Photo: Singularity University
Recently I participated in the ThinkX program sponsored by SAP Innovation Partnership Program and Singularity University. The origins of ThinkX touch the xPrize competitions and other design events which seek to leverage exponential learning. Over the past 5 years, SAP and SU have hosted over 800 SAP executives, leaders and employees to events around the world. In this first article of a three-part series I will explore the big trends, themes and take-aways – including how they may impact industry and society in the coming years.
What makes great companies outperform their peers in industry? One answer is in exponential learning. Exponential learning allows companies to grasp new ideas, concepts and techniques and to apply them in non-linear, exponential fashion. An exponential organization is an organization that can leverage this learning and create results that are 10x – an order of magnitude – greater than their peers across key performance areas. The changes required to perform at these levels will necessitate changes in leadership as well. Exponential leadership requires a broad vision across industries in anticipation of disruptions and the creation of new white space opportunities.
In the hospitality space, Airbnb has leveraged 90x listings per employee by their disruption in the short term, vacation rental segment. In automotive, Tesla achieves 30x market cap per employee (based on data from earlier in 2019) compared to its traditional automotive peers. Platform Maker and start-up Local Motors has discovered its ability to create a vehicle platform 1000x less expensive than its traditional automotive peers while improving time to market by 5-22x based on the vehicle configuration (source: Singularity University). Learning leads to leadership, which leads to performance.
Exponential leadership in many ways addresses the so-called innovator’s dilemma. Traditional companies are terrible at generating disruption and don’t typically respond well particularly to new market disruptions. As such, innovators need to be aware of what’s happening in lateral and adjacent industries in ways not seen before. In automotive and discrete manufacturing, the trend to smart products, products as a service, and consumption-based models – all enabled by sensor driven technologies and big data – is driving a shift from the “industrial revolution” through the “information revolution” and into an “artificial intelligence (AI) economy.”
Exponential performance is initially difficult to gauge and monitor, and in fact it can appear that a company may be failing compared to other traditional business models. While exponential performance starts deceptively slow, it can continue and accelerate at a tremendously fast pace. Returning to Tesla, the company’s desire to move to production tooling without a conventional prototype phase in favor of a “fail fast” and “experimentation mentality” typical of high tech and aerospace made no sense when viewed through the lens of a traditional automaker operating model. However, while the leap was painful for Tesla, the savings in time to market – and the gains in results in net promoter score (NPS) and near-term market cap previously noted are impressive.
The big “show down” between exponential organizations and traditional organizations may be netted out in a few broad areas, which when applied to companies in a given market segment or group of segments provides separation from winners and losers.
- Growth vs margins – exponential companies like Amazon look for first mover growth areas and once dominated expect margin growth to follow.
- Learning vs Outcomes – returning to exponential learning, teams need to understand how to learn in a new exponential reality, versus focusing on traditional quarterly outcomes.
- “Pipes” vs “Platforms” – the ability to leverage multipliers between ideas, concepts, and products – the connectors or “pipes” that create synergy – are giving away to the more powerful, integrated platform. Platforms that aggregate value and create ease of use will serve as the basis for exponential performance.
In the end there is a big challenge: what do we need to unlearn as individuals and organizations in order to move from a traditional model to one that embraces exponential learning, exponential leadership and – ultimately – exponential performance.
This is the first of a three-part story. Part two: AI will Eat Software may be found here after it publishes. This article is cross-posted on LinkedIn, Medium and WordPress by the author.
Filed under Uncategorized