Innovation Science

Negotiation Strategies

I’ve been interested in negotiation strategy for a while. In some ways it embodies many characteristics that are rare in scientific research, with a focus on human interaction and an unambiguous concluding point where success can be measured relatively directly. I can understand why some people thrive on it and why some people are terrible at it. It has more in common with courtroom battles than the scientific method, yet it has significant room for innovation to take play.

There was an interesting article a month ago in the Harvard Business Review on negotiating that caught my eye. The authors outline basic principles from their new book, Negotiation Genius, that provide guidance towards understanding the person/company with whom you are negotiating.

I found this article interesting because it gives more than the basic negotiating advice of understanding your counterpart so that you can drive to a win-win scenario. This basic win-win approach is, of course, an important concept to start with because people often approach negotiations as a poker game where one is trying to win as much of the pot as possible while not reveal any of their cards, with the assumption that the other side is playing the same game and trying to win as much as they can at your expense. The false assumption with this approach is that only way to win is for the other side to lose. The first step towards a successful negotiation is to realize that to be successful, both you and your counterpart must achieve your separate goals—hence, the win-win objective.

One has to understand the objectives of the other side to know what a win-win is, and the authors of this article expand upon this concept by pointing out that often negotiations stall because one side makes incorrect assumptions about the needs and motivations of the other side. The authors provide a few case studies that they have developed to test business students in which the majority of the students make wrong assumptions and therefore drive the negotiations to solutions that cannot succeed:

They are solutions to a problem that has not been diagnosed.

The authors outline how to conduct investigative negotiation, their term for the active pursuit of information about the needs of one’s counterpart in the negotiation. The five steps that they outline are (in their words):

1. Don’t just discuss what your counterparts want—find out why they want it
2. Seek to understand and mitigate the other side’s constraints
3. Interpret demands as opportunities
4. Create common ground with adversaries
5. Continue to investigate even after the deal appears to be lost

The authors provide business case examples for each of these steps that make them more intuitive. They finish with tips on how to get information out of distrustful negotiators who don’t readily explain the reasons behind their own negotiating position. All very useful stuff.

Some of this reminds me of the work of Vantage Partners, a consulting firm with origins at the Harvard Law School when the founders were asked by the Carter administration to help with negotiations between Israel and Egypt at Camp David in 1979. Their directors have published several books, including Getting to Yes. Vantage stresses the need for a thoroughly understanding of the motivations on the other side, and emphasizes the possibility that each side has a different set of values that is driving their behavior. Vantage has expanded their expertise to business collaborations, explaining with data why collaborations between different businesses typically fail, and providing guidance on how to conduct a successful collaboration. There is a set of white papers from Vantage Partners on these topics that I highly recommend, including a huge set on managing alliances.

Buy the Investigative Negotiation article here from Amazon:

Data Sharing Article in Nature

The weekly science journal Nature just published an article on online data sharing that quotes me. My comments are from an e-mail exchange that I had with their Senior Reporter Declan Butler about the potential of new online data sharing sites such as Swivel and IBM’s Many Eyes. I’ve posted about Many Eyes before.

According to Declan’s e-mail to me, some scientists are already using these new tools to share sequence and microarray data. The potential value from scientists openly sharing their data is huge, possibly akin to the value provided by open-source software development. More people exploring data is always a good thing, and someone could discover meaningful information in data that the original owner/researcher missed. Or one's interests might be different than that of the original owner/researcher and thus one could analyze the data in a different way that is meaningful to questions not investigated by the original researcher. In a scientific publication, the author can't produce every possible permutation of the data that the readers might want, so letting the "reader" explore the data themselves through online accessibility has value. As Edward Tufte says in his book Visual Explanations,

When assessing evidence, it is helpful to see a full data matrix, all observations for all variables, those private numbers from which the public displays are constructed. No telling what will turn up.

(Thanks to Squaring the Globe blog for providing this quote.)

Anyone who has tried to obtain the raw data behind published research, however, knows that it can be difficult to get for many reasons: researchers have difficulty retrieving the data from media that is no longer used, researchers not having the time to search for and provide the data in an understandable format, researchers simply not wanting to lose any perceived advantage in pursuing future funding.

I’ve thought that a way around this is for NIH (or whatever the funding organization is) to require that all data from NIH-funded research be submitted to the NIH and be made publicly available. There are many difficulties with this proposal, of course, not the least of which is ensuring that others know how to read and interpret the data. The potential for misinterpretation would be huge. One possible solution to this would be to make available only data associated with a publication that details the methods and procedures of the data collection. This could become a policy that the publishing journal mandates rather than the funding organization.

I’ve been told that a proposal was made within the NIH to do just this several years ago for a discipline that is data-heavy, but the scientists in that field shot down the idea for several reasons, one of which was that they didn’t want any errors in their own data analysis discovered. Whatever the reasons, published figures and tables have been the primary form of information transmission of data for hundreds of years. With today’s electronic tools, there is no reason to limit our data sharing ability to techniques developed centuries ago.

How to Create an Industry-Academia Mashup

I was invited as a speaker and advisor to a summit at Purdue University two weeks ago. The meeting was created to discuss how cross-department acoustics researchers at the university can collaborate on new ideas, create a new interdisciplinary research center, and develop corporate partnerships. I was the industry-researcher representative, and I spent a considerable amount of time talking about how the different departments can collaborate under a single research concept.

What I didn’t get a chance to talk about was what university researchers need to understand to better collaborate with industry sponsors. So, over a series of posts I will discuss a few ideas on this topic.

Academia is increasingly turning to companies for research funding as federal funds become harder to get. The University of California has developed a matching-fund program that generates $50 million in corporate-sponsored research each year. In this post, I’ll discuss some of the issues that a university researcher must deal with in order to have a successful partnership with industry.

1. General Relativity
Time moves at a different pace on a university campus than on a corporate park: academia seemingly travels near the speed of light because what seems like a short duration to them can seem like a lifetime to industry. The university research process allows researchers to contemplate problems deeply and discover patterns of thought that had been previously undiscovered. A couple of months is nearly a blink of an eye to a university research program.

Time literally is money in industry, however, and a week lost in contemplative thought is a week lost in revenue. When R&D departments solve problems, they are not searching for the ultimate truth but for the best approach that can be developed given their time and resource constraints, knowing that there’s always time for improvements later. University researchers are driven by “Why and how?”; R&D engineers are driven by “Make it work.” Both sides of an industry-university partnership need to be aware of the relativity of their perspectives on the passage of time. Otherwise, “frequent updates” by university researchers might be viewed as abusive negligence by the company.

2. Training Day
Part of a university’s function is to educate students, both in classrooms and in laboratories. Research labs consist of students and post-docs doing most of the heavy lifting so that they can learn the research disciplines of their own field and become experts on their topic of investigation. This, of course, means that those doing industry-sponsored research are spending a lot of time simply learning their craft. Which takes time. Which means you need to consider point #1. Post-docs, though, usually are already experts in their field and are more effective time-wise: less time spent learning, quicker at conducting the research. Corporate sponsors need to understand who will be doing the sponsored research—graduate students or post-docs—and what that means for expected time-lines.

3. Publish or Perish
A researcher in academia is judged by their list of publications. Companies typically want to keep new ideas proprietary to obtain a competitive edge. You can see the potential for conflict. University researchers will want to, and should be able to, publish the research that is being funded—otherwise they won’t maintain their grants and possibly their positions. This issue should be addressed up front and guidelines provided to allow companies to apply for a patent before any inventions are revealed in publications or presentations. If a company doesn’t want anything published, they shouldn’t fund university research.

4. Know Your Client
University researchers focus on proving hypotheses and developing new theories—they typically don’t know much about the practical aspects of a potential corporate sponsor’s applications or their customers. Why should they care? Well, this presents a problem when looking for a common bond between industry and academia to justify a partnership. If you don’t know anything about dancing, don’t expect to be asked onto the dance floor too often.

The National Institute of Health is currently trying to promote a Translational Research initiative, defined as bringing results from the lone researcher into the clinic and to the patient, i.e., provide an application to basic research. This involves clinicians collaborating with basic scientists and each understanding the other’s world. A similar level of understanding is necessary between the academic researcher and the corporate sponsor. If the researcher doesn’t understand the application, their research is less likely to be of value to the sponsor because of the unlikeliness of it translating successfully.

Industry-types are often suspicious of the usefulness of academia to their business, and university researchers need to propose ideas that demonstrate an understanding of the issues facing the sponsor’s industry. University researchers looking to create partnerships with companies need to spend some time understanding problems that companies have with their technology and their customers’ needs—find the areas of opportunity where university research overlaps with industry need. This produces the highest likelihood of a company being interested in sponsoring research and and of that research ultimately being useful to the sponsor.

5. Ownership
The area of intellectual property is such a quagmire these days and such an important part of university-industry relations that I think I’ll give this topic its own post some time soon. Sorry.