Words of Wisdom for the First Steps in Digital Transformation
I had the pleasure of speaking with Bjørn Fidjeland, Founder of PLM consulting company PLMPartner, and known for his PLM writings. Bjørn has 20+ years of consulting experience and has witnessed countless digital transformation initiatives over the years. Bjørn’s easy style and logical approach helps businesses break down the steps to see the devil, and the salvation, in the details.
In this free-form discussion, we spend some time talking about digital transformation where Bjørn shares his best pieces of advice from data governance and dictionaries to remembering to take the time to digest change. Particularly resonating advice is the required patience and acceptance that it takes time to change.Watch the complete episode with those details and so much more in between.
Digital Transformation in a PLMContext
First of all, there is no one system to rule them all. Bjørn views Digital Transformation as a holistic, enterprise-wide connection between systems that enables information flow between platforms. There must be interoperability between each department and across the company but also the software tools. Once interoperability is achieved employees, suppliers, and customers can harvest the knowledge coming from other departments both inside and outside the corporate entity.
The keyword here is interoperability. You need to have an infrastructure set up to support how information flows and how it can be translated between departments, companies, and software tools. It is not a piece of software that should run this initiative, but the business and its champions for change. As has been stated time and again – software enables people, but it does not independently create transformation.
The Concept of Engineering Master Data
Companies should put effort in harmonizing their data in different systems and across different departments. Though standards are favored as a fast track for this initiative, they often prove lacking.
Data from one department/“silo” in an organization can look like hieroglyphs for the receiving department/“silo”.
Bjørn proposes an alternative method to standards utilizing a dictionary or Rosetta Stone to translate – creating cross-organizational engineering master data. The dictionary enables users to understand the context and meaning behind enterprise data regardless as to their touchpoint or role.
Additionally, not all industries have standards and these definitions allow users to move forward with their data and parts libraries in an easy to understand way regardless of its origin.
Bjørn has also commented on companies relying on an Enterprise Service Bus (esb) to handle data flow and the limitations and complications introduced via this highway with configured exit points.
Figure 1:Representation without a dictionary, relying on an esb to handle data flow:
As stated, if we change an attribute, all adapters must be revisited and changed as well.
Figure 2: With a dictionary-enabled
Of course, an advantage to selecting an industry standard is that the same dictionary can be readily used when exchanging data with external stakeholders as well as internal applications with ease.
New applications can be added to the federation without having to modify any of the others. A dictionary-based on a standard renders communication with companies adhering to the standards easy and provides a competitive advantage.
When working without standards or in addition to standards; ideally, you should either define the different object structures, including the engineering BoM’s, design models, and design assemblies etc. in the same way. Or have some sort of dictionary that can do it for you.
Create a Dictionary
There are companies that have created a dictionary for their data to translate names in different systems. Sometimes this happens due to limitations of one system or another on attributes, characters, or other data points that cause variations in master data. Typos are another culprit.
It is still unchartered territory as there is no standard way of creating such a dictionary, but because interoperability is so important, it is vital to prioritize having a standardized naming and identification system to make your information flow seamlessly across platforms.
Data Must beConnected, Comparable,and Interoperable
Remember, data does not necessarily have to be exactly the same. For data to be fully connected, comparable, and interoperable there needs to be a dictionary that translates between the different disciplines and tools to account for those nuances.
How can we feedback information from the lifecycle phases to reveal insights and meaning without a common understanding? Interoperability is a prerequisite to enable digitalization. However – don’t underestimate the people and cultural aspect. A poorly communicated transformation initiative will fall flat. Keep people in the center of the process and ensure you’ve well articulated why the initiative is valuable and will generally impact change for good.
What is your advice?
What are your takeaways? Will you use a Rosetta Stone, a dictionary, standards or hybrid for your data? Want to share your story with the community? Drop me a line, I would love to talk to you and help get your story out.