What is Research, Development and Engineering (RD&E) Management?

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…
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Organization structures for nurturing breakthrough technologies

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.
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Do Processes and Metrics Kill Innovation?

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.

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Why Is Innovation So Hard?

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.

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Failing to fail…and then accelerating our success

Alphabet’s (Google) Project Loon team has an interesting blog post with some interesting thoughts for R&D managers trying to develop disruptive innovations or moonshots.

When you set out to explore a brave, new, weird place that no one’s ever explored before, you bring along a list of things you hope are true and right. And most of the time, you discover that you’re wrong about a lot of those things — which is why I spend so much time talking about failure being a necessary condition of moonshot-taking. I want to help our teams experience this as valuable learning rather than dispiriting setback.

We need to embrace risks and possibility of failure when targeting disruptive innovation. But we also need to manage risks…
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What is Research & Development (R&D)?

At InspiRD we get to visit R&D organizations across many industries. It is interesting to see that there is some confusion around what is R&D. Some firms define R&D as only scientific research. Others include New Product Development in R&D, but not sustaining product development. Yet others exclude incremental product development from R&D. Other names for R&D include Research and Engineering or Science and Technology. Even Wikipedia acknowledges that there is some variability about what is considered R&D:

The activities that are classified as R&D differ from company to company, but there are two primary models, with an R&D department being either staffed by engineers and tasked with directly developing new products, or staffed with industrial scientists and tasked with applied research in scientific or technological fields which may facilitate future product development. In either case, R&D differs from the vast majority of corporate activities in that it is not often intended to yield immediate profit, and generally carries greater risk and an uncertain return on investment.

There are many reasons why definition of R&D changes across companies: Corporate Culture, History, Organization Structure, etc. So, is there a good way to define what is R&D?
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Gartner selects InspiRD as a Cool Vendor in R&D

Gartner, the global leader in Information Technology research, has selected InspiRD as one of four “Cool Vendors in R&D for Manufacturing 2015”.  Here is a link to Gartner Research Director Michael Shanler’s blog post:

Here is what Gartner Research Director Michael Shanler said in the recommendation section of his research report:

“Consider these Cool Vendors when evaluating technologies to drive R&D innovation and give greater insight into decision making during NPD processes.”

To obtain the complete research, please contact your IT Department to see if they subscribe to Gartner where you can obtain the full report.  Or browse our Solutions page to learn more about our innovative products.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

How to measure R&D Effectiveness?

Metrics that measure effectiveness of ongoing R&D have been difficult to obtain. Four types of R&D metrics have traditionally been used:
  • R&D Investments / Expenses
    • Total R&D Headcount
    • Total R&D Expense
    • R&D Expense as % of Revenue
    • R&D Expense increase/decrease from prior year
    • R&D Expense compared with peers/industry average
  • Project execution status
    • Performance relative to plans (costs and schedule)
    • Concept to Market Time
    • Number of Projects in the Pipeline
  • Historic results-based Metrics
    • Fraction of Revenues from New Products
    • Number of Patents generated
    • Number of Papers Published
    • Customer satisfaction with new products
  • ROI-based metrics
    • Return on Innovation Investment
    • Target NPV for each new product
The problem with most of these metrics is that they are not actionable. As we discussed earlier, R&D effectiveness needs to drive real business results. It is hard for managers to take concrete actions using these metrics to improve R&D effectiveness. All metrics need to be able to aggregate information across the R&D portfolio to help managers see trends and make decisions. Good metrics should allow segregation of management decisions into individual project level actions.
The first two types of metrics are not directly related to ongoing R&D and its projected results. For example, what would happen if we increased our headcount or reduced it? There is no easy way to understand the impact on R&D pipeline. Will it improve revenues? When? Are there key technologies that will take time to develop no matter how much money you invest? It is not easy to tie headcounts to R&D results in the future.
Historic results-based metrics such as number of patents generated are all approximate indicators of R&D performance several years in the past. Managers can gain little direct insight into ongoing R&D effectiveness from these metrics. Nothing a manager can do now will impact number of patents issued or number of papers published. More importantly, it might be better for
ROI-based metrics tend to work better with product development projects near delivery, but they are very hard to use for early stage development. Furthermore, it is hard (if not impossible) to develop ROI on technology development effort that might impact a feature in several different products (think a new type of metal that can be used in different types of cars). ROI computation becomes even more difficult for disruptive innovation.
Over the next few weeks, we will discuss new kinds of metrics that can help managers improve R&D effectiveness…

How to Manage R&D Risks?

R&D is about building something new and delivering it in the future. The process is inherently uncertain, and hence involves risk. The more disruptive the technology, the more risk is likely to be introduced. The risk comes from several sources:

  1. Technology Uncertainties
  2. Integration Uncertainties
  3. Manufacturing Uncertainties
  4. Market Uncertainties

It is not possible to eliminate these risks, but it is definitely possible to manage them. An interesting case study can be found in The mysterious story of the battery startup that promised GM a 200-mile electric car

Image Source: Quartz.com

Image Source: Quartz.com

Energy storage systems are probably one of the most important current R&D challenges. From mobile phones to automobiles to airplanes, the implications of better performance are huge — both for the companies that develop new batteries and companies that start providing products using them. Because of this promise, a small company called Envia got an opportunity to work directly with GM:

It was to contain a deal rare to an industry newcomer—a contract worth tens and possibly hundreds of millions of dollars to provide the electric central nervous system for two showcase GM models including the next-generation Chevy Volt. Untested small suppliers almost never get in the door of the world’s major automakers, which regard them as too risky to rely on. But GM was won over by what seemed to be the world’s best lithium-ion battery—a cell that, if all went well, would catapult the company to a commanding position in the industry with a middle-class electric car that traveled 200 miles on a single charge and rid motorists of the “range anxiety” that disquieted them about such vehicles. GM would have the jump on the high-end Tesla S, the only other major model with that range but one that would cost much more. For Envia, the contract could lead to an IPO that would make both men rich.

The article points out many steps that both GM and Envia took to manage the four R&D risks we laid out above. Let us get started with Market Uncertainty. Clearly, GM would have needed to take some risk in projecting demand for a new extended range car. However, for start ups and small firms like Envia, market uncertainties potentially overwhelm other types of risks. The discussion around a potential agreement with GM took a long time (as many such agreement with large companies take):

But the talking had gone on so long and with such uncertainty that neither man had even told Envia’s staff scientists of the impending deal. Even if they felt more confident, they could not have said anything, since such news could affect GM’s share price. Word had leaked around the Envia lab anyway. An edginess hung over the lunch. … Bay and Redpoint invested another $7 million in the company a year or so after the first tranche. But the startup was burning through the cash while potential customers were slow to commit.

Unfortunately, market risks are not easy to mitigate. Pretty much the only approach might be diversification: to pursue many alternate paths so that the impact can be managed if there are any changes. Many startups such as Envia may not get the opportunity to do so. Larger companies can try alternate sources of technologies or alternate product roadmaps to mitigate market risk. For managers, this means gaining visibility into, guiding and synchronizing many alternate development paths. For R&D organizations, this means managing multiple projects. Product and Technology roadmaps are a key solution that organizations can use to address the challenge of increased R&D complexity. That brings us to the biggest source of risk in this case: Technology Uncertainty. Most new technologies take years to develop. Most disruptive technologies might even take decades to mature. Both Envia and GM took several steps to manage technology uncertainty.

  1. Acquire Partially Developed Technologies: Less mature the technology, more risky it is likely to be. An easy approach to mitigating that risk is to find out if someone else who has solved the problem. Open Innovation is a common term used for this access. There are many challenges to accessing innovation and technology (differentiation, control, innovation valley of death), but that is a topic for another post.

    Kumar and the company’s early team perused patents and journal papers and consulted experts before settling on a promising cathode invented by Argonne National Laboratory outside Chicago. The cathode combined nickel, manganese and cobalt into an exceptional composite that astonishingly had not attracted a single licensee

  2. Modify Technologies Developed Elsewhere: If a small manufacturing or processing step can let a company build on research performed elsewhere, it can mitigate technology risk while maintaining differentiation.

    The cell reported to Arpa-E and sent to GM contained anode material purchased in a confidential deal from Shin-Etsu, a Japanese supplier. Kumar said Shin-Etsu’s role was unimportant—the anode’s true value emerged in the processing steps he had developed that allowed the anode to cycle hundreds of times without shattering.

  3. Leverage new sources for funding disruptive R&D: Many sources of funding such as government research grants may be available for funding development of disruptive / innovative technologies. However, other sources of funding can bring many distractions to a company and can potentially dilute the focus and energy.

    So Kumar applied for the Arpa-E competition in collaboration with Argonne. … It won a $4 million Arpa-E grant for the work to be carried out jointly with Argonne.

  4. Setup multiple intermediate gates: Divide development in phases and only commit resources for the next phase. Develop alternate plans to mitigate technology risks. Key challenge to deploying effective intermediate gates is: quality plans; clearly defined pass /fail criteria; and misaligned development pace/cycle across different components.

    But given the stringent deadline, every day counted. GM decided to delay publicly announcing the deal. Instead, the carmaker rushed a planning team to Newark three days later—on Dec. 3—to create a quarter-by-quarter schedule of milestones that ended with delivery of the battery technology for its two signature models. As Envia hit each quarterly target, it would receive $2 million.

Beyond setting up multiple approaches for mitigating technology risks, GM and Envia did many other things right. They set up clear deliverables:

The draft contract went on to be quite specific: For the 200-mile car, Envia was to provide a working battery delivering around 350 watt-hours per kilogram that could endure 1,000 charge-discharge cycles.

They defined a clear timeline:

Kumar’s deadline for the 200-mile battery was October 2013. After that, adjustments could be made to optimize the performance until Aug. 15, 2014. But that was a full-stop deadline—Kumar could make no changes to the battery after the latter date. This point was critical to GM because once the battery was ready, all the other deadlines could follow, ending with the pure electric car’s actual launch in 2016.

And the defined intermediate milestones:

Instead, the carmaker rushed a planning team to Newark three days later—on Dec. 3—to create a quarter-by-quarter schedule of milestones that ended with delivery of the battery technology for its two signature models. As Envia hit each quarterly target, it would receive $2 million.

Envia tested and demonstrated disruptive capabilities:

It was Kumar and his Envia team. Envia, he said, had just reported (pdf) the achievement of “the world record in energy density of a rechargeable lithium-ion battery.” It had produced a prototype car battery cell that demonstrated energy density between 378 and 418 watt-hours per kilogram. Envia said the achievement had been validated by Crane, the Indiana-based testing facility of the US Naval Surface Warfare Center, which cycled the cell 22 times.

That brings us to Number 2 on our R&D risks: Integration Uncertainties. Technology capabilities that are demonstrated in a lab environment may not translate to real world results. More importantly, as the technology is integrated with other components necessary to get it to market, new problems may arise. R&D plans and roadmaps need to clearly account for these uncertainties and allow plenty of time to address them. That did not quite happen in Envia’s case. They had less than a year to move from a hand tweaked battery to mass producible system.

Increasingly alarmed queries piled up from GM in phone calls and meetings. The Arpa-E results could not be reproduced—not by a long shot. Meeting a team from the carmaker on March 4, Kumar “struggled to allay GM’s concerns,” according to Kapadia’s lawsuit. A document provides a sense of why GM was concerned.

The team never even got to a stage where they would need to address manufacturing uncertainties (Number 3 in our list of risks). Many times we can produce small batches of widgets, but processes required for mass production may not be supported. Again, the only way to mitigate this risk is careful planning, intermediate milestones (that verify manufacturability) and adequate resources…

A year later, the deal is in tatters, GM has accused Envia of misrepresenting its technology, and a document suggests why the carmaker may be right. The startup’s unraveling is a blow for GM as it transitions to a new regime next month under CEO-designate Mary Barra, setting back its ambitions in the potentially gigantic future electric-car industry. It also risks making Envia, the recipient of several small federal grants, another punching bag for critics of US government funding of advanced battery companies.

Here is the summary: R&D is risky. Some R&D efforts will fail — and that is a good thing as it means that the organization is encouraging responsible risk taking. However, the risks should be managed carefully and failures should be caught early, before significant resources have been expended. A good R&D planning process and robust tools may help.

Why Improve R&D Effectiveness?

Research & Development (R&D) is a critical component of most business strategies, and a driver for market success. However, executives typically have little visibility into the R&D pipeline or the value being generated in R&D.

Overall, like any other corporate function, improved R&D effectiveness can have two potential impacts: Improve Revenues and/or Reduce Costs. Let us explore how:

  • R&D can help increase revenues by:

    • Gain market share by developing and delivering more innovation to customers
    • Improve Average Sales Price by providing differentiating capabilities to customers
    • Address new market segments by quickly developing new products using existing capabilities and components
  • R&D can help optimize revenue timing by:

    • Align R&D pipeline with corporate strategy
    • Accelerate or slow-down R&D efforts to maximize market impact
    • Efficiently modify R&D portfolio based on new competitive or market challenges
  • R&D costs can be reduced (without significantly impacting delivery) by:

    • Leverage cross-product synergies to effectively reduce costs of developing any new feature
    • Reduce R&D management overhead costs
    • Provide R&D teams early and better visibility so they can reconfigure projects at minimal costs
  • Avoid costs of wasted development efforts:

    • Identify and kill non-viable or pet projects that have no planned insertions into new products
    • Find projects with schedule slack and slow them down to ensure parts of a new product are not ready before others
    • Effectively monitor R&D portfolio and find and fix problems early

However, as most managers know, these are hard objectives to achieve. Key challenges are:

  1. Lack of visibility and access: R&D is spread over many teams and locations. It is hard to get quick and easy access to status of the R&D pipeline. It is hard to aggregate the R&D pipeline to make management decisions and then segregate management decisions into individual R&D project-level actions.
  2. Long development timelines: The impact of decisions is not felt for quite some time. That means it is hard to make decisions that address current strategic or market challenges. It is also hard to perform what-if analysis to decide on the best course of action
  3. Complex interdependencies: R&D portfolios require investments in multiple products and technologies at various stages of maturity. Delays in one development project can have significant impact on others and on the overall development schedule. It is hard to make decisions while keeping these complex interdependencies in mind.
  4. Lack of Metrics: Most R&D metrics tend to give information about the past (such as Revenue from New Products or Number of Patents Generated). There is a lack of metrics that allow managers to quickly assess the health of the R&D pipeline and make decisions about improving it.

This blog is going to focus on both the benefits of improved R&D effectiveness and challenges to getting there…