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Published: 01/26/2023
It’s not news that data have become the lifeblood to successful businesses. Their accumulation within and outside of companies has been growing at unprecedented rates. According to IDC, they will continue to double from 2022 to 2026.
Yet a challenge that has plagued many manufacturers is how to strategically make use of their data—how to capture, clean, and share them, and most important, how to make sense of them to put them to good use. 2023 will become the year when companies get serious about getting their data houses in order.
Since information continues to be captured across many different sources—from the shop floor and quality control to finance, marketing, HR, and quality management—integrating these data into a single source becomes essential. A macro view of enterprisewide data will lead to better quality, reduced risk, regulatory compliance, and ultimately, better decision making. It’s the essential ingredient to successful Quality 4.0, and a journey many companies have begun.
As part of this data journey, companies will find ways to expand data literacy across various functions and business users, making data more democratized and accessible enterprisewide for greater insights and action.
Consider the following five data-driven trends that ETQ believes will shape the new year in quality manufacturing.
Cloud adoption soared during the pandemic because of its ability to enable remote work and consume fewer IT resources. This growth will continue in 2023 as manufacturers migrate on-premise solutions to the cloud. Gartner estimates that cloud adoption will grow 20.7 percent to $591.8 billion in 2023, up from $490.3 billion in 2022, according to its most recent forecast. A global survey conducted by Accenture found nearly 65 percent of respondents saw as much as 10 percent in cost savings from moving to the cloud.
Cloud-based QMS, ERP, and other systems will continue to migrate to the cloud, leveraging virtual public or private servers so these systems can be accessible wherever needed, with updates and new information available immediately across the network. As cloud usage increases, companies will demand cloud-native solutions because they can be much more robust and scalable than legacy systems simply moved to the cloud. Supporting this move to the cloud will be an integration of these various enterprise systems—to share data, have a single source of truth, and to enable cross-system workflows.
Artificial intelligence (AI) and data analytics capabilities embedded in quality management systems (QMS) and other systems will become a key conduit for the growing mounds of data. It will enable more accurate forecasting, automate repetitive tasks, help to identify product defects and their causes, and ultimately drive better decision making. Yet before AI can reach its potential, manufacturers need to get their data houses in order, auditing the data they have, integrating them, and making them ready for AI training.
An S&P Global report found that 95 percent of businesses consider AI to be important to their digital transformation goals. Yet integrating machine learning into quality management processes is still nascent. The reality is that it will take time for AI to be widely adopted in quality management because it requires a systemic change in how companies operate, as well as skilled personnel to implement and optimize it. Still, significant inroads will be made in 2023.
A key commitment of manufacturers everywhere in 2023 will be to improve their sustainability goals through reduced carbon emissions, scrap, waste, energy consumption, and other factors. In fact, Gartner’s 2022 CEO and Senior Business Executive Survey found that “environmental sustainability was the third largest driver, behind performance and quality, among the 80 percent of CEOs planning to invest in new products in 2022/23.”
Meeting sustainability goals requires end-to-end transparency and visibility across the enterprise, as well as systems to manage internal and external compliance requirements. Companies will be relying more than ever on their QMS to help avoid product defects or issues that create waste; better manage supply chains to ensure that quality standards are met in materials; or to automate the documentation of key sustainability metrics and uncover issues that can affect them.
Gartner says that by 2025 “labor volatility will cause 40 percent of organizations to report a material business loss, forcing a shift in talent strategy from acquisition to resilience.” Throughout 2023, labor shortages will continue to pose a threat to manufacturers as a side effect of the continuing Great Resignation among the workforce, as well as the triple threat of flu, Covid, and RSV that is on the rise, among other factors.
Manufacturers will need to learn to do more with fewer workers in 2023 and ensure that quality and safety standards are still met. For this reason, they will rely on automated systems, such as QMS, RPA, ERP, and WMS, to boost productivity, increase efficiency, and provide data-driven visibility to proactively address workforce issues.
Although manufacturers will be more discerning in where they invest in technology in 2023, thanks to the threat of a recession, those solutions that boost productivity and efficiency and help to reduce costs will be more important than ever. According to Rick Villars, IDC, “Technology and IT is not about where we cut—technology is where we invest to help the rest of the business navigate the recession.”
Enterprise systems, such as a QMS, CRM, or ERP, play a pivotal role in automating business functions and enabling informed decision making. New solutions that can integrate with those enterprise systems can augment their value and provide an attractive return on investment.
While many of the issues that challenged manufacturers and other markets in 2022 aren’t going away anytime soon, enterprises will focus on technology to better manage the risk. Informed companies, with deep visibility across their enterprises and supply chains, will make automated solutions work for them to produce better decisions, superior products, and stellar brand reputations.
Links:
[1] https://www.idc.com/getdoc.jsp?containerId=US49018922#:~:text=%22The%20Global%20DataSphere%20is%20expected,vice%20president%2C%20IDC's%20Global%20DataSphere.
[2] https://www.etq.com/blog/report-quality-4-0-adoption-requires-more-than-just-emerging-technology/
[3] https://www.gartner.com/en/newsroom/press-releases/2022-10-31-gartner-forecasts-worldwide-public-cloud-end-user-spending-to-reach-nearly-600-billion-in-2023
[4] https://www.accenture.com/us-en/insights/cloud/cloud-continuum?c=acn_glb_cloudcontinuumrgoogle_12957693&n=psgs_0422&gclid=CjwKCAiAs8acBhA1EiwAgRFdw1tfVoDtOOBIlRAsDxEUbgSU_RiWgZwDQJa8VRsNWFdJq2Uc5urv8xoCUpUQAvD_BwE&gclsrc=aw.ds
[5] file:///C:/Users/cnahil/AppData/Local/Microsoft/Windows/INetCache/Content.Outlook/YA983NRV/While%20a%20recent%20S&P%20Global%20report,%20found%20that%2095%20percent%20of%20businesses%20consider%20AI%20to%20be%20important%20to%20their%20digital%20transformation%20goals,%20integration%20of%20machine%20learning%20into%20quality%20management%20processes%20is%20still%20nascent.%20The%20reality%20is%20that%20it%20will%20take%20time%20for%20it%20to%20see%20widespread%20adoption%20in%20quality%20management%20because%20it%20requires%20a%20systemic%20change%20in%20how%20companies%20operate,%20as%20well%20as%20skilled%20personnel%20to%20implement%20and%20optimize%20it.
[6] https://www.gartner.com/en/newsroom/press-releases/2022-10-18-gartner-unveils-top-predictions-for-it-organizations-and-users-in-2023-and-beyond
[8] https://www.cnn.com/2022/12/09/health/covid-influenza-rsv-vaccine-pandemic-wellness/index.html
[9] https://www.zdnet.com/article/tech-in-2023-weve-analysed-the-data-and-heres-whats-really-going-to-matter/