
– Determine the data pattern for the existing product – for example, sales data
– Use experience and intuitive judgement to trace the expected pattern for a new product given similar market conditions
– Build in regular stress testing for your assumptions
– Test your assumptions once they’re refined against lead users in advanced analogue markets
The statement about the use of intuitive judgement is an important one. Good intuition is generally a combination of a well-ordered thinking process, extensive general reading, and broad experience. Analogue analysis can be a powerful tool for forming investment hypotheses, launching new products, and developing new pharmaceuticals. However, it relies on sound intuitive leaps. If there’s a lot of money on the line, you need to be confident in who is making those leaps.
The final statement is one born of our own experience. When you are operating in a low state of knowledge relative to an ‘expert’, it is very easy to be led. This often happens with the best of intentions, and with a collegiate spirit of positive cooperation. It is important to become somewhat expert before speaking with lead users. You must know enough to remain detached and skeptical. Our most successful engagements have come when clients have themselves gained a high degree of expertise, and we operate in a positive, friendly, but essentially adversarial way. Clients that constructively challenge our research and intuitions, rather than simply relying on us as experts, tend to get more from our projects together.
Analogue analysis can be a powerful research tool for creating investment hypotheses, innovating new products and pharmaceuticals, and developing sound go to market strategies for target markets where relevant data is scarce.
However, there are serious pitfalls associated with analogue analysis. It is a fundamentally intuitive exercise, requiring a good deal of experience, general knowledge, and ‘feel’ for what’s sensible. Many people and businesses come unstuck when trying to reason by analogy, with Enron being a notable example.
If you are looking to conduct an analogue analysis, or work with lead users in advanced analogue markets, it’s important to have a well developed research process. This process should specifically and regularly test underlying assumptions and parallels to ensure that they capture deep structural commonalities, not superficial, surface level characteristics.
The following are useful resources for anyone wanting to dig into this area of research further:
Management Science: Integrating problem solvers from Analogous markets in new product ideation: https://www.jstor.org/stable/42919585
Harvard Business Review: How Strategists Really Think: Tapping the Power of Analogy: https://hbr.org/2005/04/how-strategists-really-think-tapping-the-power-of-analogy
MIT Press: Democratizing Innovation: Chapter 10: Searching for Lead User Innovations: https://web.mit.edu/evhippel/www/books/DI/Chapter10.pdf
Journal of Business Research: Forecasting new product trial with analogous series: https://www.sciencedirect.com/science/article/abs/pii/S0148296315001460