product development processes
In recent months there have been increasing mentions of the concept of “desktop manufacturing” in both technical and lay press. “Desktop manufacturing” refers to the use of 3D Printing technologies to generate products using designs developed on or delivered to a user’s computer. This revolution has been coming for some time; with Fast Company stating that “the end of the current production- manufacturing economic model may be on the horizon” back in 2009. In a keynote at the FEI 2012 conference Chris Anderson of Wired magazine spoke on the new business models that these technologies are enabling –enthralling the audience with stories of successful application of the technology. Anderson went so far as to say we are only at the dot-matrix stage of this technology, with massive growth and development poised to occur.
Indeed, increasingly advanced 3D printers and the computer-aided design (CAD) programs that support them are being made available at lower and lower prices to small companies that rent time and capacity to other companies and to individual consumers with the interest.
But why should this topic be important to the Osmotic Innovator?
– Rapid Prototyping: the ability to quickly turn-around prototype products should not be underestimated. Only 10 years ago prototypes were used sparingly due to cost and time to manufacture, limiting consumer interactions with test concept designs to 2D images and descriptions. Even today many large companies have their own 3D printing capacity to churn out test designs quickly. The 3D printers of tomorrow may be simple enough to allow product developers with no design experience to create and modify innovative new solutions early in the process. It appears inevitable that the 3D printers of tomorrow will be capable of handling multiple materials to create complex mechanical objects. Making efficient use of these systems has the potential to transform the product development process even further.
– Do-It-Yourself Mentality: the students of today (as well as many of the tinkerers) are beginning to see this technology as a normal part of doing business. Whereas teams that want to have the capability to model and create products on the fly currently need to staff individuals with design competency and engineering backgrounds the skills needed to use these tools are increasingly part of a basic technical education. Workshops that allow creative people to access these tools in their free time are also democratizing the product development process, making it possible that competition (or opportunity) for your company is going to come from unanticipated sources in the future. Your best customers might become your worst competition as they are able to harness this technology to make their own product improvements. Having a strategy to harness this technology and those with the skills appropriately will part of doing business in the future.
– Future Technologies / Business Models: just as desktop publishing transformed the creation and distribution of printed content innovators should be ready for desktop manufacturing to have a similar impact on the creation, manufacturing, and distribution of new products. How your company will respond to, or position itself within these changes will go far to determining its future.
Regardless of your experiences with desktop manufacturing in the past, it is clear it is a concept that is poised to transform a multitude of industries. As an Osmotic Innovator there are a number of opportunities that can be leveraged to boost your teams’ effectiveness. Are you ready to seize the chance before your competitors do?
Innovation projects within corporations can take a long time, a really long time. These projects often involve lots of people and even numerous ownership changes along the way as different specialist groups contribute their skills. Managers are very much aware of this however and have any number of great modern inventions to manage the risks associated with long project leads, knowledge transfer and project ownership. Just think of the highly detailed Gantt charts, the agile management tools, the strategy meeting minutes and risk analysis reports that reside on your corporate servers, all testament to the pinnacle of project management that we have reached in the early 21st century. Because of all these modern tools it is now impossible for a project to deviate off course, to lose its way and end up in a place that was not intended. Modern project management techniques ensure that we always deliver what we started out to deliver and the economy and the world is a better place for this. Wait…what?
So, I expect that you agreed with most of the above paragraph until maybe the last few sentences. Most of us have experienced a project deviating from its goal, maybe through a slow erosion of the understanding of the original intention, claim creep over time or a simple loss of way due to personnel change at a key juncture. In our arsenal of modern project management tools is there something missing that might help us eliminate this issue? If not, should we be developing something? I suggest that there is a tool that can be used to help corporations but that it won’t be found in Silicon Valley. The tool is as old as humanity and within us all to develop. It is the art of storytelling.
Throughout history humans have managed projects. Our earliest projects may have been something like relocation of tribal groups or the exploitation of newly found food sources. During this time the project management tool most often used was storytelling (Note: This is an assumption the author has made based on the lack of Neolithic cave paintings depicting Gantt charts). Storytelling allowed complex themes with numerous important yet discrete facets to be remembered because it provided context and a relationship between the discrete elements of the theme. If Timmy isn’t stuck down the well, Lassie is just a dog running around barking and doesn’t make sense.
So how can we incorporate storytelling into our project management programs? The solution is to first think about what modern storytelling looks like. In the context of a consumer product, the story might take the form of an advertisement, maybe in video or billboard form. It could take the form of a written consumer concept or a cartoon describing the experience of the consumer. A service story might be told through the written diary of a satisfied client or mock interview. In many cases our companies are quite adept at making these stories; we just tend to make them once a project is nearing completion which renders the use of the story as project management tool redundant. The key thing that any storytelling tool should do is allow for a simple, understandable way to communicate project goals and underpinnings to new team members or management reviewers. It should enthrall and energize the project and ensure that throughout the various personnel transitions each new member champions and rallies around the common and original goal. Next time you kick off a big project consider developing some story media early on in the process, you will be surprised at the effect it can have.
We take it for granted that we live in a world of data. Google and Facebook both rely on user data to drive their innovation and products while constantly creating new ways to collect and use that data. Facebook is a great example: “[it] has some 750 million users, half of whom log in every day. The average user has 130 friends and spends about 60 minutes a day tinkering on the network.” Thanks to programs that allow them to monitor your every click the company is able to understand its consumer to an extent never before seen. In fact, it is now sometimes said that ‘Every second of every day, more data is being created than our minds can possibly process.’
This new paradigm, what some term the ‘knowledge economy’, has spread into every industry and has quickly become a standard factor in internal product and innovation evaluations. We now have a wealth of information about our consumers that we can use for good . . . or bad. As well, consumers now know far more than they ever have before. For the Osmotic Innovator, it is important to understand how this happened and how it has impacted the way we should go about innovation.
In reviewing the impact of the knowledge economy on product development and innovation we don’t need to go to far into the past to find a time when data was not so easily obtained yet product development was undergoing a renaissance. At the turn of the century, after the industrial revolution had changed both the way consumers lived and companies grew, people like Ford and Edison made fortunes inventing new products that have since become iconic. But for every Ford and Edison success there were many failures – like Edisons’ automatic vote-tally system for Congress – or a failed inventor whose radical ideas never were embraced in their time (think about Tesla). The number of failed innovations during this time period was enormous, just as some of the successes (the Model T and the Light bulb) were equally enormous. Without access to data, companies and inventors trusted their gut, valuing passion for a product as the driving force in creating and launching into the market.
Moving forward to the 1950’s & 1960’s one enters another golden age in product development in Western economies – the age of marketing. If you’ve ever watched an episode of Mad Men you know the stereotypes: bold marketers using data (and their intuition) to make new products successful by attempting to actually understand and meet new consumer needs. With a market already satiated by 50 years of new products and innovation, companies saw segmentation of markets and use of data to identify the best and safest product launches as one way to obtain a competitive advantage. Data was available and used, but it wasn’t the primary driving factor in innovation. Did this increase the number of product successes or the ratio of product success versus failure? We know that product launch success was actually higher in the 1950’s than now, but don’t have the data to understand how this stacks up against earlier periods.
Fast forward 50 more years to present day – the era of the ‘knowledge economy’. Vast improvements in computing have allowed equivalent improvements in analysis and theory. No product is launched by a large company without extensive vetting through any number of market research toolkits and analytical systems. Consumers are split into segments and dissected in every way possible as companies in mature and developed industries look for any possible unmet need. Disruptive products that don’t fit the models are scrapped while incremental innovations are launched because they are able to fit into the segments that have been so carefully developed. In many ways, the innovator in a large firm is now crushed by the weight of the data available to them instead of empowered. With all of this data in hand guiding decisions for large firms we must have achieved a new high in new product launch success, right? Actually, current measures show that only 1/3 of NPD launches are ‘successful’ – and the consensus is that this number that has actually decreased since the 1950’s. Obviously, the exponential increases in data and advances in market research tools are not returning an equivalent value in NPD success.
One might argue that only companies ignoring the market research ‘facts’ are launching disruptive new products – the ones that actually capture real substantial value and create new markets. Take it from Steve Jobs, praised universally for being a disruptive thinker and innovator: “When asked what market research went into the iPad, Jobs replied: “None. It’s not the consumers’ job to know what they want…we figure out what we want. And I think we’re pretty good at having the right discipline think through whether a lot of other people are going to want it, too.””
The figure below shows the growth of the ‘knowledge economy’, the corresponding drop in the capacity of a large company to launch disruptive or truly innovative products, and relative product launch success rates. Unless your company is willing to ignore conventional market research and analytical tools – which some might call wilfully ignoring your consumer – delivering true innovation to the market is nearly impossible. That is why disruptive innovation seems to come from smaller companies and start-ups; without a business to protect and with few resources, market research is an unnecessary luxury.
Looking at the discussion graphically – the question to ask is why are companies so reliant on data and market research when using it encourages incremental innovation without improving new product launch success? This is the trap of the knowledge economy: it promises to remove risk from new product development yet prevents the innovator from truly exploring disruptive innovation that could create new markets.
How can the Osmotic Innovator avoid falling into the trap of the knowledge economy?
- don’t make every product fit the models currently used by your company
- be willing to trust your organizations understanding of what the consumer will want (just like Steve Jobs)
- be bold in launching risky products in the face of failure – most ‘safe’ products fail anyways
Are these prescription alone enough to solve the problem of low NPD launch success rates or change the reliance of mature companies on data? No. But they should give the Osmotic Innovator something to consider the next time you are working through the portfolio.
When Fast Company ranked the 50 Most Innovative Companies for 2011 a glance at the top ten would seem to tell you one thing: the cutting edge of innovation is headquartered on the web and that, by-and-large, companies in mature industries need not apply. Does this mean that companies in mature industries need to begin raiding Silicon Valley for a new wave of entrepreneurs to replace their failing ones? I think not, as I will argue below many of the companies on this list benefit from an overly positive view of the virtues of ‘creative innovation’ compared to ‘constrained innovation’.
Most readers will be familiar with Everett Rogers theory of diffusion of innovations[i] – in his book Diffusion of Innovations Rogers’ argues that as technology is applied to a market, penetration phases from low to high along an S-curve while adoption follows a bell-curve with innovators and early adopters in the first phases and laggards at the end.
The S curve model is often also applied to technology development. Traditionally, the focus is on the creation of new technologies (embodying radical or disruptive innovations) that can create a new curve (curve B) and restart the adoption bell-curve.
However, firms in established markets often face a reality where no new technologies or disruptions are available to replace the current one and ‘incremental’ innovations become the only currency for retaining and gaining market share in the face of slow segment growth. It is within this space, where market penetration is near complete and technologies are mature that innovation becomes a real challenge (line C extension of Curve A). This is not to argue that radical and disruptive innovation is unimportant for corporate strategy, rather that it is essential to utilize incremental innovation to maintain market leadership in the absence (or during the development) of these types of innovation.
But why is it that incremental innovation is so often ignored in favor of innovation occurring at the leading edge of technology? Disruptive or radical innovation has the potential to capture the imagination not to mention the market, however, it is the incremental innovation that sustains a company while it seeks out success in these riskier areas. Companies themselves often discount their own incremental innovations – selling the innovators and themselves short in the process. This is especially frustrating to those in these environments because successful incremental innovation can be very difficult.
To understand the key differences between innovation on the leading edge of technology compared to the trailing edge the curve could be moved to a graph that shows ‘constraints’ increasing as a market or space matures. This reflects the fact that in mature markets development is constrained by higher expectations and limiting technical specifications. For sake of simplification, the curve could then be viewed in two halves around the inflection point: to the left, the ‘easy to innovate’ space, and to the right, the ‘hard to innovate’ space. (Figure 3) It is important to note – ‘easy to innovate’ is no guarantee of commercial success. For a specific example, Pets.com seemed like an easy win or innovation early in the development of the web however was a commercial failure.
Radical or disruptive innovations aren’t necessary early in a technology or market development because artistic creativity or marketing can be nearly enough to ensure continued growth, while later in development high levels of skill are necessary to continue innovation for growth when it is most important. If it were to be considered in scientific terms, it is as if in the initial stages of technology or market development innovation is free from constraint – few rules apply as companies develop the market. Take a look at the lists of ‘Most Innovative’ Companies for 2010 or earlier – it will be littered with failed start-ups and failing companies. The winners, or those that define the market, find themselves in an interesting position when the market or technology has matured. At this point, the survivors are forced to work within a falsifiable system – a system with highly developed rules and limits to pure creativity. Masters of innovation in these environments are people that can operate creatively within a highly restricted area, like Einstein developing the theory of relativity within the bounds of Physics.
Innovation in a developed market or technology field means meeting a very advanced set of customer expectations. Staying a market leading company in this case requires maintaining an advanced core technical skill set, absolute focus on the customer, and the ability to quickly transform ideas into products with limited time for redesign. This balance of skills is what we referred to earlier as ‘constrained innovation’ – the ability to create new products and excite the customer while operating within a strict set of conditions established by the market.
Can and should firms focus on creating new markets using radical or disruptive innovation? Yes. However, one cannot ignore the fact that without a strong ability to deliver ‘constrained innovation’ firms will not survive long enough to implement the more widely appreciated types of innovation. That, the ability to grow and survive regardless the market constraints, is why ‘constrained innovation’ should be recognized as an essential and critical function for any firm that should be more widely appreciated by the world at large. Imagine if we recognized the best innovations of 2012 as those that succeeded despite constraints – would we be talking about the innovators from Ragu, Dunlop, Haines and Colgate instead of Facebook, Twitter, and Google?
Most product development processes within corporations rely on a regular transition of responsibility as an idea progresses from conceptual to final product. Some of the most common examples are transitions between inventors and feasibility assessment teams, feasibility teams and development teams and even marketing and R&D operations. Often these transitions are also where we see the product development process fail as the product idea never fully takes hold in the imagination of the new team and fades away. One of my preferred ways of visualizing the issues that can arise during transition is through an analysis of idea “ownership”.
The chart in figure 1 describes the level of ownership that a team developing a particular innovation may experience over time. As the team starts out the commitment level is relatively low, no one has spent much time on the initiative and there are many different paths to success still available to the team. Over time the team feels more commitment towards the innovation path and the sunk cost of the current program of work increases, this increases the ownership of the program.
Within every product development project there is a level of complexity that the team is expecting to encounter. This expectation can vary significantly (think landing a man on mars vs. developing a new flavour ice cream) but the important factor is that there is an expectation. Deviations from this expectation are what we call “problems” (or occasionally “lucky breaks”). Tasks that do not deviate from our expectation of complexity are what we call our day job. The chart in figure 2 describes an example of the complexity curve for a project over time.
If we begin to think about how we could measure complexity in the above example it becomes obvious that the level of complexity of a given problem could be measured by the level of commitment and effort required to solve said problem. In essence what we are saying is that every problem we encounter within the product development process will require a particular level of “ownership” in order to be overcome. This allows us to overlay the two previous charts with the common y axis of the theoretical construct “ownership”, see figure 3.
Ownership and the transition
Turning our attention to the concept of ownership as it relates to idea transition between corporate groups we can imagine a (worst case?) scenario where the ownership level of the accepting group post transition is extremely low, Fig 4. This low ownership scenario can arise for many reasons including a lack of understanding of the idea potential, a poor incentive structure (the fabled “not invented here”) or simple housekeeping such as stressed resources limiting the interest in yet another project.
Fundamentally, a project in a low ownership situation is fragile. Problems encountered during this state can cause the project to fail as those responsible for the next development stage see the hurdles as insurmountable, Fig 5. Often these same hurdles are seen in a very different light by those who continue to experience high ownership for the project.
Bridging the gap
How then to avoid issues arising from transition fragility? Obviously one cannot control when an unexpected problem may arise during a project but it is possible to influence ownership in the lead up to, and directly after a responsibility transition. Examples of how this can be achieved are numerous but a couple worth considering include shadowing programs which engage the second group in the decision processes of a project prior to transition, Fig 6. Shadowing programs allow a new transition group to develop understanding and commitment before they take ultimate responsibility for the project.
Another approach uses dovetailed leadership structures which create matrix teams during transition, Fig 7. In this instance a temporary matrix team is formed during transition consisting of the (low ownership) core of the second team reporting into the (high ownership) management of the first team. After a fixed period of time the matrix team is disbanded and reporting lines are reset. This allows for a soft transition where high ownership individuals are always present in the responsible project team.
The innovation transition process within a corporate innovation program can be a very complex procedure in which success is as much down to the personalities of the individuals as the rigor of the systems employed to control it. Companies that focus on solely on the mechanical aspects (document control, handover procedures, technology debriefings etc) may be leaving themselves open to failure through no fault other than the realities of human psychology and the timing of a project hurdle. Innovation programs that incorporate ownership management within their transition processes go a long way to reducing that risk of failure.