Why Open Innovation is hard to implement

We have often discussed how innovation has become a buzzword with many myths surrounding what drives innovation. I was recently discussing Open Innovation with an R&D executive. He made a pretty significant remark: There are lots of positive articles around open innovation, but there do not seem to be many balanced evaluations of the approach. Fortuitously, Knowledge@Wharton has an interesting note about The ‘Flip Side’ of Open Innovation that addresses some of the concerns.

A lot of people have been writing about open innovation,” says Wharton management professor Felipe Monteiro. A typical example, he adds, is Procter & Gamble’s Connect + Develop strategy, which encourages collaboration with outside organizations as a way to bring new products to market faster and more efficiently.

While the P&G approach “has gained a lot of traction,” Monteiro notes, it also raises questions about whether, and when, companies should be concerned about protecting their own knowledge. Monteiro’s research into this issue has led to a paper titled, “Does Strategic Protection of Knowledge Undermine the Effectiveness of External Knowledge Sourcing?” co-authored with professor Michael Mol from the Warwick Business School, and professor Julian Birkinshaw from the London Business School.

I am going to use the article as backdrop to summarize four key concerns about Open Innovation and why it appears that many companies are not really recouping their open innovation investments (much less earn a return on them). We should all think carefully about these before investing in open innovation:

Valley of Death: A key concern in innovation is getting it transitioned into delivered products. Many companies I have worked with fail pretty frequently at this stage. We have discussed the valley of death extensively. The more disruptive (and hence the most valuable) the innovation, the more difficult it is to get it to market because it disrupts company culture and bureaucracy. When accessing innovation from the outside, this becomes even more difficult because of “Not Invented Here” mentality. Unless one can find an internal technologist or champion, open innovation just withers on the vine. This is very hard to overcome and needs active management involvement.
Trade Secrets Protection: We have often discussed how innovation is not about an aha moment or one brilliant idea. Innovation happens at the interface of multiple disciplines and technologies. (For example, iPhone could be seen as combining a capacitive touch screen with low power processing and an intuitive user interface. Each was available in the market, but the integration generated value). To access innovation from the outside, companies will need to share their problems in enough detail that potential suppliers can describe solutions. However, this description will also be available to all competitors – which defeats the whole purpose.
Evaluation / Management costs: As discussed earlier, managers need to consider many potential issues before deciding on accessing any innovation from the outside. A key issue that is forgotten is the time involved in evaluating innovation ideas. Because of trade secrets related problems described above, most companies use open innovation to access ALL innovation. Broad ideas need to be filtered before they can be sent to the technical teams – a task that requires management involvement. Companies quickly realize that this is VERY expensive. Even when ideas sound interesting, the value is difficult to estimate. Innovation needs to be accessed when needed – we can not just let innovative ideas sit on a shelf and get to them when the need arises. Innovative ideas require maturation and many cospecialized assets to get them to market. This is not cheap to evaluate.
Liability: When suppliers submit their ideas to companies, how should they be protected? Any implied protection exposes the company to potential litigation liability. Disregarding inadvertent public release, consider the possibility of independent discovery. The company may have independently developed ideas similar to those accessed through open innovation. If they decide to use internal ideas, they might still be exposed to IP litigation. Hence, most companies ask suppliers to submit ideas with all rights released! Most people are not willing to do so…

I welcome comments…

More Effective Financial Incentives

Over the weekend I had a long discussion with a friend about Occupy Wall Street and what is wrong with our corporations. A few themes emerged that may actually be interesting for R&D management as well. It has been shown that executive remuneration has grown much faster than average worker. It is also felt that the pay is disproportionately large.

A key problem with driving executive performance is the inability to tie pay to performance. Decisions made by executives have impact months (if not years) later. So, rewards based on current stock price do little to guide executive performance. Traditional approach has been to provide stock options that vest over a long period. However, stock options have shown to be ineffective in driving performance. This is mainly because the vesting of options does not have a direct relationship to the decisions made by the manager. Stock price in the future will depend on performance across multiple products. Furthermore, options will vest either with time, no matter what happens in the future.

So, here is a proposal: Why not tie rewards to performance based on actual performance of new products developed by a set of executives? R&D executives are responsible for deciding which products to develop and how. The primary and largest reward could be a fraction of the profits generated by these products when they actually reach the market (True Profit Sharing). Most organizations develop (and maintain) a business case for pursing any new product. Hence the executive reward can be built directly into that business case. Boards of directors can monitor performance using the same business case. This approach ties rewards to actual decisions executives make on new product development.

One concern of this approach might be that True Profit Sharing will generate bonuses over a long time frame. Executives are also responsible for managing R&D execution, operations and guiding sales. So, We need other bonuses that encourage performance for near and mid-term. To do that, we can tie a part of bonuses to operational effectiveness:

Health of R&D pipeline (various metrics can be used) generates annual rewards (bonuses)
Cost and schedule performance of each new product generates near-term rewards
Third party reviews and market reaction when the product is introduced contributes to mid-term rewards

We can construct similar approaches for marketing, sales, manufacturing etc. This model has the advantage that each decision has direct consequences to rewards. Just a thought…

A wake-up call for Big Pharma

Another interesting article in the McKinsey Quarterly “A wake-up call for Big Pharma” describes how big pharmaceutical companies are becoming less innovative. We had discussed the same trend in the past (Big Pharma’s Stalled R&D Machine). This chart from the article has great data about declining contribution of new products to the bottom line:

Some more evidence of this lack of innovation is in the Booze’s Global Innovation 1,000 list which does not rank pharma companies as very innovative. The article further suggests that some fundamental changes are necessary:

The good old days of the pharmaceutical industry are gone forever. Even an improved global economic climate is unlikely to halt efforts by the developed world’s governments to contain spending on drugs. Emerging markets will follow their lead and pursue further spending control measures. Regulatory requirements—particularly the linkage among the benefits, risks, and cost of products—will increase, while the industry pipeline shows little sign of delivering sufficient innovation to compensate for such pressures.

The article suggests that the pharmaceutical industry might evolve away from vertically integrated model like the automotive industry.

A look at the evolution of the automotive industry may offer some lessons. For many years, it was vertically integrated and dominated by large, primarily Western corporations. But the value chain has been disaggregated into companies specializing in narrow parts of the process. Today, component manufacturers, design houses, and basic-materials companies share much of the industry’s revenues: the automakers are responsible primarily for the design of major components (such as engines), assembly, sales, and marketing.

This whole article is a very interesting read. I suggest you consider reading it.

Creating Leaders

The article The NY Jets’ Mike Tannenbaum and SAP’s Bill McDermott: Creating Leaders On and Off the Field in Knowledge@Wharton has some interesting pointers for all R&D managers.

1. Provide precise and candid feedback (even when negative):

“The most important thing a leader can do is give people feedback,” McDermott said, recalling a meeting where an executive was complaining about a mistake made by an employee. “‘What did he say when you told him about it?’ I asked, but there was silence.” Employees deserve the respect of candor, McDermott noted, and they need to know what is expected of them and have a clear understanding of their employer’s strategy and culture.

2. Provide a big long-term vision that can get the team excited.

McDermott and Tannenbaum agreed that a leader has to focus on promoting an overall vision for his or her organization rather than dwelling on the small stuff.
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“Our thing is to go big or go home,” McDermott said, noting that SAP has had many opportunities to buy companies that would catapult the firm into a new business category.

3. Be careful in selecting team members and look beyond resume / technical capabilities:

“When he was on the cell phone in the car, did he treat the person on the other end with respect? … How did he act with the waitress? Your character is what you do when no one is looking. That will make for a better team, where everyone knows what everyone else’s job is, and we all work together.”

Something we can all learn…

Booze’s 2011 Global Innovation 1000

I have been meaning to post about a pretty good survey by Booze (Global Innovation 1000). The study has a lot of useful data for benchmarks. The overall message is very important:

As our annual Global Innovation 1000 study, now in its sixth year, has consistently demonstrated, the success of these companies is not a matter of how much these companies spend on research and development, but rather how they spend it.”

Here is the data supporting the hypothesis:

For the second year in a row, Apple led the top 10, followed by Google and 3M. This year, Facebook was named one of the world’s most innovative companies, entering the list at number 10. In a comparison of the firms voted the 10 most innovative versus the top 10 global R&D spenders, Booz & Company found that the most innovative firms outperformed the top 10 R&D spenders across three key financial metrics over a 5-year period — revenue growth, EBITDA as a percentage of revenue and market cap growth.

I guess being a consulting house, Booze would like to teach organizations how to spend their cash… But still, it is an important message. We need a culture that supports innovation and strategic alignment of innovation with goals (duh!).

Every company among the Innovation 1000 follows one of three innovation strategies — need seeker, market reader, or technology driver. While no one or another of these strategies offers superior results, companies within each strategic category perform at very different levels. And, no matter a firm’s innovation strategy — culture is key to innovation success, and its impact on performance is measurable. Specifically, the 44 percent of companies who reported that their innovation strategies are clearly aligned with their business goals —and that their cultures strongly support those innovation goals — delivered 33 percent higher enterprise value growth and 17 percent higher profit growth on five-year measures than those lacking such tight alignment.

Here is some interesting commentary from 24/7 Wall ST:

The overlap of these “innovators” with the firms that spent the most money on R&D last year is small.
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The difference between the two lists is that the largest spenders mostly invest dollars to stay in the places they already hold in the business world. Pharma companies need to replace drugs that are about to come off patent, or already have. Old world tech companies like Microsoft and Intel need to keep pace with firms that have new successful hardware and software products that challenge their sales. Auto companies are in a race to make their cars and light trucks safer and more useful to consumers.

May be it is just the industry companies are in and the maturity of the market place:

It is easy to believe that the companies growing the fastest and with the most attractive products to consumers and businesses are the most innovative. This will not last for those firms. Eventually all companies spend R&D money to hold their positions within their industries. It is just a matter of the age of the each company’s products and the state of new competition, which is always entering the market — often aimed at the innovators with sharply growing sales.

So, do we believe that all the current innovators will remain innovative for the foreseeable future? Probably not:

But Apple, Facebook, and Google are only a few years away from the need to spend R&D money to hold their own rather than advance rapidly within their own industries. Almost no one believes it about Apple, but eventually there will come a time when its revenue growth is no longer in the high double digits. Google’s products like

I guess every on believes that Apple will be an exception! Even without Steve Jobs?

Risks of government investment in innovation

We have often talked about the role of the government investment in driving innovation (and here). We had identified the risks of government investment as corruption and inefficiency. We had also discussed potential solutions: 1) Have a large number of industry participants competing for government investment and 2) address smaller industries such as wind power for innovation investment (as opposed to large fixed cost industries such as high speed rail).

The article How do we know that China is overinvesting? by Prof. Pettis has one additional major risk – lost economic value. The article discusses large investment made by the Chinese government in the electric car industry:

The electric car industry was often Exhibit A in the argument that Chinese investment was in the aggregate rational and economically sensible. This industry is clearly the industry of the future, the China bulls argued, and China’s massive investment in the technology, which would allow the country to dominate one of the key sectors of the future, showed why it was mistaken to complain about capital misallocation. This kind of investment was actually very clever stuff.

Prof. Pettis points out two major concerns about the investment:

Whether the total economic costs of investment are less than the total economic benefits: Innovation should create additional wealth for the country that more than offsets the government investment.
Whether there is a mismatch in the timing of costs and benefits: Even if the value generated is positive in the long-term, it might be negative for short to medium term and harmful to the economy.

These are good question to ask, but probably difficult to answer effectively. Computing economic value of an innovation investment is likely expensive. It would be difficult to build a business case to invest in the effort to compute economic value. However, the key problem that the article identifies is very valid:

… risky high-technology ventures are not best funded and directed by companies, industries and policymakers who are historically weak in the technology sector, especially when they have no shareholder or budget constraints and have almost unlimited access to heavily-subsidized capital. This seemed to me a recipe for wasted investment.”

After the significant thrust by the Chinese government in electric vehicles, the reality set in – there was no market for the electric vehicles. Instead of redirecting the innovation investment, the government tried to compensate for it through regulation:

…a directive signed by four government ministries encouraging 25 pilot cities, including major markets such as Beijing and Shanghai, to “actively study” exemptions for electric cars from license plate lotteries and auctions, as well as a host of other purchase restrictions.

Hence, the industry was propped up:

The only way to make electric cars economically viable in China, in other words, is to put into place administrative measures that divert buyers, but as any economics student can tell you, these kinds of administrative measures simply shift resources from one sector of the economy to another without creating wealth. In fact because they force consumers to choose something that they otherwise wouldn’t, they actually reduce overall wealth.

One way to justify this additional regulation could be reduced emission / pollution. But the fact that the regulation was not planned in the first place, and is being considered solely to account for lack of market demand reduces the efficacy of that justification.

So, we could add a couple more solutions to our list: 3) Target small businesses for the bulk of the innovation investment; 4) Focus on investment, not regulation to promote adoption of innovation; and 5) if regulation is necessary, plan for it upfront while deciding the investment.

Large vs. Small Team Performance

Knowledge@Wharton Research Roundup has some interesting learning about team performance. Increasing team size improves performance, but reduces team member satisfaction:

When it comes to teams, less is sometimes more. In a recent paper, Wharton management professor Jennifer Mueller found that while larger teams generally are more productive overall than smaller ones, members of the bigger groups were less fruitful individually than their counterparts on the smaller teams.

There are thought to be three major challenges to effectiveness of large teams:

Motivation loss: Being one of the members of a large team could reduces the sense of ownership, and hence reduce motivation to perform.
Coordination loss: Larger the team, bigger the effort required to coordinate activity. This would reduce overall efficiency of the team.
Relational loss: Large number of people involved prevents members from forming deep relationships. This lack of networks reduce collaboration and efficiency.

Based on study of 26 teams with 238 team members, the author found significant support for challenges 2 and 3 (but not for 1). The article of team satisfaction has potential solutions to these challenges.

Innovator’s DNA: Some are born, others can learn

A couple of related articles in INSEAD Knowledge (Innovator’s DNA and Innovator’s DNA: Some are born, others can learn) are quite interesting:

Some people are born innovators. Others can become innovators, providing they follow some simple guidelines. That’s the thesis of ‘The Innovator’s DNA’, just published by Harvard Business Review Press, by Hal Gregersen, INSEAD Senior Affiliate Professor of Leadership, with Jeffrey H. Dyer of Brigham Young University and Clayton Christensen of Harvard Business School.”

The premise is that we can all learn to be more innovative:

Research involving identical twins suggests that only about 20-25 per cent of our creativity ability is geneticically driven. “This means the other 75-80 per cent comes from the world we live in…

Here is my takeaway about five skills that can make us more innovative:

Observing: Innovators are “intense observers.” They learn from observing others.
Questioning: Innovators ask questions about what they have observed to find out if there is a better solution.
Associating: Innovators make unexpected connections and combine known pieces into new solutions (such as iPhone or iPod).
Experimenting: Innovators experiment with solutions to potential problems to find the optimum.
Networking: “Innovators are intentional about finding diverse people who are just the opposites of who they are, that they talk to, to get ideas that seriously challenge their own.”

Here is all of it put together in a nice summary:

Take notes when observing others. “Step back from (the problem or situation), talk to people: ‘What did you learn? What surprised you? What was interesting?’ If you like to talk to people, talk to somebody different: maybe on another floor, a different building, a different office, another country, but talk to somebody who’s 180 degrees different from you. These are things that we can do and they don’t take a lot of time to do them.”

Collaboration for New Service versus New Product Development

Another quick note: This one about differences between collaboration in new product development vs new service development in the Journal of Product Innovation Management (A Comparison of New Service versus New Product Development: Configurations of Collaborative Intensity as Predictors of Performance):

Collaboration among firms for innovation has received considerable attention. However, little is known about how firm-to-firm collaboration is configured in new service development (NSD) versus new product development (NPD).

The article measure the impact of 1) Good processes / communication vs 2) Good relationship / trust. They find that collaboration on products is more effective with good processes while collaboration on services is more effective with trust. Probably makes sense: Services are inherently unprotectatble and trust is needed to ensure the partner plays well.

How Fast and Flexible Do You Want Your Information, Really?

Here is a quick note about access to corporate information from the Sloan article: How Fast and Flexible Do You Want Your Information, Really?

access to corporate data in organizations is rarely as rapid as an Internet search. “Why can’t I get information on our sales just as quickly as I can search the Internet?” is a frequently overheard complaint. That frustration has led many organizations to try to speed up the delivery of data and analysis, particularly in the context of decision making (typically described as “business intelligence,” or BI). But few organizations have reached an optimum with regard to how fast important information reaches in boxes, desks and brains.

The article suggests that more information is not necessarily better:

Consulting companies that study information consumption routinely find that more than half of all standard reports aren’t being used by anyone anymore. Inflexible standard reporting means not only that paper is wasted, but that an even more valuable resource — executive attention — is misdirected.

Here are their findings:

The aim should be to enable faster decision making, not faster information. Focus on information speed and flexibility that facilitates that.

Not all information is needed equally fast, nor in equally perfect condition.

Executives often ask for more information than they use.

Key to success is right metrics to report so that managers can make effective decisions. Unfortunately, this is difficult to do – many times because other managers do not want to have their performance be easily visible. Good points to keep in mind though.