The Rise of Academic Accelerators

Large corporations know they have to innovate to grow and compete in the global economy. Corporate innovation outposts and other arrangements have emerged as a result and big organizations are rethinking how they get more creativity from their employees as well as impact from their research and development budgets. Academic research universities and affiliated integrated delivery networks are also testing the water. They have realized that innovative universities are not entrepreneurial universities.

Go lean or go home is the mantra.

The Cleveland Clinic, the Mayo Clinic, and other innovation centers are building a track record at an impressive rate. Some are focusing on digital health or subsegments of digital health like telemedicine, data analytics, or bioinformatics.

Health innovation center leaders and participants will need to address some issues to be effective and deliver impact. Among them:

1. The last mile. All the systems engineering in the world won't make a difference until we crack the code on how to change human behavior.

2. The rules. Most will have relatively limited impact until and unless the reimbursement rules substantially change. Rules drive ecosystems that create business models that deploy and scale innovation. Right now innovation centers are trying to use new tactics but can only deploy limited innovation strategies without a new playing field. They are living in the no man's land between the now and the new.

3. Systems thinking overcoming silos. Healthcare is notoriously siloed at almost every level, from department to department to one sick care system to the next.

4. Patient willingness and ability to engage. The assumption is that more patient "engagement" will mean better outcomes. That needs to be validated and we need to do a better job of targeted patient segments who want to take responsibility for their care and assume the consequences for the results.

5. Shifting value factors. Medical care is becoming commoditized. Patients can't judge quality and cost since they are so opaque so they use service, speed, convenience, and experience as proxies. There is relatively little correlation between satisfied patients and the quality of care they receive.

6. Data integration and interoperability. Resolving the “protect but share” dictum will be challenging.

7. Measuring and defining innovation. Big orbit change is necessary, not incrementalism. Innovation is a measure of the multiple of user-defined value that results when compared to the existing competitive offering.

8. Lead innovators, don't manage innovation. We need leaderpreneurs and followers with an entrepreneurial mindset willing to fail at low cost.

9. Innovation management systems. There are many ways to foster, package, test, validate, prioritize, and deploy components of an R/D portfolio. The process needs to be efficient, effective, and transparent to the users.

10. Execution. Inspiration and perspiration. In the end, no idea, invention, discovery, or process is worth much without a team who can execute or deploy it.

The goal of all these efforts, whether they be in the public, private, or academic sectors is to create stakeholder-defined value throughout the deployment of innovation. Entrepreneurial universities can make it happen.

Like many reorganizational efforts, merely reshuffling the deck won't succeed. We need to throw away the deck and start playing a new game.