Artificial intelligence will go long way to imbue data management with trust.
The 2013 film “Her” took us to a not-too-distant future where vital elements of the human condition—love, hate, acceptance—are quickly built or destroyed by artificial intelligence (AI). The film’s main characters, Theodore and Amy, seek meaningful connections—to other people, to their surroundings and ultimately to themselves. Operating systems (OSs) enabled by AI act as omniscient life coaches, guiding humans through optimal routines, social commitments and material purchases, customizing each to deliver feelings of confidence and belonging. Tensions arise when the OSs have “too much” information about their human counterparts, crossing boundaries of personal privacy.
Today, manufacturers are using technology to bring customers into the creative process, developing deeply satisfying, personalized product experiences. Personal data collection is critical to the process and, like the characters in “Her,” customers yearn to control the boundaries. Access to their information must begin and end on their terms.
The General Data Protection Regulation (GDPR), a European law implemented in May, shifts control back to the customer—and represents serious challenges for many global firms.
However, for some smart manufacturers, GDPR represents opportunity.
It is widely held that global customers do not trust companies with their data. But nearly 70% of the 25,000 people Accenture surveyed last year said companies could earn their trust by being more transparent about how they use customer data.
From this perspective, GDPR provides a useful framework for building trust with customers and employees in manu-
facturing. GDPR simply requires that companies and individuals agree on how personal data can be used.
This is an essential step in moving from an era of mass production to an era of mass customization—and, for some, a strategic competitive advantage. Gain proper consent, transparently demonstrate data is used properly and customers will share their data to continually improve and personalize the services you deliver.
“We’re collecting data that helps us understand how each different operator, each individual, works with our machines,” said Ben Warren of Atlas Copco. “This impacts maintenance, mean cycles between failures, operator-machine interface and training. It reduces costs and improves output quality for our customers. Being transparent with them in terms of what we’re using the data for helps us develop stronger, more collaborative relationships.”
Prettl International CEO Walter Kaufmann said if companies protect information “in an effective, compliant and socially responsible manner, they can build trust and create competitive advantage by being best in class in managing sensitive data types.”
GDPR stipulates that if information is requested, it must be easily found. However, GDPR covers certain data types that aren’t easily or uniformly grouped and classified. GDPR-covered information like customer IP addresses or online behavior is often classified under different names, depending on how it was collected or used.
Many global manufacturers achieved their size and reach through acquisition, bringing multiple systems, business processes and data classifications under the same roof. Multiple custom applications and third-party legacy systems still power supply chain process and retail relationships. What are the chances these systems are all classifying data the same way?
For these companies, the process of hunting down these data elements and changing application code, database and storage parameters is a grueling, manual task. For them, GDPR violations and fines are inevitable.
AI can help.
Companies like Delta Bravo are using machine learning to analyze large databases, confirm correctly classified data and identify data types that aren’t classified according to GDPR requirements. Instead of taking weeks or months, this work is done in seconds.
Once non-compliant data types are identified, Delta Bravo’s AI provides the code and step-by-step instructions to achieve compliant database classification, saving thousands of manhours and greatly reducing risks of GDPR violation.
“Her” ends with Theodore and Amy drawn to each other in a genuine, unassisted and purely human way. The OSs have disappeared. All that’s left is the trust and honesty of their relationship; who they are and how each fulfills the other.
This concept reflects the new manufacturing standard that GDPR is helping to crystalize (similar to the role the OSs played in “Her”): Data management can no longer be an afterthought.
Symbiotic relationships with customers, employees and supply chain partners must be built on a bedrock of trust—and AI-enabled GDPR compliance presents itself as a cornerstone for the taking.