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Disruption Across the Value Chain: What Auto Players Can Learn from Other Industries

March 27th, 2017 | Posted by Haley Jackson in Auto

With Google manufacturing cars, Tesla selling directly to the consumer, and Amazon selling non-genuine parts, the automotive industry landscape is quickly shifting. In order to succeed as the industry evolves, incumbent auto players must continually evaluate key business strategies, from pricing to marketing to new offerings.

Automakers are not the first to come up against industry disruptors. Similar competition has developed in other sectors, including travel, retail, and consumer goods manufacturing, and organizations are already using experimentation and innovation to respond. By learning from their strategies, auto OEMs can emulate their approach to refine key business programs and develop a competitive edge to profitably navigate disruption themselves.

Responding Profitably to Disruption

New players shaking up the auto space will force OEMs to re-examine key aspects of their business model and carefully think through cutting-edge strategies – and that is not necessarily a bad thing. Across industries, organizations are responding to similar competitive actions by re-evaluating pricing strategy, expanding into new areas of the value chain, and strategically targeting new marketing programs and promotions.

For example, traditional grocers are grappling with competitors ranging from online grocers, meal-delivery kits, and new, low-cost grocery players. In response, some are adjusting pricing strategies, while others are enhancing the in-store experience by adding new features like pubs and café seating. In the travel industry, airlines are introducing new services and fare classes to maintain market share in the face of emerging competitors and offerings. And in the consumer goods space, manufacturers are adjusting pricing strategy in response to the increasing prevalence of lower-priced, private label goods.

All of the above initiatives raise various questions. For example, how can grocers and consumer goods manufacturers determine the locations or product categories where pricing changes will be most profitable? In the travel industry, how can airlines determine what types of flights should receive the new offerings, in order to target broader rollout of the program and drive the greatest positive impact? Should organizations react directly to competitive actions, or innovate elsewhere? Which markets or types of customers are most severely impacted by competitors’ programs?

Across industries, the most reliable way to answer these complex analytical questions is by designing an in-market experiment to isolate each new program’s direct impact. By first testing a new program with a subset of customers, sites, or markets, and comparing their performance to  a group of similar entities that did not receive the program, organizations can answer three key questions:

  1. Is the program successful overall?
  2. How can it be tailored for maximum impact?
  3. How should it be targeted to maximize ROI?

Organizations can also conduct similar, test vs. control analyses called “natural experiments,” on the basis of past natural variation that occurred in a subset of the network. Natural experiments involve analyzing the impact of a past business action that was not a deliberately designed test, such as a competitor’s marketing campaign, but nonetheless resulted in a measurable change in performance.

Key Analytic Considerations

When contemplating how to best respond to disruption across the industry value chain, automakers should keep these analytic considerations in mind:

Avoiding Analytic Silos

It is important to consider how new business lines, like car-sharing programs, will affect traditional revenue streams. In order to understand the full impact of these initiatives, automakers must maintain analytic visibility across their entire organization. With disruption affecting different parts of the business, it will be essential for each department to adopt a culture of testing and embrace a standardized analytics process.

OEMs will also need an organizational analytic structure that fosters shared learnings and cross-functional communication. Further, they should aim to establish a centralized database that incorporates different business line data streams as needed, to provide as many actionable insights as possible.

Quantifying the Damage

Isolating the actual impact of competitive actions is critical for organizations to ensure that their reactions across functional areas don’t over- or under-compensate.  Accurately quantifying the impact new entrants have on business is critical to informing how existing business models and strategies may need to adapt. In some cases, the impact may be minimal, and not worth the potential complications and cost associated with a response. In other cases, responding may be worthwhile, but not across the entire network. Experimentation empowers companies to determine the best, and most effective, course of action in each case.

As the auto industry continues to evolve and OEMs brace themselves for continued innovation, they should take note of the past analytic learnings from other industries that have faced similar disruption.

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