Trends and Outliers

Data Analysis to Tame Manufacturing Complexity

The manufacturing sector is still struggling to emerge from the recession. Industrial production shrank 0.5% in April, according to recent data from the Federal Reserve.

In addition, the country is using about 77% of its total industrial capacity, nearly three percentage points below the 40-year average.

American manufacturers are suddenly grappling with the influx of cheaper goods from Japan, China and other overseas competitors.

“[Manufacturing] has flattened out completely and is not contributing to GDP growth right now,” Jacob Oubina, senior economist at RBC Capital Markets, tells Businessweek.

But top industry performers are building up their big data and advanced analytics to support efforts to help them take control of manufacturing complexity, according to a recent survey of more than 100 manufacturers by research firm Aberdeen Group.

“Understanding customer demands must take into account the complexities of the manufacturing process, such as time-to-market expectations, product customizations and best practices,” according to the report. “Change can be an overwhelming task – especially for companies trying to take control of the process variability. But employees must be ready to interact with operational processes and take control of the fast changing manufacturing environment.”

The report notes that top performing manufacturing companies – more so than lower performing companies – are more likely to adopt time-sensitive metrics that foster this sense of urgency including:

• Time to decisions (33% versus 13%)
• Time to market (46% versus 34%)
• On-time and complete shipments (46% versus 36%)

In addition, top performing companies are more likely than lower performing companies to turn to data analysis to support effective decision making to stay competitive.

For example, 33% of top performing companies say they have to provide timely data for critical decision making to line of business management compared to 23% of lower performing companies.

And 25% of top performing companies say they need to provide data analysis tools for various levels of the organization compared to 9% of the lowest performing companies in the survey.

“Leaders are more likely than followers to connect effective decision making with the ability to improve planning and empowerment with data,” the report notes. “For leaders, line of business managers need access to critical data in order to manage decisions impacting incremental improvements and cost cutting activities. They also see as a top priority the ability to aggregate and analyze business data across multiple products or functions.”

According to the report, manufacturers face the following data challenges:

• Complex data is fragmented across operations (45%)
• Data isn’t available when needed (31%)
• Users don’t trust the data (25%)
• Complex dashboards with too many metrics (24%)
• Old data that’s used in business activities (24%)

“Leaders see data as the new business order.  . . .  Top performers are more likely to understand that the ability to turned data into insights and actions is a game changing strategy,” the report notes. “Supported by analytics and statistical models they must characterize the impact of their decisions on engineering, supply chain and customer management and everything else affected by these decisions.”

Manufacturers identify myriad benefits from using big data and analytics including:

• Combining customer behaviors and transactional views to help establish priorities
• Identifying potential new micro-markets based on events or trending customer preferences
• Combining user requirements, new features and bug fixes to create ROI for new product launches
• Predicting recalls, supplier disruption and other crises can boost organizational readiness

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