Manufacturers collecting data faster than ever before. But now what?

Posted on 8 Sep 2014 by Callum Bentley

A new report has highlighted that while most manufacturing firms have greatly increased the volume of data they collect from the shop floor over the past two years, many are still coming to grips with exactly how to use the information.

Manufacturing and the data conundrum: Too much? Too little? Or just right?commissioned by Wipro and published by The Economist Intelligence Unit, examines how manufacturers are using integrated data collection and analysis to improve production throughput, reduce costs and improve quality. The research is based on a survey of 50 C-suite executives from manufacturers in North America and Western Europe.

  • 86% of manufacturers in US and Europe report major increases in shop-floor data collection over the past two years but 62% are not sure they have been able to keep up with larger data volumes
  • Two-thirds report data insights have led to annual quality and efficiency savings of 10% or more
  • Most companies collect data from monitoring production processes; far fewer analyse it to find solutions to problems 

The survey shows that just 42% of respondents have what they consider to be a well-defined data-management strategy. However, 62% are not sure they have been able to keep up with the large volumes of data they collect, as it comes from too many sources and in a variety of formats and speeds.

The report also found that while over 90% of manufacturers collect data from monitoring production processes, less than half have in place predictive data analytics, and less than 40% use data analysis to find solutions to production problems.

David Line, the editor of the report, said: “Manufacturing has been at the forefront of data collection and its importance to quality and cost control is well recognised. But collecting too much data, or failing to analyse what you collect, can be counterproductive.”

Nevertheless, two-thirds of companies report annual savings from data analysis of 10% or more in terms of the cost of quality (i.e. net losses incurred due to defects) and production efficiencies. About one-third say their savings on both measures have been in the range of 11% to 25%.