Cases of Innovation in the COVID-19 Era - Deepstash
Cases of Innovation in the COVID-19 Era

Cases of Innovation in the COVID-19 Era

Curated from: sloanreview.mit.edu

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Organisational challenges during a pandemic

Organisations face 3 types of challenges during a pandemic:

  • Traditional Demand: The need to satisfy the same customer demand as before but with a modified approach. 
  • Emergent Demand: The need to satisfy a new customer demand that emerged from the pandemic
  • The time period of changes: Forecasting how long these changes will last, whether temporary changes are likely to disappear once the pandemic is over or sustained changes that will become a regular part of your organization’s operations going forward.

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Innovation for addressing a pre-existing demand for a temporary period

Innovation for addressing a pre-existing demand for a temporary period

Adapters: Deliver the same products or services but likely with fewer resources

  • Restaurants creating outdoor dining and consumer-goods 
  • Reckitt Benckiser ramping up production of Lysol disinfectant spray to keep up with global demand
  • Flour, a bakery group based in Boston, has nine locations but couldn’t balance the demand for baked goods across its restaurants when they experienced changes in foot traffic under COVID-19 restrictions. In response, it centralised baking to increase the quality and consistency of food provided to customers with a much smaller workforce.

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Innovation for addressing a pre-existing demand for a sustained period

The Optimiser: Reconfigure resources to satisfy existing sustained customer demand, by increasing the efficiency by which they deliver these products and services.

  • Ikea, which had previously invested in augmented reality to help customers choose furniture without physically going to an Ikea store. During the pandemic, with foot traffic all but disappearing at times, the company decided to invest more in this new technology and added more than 2,000 products that customers could visualize from the comfort of their own homes.

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Innovation for addressing a new demand for a sustained period

Trendsetter: Developing entirely new products or services that will continue to be in high demand post-pandemic.

  • The U.S., Massachusetts General Hospital (MGH) began a new effort to offer telemedicine appointments during the pandemic. 
  • Doctors and nurses were required to learn how to use this new technology, develop new skills for providing care, and implement new routines to satisfy the emergent demand.
  • Competitive advantage by improving the user experience, reducing overhead, and satisfying its health customers by offering patients more flexibility in scheduling appointments.

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Innovation for addressing a new demand for a temporary period

Trailblazer: Use existing resources to solve new problems they had never tackled before. 

  • Dyson, a company famous for innovation, saw that the world needed more medical equipment during the pandemic and recognized that it could produce ventilators. 
  •  Dyson developed an entirely new ventilator design — one that could actually be produced at a fraction of the cost of previous designs due to limitations in resources. 
  • Alcohol distilleries producing hand sanitiser, fashion brands producing masks,
  • Pharmaceutical companies repurposing drugs to alleviate COVID-19 symptoms.

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Traditional V. Emergent Innovations

  • Companies are often more attuned to using the traditional innovation process, which allows them to address a known problem with more strategic control and direction. 
  • The coronavirus crisis has shown that it’s important for organizations and leaders to become more comfortable with uncertainty and ambiguity — fundamental parts of the emergent innovation process

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How to adopt emergent innovation in your organisation?

  • Anchor their processes on the constraints of the solution rather than the clarity of the problem.
  • focusing on a narrow set of resources within the business, asking users how their products could be useful in new ways, 
  • Iterating through several open-ended domains until a clear and specific problem emerges near the end of the process.

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