Data sharing in manufacturing can be challenging but it’s never impossible
RECENTLY, it was revealed that data sharing in manufacturing has an untapped value of US$100 billion in optimized operations alone.
Clearly, there is a pool of market opportunities that manufacturers have yet to seize until they start sharing their data with other manufacturers.
However, it is understandable that data sharing is not a common practice in the industry, so it can be difficult to initiate. Not to mention, the essence of data sharing itself can be complex.
According to a study by the World Economic Forum, manufacturers that are not sharing data cite difficulty in measuring data value to be a limiting factor.
The first key step to overcoming these barriers is to comprehensively understand how manufacturing data can be positioned as a business asset and what returns it can provide from sharing.
Certain data can be valuable for certain types of applications, so the value lies in where the data can be contextualized optimally. Here’s where it is important for manufacturers to critically evaluate the risks and outcome of sharing the data.
Of course, this comes with an effective asset management strategy. There ought to be a distinction between sharable data and private company data.
Just because data sharing is valuable, it does not mean that manufacturers must share all their data with partners.
In short, careful evaluation is required during the initial stages to ensure that only the right data is shared — something that does no harm to the business and its future productivity while also providing great returns to partners.
The next important step in ensuring successful data sharing is to identify partners with mutual business interests and foster trust in the partnership – which is considered difficult to establish.
A common issue that arises with trust when sharing data is uncertainties over ownership.
This is further fueled by the barriers that are already inherent within the industry like traditional business models that fall along the line of “every man for himself” where partnerships are not always something that manufacturers would opt for.
One way to change this is to ensure manufacturing partners speak the same language – in the sense that all parties have similarly vested interests and share common goals in data sharing.
For example, partners are all interested in augmenting operational processes or boosting customer experience in the supply chain. So the contractual partnerships that are built must focus on data sharing projects that drive desired results.
A relational-based agreement would be a good basis to support the partnership where ownership is established alongside mutual goals.
At this stage, there should no longer be much concern about what is shared between the two as the sharable data and the risks that follow have been previously assessed.
Data sharing practices might not be common right now but in light of the benefits they offer, sharing should have been the norm.
Fear and uncertainties can be resolved with just a little bit more investment in better regulations, critical assessment of data values and carefully curated partnership contracts. Manufacturers must strive to understand that each company’s unique value proposition will remain even if some of their data is shared.
- Snowflake has the perfect data platform for AI
- Did Shein finally make the bold move and file for a US IPO?
- The evolving robot: Past, present and future roles
- AWS becomes the first cloud provider to launch Nvidia GH200 Superchips with NVLink for AI cloud infrastructure
- Top 5 significant layoffs in gaming in 2023