Leveraging AI, Data Ecosystems and Strategic Technology Integration
CIO Applications Europe | Saturday, December 15, 2001
Insights into Janne Lautanal’s Professional Expertise
I have more than 25 years of experience in technology and digital business. I have worked in telco business (Telecom Finland), consulting (Accenture & Avanade), maritime/ manufacturing (Wärtsilä) as well as now in government sector (Fintraffic) in three different continents. In my current role, I can combine learnings from all my previous employers in innovation, data economy as well as digital business leveraging newest technologies.
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Technology Innovations at Fintraffic Enhancing Traffic Flow and Safety
We have a number of cool technologies in place. For example, we use artificial intelligence to detect abnormalities in traffic, whether it is a vessel getting off course, an animal in a road tunnel or an object in a railway track. Similarly, the new cars’ sensors gather increasing amount of data on e.g. slippery of the road which is being transmitted to traffic control. We are using all this data to analyze the traffic situation and proving warnings, traffic announcements or in some cases, even stopping the traffic to ensure traffic safety and smoothness.
Predicaments of Integrating New Technologies
Even though we have vast amount of data already, we are facing an increasing amount of information coming from vehicles, sensors and 3rd parties. To analyze this real time data, we need to have need types of capabilities and technologies in place.
The biggest problem, however, is to identify the most relevant use cases that provide the best value for the money.
Projects and Initiatives at Fintraffic
One example is long lasting collaboration with Bauer Media, the market leader in commercial radio in Finland.
Bauer Media has collaborated with Fintraffic for years on issues such as the publication of the national traffic bulletins on Radio Nova. The innovation introduced last year enabled round-the-clock and local traffic bulletins read by an artificial intelligence robot. In this way, listeners will be informed immediately in the specific location where traffic is congested or where there’s been an accident. The service will benefit in particular the transport sector, which is mainly active at night.
Successful Partnerships for Significant Improvements in Traffic Management
Fintraffic is leading Traffic Data Ecosystem in Finland, a community of 210+ organizations, including both public and private organization.
This ecosystem has together defined the vision for traffic data architecture, set standards to be used as well as e.g. defined agreement models to be used when sharing data (“Traffic Data Ecosystem Rulebook”, https:// www.fintraffic.fi/en/rulebook) In the ecosystem, we have made several improvements that have led to both decrease in operational costs, speeding up the development of new services as well as services to be exported to other regions.
Tips to Enhance Data and IT Strategies
My focus is on data ecosystems. When advising manufacturing organizations on enhancing their data and IT strategies, I would consider these key points:
1. Data-Driven Decision Making: I would emphasize the importance of leveraging real-time data to improve operational efficiency, predict maintenance, and enhance decision-making. I encourage building strong data analytics capabilities that allow for predictive insights and automation.
2. Integrate IoT and Smart Manufacturing: Manufacturing is rapidly adopting IoT (Internet of Things) to create smart factories. implement connected sensors and devices that provide continuous data streams for process optimization, quality control, and energy management.
3. Cloud Adoption: I recommend moving data storage and processing to the cloud. It allows for scalable infrastructure, remote access to data, and enhanced collaboration. Cloud services also provide enhanced disaster recovery and security features, which are essential for safeguarding manufacturing operations.
4. Data Interoperability: It is import to ensure that data from various systems and machines can be integrated seamlessly. Adopt standardized data formats and platforms that allow for easy data exchange and system integration, avoiding silos.
5. Cybersecurity: Prioritize cybersecurity as manufacturing environments become more digitized. Industrial control systems and IT systems should be aligned with security best practices. Regular audits, staff training, and multi-layered security protocols can help safeguard critical infrastructure.
6. Digital Twins and Simulation: Digital twins can help organizations simulate manufacturing processes and monitor systems in real-time. Use this technology to forecast system behaviors, optimize processes, and reduce downtime.
7. Collaborative Data Ecosystems: Embrace the value of building collaborative ecosystems where manufacturing firms share data with partners and suppliers to optimize the supply chain, improve product quality, and enhance innovation. The ecosystem approach leads to greater agility and a competitive edge.
It is important to focus on change management by fostering a datafirst culture, training employees and aligning their strategies with broader business goals.
8. Change Management: Implementing data and IT strategies requires a shift in culture and mindset. Focus on change management by fostering a data-first culture, training employees and aligning their strategies with broader business goals.
9. Sustainability through Data: Use data to drive sustainability initiatives. Energy consumption, waste reduction and emissions monitoring can be tracked and optimized with the right data systems, contributing to both cost savings and environmental goals.
By focusing on these areas, manufacturing organizations can modernize their operations, stay competitive, and unlock new value through technology and data.
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