If you’re like most organizations, chances are you are struggling to understand the connections found in your disparate silos of information. We live in a virtual, technologically advanced world, and the reliance on technology by both companies and their customers for conducting day-to-day transactions and interactions only continues to increase. The number of systems holding this critical data is vast and fragmented, each operating independently of one another. The challenge of identifying and reconciling data across these disparate and siloed systems makes creating a complete and accurate view of a company or customer almost impossible. This is because no single system contains this view across all departments or lines of business or is designed to manage the complete lifecycle of the data.
With the advent of the Internet of Things (IoT) there has been a sharp increase in both the availability of customer data and how much of it organizations are able to collect from their product’s everyday use. This year alone, Gartner estimates that 8.4 billion connected "things" are already in use. Today’s best-in-class companies recognize the importance of its customer data and are proactively looking to bring order and connectivity to the chaos to uncover the hidden insights it holds. Historically, customer data has been difficult to acquire, clean and, most of all, interpret.
This torrent of customer data can create significant opportunities because, for the first time, organizations can get quick feedback on product usage and, by extension, the customer experience they are providing. In fact, Forbes estimates that 70 percent of global retail decision makers are ready to adopt the IoT to improve customer experiences.
Access to this information will deeply impact how manufacturers plan, design and maintain their products in the future. It also helps ensure that products are aligned with their customers’ current expectations and future requirements. However, managing, analyzing and ultimately producing actionable insights from all this data across a product’s lifecycle will require expanding how product lifecycle management (PLM) solutions are typically used.
After all, the ability to access rich customer data can affect how products are managed throughout their lifecycle. Utilizing the vast pieces of customer data together with your product development process, organizations can gain a different level of what the customer wants (and needs), uncover trends and new use cases and, in some cases, identify possible problems before they impact loyalty or reputation. The ability to apply customer insight can have a significant impact at nearly every stage of the lifecycle, including:
- Product Design: The earliest stage of product development is undoubtedly where leveraging accurate and up-to-date customer data will have the greatest impact.
Capturing performance data and learning how products are, or aren’t, meeting customers’ expectations will enable this information to be applied during a product’s ideation stage to ensure that new products provide the experience customers expect.
- Introduction: Analyzing how customers receive your offerings can provide crucial insights into what can be improved for upcoming product lines and assortments. In addition, customer data is key in measuring product success and should be used to establish standards for future launches.
- Product Intelligence: Knowing how customers use products in real-time will enable companies to forecast necessary maintenance, fixes and updates and schedule them ahead of time. Learning usage and the product status also helps mitigate risks by providing useful compliance information.
To take advantage of this surge of customer data, organizations are investing in analytical and automation tools, effective master data management (MDM) and the necessary human capital needed to support the effort. The approach makes sense because, after all, what good is all this data if it can’t be analyzed to gain critical insights?
However, to be truly effective, a PLM system must be flexible enough to allow for the additional processes that would have to be put in place and be able to reliably and efficiently connect to the other systems where the customer data is stored and maintained.
Applying an MDM platform to an organization’s PLM streamlines the process of aggregating and consolidating information around its products, customers, suppliers, employees, assets, location and reference data that exists from multiple sources and formats. It also connects that information to derive actionable insights.
Connected devices have created an opportunity for traditional PLM to keep evolving and embrace the increasing availability of customer data. In doing so, PLM continues to broaden from its engineering roots and opens new possibilities to drive key insights that were extremely hard and slow to come by in the past, if even possible at all.