In the previous two parts of this series, we consider how business strategy and PLM strategy are important starting points that play a key role in helping life sciences companies get the most value from their PLM solutions.
A viable PLM strategy must support an overall business strategy, defining how PLM links to and enables overall business drivers that deliver better results from innovation. In a previous post, I recommended doing a cartography exercise that catalogs the entire product lifecycle and clarifies the context by which business decisions should be made.
When setting out on a PLM journey, companies must think through if a phased or incremental approach is best. Phase one of any implementation should start with the fundamentals; putting in a PLM backbone and a foundation to build from. Now it’s time to go beyond the foundation and consider more exciting possibilities for the roadmap beyond the first release.
With PLM, there are literally hundreds of things we can automate across the product lifecycle, so it’s important to select the things that will provide the most business value. The cartography exercise provides a strong characterization of each product development process and how they tie together. These results, plus our understanding of business drivers and challenges that we need to address, allow us to consider how our processes might be automated and integrated. The next step is to imagine automation initiatives, where each initiative is a component of a PLM release cycle. The list would include automating processes, framed as capabilities like DHF management, regulatory management, CAPA, and market analysis.
True PLM pioneers know that automation can be achieved in at different levels. Several years ago, my colleague Graciella Beyers and I developed three automation maturity levels for any given process. The first level is basic data management where PLM is used almost like a virtual filing cabinet for storing documents, with no smart links between the documents or the data in them. The second level introduces liberated data, stored so it can be acted upon, and includes more advanced workflow capabilities. The third level brings in predictive analytics and tools that think with you to solve problems (we called them helpers – similar to how Siri works). Graciella has an imagination for this stuff like no one I have ever worked with. She can take what seems to be the most basic or boring business processes and find ways to make them extremely useful to real people and real product teams through automation.
It’s probably overkill to identify three automation maturity levels for each capability, but it’s important to figure out what maturity level provides the optimal value for your business. My next entry will cover the process of prioritizing and grouping capabilities into individual releases to formulate a roadmap that is both defensible and addresses the business challenges in our overall business transformation strategy.
More In This Series
The Missed Opportunity and How We Can Overcome It
The Business Benefits
The Basics of Technology and Strategy
Solving Coming PLM Strategy Problems
Making it Real – People, Governance and Methodology
- Ten Traits any PLM Team Must Have
- Three Characteristics of a Successful Implementation Methodology