- Utility Transformations
- Utility Transformations
- Distributed Energy Resources
- Renewable Energy
- Renewable Energy
- Solar Power
Major Businesses, Beware Myopia
Develop Peripheral Vision to Manage Industry Disruption
The past 50 years have witnessed the collapse of many corporate giants, often caused by the systemic myopia of business leaders. The likes of Blockbuster, Kodak, and Polaroid demonstrated a failure to recognize where the value lay in the digitization of their industries, for example. As we move into 2018, energy industry disruption is accelerating. Huge opportunities stem from increasing complexity and disruption, but the risks of utilities becoming the next Kodak are also increasing. To combat competitive threats, the industry must develop peripheral vision—the use of competitive early warning signals and scenario planning—to exploit opportunities and manage threats.
Identify and Monitor Early Warning Signals
A competitive early warning system delivers this peripheral vision. By maintaining a broad perspective, utility executives can focus on where changes are happening the fastest and identify where future value lies. However, it is imperative for executives to filter signals from noise and focus attention on the developments that have the highest potential to hurt a business in the coming decade. Scenario planning is a useful filtering tool: a signal such as the development of a new technology, product, or service is extrapolated into the future in several scenarios that gauge the likelihood of adoption and potential impact.
For example, there is a growing trend for residential customers in Europe to purchase solar PV bundled with storage. German battery vendor sonnen has developed a solar plus storage product—sonnenFlat—which requires customers to only pay a flat fee every month. As part of the deal, customers provide sonnen with access to their distributed energy resources (DER) to provide grid services. In return, sonnen guarantees customers free grid-sourced power when their DER is unavailable. sonnenFlat is a new, niche product. Nonetheless, utilities globally should be assessing the risk this poses, particularly when combined with community solar programs. A self-sufficient solar plus storage customer is lost to an incumbent supplier for 20 years.
Measure the Likely Impact on Business for Each Signal
No one can claim to know the future, but with careful planning, a company can prepare for the most likely scenarios. The potential scenarios for residential solar plus storage installations span from little or no growth through near ubiquity. The industry should be asking whether solar plus storage could kill the traditional grid supply model. Careful analysis of the market—for instance, using SWOT or PESTLE approaches—will help gauge the likelihood of different scenarios.
In many countries, the cost of financing solar plus storage is less than a household’s annual electricity bill; falling technology costs and rising power prices will make the solar plus storage option more compelling. While the economic argument is increasingly convincing, there are many reasons why adoption is relatively low, including apathy and ignorance.
Expect (and Plan for) the Unexpected
Customer preference is the biggest driver of solar plus storage, and therefore beyond the industry’s sphere of influence. There is little an incumbent energy provider can do to protect existing revenue from power supply by deterring customers from making solar plus storage investments. This strategy also fails to capture the value of solar plus storage. The industry should be planning strategies to respond to the growth of solar plus storage. These include the development of solar plus storage products, aggregation services, providing the infrastructure on which third parties can offer services, or partnering with or acquiring existing providers. It is possible to be as well-prepared as possible by recognizing the biggest threats and creating risk mitigation strategies in advance.
To mitigate risk, utilities must plan scenarios for a large number of signals in a well-defined early warning system.