Executive Briefings

While Poor Quality Product Data Hinders Most Electronics Companies, Best Leverage Big Data Analytics, Study Says

While vast "smart products" opportunities are allowing many high-tech companies to grow and lower their cost of goods sold, 57 percent do not have access to reliable product genealogy information, and 72 percent believe their product data is less than 80 percent accurate.

While Poor Quality Product Data Hinders Most Electronics Companies, Best Leverage Big Data Analytics, Study Says

These are a few of the key findings from a report entitled Capitalizing on Big Data from Products, released by Iyno Advisors. This study gets at the heart of a thorny issue for fast-moving industries like electronics: many companies' IT infrastructure makes it difficult to turn current data into usable information for timely and effective business decision-making. However, select pioneers leveraging big data analytics have made enormous strides in improving product performance and enhancing decision-making.

“Electronics manufacturers’ products are enabling massive data visibility and business process changes that are disrupting industries, but are challenged themselves to use the data from across their complex eco-system effectively,” says lead study researcher Julie Fraser. Data is fragmented, dirty, in diverse formats, and challenging to put into a useful context. The complexity of the electronics supply chain compounds the problem. This research confirms that most companies struggle with data from outside their own enterprise: from suppliers and from the field as products are in use. Most of these companies know they must improve product quality, customer satisfaction, and new product introduction time. However, for more than half of the respondents, data on genealogy, root causes, and supplier engineering changes takes weeks to obtain or is not available at all.

Yet some electronics companies that harness big data analytics power are on a better track: respondents who improved their performance on four out of five business metrics, or Improvers, make up about a quarter of the survey response base. Improvers were two to 15 times more likely to see data from key business processes in minutes. These processes encompass:

• R&D: design risk including failure mode effects analysis (FMEA), engineering changes, both internal and from suppliers

• Production: yield, manufacturing test log and machine data

• Supply chain: genealogy

• Customer in-use: where shipped, return materials authorizations (RMA), field and device direct data

In addition to sharing the research results, Capitalizing on Product Data outlines five major barriers to using product data. It includes a summary of key capabilities that companies will need in their IT systems to capitalize on product data and that most electronics companies lack or have in an unworkable configuration. Finally, the report provides some suggestions based on what the Improvers are doing differently based on what they have learned.

The report is available for public download here:

Source: Iyno Advisors

These are a few of the key findings from a report entitled Capitalizing on Big Data from Products, released by Iyno Advisors. This study gets at the heart of a thorny issue for fast-moving industries like electronics: many companies' IT infrastructure makes it difficult to turn current data into usable information for timely and effective business decision-making. However, select pioneers leveraging big data analytics have made enormous strides in improving product performance and enhancing decision-making.

“Electronics manufacturers’ products are enabling massive data visibility and business process changes that are disrupting industries, but are challenged themselves to use the data from across their complex eco-system effectively,” says lead study researcher Julie Fraser. Data is fragmented, dirty, in diverse formats, and challenging to put into a useful context. The complexity of the electronics supply chain compounds the problem. This research confirms that most companies struggle with data from outside their own enterprise: from suppliers and from the field as products are in use. Most of these companies know they must improve product quality, customer satisfaction, and new product introduction time. However, for more than half of the respondents, data on genealogy, root causes, and supplier engineering changes takes weeks to obtain or is not available at all.

Yet some electronics companies that harness big data analytics power are on a better track: respondents who improved their performance on four out of five business metrics, or Improvers, make up about a quarter of the survey response base. Improvers were two to 15 times more likely to see data from key business processes in minutes. These processes encompass:

• R&D: design risk including failure mode effects analysis (FMEA), engineering changes, both internal and from suppliers

• Production: yield, manufacturing test log and machine data

• Supply chain: genealogy

• Customer in-use: where shipped, return materials authorizations (RMA), field and device direct data

In addition to sharing the research results, Capitalizing on Product Data outlines five major barriers to using product data. It includes a summary of key capabilities that companies will need in their IT systems to capitalize on product data and that most electronics companies lack or have in an unworkable configuration. Finally, the report provides some suggestions based on what the Improvers are doing differently based on what they have learned.

The report is available for public download here:

Source: Iyno Advisors

While Poor Quality Product Data Hinders Most Electronics Companies, Best Leverage Big Data Analytics, Study Says