Pandemic pushed manufacturers to greater analytics adoption: survey

By  | Supply Chain Dive | Dec 15, 2020

Dive Brief:

  • The coronavirus pandemic led 73% of U.S. manufacturers to increase their use of digital technologies such as analytics tools, IoT sensors and general productivity applications, according to a recent survey by The Harris Poll conducted for Google Cloud between mid-October and early November.
  • Manufacturers are specifically focused on data and analytics, with 65% of U.S. manufacturers reevaluating their use of these tools as a result of the pandemic.
  • A report accompanying the survey specifically highlights comments by Peter Terwiesch, the president of ABB’s industrial automation business, who said manufacturers could improve productivity 30% to 40% with analytics, according to CNBC.

Dive Insight:

The adoption of analytics in the manufacturing sector isn’t necessarily new for the industry as a whole. A PwC survey released last year found that 35% of respondents in the manufacturing industry has adopted advanced analytics in the last three years.

But this adoption has accelerated as a result of the pandemic, Dominik Wee, the managing director of manufacturing and transportation at Google Cloud, said in an emailed statement.

“The challenge has been finding less expensive, less labor-intensive ways to integrate and query across existing data sources to source meaningful insights,” Wee said. “Platforms that allow for easy data harmonization from multiple modalities and sources, producing real-time governed metrics, are critical to helping manufacturers take full advantage of data analytics adoption.”

Forecasting is one specific analytic area of interest for manufacturers who have seen demand swing dramatically throughout the pandemic.

“Manufacturers across the board are really going to have to become better at developing visibility and forecasting capabilities,” Paul Wellener, the leader of Deloitte Consulting’s U.S. industrial products and construction practice, said on a Dec. 8 webinar. “It’s a strategic imperative from what we can tell. How do we better anticipate surges in demand to be able to proactively ramp up production?”

Forecasting skills are also important for anticipating drops in demand to allow manufacturers to cut costs where needed, Wellener said.

The increased use of other technologies such as internet-connected devices will similarly increase the need for analytics capabilities to enable companies to analyze the data flowing off of the sensors. But getting talent to fill these positions isn’t necessarily going to be easy, Wellener said.

“We need to think about how we get the right kinds of analytical capabilities,” he said. “Do we build those internally? Do we continue to educate employees and retool employees to get better capabilities when it comes to analytics or digital? Or do we think about the notion of ecosystem partners to accelerate some of those areas?”

While manufacturers work to build analytics teams, the tools they’re using vary just as much as the available talent, Wellener said in a follow-up email, noting that techniques for applications such as predictive maintenance are only being used by highly developed teams.

“Many supply chain and procurement departments are still managing by Excel spreadsheets, which provide a reporting level of data analysis,” he said. “Others have moved to incorporate basic analytic tools that can help surface insights in ways that were previously impossible. The higher levels of advanced analytics, which enable prediction, are just starting to surface in a small number of manufacturing environments, and often they are in pockets.”

Read the full story at Supply Chain Dive.