How to Be a "Natural" at Selling
Many open innovation (OI) managers have expressed interest in improving their "batting average". Let's start by seeking to define "batting average". We can assume that batting average is equal to the percentage of technology candidates referred to an internal customer by an OI manager that are adopted by the customer. Applying this definition, it is important to know if the OI manager and the internal customer have established a clear, unambiguous, objective and mutually agreed set of criteria which determine the basis for a successful technology handoff. If they have, then the OI manager has considerable control over his deliverables: either they meet the success standard or they don't. In this scenario, the OI manager's batting average will be determined by their ability to identify, vet and qualify technology candidates. His batting average is directly linked to his effectiveness in establishing high calibre internal and external networks to scout and attract well qualified technical candidates. (You'll note that we haven't established what is a "good" or "bad" average. Only that we wish to improve it. This suggests that there should be metrics involved...another topic for another day).
If the customer is able to apply subjective or less rigorously defined criteria before deciding whether or not to adopt the technology candidate, then the OI manager's challenge becomes considerably greater and requires a fairly different skill set. The OI manager must "sell" his technical candidates to his customer, applying a combination persuasive presentation of facts and sound business judgment, versus only presenting its technical qualifications. In this situation, personal skill and style can heavily influence outcomes and batting averages can rise and fall accordingly.
In a selling situation, the OI manager should still seek agreement from his customer to the success definition prior to embarking on his technology search mission. This can help reduce potential ambiguity and also reduce the odds of a potentially moving target, which may be subject to his customer's whims and influenced by political considerations.
I always recommend to R&D managers that they learn to speak the same language as their customers in discussing a topic of shared interest. In other words, they should understand and become fluent in discussing a proposition in the same terms that the customer applies when considering it. For instance, Marketing is more interested in a technology's ability to support competitively compelling and differentiated advertising claims than they are in the details of the clinical study that was run to substantiate the claims. So, R&D should distort their time discussing the claims versus technical details.
I also recommend that R&D managers seek to build relationships with their customers that transcend the specifics of the particular case under consideration. I feel it is vital that the customer know that their colleague is committed to meeting their needs, and not overtly seeking to score a win for himself or his department. This often requires an ongoing time and effort investment, and should be authentic. An R&D (or any manager's) success probability increases when they are highly committed to meeting their customer's needs. This doesn't mean that the customer will or should adopt an unworthy solution just because they have a good relationship. However, a strong trust foundation will make the customer more readily accepting of qualified solutions.
We'll continue this discussion next week.