Much has been said about the declining state of innovation in the United States.   Despite increases in fundamental research and increased PhD degrees awarded, total factor productivity growth has not nearly kept pace[1].  The causes are usually attributed to funding trends and changes in corporate R&D spending or how corporate R&D interfaces with academic research.   This may all be true.  But my thesis goes to another cause not commonly identified.  The reason why innovation is on the decline in this country is a result of how we source and curate the problems we solve with technology and R&D.

The Traditional Industrial R&D Model

The old industrial model of R&D involves big price tag spending towards R&D departments, staffing them with specialized engineers, building high tech facilities, and buying high tech equipment.  There have been extraordinary successes to this approach.  The tales of bastions of R&D such as Bell Laboratories are legendary for their inventions such as the transistor and the laser.  

However, we are moving into a new era where this old model is becoming less sustainable.  As described in the book Frugal Innovation,[2] there are several reasons for this:  expense, resource constraints, and competition.  One is that R&D is becoming very expensive as highly specialized equipment and engineering skill sets command greater and greater levels of investment.   At the same time, R&D spending is decreasing overall, budgets are getting squeezed, and executives are worried about meeting their goals.  Second is constrained resources other than simply funds.  Big industrial era R&D projects can lock in high demand engineers for years at a time on projects that may be high potential but also high risk.  Big budgets also enable unexamined supply chains and materials selections.  In an age where natural resources (especially metals) are becoming harder to source and even harder to recycle, this can drive environmental impact up along with cost and supply chain risk.  Finally, competition and the proliferation of alternatives has ramped up.  As a friend of mine put it: ‘when I was a kid, there was one type of ketchup. Now there are ten that I have to choose from’.  The traditional industrial R&D model equates number of features and complexity with greater value.  However, that does not necessarily translate into better value for the customer. It is important to note that, especially for products that are new in class or category instead of iterative, oftentimes there may be less competition from other brands but more from alternatives. 

Push Versus Pull

The traditional approach to tech product development and R&D is to build something the company thinks is close enough to what the customer wants, launching it in the marketplace, and then pushing out marketing messaging and whitepapers to convince potential customers of the benefits.   This approach is rooted in the belief that customers do not know what they want (which is true in a way, but more on that later), and they have to be ‘educated’ about the solution to their problem.  This means generating marketing communications that promote brand recognition, advertising the benefits of a particular product (according to the company), and the belief that increased marketing communications translates to more sales. 

This is called ‘push’ product development.  The focus of the development starts with beliefs and ideas formulated inside the company.  There may be some engagement with customers but this is done at arm’s length or without true root cause analysis (as described below).  The ‘push’ product development can work fine when addressing a market and customers that the company understands well, has served in the past, and the offering is iterative relative to past offerings.  However, the more disruptive a technology (i.e. innovative) or the newer the market subsegment, the smaller the chance that this approach will result in good resonance with customers. 

But innovation is not about the technology, it is about finding and curating the right customer problem to solve, also known as the front end of the innovation process.  Those carefully selected and well researched problems will not fall into your lap.  Instead, product development needs to reconfigure its thinking to a ‘pull’ model.  This puts the onus on product engineers and managers and their companies to ‘pull’ customer insights from the target market subsegment.  This means engaging with customers to learn and understand what their driving issues are and fusing those insights and focus as early as possible into the product development process.

The 15,000 Foot Customer Approach

All companies will aver that they do engage with their customers.  All the time.  That is the full-time job of the sales and business development people, right?  That is why we hire them. 

Yes, but we must go much further with our engagement.   The usual business development activities start with some market research.  This comes from secondary sources and is great for identifying macro features, such as market size, technology trends, and market players.  This type of information moves the company from the 30,000 foot level of understanding the customer landscape to the 15,000 foot level.  At this level you can push your solutions out, you can market test some solutions, and you can very likely sell a few.  But will you know why they bought?  Will you know what problem you are solving?  Do you have any reason to expect more sales?

There are still many questions to research before you can answer these ‘why’ questions, and these ‘why’ questions are the ‘money’ questions.  But you cannot do it from 15,000 feet.  You simply cannot get enough specifics, and the true insights come from the specifics.  It is the way to understand your market enough to sub-segment, and the power comes from that sub-segment definition.  Furthermore, the customer definitely is not going to fly up and meet you at 15,000 feet, not in the numbers you need to close a business model.  The customers already have solutions or alternatives to solving the problem that they live with right now.  Not ideal or efficient, but they exist. 

To do the work to uncover true customer insights, you must come down from 15,000 feet and land your plane.  Pick a spot and start your exploration of customer problems.   As Steve Blank famously says[3] ‘the answers are never inside the office’, one must get outside the building and go and engage with customers directly.  Lots of them.  Find out what gets them worked up and what makes them barely raise an eyebrow.  Don’t talk.  Listen and observe.   Meet not just with the CTO or CEO of a company, but talk to those who experience the problem first-hand.  The more first-hand you can get the better.   Why?  Because to answer the ‘money’ questions (the ‘why’ questions), you must get at the root cause of the problem. 

Root Cause Analysis

There is a concept in science and engineering called ‘root cause’.  It basically means that if there is a problem you are trying to figure out, you want to research and understand the source of the problem.  The source of the problem explains ‘why’.  Without knowing this, the best you can do is address a symptom of the problem and your ‘solution’ is just a band-aid.

Customers are notorious for not knowing what they want.  The famous quote by Henry Ford is that if he had asked the customer what they wanted, they would have said a faster horse. Customers do not know what to ask for when trying to solve their problem because they do not know what is possible.   They do not know the solution space. 

What they do know a whole lot about is their problem.  They know what the problem looks like, how often it pops up, in what setting, who it affects, who it does not affect, what the ramifications are and the magnitude of those ramifications.  They know how acute that problem is, how disruptive it is, and what gymnastics people do now to try and solve the problem, or at least avoid it.   They know all of this qualitatively, and more importantly, quantitatively.  They know the number of times a day a problem surfaces, how much money it costs them to address it, how many man-hours it takes to address the problem. 

This is a level of engagement that usually falls outside the purview of the traditional sales and Business Development folks.  And more traditional marketing activities such as pushing out communications or messaging, or even market testing the solution set do not further the understanding of the root cause of the customer problem. But why do we want to do this work at all?  Because the most innovative products that deliver the most value to the customer maximize their signal to noise. 

Signal-to-Noise

In engineering, there is a concept called Signal-to-Noise ratio.   Signal is desirable, and noise is not.  You can get an idea of how this works when tuning your car radio to find your favorite station.  If you can dial in to the peak of the station signal, the desired music comes in crisp and clear. If there is any noise or static, it is at a low enough level you do not notice.  However, if you dial off the peak by a bit, you may still be able to pick out the songs on the station (signal), but there remains a lot of static or sounds from neighboring stations you don’t want (noise).   When you are not on the peak and instead are somewhat off to the side, the noise gets distracting or intolerable and you may decide it isn’t worth it and turn the radio off. 

Frugal product design comes from finding the maximum signal with the minimum noise.  That will keep the customer tuned in and coming back again and again each time they turn on their radio.  As stated above, you cannot sort out signal from noise from the 15,000 ft level.  You must land your plane and explore. Starting with first-hand interviews with customers is the way to find the signal (passionate emotion while describing the issue) from the noise (barely the eyebrow lifting, or even complete indifference). 

Figuring out what is a clear signal and what is distracting noise may sound like a mysterious art, but it is not.  It is not ‘founder intuition’. It is not guesswork.  It is a science rooted in robust, well-developed methods and tools currently available that can guide us through steps to validate our assumptions with customers.  With a relatively small investment in time, these methods can give us reasonable indications of what will resonate and what will not, both in understanding the problem and obtaining feedback on potential solutions.  All before product launch.  The further upstream we engage the customer with new technology, the more likely it is we get it right at launch time[4]. 

For example, Steve Blank is famous for launching the Lean Startup Revolution and the step-by-step customer discovery process co-authored with Bob Dorf in the Startup Owner’s Manual[5].  This is a process that involves extensive customer engagement to first uncover unmet needs and problems, then to get feedback on potential solutions, and finally to validate the economics around the solution and determine its business viability. Although his customer discovery process is tailored for a startup company, the customer engagement he lays out is more overarching than that.  It is fundamental and applicable to any sized company searching for new product ideas in new markets. 

High Signal-to-Noise Innovation

The minimization of noise and the simultaneous maximization of desired signal is a frugality of innovation and imparts a beautiful simplicity on a product offering.  But there are important benefits that transcend the aesthetic. 

From a cost of goods sold standpoint, minimizing noise means fewer features and less complexity.  This in turn means less time to develop which decreases R&D costs and manufacturing costs.  It also makes maintenance easier and less costly.  Simpler, good enough designs mean you are faster to market and impacts can be felt at a more rapid pace.  When savings are passed along to the customer in the form of a lower price point, accessibility to impactful technology goes up. 

Maximum signal with minimum noise means a greater resonance with the customer.  Adoption of the product increases because usage goes up, and a happy customer becomes a greater promoter of the product, which has a chain effect.  This level of adoption is difficult to achieve, but it is crucial especially for new and disruptive technologies.

In a bigger picture, however, the capability to understand problems at the root cause level, engage with customers, and map a technology to the problem to produce a great product is the definition of innovation.  The ability to deliver high signal-to-noise innovation to market in reasonable time scales and reasonable cost points is the way the country regains its innovation prowess and stays ahead of the competition.  

[1] Arora, A., Belenzon, S., Patacconi, A. and Suh, J., 2019. Why the US innovation ecosystem is slowing down. Harvard Business Review.

[2] Radjou, N., & Prabhu, J. C. (2016). Frugal innovation: How to do more with less. London: Profile Books.

[3] Blank, S. G., & Dorf, B. (2020). The startup owner's manual: The step-by-step guide for building a great company. Hoboken, NJ: John Wiley & Sons.

[4] Yohn, D.L. (2019). Marketing matters now more than ever. Forbes.

[5] Blank, S. G., & Dorf, B. (2020). The startup owner's manual: The step-by-step guide for building a great company. Hoboken, NJ: John Wiley & Sons.