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Leveraging Customer Feedback, Mobility and IoT for Data Capture in PLM

As products get smarter, information can be gathered from the field to develop next-generation product iterations.

By Chuck Cimalore, Omnify Software

data capture PLMManufacturers have huge amounts of data available to them—arriving anywhere from within their own departments to sales partners to suppliers to end-users. As products get smarter, information can be gathered from the field to develop next-generation product iterations. All of this data impacts the product lifecycle and the management of that cycle.

The SME (small- to medium-sized enterprises) market is no different in this scenario. These organizations want to harness the power of this available data without drowning in it and potentially losing their progress. It must be useful, meaningful data retrieved that will help SMEs in gaining a competitive edge by helping develop better-engineered products. Data is streaming in faster than ever and from more sources as the new trend for IoT (Internet of Things) and mobility brings more connectedness, resulting in more information. This information can be gleaned from PLM (product lifecycle management) software in the form of product engineering, design information, manufacturing data and supplier data.

Internet of Things: Avoiding Information Overload

What can a SME do to leverage the IoT trend in an uncomplicated way, to weed through volumes of data to find the pattern of problematic areas the quickest? PLM vendors have been grappling with this for years.

PLM technology that connects processes within multiple departments and active teams from engineering, operations and manufacturing can create a closed-loop, enabling manufacturers to develop products that are able to capitalize on IoT data to improve product development processes. The IoT data gathered from a product’s real-world performance and quality could impact all stakeholders across the company in product design and development, manufacturing, sales and marketing, customer operations and after-sales services. It also can affect suppliers since this feedback can be circulated back to the suppliers of the parts being used in the product design. Suppliers can make adjustments to parts to optimize performance.

IoT data often can deliver data points in real time and close the lifecycle loop. Product planning, design and quality departments can learn from a product’s operational behavior to improve features that customers use most. For example, IoT data will enable companies to track and configure product design requirements (within their PLM system) based on usage patterns and allow for the redesign of parts or systems to improve quality.

Trending Digital

Manufacturers have always emphasized improving quality, customer relationships, reliability and performance. However, it has become evident that the next generation of competition is digital and seems to entail change in everything from designing products to supply chain management. The product manufacturer that never had to worry about embedding electronics and software components into their product design are now finding they must do that. Original equipment manufacturers (OEMs) are dealing with how best to embed electronics and software into their product design. They are also facing challenges of managing their expanding bill of materials (BOMs) and more complex supply chains.

The IoT is taking charge and now there are more components being manufactured and more intricate design chain challenges. To aid in the development of more complex, smart device-enabled products, PLM has evolved from the backbone for managing multiple discipline processes, product documentation, complex BOMs, and engineering changes, to capturing downstream activities like manufacturing planning, quality processes, product and customer/field-level feedback. Mobility is bringing additional improvements by giving mobile users access to PLM data and processes from their mobile devices, allowing them to securely review, respond and react faster. It gives ability to record and process audit findings and any quality issues onsite or in the field.

OEMs will have to learn to trust data and analytics, where once they relied on people. To truly embrace this digital transformation, manufacturers will have to step out of their comfort zones to learn new habits, acquire new disciplines and implement organizational transformation that extends to their supply chain. They will come to rely on their PLM vendors to encompass more backend activities typically stored in CRM (customer relationship management), issue tracking and data collection systems as well as all of the supply chain activities associated with procurement.

PLM to Connect Data

With all of this interconnectedness and data sharing, PLM is able to connect data at the front and back end. Data is no longer a silo to the design and engineering environment as it once was and data interaction is increasing. Data points related to product performance and efficiency can now be shared with the rest of the organization. Products are getting more complex by adding electronic and software components, and increased digital customer interactions bring even more information and opportunity.

Product data can be centralized within a PLM system to standardize business processes and streamline communication of information across distributed product development teams. It helps to shorten development cycles, improve quality and cut the time-to-market by enabling access to current and accurate product data.

Some PLM vendors that cater to SMEs’ requirements have taken steps to build simple-to-use tools to leverage data and communications in new, more meaningful ways. Communication continues to be the cornerstone of product development, manufacturing and support. Meetings, emails and phone/conference calls are important aspects of any team that builds products. It’s about transparency and finding the best ways to get everyone on the same page. Capturing these discussions and associating them to product records provide all personnel with the visibility to understand the full impact their products have had on user, consumers and customers. Understanding this impact has a direct influence on product features and quality for future designs and updates/upgrades.

Customer is King

Customer feedback is commonly used throughout the product development process to ensure that the end product is something that solves a customer’s problem or fulfills a need. The companies that can intertwine product development and customer feedback will be the ones that reap strong competitive advantages, have sticky customer loyalty and earn raving customer advocates. The best business decisions are based off data, not hunches. This is especially true as the IoT adds an extra layer of complexity with a higher volume of customer feedback from the consumer and products. Too many times business owners’ and executives’ decisions are made based off of inaccurate data.

Customer feedback is the holy grail of tangible data. It allows the product engineering team a better ability to gather real insight into how their customers really feel about the product or service. Bill Gates put it best when he related that a company’s most unhappy customers are actually a company’s greatest source of learning.

PLM Customer Communication Portals

If a large percentage of customers suggest a product feature or want an additional customer service channel, it has now become possible to capture this information using a PLM communication portal that can not only gather all product-related discussions and feedback but also actually raise, route and track any problems. It can automatically associate customer feedback to product records to improve product development, quality and timelines. Such systems can even provide product data links to internal and external feedback that makes the process easy and highly intuitive.

PLM systems have gotten smarter and many offer an efficient pre-filtering process before an issue becomes a quality item (such as a corrective action, nonconformity, process, change, etc.) or introduces product changes (engineering change orders). There is now a way to conduct closed-loop processing of PLM related issues as well as non-PLM related ones.

It can also deliver a user blogging environment encouraging additional communication. Often it can help manage and route help tickets as well as track help ticket closure. Most importantly, it builds solutions and develops a more in-depth knowledge base to address common questions and problems for the purposes of improving product design and corporate policies.

Analysts at Frost & Sullivan have determined that SMEs are coordinating 75% or more of their supply chain activity outside their four walls, using data derived from tapping into such areas as IoT, mobility and cloud-based technologies to achieve a more collaborative PLM framework. Results can deliver positive impacts in the design and engineering of products. This data SMEs are now tapping into is providing greater data accuracy, clarity and insights, leading to better decision-making.

Extending the reach of PLM into downstream processes, data sharing and analytics improves insights into customer requirements and makes use of product performance data in real life. As smart devices and sensors become more efficient and affordable, new opportunities arise to research and track how devices are performing—and how customers are experiencing these products in various industries. Meaningful data gathered from customers, devices, suppliers and multiple departments internal to an organization could seamlessly be filtered and leveraged throughout PLM processes to create better-engineered products.

This article was written by Chuck Cimalore, chief technology officer, Omnify Software. No payment was made for its placement. 

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