Product Digital Thread: Using end-to-end lifecycle data to deliver business value

Lexmark’s journey to data democratization

At Lexmark, we understood that to truly realize the potential of digital transformation, we had to undergo massive organizational and cultural changes to democratize data for all internal stakeholders. We especially needed to break down silos for our cloud-based Managed Print Services (MPS) business. Since ridding our company of this internal friction, we have unlocked new levels of innovation and value for our customers.

In developing a global MPS solution, we sought to build a robust Internet of Things (IoT) and cloud platform that could mine for and leverage performance data from the more than 1 million devices we manage around the world. This fleet alone generates more than 1 terabyte of data per week, which had to be merged and correlated with transactional data across various business systems.

Before we could operationalize our insights, however, we needed to figure out a way to harness the institutional knowledge of our “data heroes” – data scientists and business-user data wranglers. Industry sources suggest that data wrangling – the process of cleaning and unifying messy and complex data sets for easy access and analysis – can constitute as much as 90% of data science activities. Each of our data heroes perform highly specialized analysis, but we needed a way to share each one’s knowledge of how to identify, extract, transform and make use of the data and leverage it across organizational boundaries to drive transformative change. And this is easier said than done.

To address the changing needs of our evolving organization and adopt a new level of information transparency, we sought to embrace a companywide culture shift. Our first step was merging our corporate strategy, data science, IT and software research and development groups under a unified chief information and technology officer. This new Connected Technology organization reinforces a culture without silos where information can easily flow across business units.

A formal data science and analytics team has the mission to identify and develop our data heroes. As a team, they’re tasked with continuously learning and developing best practices for deriving data-driven insights across the organization. Finally, we committed to creating transparency where people can see the tangible up- and downstream effects of their decisions. With this guiding principle, we unified as one team, openly sharing information to learn with and from each other.

The transformational potential of the Product Digital Thread

After several months of cross-functional work led by our executive team, the final result was the Product Digital Thread (PDT). The PDT is a live, integrated repository and audit trail of real-time data generated across the end-to-end lifecycle of our products – hardware, key components and supplies. This includes everything from design through manufacturing and service to recycling. This holistic approach to data management complements our IoT- and cloud-enabled as-a-service (aaS) strategy, providing a mechanism to expand our closed-loop analytics across our entire value chain.

Our Connected Technology team uses the PDT to deliver Data-as-a-Service (DaaS) to our internal business users and make our data models more agile, unified and transparent. It also supports Analytics-as-a-Service (AaaS) to provide greater analytics capabilities – using artificial intelligence (AI), machine learning (ML), automation and more – via the cloud, creating a data ecosystem that supports all tiers of analytical maturity.

The PDT has delivered real-time benefits on several levels. Today, product engineers are immediately alerted to product issues in the field. This has allowed them to quickly assess data across a component’s lifecycle to identify and address the root cause before a customer is impacted by the issue. Supply chain teams can also evaluate what, where and when to produce products based on real-world, real-time customer use trends. Product development teams can see downstream service implications from their design decisions. Finally, customer support is aware of impending needs through predictive algorithms enabling resolution that is preemptive, and 70% of the time remote. This approach has also reduced help desk calls by 30%. Lexmark was recently recognized as an industry leader for our PDT efforts.

For us, Lexmark’s digital transformation objectives focused on delivering value to customers throughout our own technical journey and decreasing the time to achieving this value. The PDT contributed to both objectives and was a key enabler for executing two novel aaS models within our business.

While 65% of businesses currently have initiatives to encourage collaboration between data science teams, analytics teams and the business, according to Forrester, many organizations are hindered by their outdated ways of doing things. From experience, we know how difficult it is to fundamentally change the way you operate as a business — but it is well worth it.

If you want to fully embrace digital transformation for your organization, here are some steps to consider: