I have meaning to write about the article in Venture Beat Making corporate innovation work. It categorizes innovations based on time horizons and suggests that management processes be modified based the category:
* Horizon 1 activities support existing business models.
* Horizon 2 is focused on extending existing businesses with partially known business models
* Horizon 3 is focused on unknown business models.
It is important to keep in mind that these time horizons are being described at project start. The actual completion time changes with development progresses or resource allocation. For example, a Horizon 3 project that was started 5 years ago will be near completion now and may even be considered a Horizon 1 project. So, management and application of processes needs to change as the project progresses.
It takes a long time to develop new technologies and integrate them into products. The wired article How Daimler Built the World’s First Self-Driving Semi has a great example:
Daimler, which owns Mercedes-Benz, has been working on autonomous driving for two decades.
As amazing as this thing is—it’s a fully autonomous 18-wheeler that works—company execs say it won’t can’t change lanes on its own, it won’t be market-ready for a decade, and could never replace human drivers.
Clearly, developing technologies takes a long time. So successful development needs intermediate productization of technologies.
Much of the technology in the Inspiration—the radars and cameras, the computing power and electrical architecture—has a long track record of commercial use in active safety features like lane departure warning and adaptive cruise control.
Concurrent Engineering is simultaneous development of different subsystems, technologies and manufacturing process of a product across suppliers. This iterative development process can accelerate time to market and lead to cost/performance optimization at a system level.
As we have discussed in the past, concurrent engineering is absolutely critical to fast-paced high-tech and electronics industries. Global competition means that companies cannot afford to wait for suppliers complete their development to start planning theirs. In fact, this trend is only accelerating.
However, concurrent engineering adds to product development complexity and makes management even more challenging. If leading-edge companies such as Toyota face challenges due to complexity, is it worth applying these methods to low volume products in industries such as Aerospace and Defense or to a lesser extent Medical Devices?
Recent news suggests that a new version of Microsoft’s critically acclaimed Surface Book is entering mass production. It appears that Microsoft had to make significant changes to the original Surface Book to meet some of its business goals…
The sources believe Microsoft’s decision to lower the price range for its new Surface Book is because the existing Surface Book’s high price level has significantly limited demand, while the detachable design also created conflict with its Surface Pro product line in terms of product position. Because of the two factors, the sources estimate that Microsoft only shipped 500,000 Surface Books in 2016.With the Surface Book to be positioned as a traditional notebook product and feature a friendlier price level, the sources expect related shipments to reach 1.2-1.5 million units in 2017, while the Surface Pro, despite weakening demand for tablets, will enjoy on-year shipment growth of 20% to reach six million units in 2017.
New product platforms that are significantly different from existing product-lines are notoriously hard to develop. It appears that even a very successful product platform such as Surface Book may actually need updates.
The article Heritage: Prowler was a vehicle ahead of its time. | driveSRT has some interesting data points about R&D portfolio executives. New technologies can have benefit far beyond the product for which they were developed.
“Magnesium instrument panels, aluminum hoods and aluminum suspensions, vital crash safety design. All are key traits featured on new SRT vehicles that originated on the Prowler.”
Focusing solely or primarily on NPV for financial metrics to prioritize portfolios will lead us away from long-term discriminators. It is possible to compute financial return on sustaining product development or on products that are close to getting to market. However, it is difficult, if not impossible to accurately compute the return on investment for technologies that apply to multiple products (it requires estimating the part of the products NPV is generated by the technology). In fact, focusing solely on financial metrics will likely scuttle innovation.
What are some solutions:
- Use financial metrics as one of many criteria for prioritization.
- Set aside a fraction of the overall R&D budget for innovation and do not use financial metrics for innovation projects.
- Demonstrate R&D value by tracking insertion of technologies across product lines (InspiRD can help)
- Design off-ramps and integration of technologies along the path to full productization. This is what Chrysler SRT appears to have done successfully in case of Prowler.
Companies around the globe pursue breakthrough technologies to grow. Surveys show that executives remain dissatisfied with the return on innovation investment.
The article Source: The big costs behind Google’s moonshot start-ups provides some useful data.
The debate among tech analysts isn’t about whether the moonshots will lose money, but rather how large the losses will be. Estimates cited in a recent Wall Street Journal article range from as little as $500 million in operating losses to $4 billion a year — and separately, one analyst, representing the “high estimate on the Street,” has placed a $9 billion price tag on Google’s far-flung efforts.
As we have discussed in the past, different organizations include different processes and disciplines in Research and Development. We at InspiRD have started using Research, Development and Engineering (RD&E) as a generic term that includes technology development, product development and sustaining engineering.
Integrated management of RD&E can provide immense benefits to organizations…
The article Organizing for New Technologies in MIT Sloan review has some interesting thoughts about organization structures necessary to get the most out of emerging technologies. The article starts off by defining and distinguishing invention and innovation:
To understand the challenge, one first needs to recognize the distinction between the new idea (invention) and its subsequent commercialization through a product or service (innovation). This is important because, within established companies, the decision-making processes and logic governing inventions differ significantly from those governing commercialization. Engineering and scientific personnel typically drive inventions within new technological domains, whereas business development and marketing managers drive the subsequent commercialization.
I am not sure if all R&D executives will agree with the definition of innovation, the ideas for organization structures seem to be quite valuable.
Many of the organizations we have visited often have the discussion about innovation vs. structure. The thought is that if we enforce processes and metrics on innovation, we will cripple it. The post Does Structure Kill Creativity? – K.L.Wightman lays out some interesting thoughts:
There are 26 letters in the alphabet and 12 notes in a musical scale, yet there are infinite ways to create a story and a song. Writing is like a science experiment: structure is the control, creativity is the variable.
The article “Why Is Innovation So Hard?” outlines cultural challenges that prevent innovation from taking root. As we have discussed many times, development of disruptive capabilities can often fail to achieve their intended results.
This means that in order to innovate we need to change our attitude toward failures and mistakes. Contrary to what many of us have been taught, avoiding failure is not a sign that we’re smart. Being smart is not about knowing all the answers and performing flawlessly. Being smart is knowing what you don’t know, prioritizing what you need to know, and being very good at finding the best evidence-based answers. Being smart requires you to become comfortable saying, “I don’t know.” It means that you do not identify yourself by your ideas but by whether you are an open-minded, good critical and innovative thinker and learner.