Executive summary
Context
Flanders Investment and Trade (FIT) is a Flemish public agency that promotes international enterprise in Flanders by supporting international trade activities of Flemish companies and by attracting foreign investors to Flanders. Every week, Flemish and foreign companies contact FIT with a multitude of questions on how to expand their business in or from Flanders. FIT’s answers and advice on these questions is a key part of the agency’s added value for its clients.
Goal of the project
Reshaping FIT’s question-answering process through artificial intelligence, allowing FIT’s advisors to give clients accurate, actionable and timely answers to their questions. The project’s aim was also to help advisors free up time to conduct more in-depth research, improving the overall quality of the process.
Solution
An AI solution that automates the question-answering process at FIT. Superlinear’s model allows FIT and its advisors to save time and resources while improving user satisfaction.
Case study
The challenge
Flanders Investment and Trade (FIT) is a Flemish public agency that:
supports the international activities of Flemish companies
attracts foreign investors by highlighting Flanders’s central European location, its strongly developed infrastructure and its renowned innovative clusters
FIT gives Flemish and foreign companies free advice and introduces them to its global network of experts in more than 90 offices around the world. The quality of service and advice provided to these companies is therefore essential.
Investing in AI to gain competitive advantage
Internationalization is a big challenge for Flemish companies. This is in part due to the very competitive nature of the environment these companies grow in. Flanders’ innovative ecosystems are competing with all their counterparts around the globe, and this is why operational excellence is required for FIT to put Flanders’ in a pole position to expand abroad, and also to attract foreign investors.
To create operational excellence, the agency has been investing a lot in IT and artificial intelligence (AI) in the last few years, as it became a key part of its strategic plans.
Along the way, some questions naturally arose. How to implement AI? Which ideas should be pursued? Which technologies and applications specifically serve the agency’s ambition to become a data-driven organization and to set an example for the public sector?
Superlinear, through its Fast Discovery framework, devised tangible areas and use cases where AI could help FIT by increasing efficiency and creating value for FIT’s clients and employees. The specific case at hand: AI-assisted question answering.
The briefing
One of FIT’s main goals is to give relevant, reliable and actionable information and advice to Flemish and foreign companies. Many foreign companies directly contact FIT to gain insights into the Flemish market. Flemish companies planning to expand internationally also directly ask FIT for counselling on markets abroad.
These contacts mostly come in the form of direct questions to FIT. Every month, FIT offices around the world receive thousands of questions. A lot of the value FIT creates comes from answering these questions. Every answer needs to be accurate, complete, and actionable. It takes FIT’s advisors a considerable amount of time to collect the needed intelligence and research in order to answer these questions.
What can be improved with AI?
As the information needs to be sent relatively fast, busy periods can often create bottlenecks, which cause some answers to be sent later than foreseen. Some complex questions or cases demand more research and more time to be answered. External events also have a big impact on operations. The COVID-19 pandemic led to a huge spike in requests relative to the numerous uncertainties worldwide relative to doing business.
Naturally, a certain amount of questions tends to be quite similar. FIT’s advisors sometimes have to answer some questions repetitively, which is not the most enjoyable part of the job. This is why FIT wanted to optimize this high added-value, but highly time-consuming process. The agency wanted to get accurate, actionable information to clients faster, allowing for more time to take on complex cases and helping the advisors focus on more rewarding parts of their jobs. These frequently asked questions can also be gathered and distributed through a broader audience on FIT’s owned channels such as website or social media.
The AI solution
Superlinear proposed a solution to assist advisors on their question answering tasks. Through AI and machine learning, Superlinear was to find a way to extract intelligent insights out of FIT’s data, allowing the agency to answer questions more easily and quickly. The entire question-answering process would then be optimized, creating value for FIT’s clients and empowering its employees.
“We interviewed a lot of companies to see how we could optimize some of our internal processes with AI. With Superlinear and its CEO Davio, we found the perfect balance between business understanding and technical capabilities. They helped us find a tangible use case that could create tremendous value for our organization. This was a really important project for us: as a public agency, we wanted to set an example of innovation through high-end technology.”
Yves Ruland - Project Manager Data Architecture and Artificial Intelligence
The work
Superlinear started to work on a minimum viable product (MVP) that could be made quickly to get direct feedback from the end-users: FIT’s advisors. Superlinear used Natural Language Processing (NLP) to create a question-answering machine learning model.
How does the model work?
NLP is a field of AI and machine learning used to process and analyze data from the human language. The model created by Superlinear selects valuable information out of the content of the question, screens similar questions answered in the past and automatically provides advisors with the most suited answer: they don’t have to go from memory or do long research to find these answers. The model automatically updates itself with every new question and answer.
When the first iterations of the model were submitted to FIT advisors for evaluation and feedback, interviews showed that advisors were excited to help work on these features. They believed this kind of technology could help them and showed great enthusiasm around AI. 100% of the advisors were open to innovation as they saw the potential of the concept. After the first sprint, 78% found value in the tool and some advisors brought up interesting features which were ultimately added to the solution.
Delivering impact with AI
After just a few weeks, Superlinear delivered the MVP. The solution showed great results in several key areas:
Saving time and money: The solution saves 27% of time spent on cases. The AI provided help for 60% of all tested cases (cases where no previous answer/data was available included). Ultimately, FIT’s advisors were able to help 36% more clients with Superlinear’s solution.
User satisfaction: The solution gives FIT advisors superpowers. It allows them to save time by providing them with relevant answers that they can adapt if need be. This process optimization saves them a lot of research time and allows them to focus on more complex cases and other parts of their jobs.
Continuity optimization: The solution is also of great help to guide new advisors or when an advisor is unavailable due to sick leave or vacation. As it solves more and more tasks, the solution becomes a knowledge database, gathering knowledge from hundreds of advisors and cases.
“Superlinear is a young and talented team, and they weren’t afraid of challenging us. We value that greatly in our partners. They involved our end user in the process. This turned an already very effective model - results-wise - into a fully-fledged solution that our advisors enjoy using. To be honest, the results were so good that we didn’t believe it at first. This is a testament to Superlinear’s work ethic, expertise and general quality.”
Peter Bulckaert - Head of Department at FIT
“During the development, we verified our solution with the eventual end-users at FIT a couple of times. It was refreshing to see the enthusiasm of FIT employees towards an innovative approach. They gladly made time to validate our intermediate results and were happy to share insight into their way of working and how we could help them. It is clear that the ambition to be a technological pioneer is widely supported at FIT.”
Victor Hutse - Machine Learning Engineer at Superlinear
The future
Based on results and learnings from the MVP, Superlinear also proposed ideas and areas to further improve the solution in the future, optimizing performance by incrementally improving what is under the hood. There have already been a few suggestions for the next iterations and a further improvement in problem-solving. The next step is to implement the solution globally.
“We intend to extend Superlinear’s solution as soon as possible. We have a roadmap describing a long-term AI vision where several specific projects will be developed in the future. We see Superlinear being one of the partners that will help us develop those cases. This successful Superlinear project helped us sell the idea of AI internally. Not only did they provide a very effective solution, but they also made mockups of what it could look like in the future, and had thorough discussions with our business people which helped to spark some great ideas. Thanks to Superlinear, we have proven that AI can be a highly valuable asset in our organization.”
Yves Ruland - Project Manager Data Architecture and Artificial Intelligence
