Organizational Barriers to Harnessing the Digital Twin

Although many articles about digital twins focus on technological aspects, fixating on different software marketed by technology firms, there is not as much talk around how companies should implement organizational changes to take full advantage of digital twin capabilities. A recent article from IndustryWeek lays out various organizational barriers that companies face when implementing digital twin solutions. It predicts that although “30% of G2000 companies will use data from digital twins in 2020 to improve workforce performance and manufacturing efficiencies, some companies are currently experiencing challenges in making this happen.” The article outlines two organizational barriers for adopting the digital twin. The first requires transitioning away from legacy data systems to enable real-time data transmission. The second requires rethinking the skillsets of the workforce so workers can use these technologies to make more effective and efficient solutions. 

Defining a Digital Twin

To understand why this technology has organization-wide implications necessitates understanding what a digital twin is. Guidehouse Insights, defines the digital twin as “At its most basic level, just a digital representation of a physical object.” For example, a data point on an Excel sheet exhibiting one characteristic for a single piece of equipment is essentially a digital twin. The difference between the digital twins in your Excel document and the digital twins that simulates a human heart are the breadth and depth of the data used, the user interface that represent the data, and the processing power of the software that analyses the data inputs. Differences in these inputs represent dimensions of digital twin maturity. For a more detailed explanation of these dimensions, see the related Guidehouse Insights report, Digital Twins and AI Deliver the Energy System of Tomorrow.

Breadth and Depth of Information

The most important dimension pertaining to the organization is the breadth and depth of the information. The latest applications of digital twin technology require real-time data from a multitude of sources throughout the organization. Enabling timely and proper access and use of this data requires retooling the data sharing, security, and access approaches within the organization. Data use protocols and procedures would need to be re-examined and rewritten to break down siloes in data ownership and access while ensuring that sensitive and confidential data is protected. In addition to changing data management practices, companies also need to train their workers to become more data literate. Companies must invest in training and hiring programs that emphasize increasing employee comfort working with data. Taking full advantage of a technology such as the digital twin with organization-wide implication requires an enterprisewide approach. 

To learn more about the prevailing elements of the digital twin, its potential effect on sustainable manufacturing, and recommendations for manufacturing companies looking to successfully implement this approach, read Guidehouse Insights’ report Leveraging the Digital Twin Approach for Sustainable Manufacturing.