Cognitive Insights to Boost Product Quality and Asset Performance – Part 1/5

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The high cost of poor product quality

There was some good news in Warranty Week’s Fifteenth Annual Product Warranty Report: warranty expenses were either flat or down slightly across all industries tracked (transportation, high-tech, and building-related trades). This may mean manufacturers improved quality, or they shifted more warranty costs onto suppliers, or some combination of the two. What is certain, however, is that unfortunately warranty costs remain onerous.

In 2017, the total worldwide warranty claims paid by U.S.-based manufacturers was $24.7 billion. As many private and non-U.S.-based companies are not required to disclose warranty expenses, global figures are hard to come by. But Warranty Week estimated that just one manufacturing sector—automakers—spent $48.0 billion worldwide on warranty claims in 2016 (2017 Worldwide Automotive Warranty Report).

That equals roughly 2.5-3% of global automotive revenue for that year (estimated at between $1.5-2.0 trillion). And warranty expenses (including recall costs) are just the tip of the iceberg of the total cost of poor quality (COPQ).

These costs include internal expenses, like scrap, rework, and equipment downtime, and external costs—those incurred once a product has shipped—including:

  • Damage to brand reputation,
  • Increased customer churn,
  • Higher warranty costs,
  • Increased insurance premiums,
  • Heightened scrutiny from regulators,
  • Decreased product or asset utilization rates, and
  • Lower sales and net profits.

At worst, defects can cause injuries or even fatalities, resulting in serious human suffering and triggering severe business impacts, including:

  • Costly recalls,
  • Civil lawsuits or criminal prosecution,
  • Punitive regulatory action, and
  • Stock price drops, multi-year revenue losses, or even bankruptcy.

It’s little wonder, then, that the true COPQ is usually estimated at 5-30% of gross sales for manufacturers and their suppliers. The good news, however, is that small investments on the prevention side of the equation can dramatically lower these costs.*

To truly minimize risks, manufacturers need to invest in processes and solutions that can help them detect issues as early as possible in every lifecycle phase, to rapidly and accurately diagnose causes and determine corrective actions, and to relay lessons-learned back to engineering and quality teams for continuous quality improvement.

Unfortunately, this type of agile, proactive strategy has traditionally been difficult to achieve. The difficulty is due in part to leadership and operational issues, but more often it is caused by weaknesses in information systems. This includes an inability to detect important quality-related signals due to information silos (which also impede the development of a systematic issue resolution process ), and the inability to effectively filter and analyze large, heterogeneous masses of data.

* See Cost of Quality (Campanella, 1999) for a seminal explanation of how one unit of currency invested in quality appraisal and defect prevention reduces the cost of poor quality many times over.

In the next blog installment, we will examine how manufacturers can overcome these challenges and information roadblocks in order to implement effective Quality Management. Part 2: Information Silos

 

Part 1: The high cost of poor product quality

Part 2: Information silos

Part 3: Weak-signal intelligence and Cognitive Insight Engines

Part 4: EXALEAD Asset Quality Intelligence solution.

Part 5: The high rewards of continuous quality improvement.

 

 

 

 

Read our White Paper on Cognitive Insights to Boost Product Quality and Asset Performance 

 

 

 

 

 

 

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